Meta-analysis of BACE1 gene rs638405 polymorphism and the risk of Alzheimer's disease in Caucasion and Asian population

Genetic polymorphism in β-site amyloid precursor protein-cleaving enzyme 1 affects the structure of medial temporal lobe and cognition in Alzheimer's disease: an exploratory study

The β-site amyloid precursor protein-cleaving enzyme 1 (BACE1) gene polymorphism (rs638405) has been widely reported to be associated with Alzheimer's disease (AD) risk. However, studies on the relationship between BACE1 gene polymorphism (rs638405), brain volume, and cognition in AD patients remain scarce. To investigate the effect of genetic polymorphism in BACE1 on gray matter volume (GMV) and cognition in AD, this study recruited 111 cognitively unimpaired (CU) controls and 144 AD patients. The effect of BACE1 rs638405 polymorphism on cognition was explored in CU and AD groups. Then the interaction effect of the diagnosis and BACE1 rs638405 polymorphism on GMV was performed, following the post-hoc analysis of regions of interest (ROIs) in interaction analysis. Mediation analysis was used to elucidate the relationship among genotypes, ROIs and cognition. BACE1 rs638405 G carriers (BACE1 G+) showed significantly lower scores in global cognition and memory function than noncarriers (BACE1 G-) in AD group. Genotypes (G+/G-) and diagnosis (CU/AD) have interaction on GMV of medial temporal lobe (MTL) including the left parahippocampus and right hippocampus. Post-hoc analysis revealed that BACE1 G+ exhibited significantly lower GMV in ROIs compared to BACE1 G- in AD. Finally, mediation analysis further demonstrated that the GMV of ROIs mediated the effect of BACE1 rs638405 polymorphism on cognition in AD. Our results emphasize the BACE1 rs638405 gene polymorphisms may affect the GMV of MTL and cognition in AD, deepening the understanding of AD pathogenesis.

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

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

A hidden layer of structural variation in transposable elements reveals potential genetic modifiers in human disease-risk loci

Genome-wide association studies (GWAS) have been highly informative in discovering disease-associated loci but are not designed to capture all structural variations in the human genome. Using long-read sequencing data, we discovered widespread structural variation within SINE-VNTR-Alu (SVA) elements, a class of great ape-specific transposable elements with gene-regulatory roles, which represents a major source of structural variability in the human population. We highlight the presence of structurally variable SVAs (SV-SVAs) in neurological disease-associated loci, and we further associate SV-SVAs to disease-associated SNPs and differential gene expression using luciferase assays and expression quantitative trait loci data. Finally, we genetically deleted SV-SVAs in the BIN1 and CD2AP Alzheimer's disease-associated risk loci and in the BCKDK Parkinson's disease-associated risk locus and assessed multiple aspects of their gene-regulatory influence in a human neuronal context. Together, this study reveals a novel layer of genetic variation in transposable elements that may contribute to identification of the structural variants that are the actual drivers of disease associations of GWAS loci.

Systematic Search for Novel Circulating Biomarkers Associated with Extracellular Vesicles in Alzheimer's Disease: Combining Literature Screening and Database Mining Approaches

miRNAs play an important role in neurodegenerative diseases. Many miRNA-target gene interactions (MTI) have been experimentally confirmed and associated with Alzheimer’s disease (AD). miRNAs may also be contained within extracellular vesicles (EVs), mediators of cellular communication and a potential source of circulating biomarkers in body fluids. Therefore, EV-associated miRNAs (EV-miRNAs) in peripheral blood could support earlier and less invasive AD diagnostics. We aimed to prioritize EV-related miRNA with AD-related genes and to identify the most promising candidates for novel AD biomarkers. A list of unique EV-miRNAs from the literature was combined with a known set of AD risk genes and enriched for MTI. Additionally, miRNAs associated with the AD phenotype were combined with all known target genes in MTI enrichment. Expression in different sample types was analyzed to identify AD-associated miRNAs with the greatest potential as AD circulating biomarkers. Four common MTI were observed between EV-miRNAs and AD-associated miRNAs: hsa-miR-375–APH1B, hsa-miR-107–CDC42SE2, hsa-miR-375–CELF2, and hsa-miR-107–IL6. An additional 61 out of 169 unique miRNAs (36.1%) and seven out of 84 unique MTI (8.3%), observed in the body fluids of AD patients, were proposed as very strong AD-circulating biomarker candidates. Our analysis summarized several potential novel AD biomarkers, but further studies are needed to evaluate their potential in clinical practice.

Associations of Plasma BACE1 Level and BACE1 C786G Gene Polymorphism with Cognitive Functions in Patients with Type 2 Diabetes: A Cross- Sectional Study

BACKGROUND

β-Site APP-cleaving enzyme 1 (BACE1) is a key enzyme involved in the pathophysiology of Type 2 Diabetes Mellitus (T2DM) and Mild Cognitive Impairment (MCI). We aimed to investigate the potential associations of plasma BACE1 levels and BACE1 gene polymorphism with different cognitive performances in T2DM patients with MCI.

METHODS

The recruited 186 T2DM subjects were divided into 92 MCI group and 94 healthy-cognition controls, according to the Montreal Cognitive Assessment (MoCA) scores. Sociodemographic characteristics, clinical parameters and neuropsychological tests were assessed. BACE1 C786G gene polymorphism and plasma BACE1 level were determined.

RESULTS

Compared to controls, MCI patients exhibited higher plasma BACE1 levels. Plasma BACE1 levels were negatively associated with MoCA, Clock Drawing Test and Logical Memory Test scores, whereas positively associated with Trail Making Test-B time in the MCI group (all p<0.05), after adjusting fasting blood glucose, glycosylated hemoglobin, and homeostasis model assessment of insulin resistance by C-peptide. Multivariable logistic regression analysis showed a significant trend towards increased MCI risk with high plasma BACE1 level in T2DM patients (OR = 1.492, p = 0.027). The plasma BACE1 levels of GG and GC genotypes were obviously higher than that of CC genotype in T2DM-MCI patients (p = 0.035; p = 0.026, respectively).

CONCLUSION

Increased plasma BACE1 levels were associated with poor overall cognition functions, especially visuospatial abilities, visual/logical memory and executive functions in T2DM-MCI patients. Additionally, elevated plasma BACE1 level was a risk factor for MCI in T2DM patients, and might be influenced by BACE1 C786G gene mutations.

Genetic Editing and Pharmacogenetics in Current And Future Therapy Of Neurocognitive Disorders

Dementia is an important issue in western societies, and in the following years, this problem will also rise in the developing regions, such as Africa and Asia. The most common types of dementia in adults are Alzheimer's Disease (AD), Dementia with Lewy Bodies (DLB), Frontotemporal Dementia (FTD) and Vascular Dementia (VaD), of which, AD accounts for more than half of the cases. The most prominent symptom of AD is cognitive impairment, currently treated with four drugs: Donepezil, rivastigmine, and galantamine, enhancing cholinergic transmission; as well as memantine, protecting neurons against glutamate excitotoxicity. Despite ongoing efforts, no new drugs in the treatment of AD have been registered for the last ten years, thus multiple studies have been conducted on genetic factors affecting the efficacy of antidementia pharmacotherapy. The researchers investigate the effects of variants in multiple genes, such as ABCB1, ACE, CHAT, CHRNA7, CYP2C9, CYP2C19, CYP2D6, CYP3A4, CYP3A5, CYP3A7, NR1I2, NR1I3, POR, PPAR, RXR, SLC22A1/2/5, SLC47A1, UGT1A6, UGT1A9 and UGT2B7, associated with numerous pathways: the development of pathological proteins, formation and metabolism of acetylcholine, transport, metabolism and excretion of antidementia drugs and transcription factors regulating the expression of genes responsible for metabolism and transport of drugs. The most promising results have been demonstrated for APOE E4, dementia risk variant, BCHE-K, reduced butyrylcholinesterase activity variant, and CYP2D6 UM, ultrarapid hepatic metabolism. Further studies investigate the possibilities of the development of emerging drugs or genetic editing by CRISPR/Cas9 for causative treatment. In conclusion, the pharmacogenetic studies on dementia diseases may improve the efficacy of pharmacotherapy in some patients with beneficial genetic variants, at the same time, identifying the carriers of unfavorable alleles, the potential group of novel approaches to the treatment and prevention of dementia.

Alterations in Alzheimer's Disease-Associated Gene Expression in Severe Obstructive Sleep Apnea Patients

Background: Obstructive sleep apnea (OSA) increases the risk of Alzheimer’s disease (AD), and inflammation may be involved in the early pathogenesis of AD in patients with OSA. However, the potential pathways between OSA and AD have yet to be established. In this study, we aimed to investigate differential expressions of AD-associated genes in OSA patients without evident AD or dementia. Methods: This prospective case-control study included five patients with severe OSA and five age and sex-matched patients with non-severe OSA without evident dementia who underwent uvulopalatopharyngoplasty between 1 January 2013 and 31 December 2015. The expressions of genes associated with AD were analyzed using whole-exome sequencing. Unsupervised two-dimensional hierarchical clustering was performed on these genes. Pearson’s correlation was used as the distance metric to simultaneously cluster subjects and genes. Results: The expressions of CCL2, IL6, CXCL8, HLA-A, and IL1RN in the patients with severe OSA were significantly different from those in the patients with non-severe OSA and contributed to changes in the immune response, cytokine–cytokine receptor interactions, and nucleotide-binding oligomerization domain-like receptor signaling pathways. Conclusions: Inflammation may contribute to the onset of AD and physicians need to be aware of the potential occurrence of AD in patients with severe OSA.

Integrated Systems Approach Reveals Sphingolipid Metabolism Pathway Dysregulation in Association with Late-Onset Alzheimer's Disease

Late-onset Alzheimer’s disease (LOAD) and age are significantly correlated such that one-third of Americans beyond 85 years of age are afflicted. We have designed and implemented a pilot study that combines systems biology approaches with traditional next-generation sequencing (NGS) analysis techniques to identify relevant regulatory pathways, infer functional relationships and confirm the dysregulation of these biological pathways in LOAD. Our study design is a most comprehensive systems approach combining co-expression network modeling derived from RNA-seq data, rigorous quality control (QC) standards, functional ontology, and expression quantitative trait loci (eQTL) derived from whole exome (WES) single nucleotide variant (SNV) genotype data. Our initial results reveal several statistically significant, biologically relevant genes involved in sphingolipid metabolism. To validate these findings, we performed a gene set enrichment analysis (GSEA). The GSEA revealed the sphingolipid metabolism pathway and regulation of autophagy in association with LOAD cases. In the execution of this study, we have successfully tested an integrative approach to identify both novel and known LOAD drivers in order to develop a broader and more detailed picture of the highly complex transcriptional and regulatory landscape of age-related dementia.

Ion channel regulation by β-secretase BACE1 - enzymatic and non-enzymatic effects beyond Alzheimer's disease

β-site APP-cleaving enzyme 1 (BACE1) has become infamous for its pivotal role in the pathogenesis of Alzheimer's disease (AD). Consequently, BACE1 represents a prime target in drug development. Despite its detrimental involvement in AD, it should be quite obvious that BACE1 is not primarily present in the brain to drive mental decline. In fact, additional functions have been identified. In this review, we focus on the regulation of ion channels, specifically voltage-gated sodium and KCNQ potassium channels, by BACE1. These studies provide evidence for a highly unexpected feature in the functional repertoire of BACE1. Although capable of cleaving accessory channel subunits, BACE1 exerts many of its physiologically significant effects through direct, non-enzymatic interactions with main channel subunits. We discuss how the underlying mechanisms can be conceived and develop scenarios how the regulation of ion conductances by BACE1 might shape electric activity in the intact and diseased brain and heart.