Genomic convergence and network analysis approach to identify candidate genes in Alzheimer's disease

Exploring the triad: VPS35, neurogenesis, and neurodegenerative diseases

Vacuolar protein sorting 35 (VPS35), a critical component of the retromer complex, plays a pivotal role in the pathogenesis of neurodegenerative diseases (NDs). It is involved in protein transmembrane sorting, facilitating the transport from endosomes to the trans-Golgi network (TGN) and plasma membrane. Recent investigations have compellingly associated mutations in the VPS35 gene with neurodegenerative disorders such as Parkinson's and Alzheimer's disease. These genetic alterations are implicated in protein misfolding, disrupted autophagic processes, mitochondrial dysregulation, and synaptic impairment. Furthermore, VPS35 exerts a notable impact on neurogenesis by influencing neuronal functionality, protein conveyance, and synaptic performance. Dysregulation or mutation of VPS35 may escalate the progression of neurodegenerative conditions, underscoring its pivotal role in safeguarding neuronal integrity. This review comprehensively discusses the role of VPS35 and its functional impairments in NDs. Furthermore, we provide an overview of the impact of VPS35 on neurogenesis and further explore the intricate relationship between neurogenesis and NDs. These research advancements offer novel perspectives and valuable insights for identifying potential therapeutic targets in the treatment of NDs.

The CHD family chromatin remodeling enzyme, Kismet, promotes both clathrin-mediated and activity-dependent bulk endocytosis

Chromodomain helicase DNA binding domain (CHD) proteins, including CHD7 and CHD8, remodel chromatin to enable transcriptional programs. Both proteins are important for proper neural development as heterozygous mutations in Chd7 and Chd8 are causative for CHARGE syndrome and correlated with autism spectrum disorders, respectively. Their roles in mature neurons are poorly understood despite influencing the expression of genes required for cell adhesion, neurotransmission, and synaptic plasticity. The Drosophila homolog of CHD7 and CHD8, Kismet (Kis), promotes neurotransmission, endocytosis, and larval locomotion. Endocytosis is essential in neurons for replenishing synaptic vesicles, maintaining protein localization, and preserving the size and composition of the presynaptic membrane. Several forms of endocytosis have been identified including clathrin-mediated endocytosis, which is coupled with neural activity and is the most prevalent form of synaptic endocytosis, and activity-dependent bulk endocytosis, which occurs during periods of intense stimulation. Kis modulates the expression of gene products involved in endocytosis including promoting shaggy/GSK3β expression while restricting PI3K92E. kis mutants electrophysiologically phenocopy a liquid facets mutant in response to paradigms that induce clathrin-mediated endocytosis and activity-dependent bulk endocytosis. Further, kis mutants do not show further reductions in endocytosis when activity-dependent bulk endocytosis or clathrin-mediated endocytosis are pharmacologically inhibited. We find that Kis is important in postsynaptic muscle for proper endocytosis but the ATPase domain of Kis is dispensable for endocytosis. Collectively, our data indicate that Kis promotes both clathrin-mediated endocytosis and activity-dependent bulk endocytosis possibly by promoting transcription of several endocytic genes and maintaining the size of the synaptic vesicle pool.

Leveraging electronic health records and knowledge networks for Alzheimer's disease prediction and sex-specific biological insights

Identification of Alzheimer's disease (AD) onset risk can facilitate interventions before irreversible disease progression. We demonstrate that electronic health records from the University of California, San Francisco, followed by knowledge networks (for example, SPOKE) allow for (1) prediction of AD onset and (2) prioritization of biological hypotheses, and (3) contextualization of sex dimorphism. We trained random forest models and predicted AD onset on a cohort of 749 individuals with AD and 250,545 controls with a mean area under the receiver operating characteristic of 0.72 (7 years prior) to 0.81 (1 day prior). We further harnessed matched cohort models to identify conditions with predictive power before AD onset. Knowledge networks highlight shared genes between multiple top predictors and AD (for example, APOE, ACTB, IL6 and INS). Genetic colocalization analysis supports AD association with hyperlipidemia at the APOE locus, as well as a stronger female AD association with osteoporosis at a locus near MS4A6A. We therefore show how clinical data can be utilized for early AD prediction and identification of personalized biological hypotheses.

Unraveling the Genetic Landscape of Neurological Disorders: Insights into Pathogenesis, Techniques for Variant Identification, and Therapeutic Approaches

Genetic abnormalities play a crucial role in the development of neurodegenerative disorders (NDDs). Genetic exploration has indeed contributed to unraveling the molecular complexities responsible for the etiology and progression of various NDDs. The intricate nature of rare and common variants in NDDs contributes to a limited understanding of the genetic risk factors associated with them. Advancements in next-generation sequencing have made whole-genome sequencing and whole-exome sequencing possible, allowing the identification of rare variants with substantial effects, and improving the understanding of both Mendelian and complex neurological conditions. The resurgence of gene therapy holds the promise of targeting the etiology of diseases and ensuring a sustained correction. This approach is particularly enticing for neurodegenerative diseases, where traditional pharmacological methods have fallen short. In the context of our exploration of the genetic epidemiology of the three most prevalent NDDs-amyotrophic lateral sclerosis, Alzheimer's disease, and Parkinson's disease, our primary goal is to underscore the progress made in the development of next-generation sequencing. This progress aims to enhance our understanding of the disease mechanisms and explore gene-based therapies for NDDs. Throughout this review, we focus on genetic variations, methodologies for their identification, the associated pathophysiology, and the promising potential of gene therapy. Ultimately, our objective is to provide a comprehensive and forward-looking perspective on the emerging research arena of NDDs.

Pooled analysis of frontal lobe transcriptomic data identifies key mitophagy gene changes in Alzheimer's disease brain

Background

The growing prevalence of Alzheimer's disease (AD) is becoming a global health challenge without effective treatments. Defective mitochondrial function and mitophagy have recently been suggested as etiological factors in AD, in association with abnormalities in components of the autophagic machinery like lysosomes and phagosomes. Several large transcriptomic studies have been performed on different brain regions from AD and healthy patients, and their data represent a vast source of important information that can be utilized to understand this condition. However, large integration analyses of these publicly available data, such as AD RNA-Seq data, are still missing. In addition, large-scale focused analysis on mitophagy, which seems to be relevant for the aetiology of the disease, has not yet been performed.

Methods

In this study, publicly available raw RNA-Seq data generated from healthy control and sporadic AD post-mortem human samples of the brain frontal lobe were collected and integrated. Sex-specific differential expression analysis was performed on the combined data set after batch effect correction. From the resulting set of differentially expressed genes, candidate mitophagy-related genes were identified based on their known functional roles in mitophagy, the lysosome, or the phagosome, followed by Protein-Protein Interaction (PPI) and microRNA-mRNA network analysis. The expression changes of candidate genes were further validated in human skin fibroblast and induced pluripotent stem cells (iPSCs)-derived cortical neurons from AD patients and matching healthy controls.

Results

From a large dataset (AD: 589; control: 246) based on three different datasets (i.e., ROSMAP, MSBB, & GSE110731), we identified 299 candidate mitophagy-related differentially expressed genes (DEG) in sporadic AD patients (male: 195, female: 188). Among these, the AAA ATPase VCP, the GTPase ARF1, the autophagic vesicle forming protein GABARAPL1 and the cytoskeleton protein actin beta ACTB were selected based on network degrees and existing literature. Changes in their expression were further validated in AD-relevant human in vitro models, which confirmed their down-regulation in AD conditions.

Conclusion

Through the joint analysis of multiple publicly available data sets, we identify four differentially expressed key mitophagy-related genes potentially relevant for the pathogenesis of sporadic AD. Changes in expression of these four genes were validated using two AD-relevant human in vitro models, primary human fibroblasts and iPSC-derived neurons. Our results provide foundation for further investigation of these genes as potential biomarkers or disease-modifying pharmacological targets.

Molecular crosstalk between COVID-19 and Alzheimer's disease using microarray and RNA-seq datasets: A system biology approach

Objective

Coronavirus disease 2019 (COVID-19) is an infectious disease caused by Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2). The clinical and epidemiological analysis reported the association between SARS-CoV-2 and neurological diseases. Among neurological diseases, Alzheimer's disease (AD) has developed as a crucial comorbidity of SARS-CoV-2. This study aimed to understand the common transcriptional signatures between SARS-CoV-2 and AD.

Materials and methods

System biology approaches were used to compare the datasets of AD and COVID-19 to identify the genetic association. For this, we have integrated three human whole transcriptomic datasets for COVID-19 and five microarray datasets for AD. We have identified differentially expressed genes for all the datasets and constructed a protein-protein interaction (PPI) network. Hub genes were identified from the PPI network, and hub genes-associated regulatory molecules (transcription factors and miRNAs) were identified for further validation.

Results

A total of 9,500 differentially expressed genes (DEGs) were identified for AD and 7,000 DEGs for COVID-19. Gene ontology analysis resulted in 37 molecular functions, 79 cellular components, and 129 biological processes were found to be commonly enriched in AD and COVID-19. We identified 26 hub genes which includes AKT1, ALB, BDNF, CD4, CDH1, DLG4, EGF, EGFR, FN1, GAPDH, INS, ITGB1, ACTB, SRC, TP53, CDC42, RUNX2, HSPA8, PSMD2, GFAP, VAMP2, MAPK8, CAV1, GNB1, RBX1, and ITGA2B. Specific miRNA targets associated with Alzheimer's disease and COVID-19 were identified through miRNA target prediction. In addition, we found hub genes-transcription factor and hub genes-drugs interaction. We also performed pathway analysis for the hub genes and found that several cell signaling pathways are enriched, such as PI3K-AKT, Neurotrophin, Rap1, Ras, and JAK-STAT.

Conclusion

Our results suggest that the identified hub genes could be diagnostic biomarkers and potential therapeutic drug targets for COVID-19 patients with AD comorbidity.

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.

Development of Computational Correlations among Known Drug Scaffolds and their Target-Specific Non-Coding RNA Scaffolds of Alzheimer's Disease

BACKGROUND

Alzheimer's disease is the most common neurodegenerative disorder. Recent development in sciences has also identified the pivotal role of microRNAs (miRNAs) in AD pathogenesis.

OBJECTIVES

We proposed a novel method to identify AD pathway-specific statistically significant miRNAs from the targets of known AD drugs. Moreover, microRNA scaffolds and corresponding drug scaffolds of different pathways were also discovered.

MATERIAL AND METHODS

A Wilcoxon signed-rank test was performed to identify pathway-specific significant miRNAs. We generated feed-forward loop regulations of microRNA-TF-gene-based networks, studied the minimum free energy structures of pre-microRNA sequences, and clustered those microRNAs with their corresponding structural motifs of robust transcription factors. Conservation analyses of significant microRNAs were done, and the phylogenetic trees were constructed. We identified 3'UTR binding sites and chromosome locations of these significant microRNAs.

RESULTS

In this study, hsa-miR-4261, hsa-miR-153-5p, hsa-miR-6766, and hsa-miR-4319 were identified as key miRNAs for the ACHE pathway and hsa-miR-326, hsa-miR-6133, hsa-miR-4251, hsa-miR-3148, hsa-miR-10527-5p, hsa-miR-527, and hsa-miR-518a were identified as regulatory miRNAs for the NMDA pathway. These miRNAs were regulated by several AD-specific TFs, namely RAD21, FOXA1, and ESR1. It has been observed that anisole and adamantane are important chemical scaffolds to regulate these significant miRNAs.

CONCLUSION

This is the first study that developed a detailed correlation between known AD drug scaffolds and their AD target-specific miRNA scaffolds. This study identified chromosomal locations of microRNAs and corresponding structural scaffolds of transcription factors that may be responsible for miRNA co-regulation for Alzheimer's disease. Our study provides hope for therapeutic improvements in the existing microRNAs by regulating pathways and targets.

Identification of candidate genes associated with clinical onset of Alzheimer's disease

Background and objective

Alzheimer's disease (AD) is the most common type of dementia, with its pathology like beta-amyloid and phosphorylated tau beginning several years before the clinical onset. The aim is to identify genetic risk factors associated with the onset of AD.

Methods

We collected three microarray data of post-mortem brains of AD patients and the healthy from the GEO database and screened differentially expressed genes between AD and healthy control. GO/KEGG analysis was applied to identify AD-related pathways. Then we distinguished differential expressed genes between symptomatic and asymptomatic AD. Feature importance with logistic regression analysis is adopted to identify the most critical genes with symptomatic AD.

Results

Data was collected from three datasets, including 184 AD patients and 132 healthy controls. We found 66 genes to be differently expressed between AD and the control. The pathway enriched in the process of exocytosis, synapse, and metabolism and identified 19 candidate genes, four of which (VSNL1, RTN1, FGF12, and ENC1) are vital.

Conclusion

VSNL1, RTN1, FGF12, and ENC1 may be the essential genes that progress asymptomatic AD to symptomatic AD. Moreover, they may serve as genetic risk factors to identify high-risk individuals showing an earlier onset of AD.

Future Newborns with Opioid-Induced Neonatal Abstinence Syndrome (NAS) Could Be Assessed with the Genetic Addiction Risk Severity (GARS) Test and Potentially Treated Using Precision Amino-Acid Enkephalinase Inhibition Therapy (KB220) as a Frontline Modality Instead of Potent Opioids

In this nonsystematic review and opinion, including articles primarily selected from PubMed, we examine the pharmacological and nonpharmacological treatments of neonatal abstinence syndrome (NAS) in order to craft a reasonable opinion to help forge a paradigm shift in the treatment and prevention of primarily opioid-induced NAS. Newborns of individuals who use illicit and licit substances during pregnancy are at risk for withdrawal, also known as NAS. In the US, the reported prevalence of NAS has increased from 4.0 per 1000 hospital births in 2010 to 7.3 per 1000 hospital births in 2017, which is an 82% increase. The management of NAS is varied and involves a combination of nonpharmacologic and pharmacologic therapy. The preferred first-line pharmacological treatment for NAS is opioid therapy, specifically morphine, and the goal is the short-term improvement in NAS symptomatology. Nonpharmacological therapies are individualized and typically focus on general care measures, the newborn-parent/caregiver relationship, the environment, and feeding. When used appropriately, nonpharmacologic therapies can help newborns with NAS avoid or reduce the amount of pharmacologic therapy required and the length of hospitalization. In addition, genetic polymorphisms of the catechol-o-methyltransferase (COMT) and mu-opioid receptor (OPRM1) genes appear to affect the length of stay and the need for pharmacotherapy in newborns with prenatal opioid exposure. Therefore, based on this extensive literature and additional research, this team of coauthors suggests that, in the future, in addition to the current nonpharmacological therapies, patients with opioid-induced NAS should undergo genetic assessment (i.e., the genetic addiction risk severity (GARS) test), which can subsequently be used to guide DNA-directed precision amino-acid enkephalinase inhibition (KB220) therapy as a frontline modality instead of potent opioids.

RETRACTED: hsa-miR-23a~27a~24-2 cluster members inhibit aggressiveness of breast cancer cells by commonly targeting NCOA1, NLK and RAP1B

This article has been retracted: please see Elsevier Policy on Article Withdrawal (http://www.elsevier.com/locate/withdrawalpolicy). This article has been retracted at the request of the Editor-in-Chief. The corresponding author notified the journal of three examples of image duplication within the published article (two in Figure 3D and one in Figure 4A), and requested a corrigendum. As per journal policy when considering corrigendum requests, the journal requested the authors to provide source data relating to these affected figures. The editorial team noticed 12 additional suspected image duplications within the supplied source data and the corresponding author was informed. Upon submission of revised source data, the editorial team noticed two new suspected image duplications. The editorial team have concerns about the provenance of the data and therefore the Editor-in-Chief decided to retract the article.

Neurogenesis in aging and age-related neurodegenerative diseases

Adult neurogenesis, the process by which neurons are generated in certain areas of the adult brain, declines in an age-dependent manner and is one potential target for extending cognitive healthspan. Aging is a major risk factor for neurodegenerative diseases and, as lifespans are increasing, these health challenges are becoming more prevalent. An age-associated loss in neural stem cell number and/or activity could cause this decline in brain function, so interventions that reverse aging in stem cells might increase the human cognitive healthspan. In this review, we describe the involvement of adult neurogenesis in neurodegenerative diseases and address the molecular mechanistic aspects of neurogenesis that involve some of the key aggregation-prone proteins in the brain (i.e., tau, Aβ, α-synuclein, …). We summarize the research pertaining to interventions that increase neurogenesis and regulate known targets in aging research, such as mTOR and sirtuins. Lastly, we share our outlook on restoring the levels of neurogenesis to physiological levels in elderly individuals and those with neurodegeneration. We suggest that modulating neurogenesis represents a potential target for interventions that could help in the fight against neurodegeneration and cognitive decline.

Association of Circulating Apolipoprotein AI Levels in Patients With Alzheimer's Disease: A Systematic Review and Meta-Analysis

With the development of medicine, our research on Alzheimer's disease (AD) has been further deepened, but the mechanism of its occurrence and development has not been fully revealed, and there is currently no effective treatment method. Several studies have shown that apolipoprotein AI (ApoA-I) can affect the occurrence and development of Alzheimer's disease by binding to amyloid β (Aβ). However, the association between circulating levels of ApoA-I and AD remains controversial. We conducted a meta-analysis of 18 studies published between 1992 and 2017 to determine whether the ApoA-I levels in the blood and cerebrospinal fluid (CSF) are abnormal in AD. Literatures were searched in PubMed, EMBASE and Web of Science databases without language limitations. A pooled subject sample including 1,077 AD patients and 1,271 healthy controls (HCs) was available to assess circulating ApoA-I levels; 747 AD patients and 680 HCs were included for ApoA-I levels in serum; 246 AD patients and 456 HCs were included for ApoA-I levels in plasma; 201 AD patients and 447 HCs were included for ApoA-I levels in CSF. It was found that serum and plasma levels of ApoA-I were significantly reduced in AD patients compared with HCs {[standardized mean difference (SMD) = −1.16; 95% confidence interval (CI) (−1.72, −0.59); P = 0.000] and [SMD = −1.13; 95% CI (−2.05, −0.21); P = 0.016]}. Patients with AD showed a tendency toward higher CSF ApoA-I levels compared with HCs, although this difference was non-significant [SMD = 0.20; 95% CI (−0.16, 0.56); P = 0.273]. In addition, when we analyzed the ApoA-I levels of serum and plasma together, the circulating ApoA-I levels in AD patients was significantly lower [SMD = −1.15; 95% CI (−1.63, −0.66); P = 0.000]. These results indicate that ApoA-I deficiency may be a risk factor of AD, and ApoA-I has the potential to serve as a biomarker for AD and provide experimental evidence for diagnosis of AD.

Systematic Review Registration: PROSPERO, identifier: 325961.

Biomarker Candidates for Alzheimer’s Disease Unraveled through In Silico Differential Gene Expression Analysis

Alzheimer’s disease (AD) is neurodegeneration that accounts for 60–70% of dementia cases. Symptoms begin with mild memory difficulties and evolve towards cognitive impairment. The underlying risk factors remain primarily unclear for this heterogeneous disorder. Bioinformatics is a relevant research tool that allows for identifying several pathways related to AD. Open-access databases of RNA microarrays from the peripheral blood and brain of AD patients were analyzed after background correction and data normalization; the Limma package was used for differential expression analysis (DEA) through statistical R programming language. Data were corrected with the Benjamini and Hochberg approach, and genes with p-values equal to or less than 0.05 were considered to be significant. The direction of the change in gene expression was determined by its variation in the log2-fold change between healthy controls and patients. We performed the functional enrichment analysis of GO using goana and topGO-Limma. The functional enrichment analysis of DEGs showed upregulated (UR) pathways: behavior, nervous systems process, postsynapses, enzyme binding; downregulated (DR) were cellular component organization, RNA metabolic process, and signal transduction. Lastly, the intersection of DEGs in the three databases showed eight shared genes between brain and blood, with potential use as AD biomarkers for blood tests.

Alzheimer's Disease Diagnostics Using miRNA Biomarkers and Machine Learning

BACKGROUND

The current standard for Alzheimer's disease (AD) diagnosis is often imprecise, as with memory tests, and invasive or expensive, as with brain scans. However, the dysregulation patterns of miRNA in blood hold potential as useful biomarkers for the non-invasive diagnosis and even treatment of AD.

OBJECTIVE

The goal of this research is to elucidate new miRNA biomarkers and create a machine-learning (ML) model for the diagnosis of AD.

METHODS

We utilized pathways and target gene networks related to confirmed miRNA biomarkers in AD diagnosis and created multiple models to use for diagnostics based on the significant differences among miRNA expression between blood profiles (serum and plasma).

RESULTS

The best performing serum-based ML model, trained on filtered disease-specific miRNA datasets, was able to identify miRNA biomarkers with 92.0% accuracy and the best performing plasma-based ML model, trained on filtered disease-specific miRNA datasets, was able to identify miRNA biomarkers with 90.9% accuracy. Through analysis of AD implicated miRNA, thousands of descriptors reliant on target gene and pathways were created which can then be used to identify novel biomarkers and strengthen disease diagnosis.

CONCLUSION

Development of a ML model including miRNA and their genomic and pathway descriptors made it possible to achieve considerable accuracy for the prediction of AD.

Validating a Genomic Convergence and Network Analysis Approach Using Association Analysis of Identified Candidate Genes in Alzheimer's Disease

Previously, we demonstrated an integrated genomic convergence and network analysis approach to identify the candidate genes associated with the complex neurodegenerative disorder, Alzheimer's disease (AD). Here, we performed a pilot study to validate the in silico approach by studying the association of genetic variants from three identified critical genes, APOE, EGFR, and ACTB, with AD. A total of 103 patients with AD and 146 healthy controls were recruited. A total of 46 single-nucleotide polymorphisms (SNPs) spanning the three genes were genotyped, of which only 19 SNPs were included in the final analyses after excluding non-polymorphic and Hardy-Weinberg equilibrium-violating SNPs. Apart from our previously reported APOE ε4, four other SNPs in APOE (rs405509, rs7259620, -rs769449, and rs7256173), one in EGFR (rs6970262), and one in ACTB (rs852423) showed a significant association with AD (p < 0.05). Our results validate the reliability of genomic convergence and network analysis approach in identifying the AD-associated candidate genes.

The HIV-1 matrix protein p17 does cross the Blood-Brain Barrier

Human immunodeficiency virus type-1(HIV-1)-associated neurocognitive disorder (HAND) remains an important neurological manifestation in HIV-1-infected (HIV⁺) patients. Furthermore, the HIV-1 matrix protein p17 (p17) detection in the central nervous system (CNS) and its ability to form toxic assemblies in the brain has been recently confirmed. Here we show for the first time using both an in vitro blood-brain barrier (BBB) model and in vivo biodistribution studies in healthy mice that p17 can cross the BBB. There is fast brain uptake with 0.35 ± 0.19% of injected activity per gram of tissue (I.A./g) two minutes after administration, followed by brain accumulation with 0.28 ± 0.09% I.A./g after 1 h. The interaction of p17 with the chemokine receptor 2 (CXCR2) at the surface of brain endothelial cells triggers transcytosis. The present study supports the hypothesis of a direct role of free p17 in neuronal dysfunction in HAND by demonstrating its intrinsic ability to reach the CNS. IMPORTANCE The number of patients affected by HIV-1-associated neurocognitive disorder (HAND) ranges from 30 to 50% of HIV-infected (HIV⁺) patients. The mechanisms leading to HAND development need to be elucidated, but the role of secreted viral proteins, chemokines, and proinflammatory molecules appears to be clear. In particular, the blood-brain barrier (BBB) represents a route for entry into the central nervous system (CNS) thus playing an important role in HAND. Several findings suggest a key role for the HIV-1 matrix protein p17 (p17) as a microenvironmental factor capable of inducing neurocognitive disorders. Here we show, the ability of the p17 to cross the BBB and to reach the CNS thus playing a crucial role in neuronal dysfunction in HAND.

Single-Cell RNA Sequencing of Peripheral Blood Reveals Immune Cell Signatures in Alzheimer's Disease

The peripheral immune system is thought to affect the pathology of the central nervous system in Alzheimer’s disease (AD). However, current knowledge is inadequate for understanding the characteristics of peripheral immune cells in AD. This study aimed to explore the molecular basis of peripheral immune cells and the features of adaptive immune repertoire at a single cell level. We profiled 36,849 peripheral blood mononuclear cells from AD patients with amyloid-positive status and normal controls with amyloid-negative status by 5’ single-cell transcriptome and immune repertoire sequencing using the cell ranger standard analysis procedure. We revealed five immune cell subsets: CD4+ T cells, CD8+ T cells, B cells, natural killer cells, and monocytes–macrophages cells, and disentangled the characteristic alterations of cell subset proportion and gene expression patterns in AD. Thirty-one cell type-specific key genes, comprising abundant human leukocyte antigen genes, and multiple immune-related pathways were identified by protein–protein interaction network and pathway enrichment analysis. We also found high-frequency amplification clonotypes in T and B cells and decreased diversity in T cells in AD. As clone amplification suggested the activation of an adaptive immune response against specific antigens, we speculated that the peripheral adaptive immune response, especially mediated by T cells, may have a role in the pathogenesis of AD. This finding may also contribute to further research regarding disease mechanism and the development of immune-related biomarkers or therapy.

Levetiracetam Treatment Normalizes Levels of Presynaptic Endocytosis Machinery and Restores Nonamyloidogenic APP Processing in App Knock-in Mice

Toxic amyloid-beta (Aβ) peptides, produced by sequential proteolytic cleavage of the amyloid precursor protein (APP), play a key role in the initial stage of Alzheimer's disease (AD). Increasing evidence indicates that Aβ₄₂ induces neuronal circuit hyperexcitability in the early stages of AD pathology. As a result, researchers have investigated treatments that modulate the excitatory/inhibitory imbalance as potential AD therapies. For example, levetiracetam, an atypical antiepileptic drug used to quell hyperexcitability, has garnered recent interest in the AD field, even though its exact mechanism(s) of action remains elusive. Here, we show that in APP knock-in mouse models of amyloid pathology, chronic levetiracetam administration decreases cortical Aβ₄₂ levels and lowers the amyloid plaque burden. In addition, using multiplexed tandem mass tag-quantitative mass spectrometry-based proteomic analysis, we determined that chronic levetiracetam administration selectively normalizes levels of presynaptic endocytic proteins. Finally, we found that levetiracetam treatment selectively lowers beta carboxyl-terminal fragment levels, while the abundance of full-length APP remains unchanged. In summary, this work reports that chronic treatment with levetiracetam serves as a useful therapeutic in AD by normalizing levels of presynaptic endocytic proteins and altering APP cleavage preference, leading to a decrease in both Aβ₄₂ levels and the amyloid plaque burden. These novel findings provide novel evidence for the previously documented therapeutic value of levetiracetam to mitigate AD pathology.

Dynamic changes in the brain protein interaction network correlates with progression of Aβ42 pathology in Drosophila

Alzheimer's disease (AD), the most prevalent form of dementia, is a progressive and devastating neurodegenerative condition for which there are no effective treatments. Understanding the molecular pathology of AD during disease progression may identify new ways to reduce neuronal damage. Here, we present a longitudinal study tracking dynamic proteomic alterations in the brains of an inducible Drosophila melanogaster model of AD expressing the Arctic mutant Aβ42 gene. We identified 3093 proteins from flies that were induced to express Aβ42 and age-matched healthy controls using label-free quantitative ion-mobility data independent analysis mass spectrometry. Of these, 228 proteins were significantly altered by Aβ42 accumulation and were enriched for AD-associated processes. Network analyses further revealed that these proteins have distinct hub and bottleneck properties in the brain protein interaction network, suggesting that several may have significant effects on brain function. Our unbiased analysis provides useful insights into the key processes governing the progression of amyloid toxicity and forms a basis for further functional analyses in model organisms and translation to mammalian systems.

Integrated Genomic Analysis Revealed Associated Genes for Alzheimer's Disease in APOE4 Non-Carriers

BACKGROUND

APOE4 is the strongest genetic risk factor for late-onset Alzheimer's disease (LOAD). LOAD patients carrying or not carrying APOE4 manifest distinct clinico-pathological characteristics. APOE4 has been shown to play a critical role in the pathogenesis of AD by affecting various aspects of pathological processes. However, the pathogenesis involved in LOAD not-carrying APOE4 remains elusive.

OBJECTIVE

We aimed to identify the associated genes involved in LOAD not-carrying APOE4.

METHODS

An integrated genomic analysis of datasets of genome-wide association study, genome-wide expression profiling and genome-wide linkage scan and protein-protein interaction network construction were applied to identify associated gene clusters in APOE4 non-carriers. The role of one of hub gene of an APOE4 non-carrier-associated gene cluster in tau phosphorylation was studied by knockdown and western blot.

RESULTS

We identified 12 gene clusters associated with AD APOE4 non-carriers. The hub genes associated with AD in these clusters were MAPK8, POU2F1, XRCC1, PRKCG, EXOC6, VAMP4, SIRT1, MME, NOS1, ABCA1 and LDLR. The associated genes for APOE4 non-carriers were enriched in hereditary disorder, neurological disease and psychological disorders. Moreover, knockdown of PRKCG to reduce the expression of protein kinase Cγ isoform enhanced tau phosphorylation at Thr181 and Thr231 and the expression of glycogen synthase kinase 3β and cyclin-dependent kinase 5 in the presence of APOE3 but not APOE4.

CONCLUSION

The study provides new insight into the mechanism of distinct pathogenesis of LOAD not carrying APOE4 and prompts the functional exploration of identified genes based on APOE genotypes.

O-GlcNAcylation of Amyloid-β Protein Precursor by Insulin Signaling Reduces Amyloid-β Production

Alzheimer's disease (AD) is caused by the accumulation of neurotoxic amyloid-β (Aβ) peptides. Aβ is derived from amyloid-β protein precursor (AβPP). In the non-amyloidogenic pathway, AβPP is cleaved by α-secretase and γ-secretase at the plasma membrane, excluding Aβ production. Alternatively, AβPP in the plasma membrane is internalized via endocytosis, and delivered to early endosomes and lysosomes, where it is cleaved by β-secretase and γ-secretase. Recent studies have shown that insulin in the periphery crosses the blood-brain barrier, and plays important roles in the brain. Furthermore, impaired insulin signaling has been linked to the progression of AD, and intranasal insulin administration improves memory impairments and cognition. However, the underlying molecular mechanisms of insulin treatment remain largely unknown. To investigate the effects of insulin on AβPP processing, we tested the effects of insulin on neuroblastoma SH-SY5Y cells overexpressing AβPP, and cultured rat cortical neurons. We found that insulin increased the level of cell surface AβPP, decreasing the endocytosis rate of AβPP. Insulin reduced Aβ generation through upregulation of AβPP O-GlcNAcylation via Akt insulin signaling. Our present data suggest that insulin affects Aβ production by regulating AβPP processing through AβPP O-GlcNAcylation. These results provide mechanistic insight into the beneficial effects of insulin, and a possible link between insulin deficient diabetes and cerebral amyloidosis in the pathogenesis of AD.

Meta-Analysis of Gene Expression Changes in the Blood of Patients with Mild Cognitive Impairment and Alzheimer's Disease Dementia

Background: Dementia is a major public health concern affecting approximately 47 million people worldwide. Mild cognitive impairment (MCI) is one form of dementia that affects an individual’s memory with or without affecting their daily life. Alzheimer’s disease dementia (ADD) is a more severe form of dementia that usually affects elderly individuals. It remains unclear whether MCI is a distinct disorder from or an early stage of ADD. Methods: Gene expression data from blood were analyzed to identify potential biomarkers that may be useful for distinguishing between these two forms of dementia. Results: A meta-analysis revealed 91 genes dysregulated in individuals with MCI and 387 genes dysregulated in ADD. Pathway analysis identified seven pathways shared between MCI and ADD and nine ADD-specific pathways. Fifteen transcription factors were associated with MCI and ADD, whereas seven transcription factors were specific for ADD. Mir-335-5p was specific for ADD, suggesting that it may be useful as a biomarker. Diseases that are associated with MCI and ADD included developmental delays, cognition impairment, and movement disorders. Conclusion: These results provide a better molecular understanding of peripheral changes that occur in MCI and ADD patients and may be useful in the identification of diagnostic and prognostic biomarkers.

Systemic Immune Dyshomeostasis Model and Pathways in Alzheimer's Disease

Alzheimer's disease (AD) still remains an enigma for researchers and clinicians. The onset of AD is insidious, gradually progressive and multifactorial. The recent accumulated scientific evidences suggests that the pathological changes resemble the autoimmune-driven self-sustaining inflammatory process as a result of prolonged oxidative stress and immune dyshomeostasis. Apart from aging, during life span various other factors-mainly environmental, lifestyle, chronic stress, polymicrobial infections and neuroendocrine functions-affect the immune system. Here, we provide crosstalk among "trigger insults/inflammatory stimulus" i.e., polymicrobial infection, chronic stress, pro-inflammatory diet and cholinergic signaling to put forward a "Systemic Immune Dyshomeostasis" model as to connect the events leading to AD development and progression. Our model implicates altered cholinergic signaling and suggests pathological stages with various modifiable risk factors and triggers at different chronological age and stage of cognitive decline. The search of specific autoantibodies for AD which may serve as the suitable blood/CSF biomarkers should be actively pursued for the early diagnosis of AD. The preventive and therapeutic strategies should be directed towards maintaining the normal functioning of the immune system throughout the life span and specific modulation of the immune responses in the brain depending on the stage of changes in brain.

Type II Diabetes Mellitus Accelerates Age-Dependent Aβ Pathology in Cynomolgus Monkey Brain

Accumulating evidence suggests that diabetes mellitus (DM) is one of the strongest risk factors for developing Alzheimer's disease (AD). However, it remains unclear how DM accelerates AD pathology in the brain. Cynomolgus monkey (Macaca fascicularis) is one of the nonhuman primates used for biomedical research, and we can observe spontaneous formation of AD pathology, such as senile plaques (SPs) and neurofibrillary tangles (NFTs), with the advance of aging. Furthermore, obesity is occasionally observed and frequently leads to development of type II DM (T2DM) in laboratory-housed cynomolgus monkeys. These findings suggest that cynomolgus monkey is a useful species to study the relationship between T2DM and AD pathology. In T2DM-affected monkey brains, SPs were observed in frontal and temporal lobe cortices almost 5 years earlier than healthy control monkeys. Moreover, age-related endocytic pathology, such as intraneuronal accumulation of enlarged endosomes, was exacerbated in T2DM-affected monkey brains. Since accumulating evidences suggest that endocytic dysfunction is involved in Aβ pathology, T2DM may aggravate age-related endocytic dysfunction, leading to the acceleration of Aβ pathology.

Network approach identifies Pacer as an autophagy protein involved in ALS pathogenesis

BACKGROUND

Amyotrophic lateral sclerosis (ALS) is a multifactorial fatal motoneuron disease without a cure. Ten percent of ALS cases can be pointed to a clear genetic cause, while the remaining 90% is classified as sporadic. Our study was aimed to uncover new connections within the ALS network through a bioinformatic approach, by which we identified C13orf18, recently named Pacer, as a new component of the autophagic machinery and potentially involved in ALS pathogenesis.

METHODS

Initially, we identified Pacer using a network-based bioinformatic analysis. Expression of Pacer was then investigated in vivo using spinal cord tissue from two ALS mouse models (SOD1^G93A and TDP43^A315T) and sporadic ALS patients. Mechanistic studies were performed in cell culture using the mouse motoneuron cell line NSC34. Loss of function of Pacer was achieved by knockdown using short-hairpin constructs. The effect of Pacer repression was investigated in the context of autophagy, SOD1 aggregation, and neuronal death.

RESULTS

Using an unbiased network-based approach, we integrated all available ALS data to identify new functional interactions involved in ALS pathogenesis. We found that Pacer associates to an ALS-specific subnetwork composed of components of the autophagy pathway, one of the main cellular processes affected in the disease. Interestingly, we found that Pacer levels are significantly reduced in spinal cord tissue from sporadic ALS patients and in tissues from two ALS mouse models. In vitro, Pacer deficiency lead to impaired autophagy and accumulation of ALS-associated protein aggregates, which correlated with the induction of cell death.

CONCLUSIONS

This study, therefore, identifies Pacer as a new regulator of proteostasis associated with ALS pathology.

ApoE4: an emerging therapeutic target for Alzheimer's disease

BACKGROUND

The growing body of evidence indicating the heterogeneity of Alzheimer's disease (AD), coupled with disappointing clinical studies directed at a fit-for-all therapy, suggest that the development of a single magic cure suitable for all cases may not be possible. This calls for a shift in paradigm where targeted treatment is developed for specific AD subpopulations that share distinct genetic or pathological properties. Apolipoprotein E4 (apoE4), the most prevalent genetic risk factor of AD, is expressed in more than half of AD patients and is thus an important possible AD therapeutic target.

REVIEW

This review focuses initially on the pathological effects of apoE4 in AD, as well as on the corresponding cellular and animal models and the suggested cellular and molecular mechanisms which mediate them. The second part of the review focuses on recent apoE4-targeted (from the APOE gene to the apoE protein and its interactors) therapeutic approaches that have been developed in animal models and are ready to be translated to human. Further, the issue of whether the pathological effects of apoE4 are due to loss of protective function or due to gain of toxic function is discussed herein. It is possible that both mechanisms coexist, with certain constituents of the apoE4 molecule and/or its downstream signaling mediating a toxic effect, while others are associated with a loss of protective function.

CONCLUSION

ApoE4 is a promising AD therapeutic target that remains understudied. Recent studies are now paving the way for effective apoE4-directed AD treatment approaches.

Regional protein expression in human Alzheimer's brain correlates with disease severity

Alzheimer's disease (AD) is a progressive neurodegenerative disorder that currently affects 36 million people worldwide with no effective treatment available. Development of AD follows a distinctive pattern in the brain and is poorly modelled in animals. Therefore, it is vital to widen the spatial scope of the study of AD and prioritise the study of human brains. Here we show that functionally distinct human brain regions display varying and region-specific changes in protein expression. These changes provide insights into the progression of disease, novel AD-related pathways, the presence of a gradient of protein expression change from less to more affected regions and a possibly protective protein expression profile in the cerebellum. This spatial proteomics analysis provides a framework which can underpin current research and open new avenues to enhance molecular understanding of AD pathophysiology, provide new targets for intervention and broaden the conceptual frameworks for future AD research.

p17 from HIV induces brain endothelial cell angiogenesis through EGFR-1-mediated cell signalling activation

HIV-associated neurocognitive disorder in HIV patients substantially reduces their quality of life. We previously showed that the HIV matrix protein, p17 could stimulate lymph-angiogenesis in vitro potentially contributing to lymphoma tumour growth and in addition is associated with vascular activation in neuro-degenerating brain tissue; here, therefore, we have investigated the detailed molecular mechanisms of this action. We performed in vitro cell culture, angiogenesis experiments, phospho-protein microarrays and Western blotting to identify cellular signalling induced by p17 within human brain endothelial cells (HbMEC), and inhibitor studies to block p17-induced vascular growth. We also characterised the effects of hippocampal CA1 injection of p17 on epidermal growth factor receptor-1 (EGFR1) expression linked to our murine model of dementia. p17 strongly induced angiogenesis of HbMEC (migration, tube formation and spheroid growth). p17 concomitantly increased phosphorylation of EGFR1 as well as down-stream intermediates ERK1/2, FAK, PLC-γ and PKC-β whilst an inhibitor peptide of EGFR, blocked cell signalling and angiogenesis. Finally, Mice that showed reduced cognitive function and behavioural deficiencies after p17 injection, demonstrated that p17 localised in cortical microvessels and also neurones many of which stained positive for p-EGFR1 by histology/IHC. This work provides strong support that p17 may be involved in initiating and/or perpetuating vascular tissue pathophysiology associated with comorbidity in HIV patients.

The exploration of novel Alzheimer's therapeutic agents from the pool of FDA approved medicines using drug repositioning, enzyme inhibition and kinetic mechanism approaches

Novel drug development is onerous, time consuming and overpriced process with particularly low success and relatively high enfeebling rates. To overcome this burden, drug repositioning approach is being used to predict the possible therapeutic effects of FDA approved drugs in different diseases. Herein, we designed a computational and enzyme inhibitory mechanistic approach to fetch the promising drugs from the pool of FDA approved drugs against AD. The binding interaction patterns and conformations of screened drugs within active region of AChE were confirmed through molecular docking profiles. The possible associations of selected drugs with AD genes were predicted by pharmacogenomics analysis and confirmed through data mining. The stability behaviour of docked complexes (Drugs-AChE) were checked by MD simulations. The possible therapeutic potential of repositioned drugs against AChE were checked by in vitro analysis. Taken together, Cinitapride displayed a comparable results with standard and can be used as possible therapeutic agent in the treatment of AD.

Elevated Membrane Cholesterol Disrupts Lysosomal Degradation to Induce β-Amyloid Accumulation: The Potential Mechanism Underlying Augmentation of β-Amyloid Pathology by Type 2 Diabetes Mellitus

The endocytic membrane trafficking system is altered in the brains of early-stage Alzheimer disease (AD) patients, and endocytic disturbance affects the metabolism of β-amyloid (Aβ) protein, a key molecule in AD pathogenesis. It is widely accepted that type 2 diabetes mellitus (T2DM) is one of the strongest risk factors for development of AD. Supporting this link, experimentally induced T2DM enhances AD pathology in various animal models. Spontaneous T2DM also enhances Aβ pathology with severe endocytic pathology, even in nonhuman primate brains. However, it remains unclear how T2DM accelerates Aβ pathology. Herein, we demonstrate that cholesterol metabolism-related protein levels are increased and that membrane cholesterol level is elevated in spontaneous T2DM-affected cynomolgus monkey brains. Moreover, in vitro studies that manipulate cellular cholesterol reveal that elevated membrane cholesterol disrupts lysosomal degradation and enhances chemical-induced endocytic disturbance, resulting in great accumulation of Aβ in Neuro2a cells. These findings suggest that an alteration of cerebral cholesterol metabolism may be responsible for augmentation of Aβ pathology in T2DM-affected brains, which, in turn, may increase the risk for developing AD.

Re-thinking Alzheimer's disease therapeutic targets using gene-based tests

Background

Alzheimer's disease (AD) is a devastating condition with no known effective drug treatments. Existing drugs only alleviate symptoms. Given repeated expensive drug failures, we assessed systematically whether approved and investigational AD drugs are targeting products of genes strongly associated with AD and whether these genes are targeted by existing drugs for other indications which could be re-purposed.

Methods

We identified genes strongly associated with late-onset AD from the loci of genetic variants associated with AD at genome-wide-significance and from a gene-based test applied to the most extensively genotyped late-onset AD case (n = 17,008)-control (n = 37,154) study, the International Genomics of Alzheimer's Project. We used three gene-to-drug cross-references, Kyoto Encyclopedia of Genes and Genomes, Drugbank and Drug Repurposing Hub, to identify genetically validated targets of AD drugs and any existing drugs or nutraceuticals targeting products of the genes strongly associated with late-onset AD.

Findings

A total of 67 autosomal genes (forming 9 gene clusters) were identified as strongly associated with late-onset AD, 28 from the loci of single genetic variants, 51 from the gene-based test and 12 by both methods. Existing approved or investigational AD drugs did not target products of any of these 67 genes. Drugs for other indications targeted 11 of these genes, including immunosuppressive disease-modifying anti-rheumatic drugs targeting PTK2B gene products.

Interpretation

Approved and investigational AD drugs are not targeting products of genes strongly associated with late-onset AD. However, other drugs targeting products of these genes exist and could perhaps be re-purposing to combat late-onset AD after further scrutiny.

Machine learning-based identification of genetic interactions from heterogeneous gene expression profiles

The identification of disease-related genes and disease mechanisms is an important research goal; many studies have approached this problem by analysing genetic networks based on gene expression profiles and interaction datasets. To construct a gene network, correlations or associations among pairs of genes must be obtained. However, when gene expression data are heterogeneous with high levels of noise for samples assigned to the same condition, it is difficult to accurately determine whether a gene pair represents a significant gene-gene interaction (GGI). In order to solve this problem, we proposed a random forest-based method to classify significant GGIs from gene expression data. To train the model, we defined novel feature sets and utilised various high-confidence interactome datasets to deduce the correct answer set from known disease-specific genes. Using Alzheimer's disease data, the proposed method showed remarkable accuracy, and the GGIs established in the analysis can be used to build a meaningful genetic network that can explain the mechanisms underlying Alzheimer's disease.

NetControl4BioMed: a pipeline for biomedical data acquisition and analysis of network controllability

BACKGROUND

Network controllability focuses on discovering combinations of external interventions that can drive a biological system to a desired configuration. In practice, this approach translates into finding a combined multi-drug therapy in order to induce a desired response from a cell; this can lead to developments of novel therapeutic approaches for systemic diseases like cancer.

RESULT

We develop a novel bioinformatics data analysis pipeline called NetControl4BioMed based on the concept of target structural control of linear networks. Our pipeline generates novel molecular interaction networks by combining pathway data from various public databases starting from the user's query. The pipeline then identifies a set of nodes that is enough to control a given, user-defined set of disease-specific essential proteins in the network, i.e., it is able to induce a change in their configuration from any initial state to any final state. We provide both the source code of the pipeline as well as an online web-service based on this pipeline http://combio.abo.fi/nc/net_control/remote_call.php .

CONCLUSION

The pipeline can be used by researchers for controlling and better understanding of molecular interaction networks through combinatorial multi-drug therapies, for more efficient therapeutic approaches and personalised medicine.

Multifactorial Analysis of a Biomarker Pool for Alzheimer Disease Risk in a North Indian Population

BACKGROUND

Alzheimer disease (AD) is a progressive neurodegenerative disease with a complex multifactorial etiology. Here, we aim to identify a biomarker pool comprised of genetic variants and blood biomarkers as predictor of AD risk.

METHODS

We performed a case-control study involving 108 cases and 159 non-demented healthy controls to examine the association of multiple biomarkers with AD risk.

RESULTS

The APOE genotyping revealed that ε4 allele frequency was significantly high (p value = 0.0001, OR = 2.66, 95% CI 1.58-4.46) in AD as compared to controls, whereas ε2 (p = 0.0430, OR = 0.29, CI 0.07-1.10) was overrepresented in controls. In biochemical assays, significant differences in levels of total copper, free copper, zinc, copper/zinc ratio, iron, epidermal growth factor receptor (EGFR), leptin, and albumin were also observed. The AD risk score (ADRS) as a linear combination of 6 candidate markers involving age, education status, APOE ε4 allele, levels of iron, Cu/Zn ratio, and EGFR was created using stepwise linear discriminant analysis. The area under the ROC curve of the ADRS panel for predicting AD risk was significantly high (AUC = 0.84, p < 0.0001, 95% CI 0.78-0.89, sensitivity = 70.0%, specificity = 83.8%) compared to individual parameters.

CONCLUSION

These findings support the multifactorial etiology of AD and demonstrate the ability of a panel involving 6 biomarkers to discriminate AD cases from non-demented healthy controls.

Biomedical informatics applications for precision management of neurodegenerative diseases

Modern medicine is in the midst of a revolution driven by "big data," rapidly advancing computing power, and broader integration of technology into healthcare. Highly detailed and individualized profiles of both health and disease states are now possible, including biomarkers, genomic profiles, cognitive and behavioral phenotypes, high-frequency assessments, and medical imaging. Although these data are incredibly complex, they can potentially be used to understand multi-determinant causal relationships, elucidate modifiable factors, and ultimately customize treatments based on individual parameters. Especially for neurodegenerative diseases, where an effective therapeutic agent has yet to be discovered, there remains a critical need for an interdisciplinary perspective on data and information management due to the number of unanswered questions. Biomedical informatics is a multidisciplinary field that falls at the intersection of information technology, computer and data science, engineering, and healthcare that will be instrumental for uncovering novel insights into neurodegenerative disease research, including both causal relationships and therapeutic targets and maximizing the utility of both clinical and research data. The present study aims to provide a brief overview of biomedical informatics and how clinical data applications such as clinical decision support tools can be developed to derive new knowledge from the wealth of available data to advance clinical care and scientific research of neurodegenerative diseases in the era of precision medicine.

Integrative Analysis of Hippocampus Gene Expression Profiles Identifies Network Alterations in Aging and Alzheimer's Disease

Alzheimer's disease (AD) is a neurodegenerative disorder contributing to rapid decline in cognitive function and ultimately dementia. Most cases of AD occur in elderly and later years. There is a growing need for understanding the relationship between aging and AD to identify shared and unique hallmarks associated with the disease in a region and cell-type specific manner. Although genomic studies on AD have been performed extensively, the molecular mechanism of disease progression is still not clear. The major objective of our study is to obtain a higher-order network-level understanding of aging and AD, and their relationship using the hippocampal gene expression profiles of young (20-50 years), aging (70-99 years), and AD (70-99 years). The hippocampus is vulnerable to damage at early stages of AD and altered neurogenesis in the hippocampus is linked to the onset of AD. We combined the weighted gene co-expression network and weighted protein-protein interaction network-level approaches to study the transition from young to aging to AD. The network analysis revealed the organization of co-expression network into functional modules that are cell-type specific in aging and AD. We found that modules associated with astrocytes, endothelial cells and microglial cells are upregulated and significantly correlate with both aging and AD. The modules associated with neurons, mitochondria and endoplasmic reticulum are downregulated and significantly correlate with AD than aging. The oligodendrocytes module does not show significant correlation with neither aging nor disease. Further, we identified aging- and AD-specific interactions/subnetworks by integrating the gene expression with a human protein-protein interaction network. We found dysregulation of genes encoding protein kinases (FYN, SYK, SRC, PKC, MAPK1, ephrin receptors) and transcription factors (FOS, STAT3, CEBPB, MYC, NFKβ, and EGR1) in AD. Further, we found genes that encode proteins with neuroprotective function (14-3-3 proteins, PIN1, ATXN1, BDNF, VEGFA) to be part of the downregulated AD subnetwork. Our study highlights that simultaneously analyzing aging and AD will help to understand the pre-clinical and clinical phase of AD and aid in developing the treatment strategies.

Shared pathological pathways of Alzheimer's disease with specific comorbidities: current perspectives and interventions

Alzheimer's disease (AD) belongs to one of the most multifactorial, complex and heterogeneous morbidity-leading disorders. Despite the extensive research in the field, AD pathogenesis is still at some extend obscure. Mechanisms linking AD with certain comorbidities, namely diabetes mellitus, obesity and dyslipidemia, are increasingly gaining importance, mainly because of their potential role in promoting AD development and exacerbation. Their exact cognitive impairment trajectories, however, remain to be fully elucidated. The current review aims to offer a clear and comprehensive description of the state-of-the-art approaches focused on generating in-depth knowledge regarding the overlapping pathology of AD and its concomitant ailments. Thorough understanding of associated alterations on a number of molecular, metabolic and hormonal pathways, will contribute to the further development of novel and integrated theranostics, as well as targeted interventions that may be beneficial for individuals with age-related cognitive decline.

Systematic tissue-specific functional annotation of the human genome highlights immune-related DNA elements for late-onset Alzheimer's disease

Continuing efforts from large international consortia have made genome-wide epigenomic and transcriptomic annotation data publicly available for a variety of cell and tissue types. However, synthesis of these datasets into effective summary metrics to characterize the functional non-coding genome remains a challenge. Here, we present GenoSkyline-Plus, an extension of our previous work through integration of an expanded set of epigenomic and transcriptomic annotations to produce high-resolution, single tissue annotations. After validating our annotations with a catalog of tissue-specific non-coding elements previously identified in the literature, we apply our method using data from 127 different cell and tissue types to present an atlas of heritability enrichment across 45 different GWAS traits. We show that broader organ system categories (e.g. immune system) increase statistical power in identifying biologically relevant tissue types for complex diseases while annotations of individual cell types (e.g. monocytes or B-cells) provide deeper insights into disease etiology. Additionally, we use our GenoSkyline-Plus annotations in an in-depth case study of late-onset Alzheimer's disease (LOAD). Our analyses suggest a strong connection between LOAD heritability and genetic variants contained in regions of the genome functional in monocytes. Furthermore, we show that LOAD shares a similar localization of SNPs to monocyte-functional regions with Parkinson's disease. Overall, we demonstrate that integrated genome annotations at the single tissue level provide a valuable tool for understanding the etiology of complex human diseases. Our GenoSkyline-Plus annotations are freely available at http://genocanyon.med.yale.edu/GenoSkyline.

Dissecting the Molecular Mechanisms of Neurodegenerative Diseases through Network Biology

Neurodegenerative diseases are rarely caused by a mutation in a single gene but rather influenced by a combination of genetic, epigenetic and environmental factors. Emerging high-throughput technologies such as RNA sequencing have been instrumental in deciphering the molecular landscape of neurodegenerative diseases, however, the interpretation of such large amounts of data remains a challenge. Network biology has become a powerful platform to integrate multiple omics data to comprehensively explore the molecular networks in the context of health and disease. In this review article, we highlight recent advances in network biology approaches with an emphasis in brain-networks that have provided insights into the molecular mechanisms leading to the most prevalent neurodegenerative diseases including Alzheimer’s (AD), Parkinson’s (PD) and Huntington’s diseases (HD). We discuss how integrative approaches using multi-omics data from different tissues have been valuable for identifying biomarkers and therapeutic targets. In addition, we discuss the challenges the field of network medicine faces toward the translation of network-based findings into clinically actionable tools for personalized medicine applications.

Integrated late onset Alzheimer's disease (LOAD) susceptibility genes: Cholesterol metabolism and trafficking perspectives

Late onset Alzheimer's disease (LOAD) is the most common type of dementia and is characterized by decreased amyloid-β (Aβ) clearance from the brain. Cholesterol regulates the production and clearance of Aβ. Genome-wide association study (GWAS) suggests that at least 20 genes are associated with LOAD. The genes APOE, CLU, SORL1, PICALM, and BIN1 have a relatively high LOAD susceptibility. Additional experimental and bioinformatic approaches to integrate data from genetics, epigenetics, and molecular networks may further increase our understanding of LOAD in relation to cholesterol metabolism and trafficking.

A Systems View of the Differences between APOE ε4 Carriers and Non-carriers in Alzheimer's Disease

APOE ε4 is the strongest genetic risk factor for late-onset Alzheimer's disease (AD) and accounts for 50-65% of late-onset AD. Late-onset AD patients carrying or not carrying APOE ε4 manifest many clinico-pathological distinctions. Thus, we applied a weighted gene co-expression network analysis to identify specific co-expression modules in AD based on APOE ε4 stratification. Two specific modules were identified in AD APOE ε4 carriers and one module was identified in non-carriers. The hub genes of one module of AD APOE ε4 carriers were ISOC1, ENO3, GDF10, GNB3, XPO4, ACLY and MATN2. The other module of AD APOE ε4 carriers consisted of 10 hub genes including ANO3, ARPP21, HPCA, RASD2, PCP4 and ADORA2A. The module of AD APOE ε4 non-carriers consisted of 16 hub genes including DUSP5, TNFRSF18, ZNF331, DNAJB5 and RIN1. The module of AD APOE ε4 carriers including ISOC1 and ENO3 and the module of non-carriers contained the most highly connected hub gene clusters. mRNA expression of the genes in the cluster of the ISOC1 and ENO3 module of carriers was shown to be correlated in a time-dependent manner under APOE ε4 treatment but not under APOE ε3 treatment. In contrast, mRNA expression of the genes in the cluster of non-carriers' module was correlated under APOE ε3 treatment but not under APOE ε4 treatment. The modules of carriers demonstrated genetic bases and were mainly enriched in hereditary disorders and neurological diseases, energy metabolism-associated signaling and G protein-coupled receptor-associated pathways. The module including ISOC1 and ENO3 harbored two conserved promoter motifs in its hub gene cluster that could be regulated by common transcription factors and miRNAs. The module of non-carriers was mainly enriched in neurological, immunological and cardiovascular diseases and was correlated with Parkinson's disease. These data demonstrate that AD in APOE ε4 carriers involves more genetic factors and particular biological processes, whereas AD in APOE ε4 non-carriers shares more common pathways with other types of diseases. The study reveals differential genetic bases and pathogenic and pathological processes between carriers and non-carriers, providing new insight into the mechanisms of the differences between APOE ε4 carriers and non-carriers in AD.

NeuroRDF: semantic integration of highly curated data to prioritize biomarker candidates in Alzheimer's disease

BACKGROUND

Neurodegenerative diseases are incurable and debilitating indications with huge social and economic impact, where much is still to be learnt about the underlying molecular events. Mechanistic disease models could offer a knowledge framework to help decipher the complex interactions that occur at molecular and cellular levels. This motivates the need for the development of an approach integrating highly curated and heterogeneous data into a disease model of different regulatory data layers. Although several disease models exist, they often do not consider the quality of underlying data. Moreover, even with the current advancements in semantic web technology, we still do not have cure for complex diseases like Alzheimer's disease. One of the key reasons accountable for this could be the increasing gap between generated data and the derived knowledge.

RESULTS

In this paper, we describe an approach, called as NeuroRDF, to develop an integrative framework for modeling curated knowledge in the area of complex neurodegenerative diseases. The core of this strategy lies in the usage of well curated and context specific data for integration into one single semantic web-based framework, RDF. This increases the probability of the derived knowledge to be novel and reliable in a specific disease context. This infrastructure integrates highly curated data from databases (Bind, IntAct, etc.), literature (PubMed), and gene expression resources (such as GEO and ArrayExpress). We illustrate the effectiveness of our approach by asking real-world biomedical questions that link these resources to prioritize the plausible biomarker candidates. Among the 13 prioritized candidate genes, we identified MIF to be a potential emerging candidate due to its role as a pro-inflammatory cytokine. We additionally report on the effort and challenges faced during generation of such an indication-specific knowledge base comprising of curated and quality-controlled data.

CONCLUSION

Although many alternative approaches have been proposed and practiced for modeling diseases, the semantic web technology is a flexible and well established solution for harmonized aggregation. The benefit of this work, to use high quality and context specific data, becomes apparent in speculating previously unattended biomarker candidates around a well-known mechanism, further leveraged for experimental investigations.

Expression and Function of the Epidermal Growth Factor Receptor in Physiology and Disease

The epidermal growth factor receptor (EGFR) is the prototypical member of a family of membrane-associated intrinsic tyrosine kinase receptors, the ErbB family. EGFR is activated by multiple ligands, including EGF, transforming growth factor (TGF)-α, HB-EGF, betacellulin, amphiregulin, epiregulin, and epigen. EGFR is expressed in multiple organs and plays important roles in proliferation, survival, and differentiation in both development and normal physiology, as well as in pathophysiological conditions. In addition, EGFR transactivation underlies some important biologic consequences in response to many G protein-coupled receptor (GPCR) agonists. Aberrant EGFR activation is a significant factor in development and progression of multiple cancers, which has led to development of mechanism-based therapies with specific receptor antibodies and tyrosine kinase inhibitors. This review highlights the current knowledge about mechanisms and roles of EGFR in physiology and disease.

Recent approaches and challenges in iPSCs: modeling and cell-based therapy of Alzheimer's disease

The lack of effective therapies for different neurodegenerative disorders has placed huge burdens on society. To overcome the restricted capacity of the central nervous system for regeneration, the promising alternative would be to use stem cells for more effective treatment of chronic degenerative and inflammatory neurological conditions and also of acute neuronal damage and from injuries or cerebrovascular diseases. The generation of induced pluripotent stem cells from somatic cells by the ectopic expression of specific transcription factors has provided the regenerative medicine field with a new tool for investigating and treating neurodegenerative diseases, including Alzheimer's disease (AD). This technology provides an alternative to traditional approaches, such as nuclear transfer and somatic cell fusion using embryonic stem cells. However, due to a problem in standardization of certain reprogramming techniques and systems research, the induced pluripotent stem cell-based technology is still in its infancy. The present paper is aimed at a brief review of the current status in modeling and cell-based therapies for AD.