Functional genomics of brain aging and Alzheimer's disease: focus on selective neuronal vulnerability

Alzheimer's Disease: Exploring the Landscape of Cognitive Decline

Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by cognitive decline, memory loss, and impaired daily functioning. The pathology of AD is marked by the accumulation of amyloid beta plaques and tau protein tangles in the brain, along with neuroinflammation and synaptic dysfunction. Genetic factors, such as mutations in APP, PSEN1, and PSEN2 genes, as well as the APOE ε4 allele, contribute to increased risk of acquiring AD. Currently available treatments provide symptomatic relief but do not halt disease progression. Research efforts are focused on developing disease-modifying therapies that target the underlying pathological mechanisms of AD. Advances in identification and validation of reliable biomarkers for AD hold great promise for enhancing early diagnosis, monitoring disease progression, and assessing treatment response in clinical practice in effort to alleviate the burden of this devastating disease. In this paper, we analyze data from the CAS Content Collection to summarize the research progress in Alzheimer's disease. We examine the publication landscape in effort to provide insights into current knowledge advances and developments. We also review the most discussed and emerging concepts and assess the strategies to combat the disease. We explore the genetic risk factors, pharmacological targets, and comorbid diseases. Finally, we inspect clinical applications of products against AD with their development pipelines and efforts for drug repurposing. The objective of this review is to provide a broad overview of the evolving landscape of current knowledge regarding AD, to outline challenges, and to evaluate growth opportunities to further efforts in combating the disease.

Deep learning techniques for Alzheimer's disease detection in 3D imaging: A systematic review

Background and Aims

Alzheimer's disease (AD) is a degenerative neurological condition that worsens over time and leads to deterioration in cognitive abilities, reduced memory, and, eventually, a decrease in overall functioning. Timely and correct identification of Alzheimer's is essential for effective treatment. The systematic study specifically examines the application of deep learning (DL) algorithms in identifying AD using three-dimensional (3D) imaging methods. The main goal is to evaluate these methods' current state, efficiency, and potential enhancements, offering valuable insights into how DL could improve AD's rapid and precise diagnosis.

Methods

We searched different online repositories, such as IEEE Xplore, Elsevier, MDPI, PubMed Central, Science Direct, ACM, Springer, and others, to thoroughly summarize current research on DL methods to diagnose AD by analyzing 3D imaging data published between 2020 and 2024. We use PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines to ensure the organization and understandability of the information collection process. We thoroughly analyzed the literature to determine the primary techniques used in these investigations and their findings.

Results and Conclusion

The ability of convolutional neural networks (CNNs) and their variations, including 3D CNNs and recurrent neural networks, to detect both temporal and spatial characteristics in volumetric data has led to their widespread use. Methods such as transfer learning, combining multimodal data, and using attention procedures have improved models' precision and reliability. We selected 87 articles for evaluation. Out of these, 31 papers included various concepts, explanations, and elucidations of models and theories, while the other 56 papers primarily concentrated on issues related to practical implementation. This article introduces popular imaging types, 3D imaging for Alzheimer's detection, discusses the benefits and restrictions of the DL-based approach to AD assessment, and gives a view toward future developments resulting from critical evaluation.

Systematic Analysis of Biological Processes Reveals Gene Co-expression Modules Driving Pathway Dysregulation in Alzheimer's Disease

Alzheimer's disease (AD) manifests as a complex systems pathology with intricate interplay among various genes and biological processes. Traditional differential gene expression (DEG) analysis, while commonly employed to characterize AD-driven perturbations, does not sufficiently capture the full spectrum of underlying biological processes. Utilizing single-nucleus RNA-sequencing data from postmortem brain samples across key regions-middle temporal gyrus, superior frontal gyrus, and entorhinal cortex-we provide a comprehensive systematic analysis of disrupted processes in AD. We go beyond the DEG-centric analysis by integrating pathway activity analysis with weighted gene co-expression patterns to comprehensively map gene interconnectivity, identifying region- and cell-type-specific drivers of biological processes associated with AD. Our analysis reveals profound modular heterogeneity in neurons and glia as well as extensive AD-related functional disruptions. Co-expression networks highlighted the extended involvement of astrocytes and microglia in biological processes beyond neuroinflammation, such as calcium homeostasis, glutamate regulation, lipid metabolism, vesicle-mediated transport, and TOR signaling. We find limited representation of DEGs within dysregulated pathways across neurons and glial cells, suggesting that differential gene expression alone may not adequately represent the disease complexity. Further dissection of inferred gene modules revealed distinct dynamics of hub DEGs in neurons versus glia, suggesting that DEGs exert more impact on neurons compared to glial cells in driving modular dysregulations underlying perturbed biological processes. Interestingly, we observe an overall downregulation of astrocyte and microglia modules across all brain regions in AD, indicating a prevailing trend of functional repression in glial cells across these regions. Notable genes from the CALM and HSP90 families emerged as hub genes across neuronal modules in all brain regions, suggesting conserved roles as drivers of synaptic dysfunction in AD. Our findings demonstrate the importance of an integrated, systems-oriented approach combining pathway and network analysis to comprehensively understand the cell-type-specific roles of genes in AD-related biological processes.

Hippocampal transcriptome-wide association study and pathway analysis of mitochondrial solute carriers in Alzheimer's disease

The etiopathogenesis of late-onset Alzheimer's disease (AD) is increasingly recognized as the result of the combination of the aging process, toxic proteins, brain dysmetabolism, and genetic risks. Although the role of mitochondrial dysfunction in the pathogenesis of AD has been well-appreciated, the interaction between mitochondrial function and genetic variability in promoting dementia is still poorly understood. In this study, by tissue-specific transcriptome-wide association study (TWAS) and further meta-analysis, we examined the genetic association between mitochondrial solute carrier family (SLC25) genes and AD in three independent cohorts and identified three AD-susceptibility genes, including SLC25A10, SLC25A17, and SLC25A22. Integrative analysis using neuroimaging data and hippocampal TWAS-predicted gene expression of the three susceptibility genes showed an inverse correlation of SLC25A22 with hippocampal atrophy rate in AD patients, which outweighed the impacts of sex, age, and apolipoprotein E4 (ApoE4). Furthermore, SLC25A22 downregulation demonstrated an association with AD onset, as compared with the other two transcriptome-wide significant genes. Pathway and network analysis related hippocampal SLC25A22 downregulation to defects in neuronal function and development, echoing the enrichment of SLC25A22 expression in human glutamatergic neurons. The most parsimonious interpretation of the results is that we have identified AD-susceptibility genes in the SLC25 family through the prediction of hippocampal gene expression. Moreover, our findings mechanistically yield insight into the mitochondrial cascade hypothesis of AD and pave the way for the future development of diagnostic tools for the early prevention of AD from a perspective of precision medicine by targeting the mitochondria-related genes.

Ad-derived bone marrow transplant induces proinflammatory immune peripheral mechanisms accompanied by decreased neuroplasticity and reduced gut microbiome diversity affecting AD-like phenotype in the absence of Aβ neuropathology

Immune system dysfunction is increasingly recognized as a significant feature that contributes to Alzheimer's disease (AD) pathogenesis, reflected by alterations in central and peripheral responses leading to detrimental mechanisms that can contribute to the worsening of the disease. The damaging alterations in the peripheral immune system may disrupt the peripheral-central immune crosstalk, implicating the gut microbiota in this complex interaction. The central hypothesis posits that the immune signature inherently harbored in bone marrow (BM) cells can be transferred through allogeneic transplantation, influencing the recipient's immune system and modulating peripheral, gut, and brain immune responses. Employing a genetically modified mouse model to develop AD-type pathology we found that recipient wild-type (WT) mice engrafted with AD-derived BM, recapitulated the peripheral immune inflammatory donor phenotype, associated with a significant acceleration of cognitive deterioration in the absence of any overt change in AD-type amyloid neuropathology. Moreover, transcriptomic and phylogenetic 16S microbiome analysis evidence on these animals revealed a significantly impaired expression of genes associated with synaptic plasticity and neurotransmission in the brain and reduced bacteria diversity, respectively, compared to mice engrafted with WT BM. This investigation sheds light on the pivotal role of the peripheral immune system in the brain-gut-periphery axis and its profound potential to shape the trajectory of AD. In summary, this study advances our understanding of the complex interplay among the peripheral immune system, brain functionality, and the gut microbiome, which collectively influence AD onset and progression.

Systematic Analysis of Biological Processes Reveals Gene Co-expression Modules Driving Pathway Dysregulation in Alzheimer's Disease

Alzheimer's disease (AD) manifests as a complex systems pathology with intricate interplay among various genes and biological processes. Traditional differential gene expression (DEG) analysis, while commonly employed to characterize AD-driven perturbations, does not sufficiently capture the full spectrum of underlying biological processes. Utilizing single-nucleus RNA-sequencing data from postmortem brain samples across key regions-middle temporal gyrus, superior frontal gyrus, and entorhinal cortex-we provide a comprehensive systematic analysis of disrupted processes in AD. We go beyond the DEG-centric analysis by integrating pathway activity analysis with weighted gene co-expression patterns to comprehensively map gene interconnectivity, identifying region- and cell-type-specific drivers of biological processes associated with AD. Our analysis reveals profound modular heterogeneity in neurons and glia as well as extensive AD-related functional disruptions. Co-expression networks highlighted the extended involvement of astrocytes and microglia in biological processes beyond neuroinflammation, such as calcium homeostasis, glutamate regulation, lipid metabolism, vesicle-mediated transport, and TOR signaling. We find limited representation of DEGs within dysregulated pathways across neurons and glial cells, indicating that differential gene expression alone may not adequately represent the disease complexity. Further dissection of inferred gene modules revealed distinct dynamics of hub DEGs in neurons versus glia, highlighting the differential impact of DEGs on neurons compared to glial cells in driving modular dysregulations underlying perturbed biological processes. Interestingly, we note an overall downregulation of both astrocyte and microglia modules in AD across all brain regions, suggesting a prevailing trend of functional repression in glial cells across these regions. Notable genes, including those of the CALM and HSP90 family genes emerged as hub genes across neuronal modules in all brain regions, indicating conserved roles as drivers of synaptic dysfunction in AD. Our findings demonstrate the importance of an integrated, systems-oriented approach combining pathway and network analysis for a comprehensive understanding of the cell-type-specific roles of genes in AD-related biological processes.

A hybrid multimodal machine learning model for Detecting Alzheimer's disease

Alzheimer's disease (AD) diagnosis utilizing single modality neuroimaging data has limitations. Multimodal fusion of complementary biomarkers may improve diagnostic performance. This study proposes a multimodal machine learning framework integrating magnetic resonance imaging (MRI), positron emission tomography (PET) and cerebrospinal fluid (CSF) assays for enhanced AD characterization. The model incorporates a hybrid algorithm combining enhanced Harris Hawks Optimization (HHO) algorithm referred to as ILHHO, with Kernel Extreme Learning Machine (KELM) classifier for simultaneous feature selection and classification. ILHHO enhances HHO's search efficiency by integrating iterative mapping (IM) to improve population diversity and local escaping operator (LEO) to balance exploration-exploitation. Comparative analysis with other improved HHO algorithms, classic meta-heuristic algorithms (MHAs), and state-of-the-art MHAs on IEEE CEC2014 benchmark functions indicates that ILHHO achieves superior optimization performance compared to other comparative algorithms. The synergistic ILHHO-KELM model is evaluated on 202 AD Neuroimaging Initiative (ADNI) subjects. Results demonstrate superior multimodal classification accuracy over single modalities, validating the importance of fusing heterogeneous biomarkers. MRI + PET + CSF achieves 99.2 % accuracy for AD vs. normal control (NC), outperforming conventional and proposed methods. Discriminative feature analysis provides further insights into differential AD-related neurodegeneration patterns detected by MRI and PET. The differential PET and MRI features demonstrate how the two modalities provide complementary biomarkers. The neuroanatomical relevance of selected features supports ILHHO-KELM's potential for extracting sensitive AD imaging signatures. Overall, the study showcases the advantages of capitalizing on complementary multimodal data through advanced feature learning techniques for improving AD diagnosis.

Novel methodology for detection and prediction of mild cognitive impairment using resting-state EEG

BACKGROUND

Early discrimination and prediction of cognitive decline are crucial for the study of neurodegenerative mechanisms and interventions to promote cognitive resiliency.

METHODS

Our research is based on resting-state electroencephalography (EEG) and the current dataset includes 137 consensus-diagnosed, community-dwelling Black Americans (ages 60-90 years, 84 healthy controls [HC]; 53 mild cognitive impairment [MCI]) recruited through Wayne State University and Michigan Alzheimer's Disease Research Center. We conducted multiscale analysis on time-varying brain functional connectivity and developed an innovative soft discrimination model in which each decision on HC or MCI also comes with a connectivity-based score.

RESULTS

The leave-one-out cross-validation accuracy is 91.97% and 3-fold accuracy is 91.17%. The 9 to 18 months' progression trend prediction accuracy over an availability-limited subset sample is 84.61%.

CONCLUSION

The EEG-based soft discrimination model demonstrates high sensitivity and reliability for MCI detection and shows promising capability in proactive prediction of people at risk of MCI before clinical symptoms may occur.

Adaptive responses of neuronal cells to chronic endoplasmic reticulum (ER) stress

Accumulation of misfolded proteins or perturbation of calcium homeostasis leads to endoplasmic reticulum (ER) stress and is linked to the pathogenesis of neurodegenerative diseases. Hence, understanding the ability of neuronal cells to cope with chronic ER stress is of fundamental interest. Interestingly, several brain areas uphold functions that enable them to resist challenges associated with neurodegeneration. Here, we established novel clonal mouse hippocampal (HT22) cell lines that are resistant to prolonged (chronic) ER stress induced by thapsigargin (TgR) or tunicamycin (TmR) as in vitro models to study the adaption to ER stress. Morphologically, we observed a significant increase in vesicular und autophagosomal structures in both resistant lines and 'giant lysosomes', especially striking in TgR cells. While autophagic activity increased under ER stress, lysosomal function appeared slightly impaired; in both cell lines, we observed enhanced ER-phagy. However, proteomic analyses revealed that various protein clusters and signaling pathways were differentially regulated in TgR versus TmR cells in response to chronic ER stress. Additionally, bioenergetic analyses in both resistant cell lines showed a shift toward aerobic glycolysis ('Warburg effect') and a defective complex I of the oxidative phosphorylation (OXPHOS) machinery. Furthermore, ER stress-resistant cells differentially activated the unfolded protein response (UPR) comprising IRE1α and ATF6 pathways. These findings display the wide portfolio of adaptive responses of neuronal cells to chronic ER stress. ER stress-resistant neuronal cells could be the basis to uncover molecular modulators of adaptation, resistance, and neuroprotection as potential pharmacological targets for preventing neurodegeneration.

Enhanced Harris hawks optimization-based fuzzy k-nearest neighbor algorithm for diagnosis of Alzheimer's disease

In order to stop deterioration and give patients with Alzheimer's disease (AD) early therapy, it is crucial to correctly diagnose AD and its early stage, mild cognitive impairment (MCI). A framework for diagnosing AD is presented in this paper, which includes magnetic resonance imaging (MRI) image preprocessing, feature extraction, and the Fuzzy k-nearest neighbor algorithm (FKNN) model. In particular, the framework's novelty lies in the use of an improved Harris Hawks Optimization (HHO) algorithm named SSFSHHO, which integrates the Sobol sequence and Stochastic Fractal Search (SFS) mechanisms for optimizing the parameters of FKNN. The HHO method improves the quality of the initial population overall by incorporating the Sobol sequence, and the SFS mechanism increases the algorithm's capacity to get out of the local optimum solution. Comparisons with other classical meta-heuristic algorithms, state-of-the-art HHO variants in low and high dimensions, and enhanced meta-heuristic algorithms on 30 typical IEEE CEC2014 benchmark test problems show that the overall performance of SSFSHHO is significantly better than other comparative algorithms. Moreover, the created framework based on the SSFSHHO-FKNN model is employed to classify AD and MCI using MRI scans from the ADNI dataset, achieving high classification performance for 6 representative cases. Experimental findings indicate that the proposed algorithm performs better than a number of high-performance optimization algorithms and classical machine learning algorithms, thus offering a promising approach for AD classification. Additionally, the proposed strategy can successfully identify relevant features and enhance classification performance for AD diagnosis.

A protein-coding gene expression atlas from the brain of pregnant and non-pregnant goats

Background: The brain is an extraordinarily complex organ with multiple anatomical structures involved in highly specialized functions related with behavior and physiological homeostasis. Our goal was to build an atlas of protein-coding gene expression in the goat brain by sequencing the transcriptomes of 12 brain regions in seven female Murciano-Granadina goats, from which three of them were 1-month pregnant. Results: Between 14,889 (cerebellar hemisphere) and 15,592 (pineal gland) protein-coding genes were expressed in goat brain regions, and most of them displayed ubiquitous or broad patterns of expression across tissues. Principal component analysis and hierarchical clustering based on the patterns of mRNA expression revealed that samples from certain brain regions tend to group according to their position in the anterior-posterior axis of the neural tube, i.e., hindbrain (pons and medulla oblongata), midbrain (rostral colliculus) and forebrain (frontal neocortex, olfactory bulb, hypothalamus, and hippocampus). Exceptions to this observation were cerebellum and glandular tissues (pineal gland and hypophysis), which showed highly divergent mRNA expression profiles. Differential expression analysis between pregnant and non-pregnant goats revealed moderate changes of mRNA expression in the frontal neocortex, hippocampus, adenohypophysis and pons, and very dramatic changes in the olfactory bulb. Many genes showing differential expression in this organ are related to olfactory function and behavior in humans. Conclusion: With the exception of cerebellum and glandular tissues, there is a relationship between the cellular origin of sampled regions along the anterior-posterior axis of the neural tube and their mRNA expression patterns in the goat adult brain. Gestation induces substantial changes in the mRNA expression of the olfactory bulb, a finding consistent with the key role of this anatomical structure on the development of maternal behavior.

Cancer and Alzheimer's Inverse Correlation: an Immunogenetic Analysis

Numerous studies have demonstrated an inverse link between cancer and Alzheimer's disease (AD), with data suggesting that people with Alzheimer's have a decreased risk of cancer and vice versa. Although other studies have investigated mechanisms to explain this relationship, the connection between these two diseases remains largely unexplained. Processes seen in cancer, such as decreased apoptosis and increased cell proliferation, seem to be reversed in AD. Given the need for effective therapeutic strategies for AD, comparisons with cancer could yield valuable insights into the disease process and perhaps result in new treatments. Here, through a review of existing literature, we compared the expressions of genes involved in cell proliferation and apoptosis to establish a genetic basis for the reciprocal association between AD and cancer. We discuss an array of genes involved in the aforementioned processes, their relevance to both diseases, and how changes in those genes produce varying effects in either disease.

The expression pattern of GDF15 in human brain changes during aging and in Alzheimer's disease

Introduction

Growth Differentiation Factor 15 (GDF15) is a mitochondrial-stress-responsive molecule whose expression strongly increases with aging and age-related diseases. However, its role in neurodegenerative diseases, including Alzheimer's disease (AD), is still debated.

Methods

We have characterized the expression of GDF15 in brain samples from AD patients and non-demented subjects (controls) of different ages.

Results

Although no difference in CSF levels of GDF15 was found between AD patients and controls, GDF15 was expressed in different brain areas and seems to be predominantly localized in neurons. The ratio between its mature and precursor form was higher in the frontal cortex of AD patients compared to age-matched controls (p < 0.05). Moreover, this ratio was even higher for centenarians (p < 0.01), indicating that aging also affects GDF15 expression and maturation. A lower expression of OXPHOS complexes I, III, and V in AD patients compared to controls was also noticed, and a positive correlation between GDF15 and IL-6 mRNA levels was observed. Finally, when GDF15 was silenced in vitro in dermal fibroblasts, a decrease in OXPHOS complexes transcript levels and an increase in IL-6 levels were observed.

Discussion

Although GDF15 seems not to be a reliable CSF marker for AD, it is highly expressed in aging and AD brains, likely as a part of stress response aimed at counteracting mitochondrial dysfunction and neuroinflammation.

Role of primary aging hallmarks in Alzheimer´s disease

Alzheimer's disease (AD) is the most common neurodegenerative disease, which severely threatens the health of the elderly and causes significant economic and social burdens. The causes of AD are complex and include heritable but mostly aging-related factors. The primary aging hallmarks include genomic instability, telomere wear, epigenetic changes, and loss of protein stability, which play a dominant role in the aging process. Although AD is closely associated with the aging process, the underlying mechanisms involved in AD pathogenesis have not been well characterized. This review summarizes the available literature about primary aging hallmarks and their roles in AD pathogenesis. By analyzing published literature, we attempted to uncover the possible mechanisms of aberrant epigenetic markers with related enzymes, transcription factors, and loss of proteostasis in AD. In particular, the importance of oxidative stress-induced DNA methylation and DNA methylation-directed histone modifications and proteostasis are highlighted. A molecular network of gene regulatory elements that undergoes a dynamic change with age may underlie age-dependent AD pathogenesis, and can be used as a new drug target to treat AD.

Preliminary exploration of the co-regulation of Alzheimer's disease pathogenic genes by microRNAs and transcription factors

Background

Alzheimer's disease (AD) is the most common form of age-related neurodegenerative disease. Unfortunately, due to the complexity of pathological types and clinical heterogeneity of AD, there is a lack of satisfactory treatment for AD. Previous studies have shown that microRNAs and transcription factors can modulate genes associated with AD, but the underlying pathophysiology remains unclear.

Methods

The datasets GSE1297 and GSE5281 were downloaded from the gene expression omnibus (GEO) database and analyzed to obtain the differentially expressed genes (DEGs) through the "R" language "limma" package. The GSE1297 dataset was analyzed by weighted correlation network analysis (WGCNA), and the key gene modules were selected. Next, gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analysis for the key gene modules were performed. Then, the protein-protein interaction (PPI) network was constructed and the hub genes were identified using the STRING database and Cytoscape software. Finally, for the GSE150693 dataset, the "R" package "survivation" was used to integrate the data of survival time, AD transformation status and 35 characteristics, and the key microRNAs (miRNAs) were selected by Cox method. We also performed regression analysis using least absolute shrinkage and selection operator (Lasso)-Cox to construct and validate prognostic features associated with the four key genes using different databases. We also tried to find drugs targeting key genes through DrugBank database.

Results

GO and KEGG enrichment analysis showed that DEGs were mainly enriched in pathways regulating chemical synaptic transmission, glutamatergic synapses and Huntington's disease. In addition, 10 hub genes were selected from the PPI network by using the algorithm Between Centrality. Then, four core genes (TBP, CDK7, GRM5, and GRIA1) were selected by correlation with clinical information, and the established model had very good prognosis in different databases. Finally, hsa-miR-425-5p and hsa-miR-186-5p were determined by COX regression, AD transformation status and aberrant miRNAs.

Conclusion

In conclusion, we tried to construct a network in which miRNAs and transcription factors jointly regulate pathogenic genes, and described the process that abnormal miRNAs and abnormal transcription factors TBP and CDK7 jointly regulate the transcription of AD central genes GRM5 and GRIA1. The insights gained from this study offer the potential AD biomarkers, which may be of assistance to the diagnose and therapy of AD.

Somatic copy number variant load in neurons of healthy controls and Alzheimer's disease patients

The possible role of somatic copy number variations (CNVs) in Alzheimer's disease (AD) aetiology has been controversial. Although cytogenetic studies suggested increased CNV loads in AD brains, a recent single-cell whole-genome sequencing (scWGS) experiment, studying frontal cortex brain samples, found no such evidence. Here we readdressed this issue using low-coverage scWGS on pyramidal neurons dissected via both laser capture microdissection (LCM) and fluorescence activated cell sorting (FACS) across five brain regions: entorhinal cortex, temporal cortex, hippocampal CA1, hippocampal CA3, and the cerebellum. Among reliably detected somatic CNVs identified in 1301 cells obtained from the brains of 13 AD patients and 7 healthy controls, deletions were more frequent compared to duplications. Interestingly, we observed slightly higher frequencies of CNV events in cells from AD compared to similar numbers of cells from controls (4.1% vs. 1.4%, or 0.9% vs. 0.7%, using different filtering approaches), although the differences were not statistically significant. On the technical aspects, we observed that LCM-isolated cells show higher within-cell read depth variation compared to cells isolated with FACS. To reduce within-cell read depth variation, we proposed a principal component analysis-based denoising approach that significantly improves signal-to-noise ratios. Lastly, we showed that LCM-isolated neurons in AD harbour slightly more read depth variability than neurons of controls, which might be related to the reported hyperploid profiles of some AD-affected neurons.

The Brilliance of the Zebrafish Model: Perception on Behavior and Alzheimer's Disease

Alzheimer's disease (AD) has become increasingly prevalent in the elderly population across the world. It's pathophysiological markers such as overproduction along with the accumulation of amyloid beta (Aβ) plaques and neurofibrillary tangles (NFT) are posing a serious challenge to novel drug development processes. A model which simulates the human neurodegenerative mechanism will be beneficial for rapid screening of potential drug candidates. Due to the comparable neurological network with humans, zebrafish has emerged as a promising AD model. This model has been thoroughly validated through research in aspects of neuronal pathways analogous to the human brain. The cholinergic, glutamatergic, and GABAergic pathways, which play a role in the manifested behavior of the zebrafish, are well defined. There are several behavioral models in both adult zebrafish and larvae to establish various aspects of cognitive impairment including spatial memory, associative memory, anxiety, and other such features that are manifested in AD. The zebrafish model eliminates the shortcomings of previously recognized mammalian models, in terms of expense, extensive assessment durations, and the complexity of imaging the brain to test the efficacy of therapeutic interventions. This review highlights the various models that analyze the changes in the normal behavioral patterns of the zebrafish when exposed to AD inducing agents. The mechanistic pathway adopted by drugs and novel therapeutic strategies can be explored via these behavioral models and their efficacy to slow the progression of AD can be evaluated.

Combination of magnesium supplementation with treadmill exercise improves memory deficit in aged rats by enhancing hippocampal neurogenesis and plasticity: a functional and histological study

This study aimed to investigate the possible ameliorative effects of co-supplementation with Mg²⁺ and treadmill exercise on memory deficit in aged rats. Fifty male albino rats (10 young and 40 aged rats) were divided into 5 groups (10 rats/group): young, aged sedentary, aged exercised, aged Mg²⁺-supplemented, and aged exercised and Mg²⁺-supplemented. Memory was assessed using the Y-maze and novel object recognition tests. Plasma samples were collected for measurement of C-reactive protein (CRP). Subsequently, brain malondialdehyde and catalase levels were measured. Histological and immunohistochemical analyses of the hippocampi were performed. Our results showed impaired memory in aged sedentary rats, with significantly elevated plasma CRP and brain malondialdehyde levels and decreased brain catalase. The hippocampus of aged sedentary rats showed cellular degeneration, downregulation of synaptophysin (SYP) and proliferating cell nuclear antigen (PCNA), and upregulation of glial fibrillary acidic protein (GFAP) and caspase-3. Mg²⁺ supplementation and/or treadmill exercise significantly improved memory tests in aged rats, which could be explained by the upregulation of hippocampal SYP and PCNA expression and downregulation of GFAP and caspase-3 expression with antioxidant and anti-inflammatory mechanisms. The combined therapy had a better effect than both treatments alone, confirming the role of Mg²⁺ supplementation with physical exercise in enhancing age-related memory deficit. Novelty: Magnesium supplementation with treadmill exercise improves memory deficit in aged rats. The possible mechanisms are upregulation of the hippocampal synaptophysin and PCNA, downregulation of GFAP and caspase-3, the antioxidant and anti-inflammatory mechanisms.

Behavioral and hypothalamic transcriptome analyses reveal sex-specific responses to phenanthrene exposure in the fathead minnow (Pimephales promelas)

Environmental concentrations of the polycyclic aromatic hydrocarbon phenanthrene can become elevated with petroleum processing, industrial activities, and urban run-off into waterbodies. However, mechanisms related to its neurotoxicity in fish are not fully described. Here, we exposed adult fathead minnows (FHM) to an average measured concentration of 202 μg phenanthrene/L over a 47-d period. Behaviors of male and female FHM were assessed using a novel aquarium test. Phenanthrene exposed females displayed equilibrium loss, while phenanthrene exposed males spent less time in the aquarium bottom, suggesting phenanthrene reduced anxiety-related behavior. To elucidate putative mechanisms underlying behaviors, we determined the hypothalamic transcriptome profile, a critical integration centre for the regulation of behaviors. There were 1075 hypothalamic transcripts differentially expressed between males and females (sex-specific) while 15 transcripts were phenanthrene-specific. Thus, sex of the animal was more pervasive at influencing the transcriptome compared to phenanthrene and this may partially explain the divergent behavioral responses between sexes. Transcripts altered by phenanthrene included palmitoylated 3 membrane protein, plectin 1,ATP synthase membrane subunit c, and mitochondrial ribosomal protein S11. Gene set enrichment analysis revealed less than 5% of the gene networks perturbed by phenanthrene were shared between males and females, thus phenanthrene altered the hypothalamic transcriptome in a sex-specific manner. Gene networks shared between both sexes and associated with phenanthrene-induced neurotoxicity included processes related to mitochondrial respiratory chain dysfunction, epinephrine/norepinephrine release, and glutamate biosynthesis pathways. Such energy deficits and neurotransmitter disruptions are hypothesized to lead to behavioral deficits in fish. This study provides mechanistic insights into phenanthrene-induced neurotoxicity and how it may relate to changes in fish behaviors.

Cell competition from development to neurodegeneration

Cell competition is a process by which suboptimal cells are eliminated to the benefit of cells with higher fitness. It is a surveillance mechanism that senses differences in the fitness status by several modes, such as expression of fitness fingerprints, survival factor uptake rate and resistance to mechanical stress. Fitness fingerprints-mediated cell competition recognizes isoforms of the transmembrane protein Flower, and translates the relative fitness of cells into distinct fates through the Flower code. Impairments in cell competition potentiate the development of diseases like cancer and ageing-related pathologies. In cancer, malignant cells acquire a supercompetitor behaviour, killing the neighbouring cells and overtaking the tissue, thus avoiding elimination. Neurodegenerative disorders affect millions of people and are characterized by cognitive decline and locomotor deficits. Alzheimer's disease is the most common form of dementia, and one of the largely studied diseases. However, the cellular processes taking place remain unclear. Drosophila melanogaster is an emerging neurodegeneration model due to its versatility as a tool for genetic studies. Research in a Drosophila Alzheimer's disease model detected fitness markers in the suboptimal and hyperactive neurons, thus establishing a link between cell competition and Alzheimer's disease. In this Review, we overview cell competition and the new insights related to neurodegenerative disorders, and discuss how research in the field might contribute to the development of new therapeutic targets for these diseases.

New insights into human prefrontal cortex aging with a lipidomics approach

INTRODUCTION

Human prefrontal cortex (hPFC) is a recent evolutionarily developed brain region involved in cognitive functions. Human cognitive functions decline during aging. Yet the molecular mechanisms underlying the functional deterioration of the neural cells of this brain region still remain to be fully described.

AREAS COVERED

In this review, we explore the role of lipids in hPFC aging. Firstly, we briefly consider the approaches used to identify lipid species in brain tissue with special attention paid to a lipidomics analysis. Then, as the evolution process has conferred a specific lipid profile on the hPFC, we consider the lipidome of hPFC. In addition, the role of lipids in hPFC aging, and in particular, the cognitive decline associated with aging, is discussed. Finally, nutritional and pharmacological interventions designed to modulate this process are examined. It is suggested that the dysfunction of key cellular processes secondarily to the damage of lipid membrane underlies the cognitive decline of hPFC during aging.

EXPERT OPINION

Lipidomics methods are and will continue to be key tools in the effort to gain additional insights into the aging of the human brain.

Reassessment of Pioglitazone for Alzheimer's Disease

Alzheimer's disease is a quintessential 'unmet medical need', accounting for ∼65% of progressive cognitive impairment among the elderly, and 700,000 deaths in the United States in 2020. In 2019, the cost of caring for Alzheimer's sufferers was $244B, not including the emotional and physical toll on caregivers. In spite of this dismal reality, no treatments are available that reduce the risk of developing AD or that offer prolonged mitiagation of its most devestating symptoms. This review summarizes key aspects of the biology and genetics of Alzheimer's disease, and we describe how pioglitazone improves many of the patholophysiological determinants of AD. We also summarize the results of pre-clinical experiments, longitudinal observational studies, and clinical trials. The results of animal testing suggest that pioglitazone can be corrective as well as protective, and that its efficacy is enhanced in a time- and dose-dependent manner, but the dose-effect relations are not monotonic or sigmoid. Longitudinal cohort studies suggests that it delays the onset of dementia in individuals with pre-existing type 2 diabetes mellitus, which small scale, unblinded pilot studies seem to confirm. However, the results of placebo-controlled, blinded clinical trials have not borne this out, and we discuss possible explanations for these discrepancies.

Transcriptional, Behavioral and Biochemical Profiling in the 3xTg-AD Mouse Model Reveals a Specific Signature of Amyloid Deposition and Functional Decline in Alzheimer's Disease

Alzheimer’s disease (AD)-related degenerative decline is associated to the presence of amyloid beta (Aβ) plaque lesions and neuro fibrillary tangles (NFT). However, the precise molecular mechanisms linking Aβ deposition and neurological decline are still unclear. Here we combine genome-wide transcriptional profiling of the insular cortex of 3xTg-AD mice and control littermates from early through to late adulthood (2–14 months of age), with behavioral and biochemical profiling in the same animals to identify transcriptional determinants of functional decline specifically associated to build-up of Aβ deposits. Differential expression analysis revealed differentially expressed genes (DEGs) in the cortex long before observed onset of behavioral symptoms in this model. Using behavioral and biochemical data derived from the same mice and samples, we found that down but not up-regulated DEGs show a stronger average association with learning performance than random background genes in control not seen in AD mice. Conversely, these same genes were found to have a stronger association with Aβ deposition than background genes in AD but not in control mice, thereby identifying these genes as potential intermediaries between abnormal Aβ/NFT deposition and functional decline. Using a complementary approach, gene ontology analysis revealed a highly significant enrichment of learning and memory, associative, memory, and cognitive functions only among down-regulated, but not up-regulated, DEGs. Our results demonstrate wider transcriptional changes triggered by the abnormal deposition of Aβ/NFT occurring well before behavioral decline and identify a distinct set of genes specifically associated to abnormal Aβ protein deposition and cognitive decline.

Copper Toxicity Links to Pathogenesis of Alzheimer's Disease and Therapeutics Approaches

Alzheimer's disease (AD) is an irreversible, age-related progressive neurological disorder, and the most common type of dementia in aged people. Neuropathological lesions of AD are neurofibrillary tangles (NFTs), and senile plaques comprise the accumulated amyloid-beta (Aβ), loaded with metal ions including Cu, Fe, or Zn. Some reports have identified metal dyshomeostasis as a neurotoxic factor of AD, among which Cu ions seem to be a central cationic metal in the formation of plaque and soluble oligomers, and have an essential role in the AD pathology. Cu-Aβ complex catalyzes the generation of reactive oxygen species (ROS) and results in oxidative damage. Several studies have indicated that oxidative stress plays a crucial role in the pathogenesis of AD. The connection of copper levels in AD is still ambiguous, as some researches indicate a Cu deficiency, while others show its higher content in AD, and therefore there is a need to increase and decrease its levels in animal models, respectively, to study which one is the cause. For more than twenty years, many in vitro studies have been devoted to identifying metals' roles in Aβ accumulation, oxidative damage, and neurotoxicity. Towards the end, a short review of the modern therapeutic approach in chelation therapy, with the main focus on Cu ions, is discussed. Despite the lack of strong proofs of clinical advantage so far, the conjecture that using a therapeutic metal chelator is an effective strategy for AD remains popular. However, some recent reports of genetic-regulating copper transporters in AD models have shed light on treating this refractory disease. This review aims to succinctly present a better understanding of Cu ions' current status in several AD features, and some conflicting reports are present herein.

Antioxidant and Neuroprotective Effects of Caffeine against Alzheimer's and Parkinson's Disease: Insight into the Role of Nrf-2 and A2AR Signaling

This paper reviews the results of studies conducted on the role of caffeine in the management of different neurological disorders, such as Parkinson's disease (PD) and Alzheimer's disease (AD). To highlight the potential role of caffeine in managing different neurodegenerative diseases, we identified studies by searching PubMed, Web of Science, and Google Scholar by scrutinizing the lists of pertinent publications. According to the collected overall findings, caffeine may reduce the elevated oxidative stress; inhibit the activation of adenosine A2A, thereby regulating the accumulation of Aβ; reduce the hyperphosphorylation of tau; and reduce the accumulation of misfolded proteins, such as α-synuclein, in Alzheimer's and Parkinson's diseases. The studies have suggested that caffeine has promising protective effects against different neurodegenerative diseases and that these effects may be used to tackle the neurological diseases and/or their consequences. Here, we review the ongoing research on the role of caffeine in the management of different neurodegenerative disorders, focusing on AD and PD. The current findings suggest that caffeine produces potent antioxidant, inflammatory, and anti-apoptotic effects against different models of neurodegenerative disease, including AD, PD, and other neurodegenerative disorders. Caffeine has shown strong antagonistic effects against the adenosine A2A receptor, which is a microglial receptor, and strong agonistic effects against nuclear-related factor-2 (Nrf-2), thereby regulating the cellular homeostasis at the brain by reducing oxidative stress, neuroinflammation, regulating the accumulation of α-synuclein in PD and tau hyperphosphorylation, amyloidogenesis, and synaptic deficits in AD, which are the cardinal features of these neurodegenerative diseases.

Cognitive function and cerebellar morphometric changes relate to abnormal intra-cerebellar and cerebro-cerebellum functional connectivity in old adults

INTRODUCTION

Numerous structural studies have already reported volumetric reduction in cerebellum with aging. However, there are still limited studies particularly focusing on analysis of the cerebellar resting state FC in old adults. Even so, the least related studies were unable to include some important cerebellar lobules due to limited cerebellum segmentation methods.

OBJECTIVE

The purpose of this study is to explore cognitive function in relation to cerebellar lobular morphometry and cortico-cerebellar connectivity changes in old adults' lifespan by incorporating previously undetected cerebellar lobules.

METHODS

This study includes a sample of 264 old adults subdivided into five cognitively normal age groups (G1 through G5). Cerebellum Segmentation (CERES) software was used to obtain morphometric measures and brain masks of all the 24 cerebellar lobules. We then defined individual lobules as seed regions and mapped the whole-brain to get functional connectivity maps. To analyze age group differences in cortico-cerebellar connectivity and cerebellar lobular volume, we used one way ANOVA and post hoc analysis was performed for multiple comparisons using Bonferroni method.

RESULTS

Our results report cerebellar lobular volumetric reduction, disrupted intra-cerebellar connectivity and significant differences in cortico-cerebellar resting state FC across age groups. In addition, our results show that disrupted FC between left Crus-II and right ACC relates to well emotion regulation and cognitive decline and is associated with poor performance on TMT-B and logical memory tests in older adults.

CONCLUSION

Overall, our findings confirm that as humans get older and older, the cerebellar lobular volumes as well as the cortico-cerebellar functional connectivity are affected and hence reduces cognition.

Comparative functional genomic analysis of Alzheimer's affected and naturally aging brains

Background

Alzheimer’s disease (AD) is a prevalent progressive neurodegenerative human disease whose cause remains unclear. Numerous initially highly hopeful anti-AD drugs based on the amyloid-β (Aβ) hypothesis of AD have failed recent late-phase tests. Natural aging (AG) is a high-risk factor for AD. Here, we aim to gain insights in AD that may lead to its novel therapeutic treatment through conducting meta-analyses of gene expression microarray data from AG and AD-affected brain.

Methods

Five sets of gene expression microarray data from different regions of AD (hereafter, ALZ when referring to data)-affected brain, and one set from AG, were analyzed by means of the application of the methods of differentially expressed genes and differentially co-expressed gene pairs for the identification of putatively disrupted biological pathways and associated abnormal molecular contents.

Results

Brain-region specificity among ALZ cases and AG-ALZ differences in gene expression and in KEGG pathway disruption were identified. Strong heterogeneity in AD signatures among the five brain regions was observed: HC/PC/SFG showed clear and pronounced AD signatures, MTG moderately so, and EC showed essentially none. There were stark differences between ALZ and AG. OXPHOS and Proteasome were the most disrupted pathways in HC/PC/SFG, while AG showed no OXPHOS disruption and relatively weak Proteasome disruption in AG. Metabolic related pathways including TCA cycle and Pyruvate metabolism were disrupted in ALZ but not in AG. Three pathogenic infection related pathways were disrupted in ALZ. Many cancer and signaling related pathways were shown to be disrupted AG but far less so in ALZ, and not at all in HC. We identified 54 “ALZ-only” differentially expressed genes, all down-regulated and which, when used to augment the gene list of the KEGG AD pathway, made it significantly more AD-specific.

Microarray Analysis of Differential Gene Expression in Alzheimer's Disease Identifies Potential Biomarkers with Diagnostic Value

BACKGROUND Alzheimer disease (AD) is a common and fatal subtype of dementia that remains a challenge to diagnose and treat. This study aimed to identify potential biomarkers that influence the prognosis of AD. MATERIAL AND METHODS A total of 6 gene expression profiles from the Gene Expression Omnibus (GEO) database were assessed for their potential as AD biomarkers. We identified differentially expressed genes (DEGs) using the prediction analysis for microarray (PAM) algorithm and obtained hub genes through the analysis of the protein-protein interaction (PPI) network and module analysis. RESULTS We identified 6 gene expression profiles from the GEO database and assessed their potential as AD biomarkers. Shared gene sets were extracted and integrated into large expression profile matrices. We identified 2514 DEGs including 68 upregulated- and 2446 downregulated genes through analysis of the limma package. We screened 379 significant DEGs including 68 upregulated and 307 downregulated genes for their ability to distinguish AD from control samples using PAM algorithm. Functional enrichment of the 379 target genes was produced from Database for Annotation, Visualization and Integrated Discovery.(DAVID) and included histone function, beta receptor signaling, cell growth, and angiogenesis. The downregulated genes were significantly enriched in MAPK signaling, synaptic signaling, neuronal apoptosis and AD associated pathways. Upon analysis of the PPI network, 32 hub genes including ENO2, CCT2, CALM2, ACACB, ATP5B, MDH1, and PP2CA were screened. Of these hub genes, NFKBIA and ACACB were upregulated and 29 genes were downregulated in AD patients. CONCLUSIONS We screened 379 significant DEGs as potential biomarkers of AD using PAM and obtained 32 hub genes through PPI network and module analysis. These findings reveal new potential AD biomarkers with prognostic and therapeutic value.

Redox lipidomics to better understand brain aging and function

Human prefrontal cortex (PFC) is a recently evolutionary emerged brain region involved in cognitive functions. Human cognitive abilities decline during aging. Yet the molecular mechanisms that sustain the preservation or deterioration of neurons and PFC functions are unknown. In this review, we focus on the role of lipids in human PFC aging. As the evolution of brain lipid concentrations is particularly accelerated in the human PFC, conferring a specific lipid profile, a brief approach to the lipidome of PFC was consider along with the relationship between lipids and lipoxidative damage, and the role of lipids in human PFC aging. In addition, the specific targets of lipoxidative damage in human PFC, the affected biological processes, and their potential role in the cognitive decline associated with aging are discussed. Finally, interventions designed to modify this process are considered. We propose that the dysfunction of key biological processes due to selective protein lipoxidation damage may have a role the cognitive decline of PFC during aging.

Lipid and Lipid Raft Alteration in Aging and Neurodegenerative Diseases: A Window for the Development of New Biomarkers

Lipids in the brain are major components playing structural functions as well as physiological roles in nerve cells, such as neural communication, neurogenesis, synaptic transmission, signal transduction, membrane compartmentalization, and regulation of gene expression. Determination of brain lipid composition may provide not only essential information about normal brain functioning, but also about changes with aging and diseases. Indeed, deregulations of specific lipid classes and lipid homeostasis have been demonstrated in neurodegenerative disorders such as Alzheimer's disease (AD) and Parkinson's disease (PD). Furthermore, recent studies have shown that membrane microdomains, named lipid rafts, may change their composition in correlation with neuronal impairment. Lipid rafts are key factors for signaling processes for cellular responses. Lipid alteration in these signaling platforms may correlate with abnormal protein distribution and aggregation, toxic cell signaling, and other neuropathological events related with these diseases. This review highlights the manner lipid changes in lipid rafts may participate in the modulation of neuropathological events related to AD and PD. Understanding and characterizing these changes may contribute to the development of novel and specific diagnostic and prognostic biomarkers in routinely clinical practice.

Novel methods for integration and visualization of genomics and genetics data in Alzheimer's disease

INTRODUCTION

Numerous omics studies have been conducted to understand the molecular networks involved in Alzheimer's disease (AD), but the pathophysiology is still not completely understood; new approaches that enable neuroscientists to better interpret the results of omics analysis are required.

METHODS

We have developed advanced methods to analyze and visualize publicly-available genomics and genetics data. The tools include a composite clinical-neuropathological score for defining AD, gene expression maps in the brain, and networks integrating omics data to understand the impact of polymorphisms on AD pathways.

RESULTS

We have analyzed over 50 public human gene expression data sets, spanning 19 different brain regions and encompassing three separate cohorts. We integrated genome-wide association studies with expression data to identify important genes in the pathophysiology of AD, which provides further insight into the calcium signaling and calcineurin pathways.

DISCUSSION

Biologists can use these freely-available tools to obtain a comprehensive, information-rich view of the pathways in AD.

Identification of a noncoding RNA‑mediated gene pair‑based regulatory module in Alzheimer's disease

Alzheimer's disease (AD) is the most common type of neurological disorder that results from brain cell death; however, not all brain regions are simultaneously affected to the same extent. Despite single biomarkers for AD having been determined on a genome-wide scale, the differential co-expression in gene pairs between regions and interactions with other types of cellular molecules, particularly non-coding (nc)RNAs, are often overlooked in studies investigating the underlying mechanisms associated with AD. In the present study, based on 1,548 samples obtained from a cohort of 90 patients with AD spanning 19 brain regions, a gene-pair based method was established for the classification of 19 brain regions into seven different groups, including marked disparate groupings of six single regions and a cluster of another 13 regions as revealed by principal component analysis (PCA). To further investigate the different underlying mechanisms associated with each group, five highly interconnected functional modules of the protein-protein interaction network were demonstrated to characterize the seven region groups containing six single groups and 13 clustered regions based on 4,731 gene-pairs. Genes in two of the functional modules exhibited a strong association with pathways associated with the nervous system, including cholinergic synapses, circadian entrainment and dopaminergic synapses. Notably, following integration of these two modules with a ncRNA-mediated network, one module demonstrated a strong association with micro (mi)RNAs, which were revealed to interact with numerous long non-coding (lnc)RNAs associated with AD, such as metastasis associated lung adenocarcinoma transcript 1 and taurine upregulated 1. This suggested that mRNAs and lncRNAs may represent competing endogenous RNAs for binding with miRNAs. Thus, these results indicated that the ncRNA-mediated gene regulatory module detected by the established gene pair-based method may further the understanding of underlying mechanisms associated with AD as well as aid the development of novel therapeutic strategies for the treatment of patients with AD.

Analytical Strategy to Prioritize Alzheimer's Disease Candidate Genes in Gene Regulatory Networks Using Public Expression Data

Alzheimer’s disease (AD) progressively destroys cognitive abilities in the aging population with tremendous effects on memory. Despite recent progress in understanding the underlying mechanisms, high drug attrition rates have put a question mark behind our knowledge about its etiology. Re-evaluation of past studies could help us to elucidate molecular-level details of this disease. Several methods to infer such networks exist, but most of them do not elaborate on context specificity and completeness of the generated networks, missing out on lesser-known candidates. In this study, we present a novel strategy that corroborates common mechanistic patterns across large scale AD gene expression studies and further prioritizes potential biomarker candidates. To infer gene regulatory networks (GRNs), we applied an optimized version of the BC3Net algorithm, named BC3Net10, capable of deriving robust and coherent patterns. In principle, this approach initially leverages the power of literature knowledge to extract AD specific genes for generating viable networks. Our findings suggest that AD GRNs show significant enrichment for key signaling mechanisms involved in neurotransmission. Among the prioritized genes, well-known AD genes were prominent in synaptic transmission, implicated in cognitive deficits. Moreover, less intensive studied AD candidates (STX2, HLA-F, HLA-C, RAB11FIP4, ARAP3, AP2A2, ATP2B4, ITPR2, and ATP2A3) are also involved in neurotransmission, providing new insights into the underlying mechanism. To our knowledge, this is the first study to generate knowledge-instructed GRNs that demonstrates an effective way of combining literature-based knowledge and data-driven analysis to identify lesser known candidates embedded in stable and robust functional patterns across disparate datasets.

Normalization and the Cholinergic Microcircuit: A Unified Basis for Attention

Attention alters three key properties of population neural activity - firing rate, rate variability, and shared variability between neurons. All three properties are well explained by a single canonical computation - normalization - that acts across hierarchically integrated brain systems. Combining data from rodents and nonhuman primates, we argue that cortical cholinergic modulation originating from the basal forebrain closely mimics the effects of directed attention on these three properties of population neural activity. Cholinergic modulation of the cortical microcircuit underlying normalization may represent a key biological basis for the rapid and flexible changes in population neuronal coding that are required by directed attention.

Altered function of neuronal L-type calcium channels in ageing and neuroinflammation: Implications in age-related synaptic dysfunction and cognitive decline

The rapid developments in science have led to an increase in human life expectancy and thus, ageing and age-related disorders/diseases have become one of the greatest concerns in the 21st century. Cognitive abilities tend to decline as we get older. This age-related cognitive decline is mainly attributed to aberrant changes in synaptic plasticity and neuronal connections. Recent studies show that alterations in Ca²⁺ homeostasis underlie the increased vulnerability of neurons to age-related processes like cognitive decline and synaptic dysfunctions. Dysregulation of Ca²⁺ can lead to dramatic changes in neuronal functions. We discuss in this review, the recent advances on the potential role of dysregulated Ca²⁺ homeostasis through altered function of L-type voltage gated Ca²⁺ channels (LTCC) in ageing, with an emphasis on cognitive decline. This review therefore focuses on age-related changes mainly in the hippocampus, and with mention of other brain areas, that are important for learning and memory. This review also highlights age-related memory deficits via synaptic alterations and neuroinflammation. An understanding of these mechanisms will help us formulate strategies to reverse or ameliorate age-related disorders like cognitive decline.

Environmental Chemicals and Aging

PURPOSE OF REVIEW

Innovations in agriculture and medicine as well as industrial and domestic technologies are essential for the growing and aging global population. These advances generally require the use of novel natural or synthetic chemical agents with the potential to affect human health. Here, we attempt to highlight environmental chemicals and select drugs with the potential to exacerbate aging by directly affecting molecular aging cascades focusing particular attention on the brain. Finally, we call attention to some potential fruitful areas of research, particularly with advanced molecular profiling that could aid in prevention or mitigation of environmental chemical toxic influences in the periphery and the brain.

RECENT FINDINGS

We briefly summarize new research and highlight a recent study designed to prospectively identify agrochemicals with the potential to induce neurological diseases and place these discoveries into the already rich neurodegeneration and aging literature. Collectively, the research reviewed briefly here highlight chemicals with the true potential to accelerate aging, particularly in the brain, by eliciting elevated free radical stress and mitochondrial dysfunction. We make general recommendations about improved methodological approaches toward identification and regulation of chemicals that are gerontogenic to the brain.

The Endosomal-Lysosomal Pathway Is Dysregulated by APOE4 Expression in Vivo

Possession of the ε4 allele of apolipoprotein E (APOE) is the major genetic risk factor for late-onset Alzheimer's disease (AD). Although numerous hypotheses have been proposed, the precise cause of this increased AD risk is not yet known. In order to gain a more comprehensive understanding of APOE4's role in AD, we performed RNA-sequencing on an AD-vulnerable vs. an AD-resistant brain region from aged APOE targeted replacement mice. This transcriptomics analysis revealed a significant enrichment of genes involved in endosomal–lysosomal processing, suggesting an APOE4-specific endosomal–lysosomal pathway dysregulation in the brains of APOE4 mice. Further analysis revealed clear differences in the morphology of endosomal–lysosomal compartments, including an age-dependent increase in the number and size of early endosomes in APOE4 mice. These findings directly link the APOE4 genotype to endosomal–lysosomal dysregulation in an in vivo, AD pathology-free setting, which may play a causative role in the increased incidence of AD among APOE4 carriers.

Neuronal hyperactivity due to loss of inhibitory tone in APOE4 mice lacking Alzheimer's disease-like pathology

The ε4 allele of apolipoprotein E (APOE) is the dominant genetic risk factor for late-onset Alzheimer’s disease (AD). However, the reason APOE4 is associated with increased AD risk remains a source of debate. Neuronal hyperactivity is an early phenotype in both AD mouse models and in human AD, which may play a direct role in the pathogenesis of the disease. Here, we have identified an APOE4-associated hyperactivity phenotype in the brains of aged APOE mice using four complimentary techniques—fMRI, in vitro electrophysiology, in vivo electrophysiology, and metabolomics—with the most prominent hyperactivity occurring in the entorhinal cortex. Further analysis revealed that this neuronal hyperactivity is driven by decreased background inhibition caused by reduced responsiveness of excitatory neurons to GABAergic inhibitory inputs. Given the observations of neuronal hyperactivity in prodromal AD, we propose that this APOE4-driven hyperactivity may be a causative factor driving increased risk of AD among APOE4 carriers.

The APOE4 allele is the leading risk factor for late-onset Alzheimer’s disease, but how it might contribute to the disease is not clear. Here the authors show that a mouse expressing the human APOE4 allele displays hyperactivity in the entorhinal cortex due to a decreased inhibitory tone, which may in part explain accelerated Alzheimer’s pathology in APOE4 carriers.

Proteomic mapping of differentially vulnerable pre-synaptic populations identifies regulators of neuronal stability in vivo

Synapses are an early pathological target in many neurodegenerative diseases ranging from well-known adult onset conditions such as Alzheimer and Parkinson disease to neurodegenerative conditions of childhood such as spinal muscular atrophy (SMA) and neuronal ceroid lipofuscinosis (NCLs). However, the reasons why synapses are particularly vulnerable to such a broad range of neurodegeneration inducing stimuli remains unknown. To identify molecular modulators of synaptic stability and degeneration, we have used the Cln3^−/− mouse model of a juvenile form of NCL. We profiled and compared the molecular composition of anatomically-distinct, differentially-affected pre-synaptic populations from the Cln3^−/− mouse brain using proteomics followed by bioinformatic analyses. Identified protein candidates were then tested using a Drosophila CLN3 model to study their ability to modify the CLN3-neurodegenerative phenotype in vivo. We identified differential perturbations in a range of molecular cascades correlating with synaptic vulnerability, including valine catabolism and rho signalling pathways. Genetic and pharmacological targeting of key ‘hub’ proteins in such pathways was sufficient to modulate phenotypic presentation in a Drosophila CLN3 model. We propose that such a workflow provides a target rich method for the identification of novel disease regulators which could be applicable to the study of other conditions where appropriate models exist.

A CRISPR Approach to Neurodegenerative Diseases

A major barrier to developing effective therapies for neurodegenerative diseases is our incomplete understanding of the underlying cellular mechanisms. Genetic screens in human-induced pluripotent stem cell-derived neurons can elucidate such mechanisms. Genome-wide screens using CRISPR interference and CRISPR activation provide complementary biological insights and may reveal potential therapeutic targets.

Calcium Hypothesis of Alzheimer's disease and brain aging: A framework for integrating new evidence into a comprehensive theory of pathogenesis

This article updates the Calcium Hypothesis of Alzheimer's disease and brain aging on the basis of emerging evidence since 1994 (The present article, with the subtitle "New evidence for a central role of Ca²⁺ in neurodegeneration," includes three appendices that provide context and further explanations for the rationale for the revisions in the updated hypothesis-the three appendices are as follows: Appendix I "Emerging concepts on potential pathogenic roles of [Ca²⁺]," Appendix II "Future studies to validate the central role of dysregulated [Ca²⁺] in neurodegeneration," and Appendix III "Epilogue: towards a comprehensive hypothesis.") (Marx J. Fresh evidence points to an old suspect: calcium. Science 2007; 318:384-385). The aim is not only to re-evaluate the original key claims of the hypothesis with a critical eye but also to identify gaps in knowledge required to validate relevant claims and delineate additional studies and/or data that are needed. Some of the key challenges for this effort included examination of questions regarding (1) the temporal and spatial relationships of molecular mechanisms that regulate neuronal calcium ion (Ca²⁺), (2) the role of changes in concentration of calcium ion [Ca²⁺] in various subcellular compartments of neurons, (3) how alterations in Ca²⁺ signaling affect the performance of neurons under various conditions, ranging from optimal functioning in a healthy state to conditions of decline and deterioration in performance during aging and in disease, and (4) new ideas about the contributions of aging, genetic, and environmental factors to the causal relationships between dysregulation of [Ca²⁺] and the functioning of neurons (see Appendices I and II). The updated Calcium Hypothesis also includes revised postulates that are intended to promote further crucial experiments to confirm or reject the various predictions of the hypothesis (see Appendix III).

Aging, microglia and cytoskeletal regulation are key factors in the pathological evolution of the APP23 mouse model for Alzheimer's disease

Aging is the key risk factor for Alzheimer's disease (AD). In addition, the amyloid-beta (Aβ) peptide is considered a critical neurotoxic agent in AD pathology. However, the connection between these factors is unclear. We aimed to provide an extensive characterization of the gene expression profiles of the amyloidosis APP23 model for AD and control mice and to evaluate the effect of aging on these profiles. We also correlated our findings to changes in soluble Aβ-levels and other pathological and symptomatic features of the model. We observed a clear biphasic expression profile. The first phase displayed a maturation profile, which resembled features found in young carriers of familial AD mutations. The second phase reflected aging processes and showed similarities to the progression of human AD pathology. During this phase, the model displayed a clear upregulation of microglial activation and lysosomal pathways and downregulation of neuron differentiation and axon guidance pathways. Interestingly, the changes in expression were all correlated to aging in general, but appeared more extensive/accelerated in APP23 mice.

Integrative network analysis of nineteen brain regions identifies molecular signatures and networks underlying selective regional vulnerability to Alzheimer's disease

Background

Alzheimer’s disease (AD) is the most common form of dementia, characterized by progressive cognitive impairment and neurodegeneration. However, despite extensive clinical and genomic studies, the molecular basis of AD development and progression remains elusive.

Methods

To elucidate molecular systems associated with AD, we developed a large scale gene expression dataset from 1053 postmortem brain samples across 19 cortical regions of 125 individuals with a severity spectrum of dementia and neuropathology of AD. We excluded brain specimens that evidenced neuropathology other than that characteristic of AD. For the first time, we performed a pan-cortical brain region genomic analysis, characterizing the gene expression changes associated with a measure of dementia severity and multiple measures of the severity of neuropathological lesions associated with AD (neuritic plaques and neurofibrillary tangles) and constructing region-specific co-expression networks. We rank-ordered 44,692 gene probesets, 1558 co-expressed gene modules and 19 brain regions based upon their association with the disease traits.

Results

The neurobiological pathways identified through these analyses included actin cytoskeleton, axon guidance, and nervous system development. Using public human brain single-cell RNA-sequencing data, we computed brain cell type-specific marker genes for human and determined that many of the abnormally expressed gene signatures and network modules were specific to oligodendrocytes, astrocytes, and neurons. Analysis based on disease severity suggested that: many of the gene expression changes, including those of oligodendrocytes, occurred early in the progression of disease, making them potential translational/treatment development targets and unlikely to be mere bystander result of degeneration; several modules were closely linked to cognitive compromise with lesser association with traditional measures of neuropathology. The brain regional analyses identified temporal lobe gyri as sites associated with the greatest and earliest gene expression abnormalities.

Conclusions

This transcriptomic network analysis of 19 brain regions provides a comprehensive assessment of the critical molecular pathways associated with AD pathology and offers new insights into molecular mechanisms underlying selective regional vulnerability to AD at different stages of the progression of cognitive compromise and development of the canonical neuropathological lesions of AD.

Electronic supplementary material

The online version of this article (doi:10.1186/s13073-016-0355-3) contains supplementary material, which is available to authorized users.

Lipidomics of human brain aging and Alzheimer's disease pathology

Lipids stimulated and favored the evolution of the brain. Adult human brain contains a large amount of lipids, and the largest diversity of lipid classes and lipid molecular species. Lipidomics is defined as "the full characterization of lipid molecular species and of their biological roles with respect to expression of proteins involved in lipid metabolism and function, including gene regulation." Therefore, the study of brain lipidomics can help to unravel the diversity and to disclose the specificity of these lipid traits and its alterations in neural (neurons and glial) cells, groups of neural cells, brain, and fluids such as cerebrospinal fluid and plasma, thus helping to uncover potential biomarkers of human brain aging and Alzheimer disease. This review will discuss the lipid composition of the adult human brain. We first consider a brief approach to lipid definition, classification, and tools for analysis from the new point of view that has emerged with lipidomics, and then turn to the lipid profiles in human brain and how lipids affect brain function. Finally, we focus on the current status of lipidomics findings in human brain aging and Alzheimer's disease pathology. Neurolipidomics will increase knowledge about physiological and pathological functions of brain cells and will place the concept of selective neuronal vulnerability in a lipid context.

DNA methylation and cognitive aging

With ever-increasing elder population, the high incidence of age-related diseases such as neurodegenerative disorders has turned out to be a huge public concern. Especially the elders and their families dreadfully suffer from the learning, behavioral and cognitive impairments. The lack of effective therapies for such a horrible symptom makes a great demanding for biological mechanism study for cognitive aging. Epigenetics is an emerging field that broadens the dimensions of mammalian genome blueprint. It is, unlike genetics, not only inheritable but also reversible. Recent studies suggest that DNA methylation, one of major epigenetic mechanisms, plays a pivotal role in the pathogenesis of age-related neurodegenerations and cognitive defects. In this review, the evolving knowledge of age-related cognitive functions and the potential DNA methylation mechanism of cognitive aging are discussed. That indicates the impairment of DNA methylation may be a crucial but reversible mechanism of behavioral and cognitive related neurodegeneration. The methods to examine the dynamics of DNA methylation patterns at tissue and single cell level and at the representative scale as well as the whole genome single base resolution are also briefly discussed. Importantly, the challenges of DNA methylation mechanism of cognitive aging research are brought up, and the possible solutions to tackle these difficulties are put forward.

Role of the Insulin-Like Growth Factor Type 1 Receptor in the Pathogenesis of Diabetic Encephalopathy

Defective cognitive function is common in patients with diabetes, suggesting that insulin normally exerts anabolic actions in neuron, namely, diabetic encephalopathy. However, because insulin can cross-activate the insulin-like growth factor type 1 receptor (IGF-1R), which also functions in most of tissues, such as muscle and bone, it has been difficult to establish the direct (IGF-1-independent) actions of insulin in the pathogenesis of diabetic encephalopathy. To overcome this problem, we examined insulin signaling and action in primary PC-12 cells engineered for conditional disruption of the IGF-1 receptor (ΔIGF-1R). The results showed that the lower glucose metabolism and high expression of IGF-1R occurred in the brain of the DE rat model. The results also showed the defect of IGF-1R could significantly improve the ability of glucose consumption and enhance sensitivity to insulin-induced IR and Akt phosphorylation in PC12 cells. And meanwhile, IGF-1R allele gene knockout (IGF-1R(neo)) mice treated with HFD/STZ had better cognitive abilities than those of wild mice. Those results indicate that insulin exerts direct anabolic actions in neuron-like cells by activation of its cognate receptor and prove that IGF-1R plays an important role in the pathogenesis of diabetic encephalopathy.