Bridging integrator 1 (BIN1): form, function, and Alzheimer's disease

The Role of Changes in the Expression of Inflammation-Associated Genes in the Variants of Cerebral Small Vessel Disease

Age-dependent cerebral small vessel disease (CSVD) is a common disease with a high social burden characterized by heterogeneity of forms and frequent comorbidity with Alzheimer's disease (AD). Previously, we identified two MRI types of CSVD with specific clinical presentation and, probably, different mechanisms. The present study included 34 patients with CSVD and white matter hyperintensity (WMH) of stage Fazekas (F) 3 (mean age 61.7 ± 8.9) and 11 volunteers (mean age 57.3 ± 9.7). Total RNA was isolated from peripheral blood leukocytes. The expression of 58 protein-coding genes associated with CSVD and/or AD and 4 reference genes were assessed as part of the original panel for the NanoString nCounter analyzer. Testing results were validated by real-time PCR. There was a significant decrease in the expression levels of the ACOX1, CD33, CD2AP, TNFR1, and VEGFC genes in MRI type 2 relative to the control group as well as a decrease in the expression level of the CD33 gene in MRI type 2 compared to MRI type 1. Processes associated with inflammatory pathways with decreased expression of the identified genes are important in the development of MRI type 2 of CSVD. Given the direct connection of the established genes with AD, the importance of this form of CSVD in comorbidity with AD has been assumed.

Amphiphysin-2 (BIN1) functions and defects in cardiac and skeletal muscle

Amphiphysin-2 is a ubiquitously expressed protein also known as bridging integrator 1 (BIN1), playing a critical role in membrane remodeling, trafficking, and cytoskeleton dynamics in a wide range of tissues. Mutations in the gene encoding BIN1 cause centronuclear myopathies (CNM), and recent evidence has implicated BIN1 in heart failure, underlining its crucial role in both skeletal and cardiac muscle. Furthermore, altered expression of BIN1 is linked to an increased risk of late-onset Alzheimer's disease and several types of cancer, including breast, colon, prostate, and lung cancers. Recently, the first proof-of-concept for potential therapeutic strategies modulating BIN1 were obtained for muscle diseases. In this review article, we discuss the similarities and differences in BIN1's functions in cardiac and skeletal muscle, along with its associated diseases and potential therapies.

BIN1 knockdown rescues systolic dysfunction in aging male mouse hearts

Cardiac dysfunction is a hallmark of aging in humans and mice. Here we report that a two-week treatment to restore youthful Bridging Integrator 1 (BIN1) levels in the hearts of 24-month-old mice rejuvenates cardiac function and substantially reverses the aging phenotype. Our data indicate that age-associated overexpression of BIN1 occurs alongside dysregulated endosomal recycling and disrupted trafficking of cardiac CaV1.2 and type 2 ryanodine receptors. These deficiencies affect channel function at rest and their upregulation during acute stress. In vivo echocardiography reveals reduced systolic function in old mice. BIN1 knockdown using an adeno-associated virus serotype 9 packaged shRNA-mBIN1 restores the nanoscale distribution and clustering plasticity of ryanodine receptors and recovers Ca2+ transient amplitudes and cardiac systolic function toward youthful levels. Enhanced systolic function correlates with increased phosphorylation of the myofilament protein cardiac myosin binding protein-C. These results reveal BIN1 knockdown as a novel therapeutic strategy to rejuvenate the aging myocardium.

Biofluid biomarkers for Alzheimer's disease

Alzheimer's disease (AD) is a multifactorial neurodegenerative disease, with a complex pathogenesis and an irreversible course. Therefore, the early diagnosis of AD is particularly important for the intervention, prevention, and treatment of the disease. Based on the different pathophysiological mechanisms of AD, the research progress of biofluid biomarkers are classified and reviewed. In the end, the challenges and perspectives of future research are proposed.

BIN1K358R suppresses glial response to plaques in mouse model of Alzheimer's disease

INTRODUCTION

The BIN1 coding variant rs138047593 (K358R) is linked to Late-Onset Alzheimer's Disease (LOAD) via targeted exome sequencing.

METHODS

To elucidate the functional consequences of this rare coding variant on brain amyloidosis and neuroinflammation, we generated BIN1K358R knock-in mice using CRISPR/Cas9 technology. These mice were subsequently bred with 5xFAD transgenic mice, which serve as a model for Alzheimer's pathology.

RESULTS

The presence of the BIN1K358R variant leads to increased cerebral amyloid deposition, with a dampened response of astrocytes and oligodendrocytes, but not microglia, at both the cellular and transcriptional levels. This correlates with decreased neurofilament light chain in both plasma and brain tissue. Synaptic densities are significantly increased in both wild-type and 5xFAD backgrounds homozygous for the BIN1K358R variant.

DISCUSSION

The BIN1 K358R variant modulates amyloid pathology in 5xFAD mice, attenuates the astrocytic and oligodendrocytic responses to amyloid plaques, decreases damage markers, and elevates synaptic densities.

HIGHLIGHTS

BIN1 rs138047593 (K358R) coding variant is associated with increased risk of LOAD. BIN1 K358R variant increases amyloid plaque load in 12-month-old 5xFAD mice. BIN1 K358R variant dampens astrocytic and oligodendrocytic response to plaques. BIN1 K358R variant decreases neuronal damage in 5xFAD mice. BIN1 K358R upregulates synaptic densities and modulates synaptic transmission.

Deregulation of the Glymphatic System in Alzheimer's Disease: Genetic and Non-Genetic Factors

Alzheimer's disease (AD) is the most prevalent form of dementia and is characterized by progressive degeneration of brain function. AD gradually affects the parts of the brain that control thoughts, language, behavior and mental function, severely impacting a person's ability to carry out daily activities and ultimately leading to death. The accumulation of extracellular amyloid-β peptide (Aβ) and the aggregation of intracellular hyperphosphorylated tau are the two key pathological hallmarks of AD. AD is a complex condition that involves both non-genetic risk factors (35%) and genetic risk factors (58-79%). The glymphatic system plays an essential role in clearing metabolic waste, transporting tissue fluid, and participating in the immune response. Both non-genetic and genetic risk factors affect the glymphatic system to varying degrees. The main purpose of this review is to summarize the underlying mechanisms involved in the deregulation of the glymphatic system during the progression of AD, especially concerning the diverse contributions of non-genetic and genetic risk factors. In the future, new targets and interventions that modulate these interrelated mechanisms will be beneficial for the prevention and treatment of AD.

Cerebrospinal fluid proteomics in patients with Alzheimer's disease reveals five molecular subtypes with distinct genetic risk profiles

Alzheimer's disease (AD) is heterogenous at the molecular level. Understanding this heterogeneity is critical for AD drug development. Here we define AD molecular subtypes using mass spectrometry proteomics in cerebrospinal fluid, based on 1,058 proteins, with different levels in individuals with AD (n = 419) compared to controls (n = 187). These AD subtypes had alterations in protein levels that were associated with distinct molecular processes: subtype 1 was characterized by proteins related to neuronal hyperplasticity; subtype 2 by innate immune activation; subtype 3 by RNA dysregulation; subtype 4 by choroid plexus dysfunction; and subtype 5 by blood-brain barrier impairment. Each subtype was related to specific AD genetic risk variants, for example, subtype 1 was enriched with TREM2 R47H. Subtypes also differed in clinical outcomes, survival times and anatomical patterns of brain atrophy. These results indicate molecular heterogeneity in AD and highlight the need for personalized medicine.

Prevention of Alzheimer's disease through diet: An exploratory review

Introduction

This exploratory review article describes about the genetic factors behind Alzheimer's disease (AD), their association with foods, and their relationships with cognitive impairment. It explores the dietary patterns and economic challenges in AD prevention.

Methods

Scopus, PubMed and Google Scholar were searched for articles that examined the relationships between Diets, Alzheimer's Disease (AD), and Socioeconomic conditions in preventative Alzheimer's disease studies. Graphs and Network analysis data were taken from Scopus under the MeSH search method, including words, Alzheimer's, APoE4, Tau protein, APP, Amyloid precursor protein, Beta-Amyloid, Aβ, Mediterranean Diet, MD, DASH diet, MIND diet, SES, Socioeconomic, Developed country, Underdeveloped country, Preventions. The network analysis was done through VOS viewer.

Results

Mediterranean diet (MD) accurately lowers AD (Alzheimer's Disease) risk to 53% and 35% for people who follow it moderately. MIND scores had a statistically significant reduction in AD rate compared to those in the lowest tertial (53% and 35% reduction, respectively). Subjects with the highest adherence to the MD and DASH had a 54% and 39% lower risk of developing AD, respectively, compared to those in the lowest tertial. Omega-6, PUFA, found in nuts and fish, can play most roles in the clearance of Aβ. Vitamin D inhibits induced fibrillar Aβ apoptosis. However, the high cost of these diet components rise doubt about the effectiveness of AD prevention through healthy diets.

Conclusion

The finding of this study revealed an association between diet and the effects of the chemical components of foods on AD biomarkers. More research is required to see if nutrition is a risk or a protective factor for Alzheimer's disease to encourage research to be translated into therapeutic practice and to clarify nutritional advice.

BIN1 in the Pursuit of Ousting the Alzheimer's Reign: Impact on Amyloid and Tau Neuropathology

Alzheimer's disease contributes to 60-70% of all dementia cases in the general population. Belonging to the BIN1/amphiphysin/RVS167 (BAR) superfamily, the bridging integrator (BIN1) has been identified to impact two major pathological hallmarks in Alzheimer's disease (AD), i.e., amyloid beta (Aβ) and tau accumulation. Aβ accumulation is found to increase by BIN1 knockdown in cortical neurons in late-onset AD, due to BACE1 accumulation at enlarged early endosomes. Two BIN1 mutants, KR and PL, were identified to exhibit Aβ accumulation. Furthermore, BIN1 deficiency by BIN1-related polymorphisms impairs the interaction with tau, thus elevating tau phosphorylation, altering synapse structure and tau function. Even though the precise role of BIN1 in the neuronal tissue needs further investigation, the authors aim to throw light on the potential of BIN1 and unfold its implications on tau and Aβ pathology, to aid AD researchers across the globe to examine BIN1, as an appropriate target gene for disease management.

BIN1 in cancer: biomarker and therapeutic target

BACKGROUND

The bridging integrator 1 (BIN1) protein was originally identified as a pro-apoptotic tumor suppressor that binds to and inhibits oncogenic MYC transcription factors. BIN1 has complex physiological functions participating in endocytosis, membrane cycling, cytoskeletal regulation, DNA repair deficiency, cell-cycle arrest, and apoptosis. The expression of BIN1 is closely related to the development of various diseases such as cancer, Alzheimer's disease, myopathy, heart failure, and inflammation.

PURPOSE

Because BIN1 is commonly expressed in terminally differentiated normal tissues and is usually undetectable in refractory or metastatic cancer tissues, this differential expression has led us to focus on human cancers associated with BIN1. In this review, we discuss the potential pathological mechanisms of BIN1 during cancer development and its feasibility as a prognostic marker and therapeutic target for related diseases based on recent findings on its molecular, cellular, and physiological roles.

CONCLUSION

BIN1 is a tumor suppressor that regulates cancer development through a series of signals in tumor progression and microenvironment. It also makes BIN1 a feasible early diagnostic or prognostic marker for cancer.

Gut-brain connections in neurodegenerative disease: immunotherapeutic targeting of Bin1 in inflammatory bowel disease and Alzheimer's disease

Longer lifespan produces risks of age-associated neurodegenerative disorders such as Alzheimer's disease (AD), which is characterized by declines in memory and cognitive function. The pathogenic causes of AD are thought to reflect a progressive aggregation in the brain of amyloid plaques composed of beta-amyloid (Aß) peptides and neurofibrillary tangles composed of phosphorylated tau protein. Recently, long-standing investigations of the Aß disease hypothesis gained support via a passive immunotherapy targeting soluble Aß protein. Tau-targeting approaches using antibodies are also being pursued as a therapeutic approach to AD. In genome-wide association studies, the disease modifier gene Bin1 has been identified as a top risk factor for late-onset AD in human populations, with recent studies suggesting that Bin1 binds tau and influences its extracellular deposition. Interestingly, before AD emerges in the brain, tau levels rise in the colon, where Bin1-a modifier of tissue barrier function and inflammation-acts to promote inflammatory bowel disease (IBD). This connection is provocative given clinical evidence of gut-brain communication in age-associated neurodegenerative disorders, including AD. In this review, we discuss a Bin1-targeting passive immunotherapy developed in our laboratory to treat IBD that may offer a strategy to indirectly reduce tau deposition and limit AD onset or progression.

Genetic insights into immune mechanisms of Alzheimer's and Parkinson's disease

Microglia, the macrophages of the brain, are vital for brain homeostasis and have been implicated in a broad range of brain disorders. Neuroinflammation has gained traction as a possible therapeutic target for neurodegeneration, however, the precise function of microglia in specific neurodegenerative disorders is an ongoing area of research. Genetic studies offer valuable insights into understanding causality, rather than merely observing a correlation. Genome-wide association studies (GWAS) have identified many genetic loci that are linked to susceptibility to neurodegenerative disorders. (Post)-GWAS studies have determined that microglia likely play an important role in the development of Alzheimer's disease (AD) and Parkinson's disease (PD). The process of understanding how individual GWAS risk loci affect microglia function and mediate susceptibility is complex. A rapidly growing number of publications with genomic datasets and computational tools have formulated new hypotheses that guide the biological interpretation of AD and PD genetic risk. In this review, we discuss the key concepts and challenges in the post-GWAS interpretation of AD and PD GWAS risk alleles. Post-GWAS challenges include the identification of target cell (sub)type(s), causal variants, and target genes. Crucially, the prediction of GWAS-identified disease-risk cell types, variants and genes require validation and functional testing to understand the biological consequences within the pathology of the disorders. Many AD and PD risk genes are highly pleiotropic and perform multiple important functions that might not be equally relevant for the mechanisms by which GWAS risk alleles exert their effect(s). Ultimately, many GWAS risk alleles exert their effect by changing microglia function, thereby altering the pathophysiology of these disorders, and hence, we believe that modelling this context is crucial for a deepened understanding of these disorders.

NQO1 regulates expression and alternative splicing of apoptotic genes associated with Alzheimer's disease in PC12 cells

PURPOSE

Alzheimer's disease (AD) is a neurodegenerative disorder characterized by progressive memory loss and cognitive dysfunction. Quinone oxidoreductase 1 (NQO1) is an antioxidant enzyme that plays an important role in controlling cellular redox state, whose expression is altered in the brain tissues of AD patients. In addition to its traditional antioxidant effects, NQO1 also acts as a multifunctional RNA-binding protein involved in posttranscriptional regulation. Whether the RNA-binding activity of NQO1 influences AD pathology has not been investigated yet.

METHODS

The RNA-binding functions of NQO1 in rat pheochromocytoma (PC12) cells were investigated using siRNA knockdown followed by total RNA sequencing. Reverse transcription quantitative polymerase chain reaction was performed to explore the impact of NQO1 on the transcription and alternative splicing of apoptotic genes.

RESULTS

NQO1 knockdown led to a significant increase in cellular apoptosis. Genes involved in certain apoptosis pathways, such as positive regulation of apoptotic processes and mitogen-activated protein kinase signaling, were under global transcriptional and alternative splicing regulation. NQO1 regulated the transcription of apoptotic genes Cryab, Lgmn, Ngf, Apoe, Brd7, and Stat3, as well as the alternative splicing of apoptotic genes BIN1, Picalm, and Fyn.

CONCLUSION

Our findings suggest that NQO1 participates in the pathology of AD by regulating the expression and alternative splicing of the genes involved in apoptosis. These results extend our understanding of NQO1 in apoptotic pathways at the posttranscriptional level in AD.

[A role of altered inflammation-related gene expression in cerebral small vessel disease with cognitive impairment]

OBJECTIVE

To identify the role of changes in the expression of inflammation-related genes in cerebral microangiopathy/cerebral small vessel disease (cSVD).

MATERIAL AND METHODS

Forty-four cSVD patients (mean age 61.4±9.2) and 11 controls (mean age 57.3±9.7) were studied. Gene expression was assessed on an individual NanoString nCounter panel of 58 inflammation-related genes and 4 reference genes. A set of genes was generated based on converging results of complete genome-wide association studies (GWAS) in cSVD and Alzheimer's disease (AD) and circulating markers associated with vascular wall and Brain lesions in cSVD. RNA was isolated from blood leukocytes and analyzed with the nCounter Analysis System, followed by analysis in nSolver 4.0. Results were verified by real-time PCR.

RESULTS

CSVD patients had a significant decrease in BIN1 (log2FC=-1.272; p=0.039) and VEGFA (log2FC=-1.441; p=0.038) expression compared to controls, which showed predictive ability for cSVD. The cut-off for BIN1 expression was 5.76 a.u. (sensitivity 73%; specificity 75%) and the cut-off for VEGFA expression was 9.27 a.u. (sensitivity 64%; specificity 86%). Reduced expression of VEGFA (p=0.011), VEGFC (p=0.017), CD2AP (p=0.044) was associated with cognitive impairment (CI). There was a significant direct correlation between VEGFC expression and the scores on the Montreal Cognitive Assessment test and between BIN1 and VEGFC expression and delayed memory.

CONCLUSION

The possible prediction of cSVD by reduced expression levels of BIN1, VEGFA and the association of clinically significant CI with reduced VEGFA and VEGFC expression indicate their importance in the development and progression of the disease. The established importance of these genes in the pathogenesis of AD suggests that similar changes in their expression profile in cSVD may be one of the conditions for the comorbidity of the two pathologies.

Exosome-based approaches in the management of Alzheimer's disease

Alzheimer's disease (AD) has been the most extensively studied neurological disorders that affects millions of individuals globally and is associated with misfolding of proteins in the brain. Amyloid-β and tau are predominantly involved in the pathogenesis of AD. Therapeutic interventions and nanotechnological advancements are useful only in managing the AD symptoms and the cure for this disease remains elusive. Exosomes, originating from most cell and tissue types are regarded as a double-edged sword, considering their roles in the progression and treatment of AD. Exosomes can be manipulated as drug delivery vehicles for a wide range of therapeutic cargos-both small molecules and macromolecules. Herein, we review the roles of exosomes in the pathology, diagnosis, and treatment of AD and highlight their application as a drug carrier to the brain for AD treatment.

Interpretable deep learning translation of GWAS and multi-omics findings to identify pathobiology and drug repurposing in Alzheimer's disease

Translating human genetic findings (genome-wide association studies [GWAS]) to pathobiology and therapeutic discovery remains a major challenge for Alzheimer's disease (AD). We present a network topology-based deep learning framework to identify disease-associated genes (NETTAG). We leverage non-coding GWAS loci effects on quantitative trait loci, enhancers and CpG islands, promoter regions, open chromatin, and promoter flanking regions under the protein-protein interactome. Via NETTAG, we identified 156 AD-risk genes enriched in druggable targets. Combining network-based prediction and retrospective case-control observations with 10 million individuals, we identified that usage of four drugs (ibuprofen, gemfibrozil, cholecalciferol, and ceftriaxone) is associated with reduced likelihood of AD incidence. Gemfibrozil (an approved lipid regulator) is significantly associated with 43% reduced risk of AD compared with simvastatin using an active-comparator design (95% confidence interval 0.51-0.63, p < 0.0001). In summary, NETTAG offers a deep learning methodology that utilizes GWAS and multi-genomic findings to identify pathobiology and drug repurposing in AD.

Bridging Integrator 1 (BIN1, rs6733839) and Sex Are Moderators of Vascular Health Predictions of Memory Aging Trajectories

Background: A promising risk loci for sporadic Alzheimer’s disease (AD), Bridging Integrator 1 (BIN1), is thought to operate through the tau pathology pathway. Objective: We examine BIN1 risk for a moderating role with vascular health (pulse pressure; PP) and sex in predictions of episodic memory trajectories in asymptomatic aging adults. Methods: The sample included 623 participants (Baseline Mean age = 70.1; 66.8% female) covering a 44-year longitudinal band (53–97 years). With an established memory latent variable arrayed as individualized trajectories, we applied Mplus 8.5 to determine the best fitting longitudinal growth model. Main analyses were conducted in three sequential phases to investigate: 1) memory trajectory prediction by PP, 2) moderation by BIN1 genetic risk, and 3) stratification by sex. Results: We first confirmed that good vascular health (lower PP) was associated with higher memory level and shallower decline and males were more severely affected by worsening PP in both memory performance and longitudinal decline. Second, the PP prediction of memory trajectories was significant for BIN1 C/C and C/T carriers but not for persons with the highest AD risk (T/T homozygotes). Third, when further stratified by sex, the BIN1 moderation of memory prediction by PP was selective for females. Conclusion: We observed a novel interaction whereby BIN1 (linked with tauopathy in AD) and sex sequentially moderated a benchmark PP prediction of differential memory decline in asymptomatic aging. This multi-modal biomarker interaction approach, disaggregated by sex, can be an effective method for enhancing precision of AD genetic risk assessment.

The impact of Alzheimer's disease susceptibility loci on lateral ventricular surface morphology in older adults

The enlargement of ventricular volume is a general trend in the elderly, especially in patients with Alzheimer's disease (AD). Multiple susceptibility loci have been reported to have an increased risk for AD and the morphology of brain structures are affected by the variations in the risk loci. Therefore, we hypothesized that genes contributed significantly to the ventricular surface, and the changes of ventricular surface were associated with the impairment of cognitive functions. After the quality controls (QC) and genotyping, a lateral ventricular segmentation method was employed to obtain the surface features of lateral ventricle. We evaluated the influence of 18 selected AD susceptibility loci on both volume and surface morphology across 410 subjects from Alzheimer's Disease Neuroimaging Initiative (ADNI). Correlations were conducted between radial distance (RD) and Montreal Cognitive Assessment (MoCA) subscales. Only the C allele at the rs744373 loci in BIN1 gene significantly accelerated the atrophy of lateral ventricle, including the anterior horn, body, and temporal horn of left lateral ventricle. No significant effect on lateral ventricle was found at other loci. Our results revealed that most regions of the bilateral ventricular surface were significantly negatively correlated with cognitive scores, particularly in delayed recall. Besides, small areas of surface were negatively correlated with language, orientation, and visuospatial scores. Together, our results indicated that the genetic variation affected the localized areas of lateral ventricular surface, and supported that lateral ventricle was an important brain structure associated with cognition in the elderly.

Associations of ARHGAP26 Polymorphisms with Alzheimer's Disease and Cardiovascular Disease

The Rho GTPase activating protein 26 (ARHGAP26) gene has been reported to be associated with neuropsychiatric diseases and neurodegenerative diseases including Parkinson's disease. We examined whether the ARHGAP26 gene is associated with Alzheimer's disease (AD) and/or cardiovascular disease (CVD). Multivariable logistic regression model was used to examine the associations of 154 single nucleotide polymorphisms (SNPs) within the ARHGAP26 gene with AD and CVD using the Alzheimer's Disease Neuroimaging Initiative 1 (ADNI-1) cohort. Fourteen SNPs were associated with AD (top SNP rs3776362 with p = 3.43 × 10^-3), while 37 SNPs revealed associations with CVD (top SNP rs415235 with p = 2.06 × 10^-4). Interestingly, 13 SNPs were associated with both AD and CVD. SNP rs3776362 was associated with CVD, Functional Activities Questionnaire (FAQ), and Clinical Dementia Rating Sum of Boxes (CDR-SB). A replication study using a Caribbean Hispanics sample showed that 17 SNPs revealed associations with AD, and 12 SNPs were associated with CVD. The third sample using a family-based study design showed that 9 SNPs were associated with AD, and 3 SNPs were associated with CVD. SNP rs6836509 within the ARHGAP10 gene (an important paralogon of ARHGAP26) was associated with AD and cerebrospinal fluid total tau (t-tau) level in the ADNI sample. Several SNPs were functionally important using the RegulomeDB, while a number of SNPs were associated with significant expression quantitative trait loci (eQTLs) using Genotype-Tissue Expression (GTEx) databases. In conclusion, genetic variants within ARHGAP26 were associated with AD and CVD. These findings add important new insights into the potentially shared pathogenesis of AD and CVD.

Evaluation of mild cognitive impairment genetic susceptibility risks in a Chinese population

BACKGROUND

Mild cognitive impairment (MCI) is a kind of non-functional cognitive decline between normal aging and dementia. With the increase of individual age, the quality of cognitive function has become a more and more important topic. The study of gene loci in patients with MCI is essential for the prevention of dementia. In this study, we evaluate the gene polymorphism in Chinese Han patients with MCI by propensity score matching (PSM) and comparing them to healthy control (HC) subjects.

METHODS

Four hundred seventeen patients with mild cognitive impairment and 508 healthy people were included. The two groups were matched by applying one-to-one PSM, and the matching tolerance was set to 0.002. The matching covariates included gender,age,occupation,marital status,living mode. Then, a case-control associated analysis was conducted to analyze the genotype and allele frequencies of single nucleotide polymorphisms (SNPs) in the MCI group and the control group.

RESULTS

Three hundred eleven cases were successfully matched in each group, and there was no statistical difference on all the matching variables, gender, age, occupation, marital status, living mode between two groups after the match (P > 0.05). The allele frequency of bridging integrator 1(BIN1) rs7561528 showed minimal association with MCI in the Han Chinese population (P = 0.01). Compared with the healthy control (HC) group, A allele frequency of MCI group patients was significantly decreased. The genotype frequency of BIN1 rs6733839 showed minimal association with MCI in the recessive model (P = 0.03). The genotype frequency of rs7561528 showed minimal association with MCI in the codominant, dominant, overdominant, and log-additive model (P < 0.05). The genotype frequencies of StAR-related lipid transfer domain 6 (STARD6) rs10164112 showed nominal association with MCI in the codominant, dominant, and log-additive model (P < 0.05). Unfortunately, the significant differences did not survive Benjamini-Hochberg false discovery rate correction (adjusted P > 0.05). The patients with SPI1 rs1057233 may be the protective factor of MCI (OR = 0.733, 95%CI 0.625-0.859, P < 0.001), and patients with APOE rs10164112 may be a risk factor for MCI (OR = 1.323, 95%CI 1.023-1.711, P = 0.033).

CONCLUSIONS

The polymorphisms of rs7561528, rs6733839 loci in the BIN1 gene, and rs1057233 loci in the SPI1 gene may be associated with the MCI in Chinese Han population. APOE gene was the risk factor of MCI, but further verification in a large sample population is still needed.

DNA Methylation: A Promising Approach in Management of Alzheimer's Disease and Other Neurodegenerative Disorders

Simple Summary

DNA methylation is an epigenetic modification of genes which affects corresponding gene expression. During the developmental stage, embryonic stem cells undergo various epigenetic modifications to produce different specialized cells. DNA methylation appears as one of the important epigenetic modifications which not only potentiate neuronal development but also have been sought in various neurodegenerative diseases, such as Alzheimer’s disease. The present work focuses on the history of DNA methylation, its role in neurodevelopment functions, and how assessment of DNA hypermethylation and hypomethylation can be utilized for the prognosis of AD and other neurodegenerative diseases. This review also paves the way for the development of novel treatment strategies based on targeting DNA methylation in neurodegenerative diseases.

Abstract

DNA methylation, in the mammalian genome, is an epigenetic modification that involves the transfer of a methyl group on the C5 position of cytosine to derive 5-methylcytosine. The role of DNA methylation in the development of the nervous system and the progression of neurodegenerative diseases such as Alzheimer’s disease has been an interesting research area. Furthermore, mutations altering DNA methylation affect neurodevelopmental functions and may cause the progression of several neurodegenerative diseases. Epigenetic modifications in neurodegenerative diseases are widely studied in different populations to uncover the plausible mechanisms contributing to the development and progression of the disease and detect novel biomarkers for early prognosis and future pharmacotherapeutic targets. In this manuscript, we summarize the association of DNA methylation with the pathogenesis of the most common neurodegenerative diseases, such as, Alzheimer’s disease, Parkinson’s disease, Huntington diseases, and amyotrophic lateral sclerosis, and discuss the potential of DNA methylation as a potential biomarker and therapeutic tool for neurogenerative diseases.

Alzheimer's Disease: Pathogenesis and Therapeutic Interventions

BACKGROUND

Alzheimer's Disease (AD) is the most common cause of dementia. Genetics, excessive exposure to environmental pollutants, as well as unhealthy lifestyle practices are often linked to the development of AD. No therapeutic approach has achieved complete success in treating AD; however, early detection and management with appropriate drugs are key to improving prognosis.

INTERVENTIONS

The pathogenesis of AD was extensively discussed in order to understand the reasons for the interventions suggested. The interventions reviewed include the use of different therapeutic agents and approaches, gene therapy, adherence to healthy dietary plans (Mediterranean diet, Okinawan diet and MIND diet), as well as the use of medicinal plants. The potential of nanotechnology as a multidisciplinary and interdisciplinary approach in the design of nano-formulations of AD drugs and the use of Superparamagnetic Iron Oxide Nanoparticles (SPIONs) as theranostic tools for early detection of Alzheimer's disease were also discussed.

Attenuated Negative Feedback in Monocyte-Derived Macrophages From Persons Living With HIV: A Role for IKAROS

Persons living with HIV (PLWH) are at higher risk of developing secondary illnesses than their uninfected counterparts, suggestive of a dysfunctional immune system in these individuals. Upon exposure to pathogens, monocytes undergo epigenetic remodeling that results in either a trained or a tolerant phenotype, characterized by hyper-responsiveness or hypo-responsiveness to secondary stimuli, respectively. We utilized CD14⁺ monocytes from virally suppressed PLWH and healthy controls for in vitro analysis following polarization of these cells toward a pro-inflammatory monocyte-derived macrophage (MDM) phenotype. We found that in PLWH-derived MDMs, pro-inflammatory signals (TNFA, IL6, IL1B, miR-155-5p, and IDO1) dominate over negative feedback signals (NCOR2, GSN, MSC, BIN1, and miR-146a-5p), favoring an abnormally trained phenotype. The mechanism of this reduction in negative feedback involves the attenuated expression of IKZF1, a transcription factor required for de novo synthesis of RELA during LPS-induced inflammatory responses. Furthermore, restoring IKZF1 expression in PLWH-MDMs partially reinstated expression of negative regulators of inflammation and lowered the expression of pro-inflammatory cytokines. Overall, this mechanism may provide a link between dysfunctional immune responses and susceptibility to co-morbidities in PLWH with low or undetectable viral load.

RNA Modifications and RNA Metabolism in Neurological Disease Pathogenesis

The intrinsic cellular heterogeneity and molecular complexity of the mammalian nervous system relies substantially on the dynamic nature and spatiotemporal patterning of gene expression. These features of gene expression are achieved in part through mechanisms involving various epigenetic processes such as DNA methylation, post-translational histone modifications, and non-coding RNA activity, amongst others. In concert, another regulatory layer by which RNA bases and sugar residues are chemically modified enhances neuronal transcriptome complexity. Similar RNA modifications in other systems collectively constitute the cellular epitranscriptome that integrates and impacts various physiological processes. The epitranscriptome is dynamic and is reshaped constantly to regulate vital processes such as development, differentiation and stress responses. Perturbations of the epitranscriptome can lead to various pathogenic conditions, including cancer, cardiovascular abnormalities and neurological diseases. Recent advances in next-generation sequencing technologies have enabled us to identify and locate modified bases/sugars on different RNA species. These RNA modifications modulate the stability, transport and, most importantly, translation of RNA. In this review, we discuss the formation and functions of some frequently observed RNA modifications—including methylations of adenine and cytosine bases, and isomerization of uridine to pseudouridine—at various layers of RNA metabolism, together with their contributions to abnormal physiological conditions that can lead to various neurodevelopmental and neurological disorders.

Deep post-GWAS analysis identifies potential risk genes and risk variants for Alzheimer's disease, providing new insights into its disease mechanisms

Alzheimer’s disease (AD) is a genetically complex, multifactorial neurodegenerative disease. It affects more than 45 million people worldwide and currently remains untreatable. Although genome-wide association studies (GWAS) have identified many AD-associated common variants, only about 25 genes are currently known to affect the risk of developing AD, despite its highly polygenic nature. Moreover, the risk variants underlying GWAS AD-association signals remain unknown. Here, we describe a deep post-GWAS analysis of AD-associated variants, using an integrated computational framework for predicting both disease genes and their risk variants. We identified 342 putative AD risk genes in 203 risk regions spanning 502 AD-associated common variants. 246 AD risk genes have not been identified as AD risk genes by previous GWAS collected in GWAS catalogs, and 115 of 342 AD risk genes are outside the risk regions, likely under the regulation of transcriptional regulatory elements contained therein. Even more significantly, for 109 AD risk genes, we predicted 150 risk variants, of both coding and regulatory (in promoters or enhancers) types, and 85 (57%) of them are supported by functional annotation. In-depth functional analyses showed that AD risk genes were overrepresented in AD-related pathways or GO terms—e.g., the complement and coagulation cascade and phosphorylation and activation of immune response—and their expression was relatively enriched in microglia, endothelia, and pericytes of the human brain. We found nine AD risk genes—e.g., IL1RAP, PMAIP1, LAMTOR4—as predictors for the prognosis of AD survival and genes such as ARL6IP5 with altered network connectivity between AD patients and normal individuals involved in AD progression. Our findings open new strategies for developing therapeutics targeting AD risk genes or risk variants to influence AD pathogenesis.

lncRNA SNHG1 Knockdown Alleviates Amyloid-β-Induced Neuronal Injury by Regulating ZNF217 via Sponging miR-361-3p in Alzheimer's Disease

BACKGROUND

Long noncoding RNAs have been proven to play an important role in the progression of Alzheimer's disease (AD). However, the function of small nucleolar RNA host gene 1 (SNHG1) in AD progression remains to be studied.

OBJECTIVE

To explore the role of SNHG1 in AD progression and clarify its potential mechanism.

METHODS

Amyloid β-protein (Aβ) was used to construct an AD cell model in vitro. The expression levels of SNHG1 and miR-361-3p were determined by quantitative real-time polymerase chain reaction. Cell viability and apoptosis were measured by cell counting kit 8 assay and flow cytometry. The levels of apoptosis-related proteins and zinc finger gene 217 (ZNF217) protein were evaluated by western blot analysis. Additionally, the contents of inflammatory cytokines and oxidative stress markers were tested by enzyme-linked immunosorbent assay. Furthermore, dual-luciferase reporter and RNA immunoprecipitation assays were used to verify the interaction between miR-361-3p and SNHG1 or ZNF217.

RESULTS

Aβ could induce cell injury, while resveratrol could reverse this effect. SNHG1 expression was positively regulated by Aβ and negatively regulated by resveratrol. SNHG1 knockdown could reverse the promotion effect of Aβ on cell injury. Moreover, SNHG1 sponged miR-361-3p, and miR-361-3p targeted ZNF217. Additionally, miR-361-3p overexpression reversed the promotion effect of SNHG1 overexpression on cell injury, and ZNF217 silencing also reversed the promotion effect of miR-361-3p inhibitor on cell injury.

CONCLUSION

SNHG1 promoted cell injury by regulating the miR-361-3p/ZNF217 axis, which might provide a theoretical basis for molecular therapy of AD.

Alzheimer's disease BIN1 coding variants increase intracellular Aβ levels by interfering with BACE1 recycling

Genetic studies have identified BIN1 as the second most important risk locus associated with late-onset Alzheimer's disease (LOAD). However, it is unclear how mutation of this locus mechanistically promotes Alzheimer's disease (AD) pathology. Here we show the consequences of two coding variants in BIN1 (rs754834233 and rs138047593), both in terms of intracellular beta-amyloid (iAbeta) accumulation and early endosome enlargement, two interrelated early cytopathological AD phenotypes, supporting their association with LOAD risk. We previously found that Bin1 deficiency potentiates iAbeta production by enabling BACE1 cleavage of the amyloid precursor protein in enlarged early endosomes due to decreased BACE1 recycling. Here, we discovered that the expression of the two LOAD mutant forms of Bin1 does not rescue the iAbeta accumulation and early endosome enlargement induced by Bin1 knockdown and recovered by wild-type Bin1. Moreover, the overexpression of Bin1 mutants, but not wild-type Bin1, increased the iAbeta42 fragment by reducing the recycling of BACE1, which accumulated in early endosomes, recapitulating the phenotype of Bin1 knockdown. We showed that the mutations in Bin1 reduced its interaction with BACE1. The endocytic recycling of transferrin was similarly affected, indicating that Bin1 is a general regulator of endocytic recycling. These data demonstrate that the LOAD-coding variants in Bin1 lead to a loss of function in endocytic recycling, which may be an early causal mechanism of LOAD.

On the border of the amyloidogenic sequences: prefix analysis of the parallel beta sheets in the PDB_Amyloid collection

The Protein Data Bank (PDB) today contains more than 174,000 entries with the 3-dimensional structures of biological macromolecules. Using the rich resources of this repository, it is possible identifying subsets with specific, interesting properties for different applications. Our research group prepared an automatically updated list of amyloid- and probably amyloidogenic molecules, the PDB_Amyloid collection, which is freely available at the address http://pitgroup.org/amyloid. This resource applies exclusively the geometric properties of the steric structures for identifying amyloids. In the present contribution, we analyze the starting (i.e., prefix) subsequences of the characteristic, parallel beta-sheets of the structures in the PDB_Amyloid collection, and identify further appearances of these length-5 prefix subsequences in the whole PDB data set. We have identified this way numerous proteins, whose normal or irregular functions involve amyloid formation, structural misfolding, or anti-coagulant properties, simply by containing these prefixes: including the T-cell receptor (TCR), bound with the major histocompatibility complexes MHC-1 and MHC-2; the p53 tumor suppressor protein; a mycobacterial RNA polymerase transcription initialization complex; the human bridging integrator protein BIN-1; and the tick anti-coagulant peptide TAP.

GWAS-Top Polymorphisms Associated With Late-Onset Alzheimer Disease in Brazil: Pointing Out Possible New Culprits Among Non-Coding RNAs

Several genome-wide association studies (GWAS) have been carried out with late-onset Alzheimer's disease (LOAD), mainly in European and Asian populations. Different polymorphisms were associated, but several of them without a functional explanation. GWAS are fundamental for identifying loci associated with diseases, although they often do not point to causal polymorphisms. In this sense, functional investigations are a fundamental tool for discovering causality, although the failure of this validation does not necessarily indicate a non-causality. Furthermore, the allele frequency of associated genetic variants may vary widely between populations, requiring replication of these associations in other ethnicities. In this sense, our study sought to replicate in 150 AD patients and 114 elderly controls from the South Brazilian population 18 single-nucleotide polymorphisms (SNPs) associated with AD in European GWAS, with further functional investigation using bioinformatic tools for the associated SNPs. Of the 18 SNPs investigated, only four were associated in our population: rs769449 (APOE), rs10838725 (CELF1), rs6733839, and rs744373 (BIN1-CYP27C1). We identified 54 variants in linkage disequilibrium (LD) with the associated SNPs, most of which act as expression or splicing quantitative trait loci (eQTLs/sQTLs) in genes previously associated with AD or with a possible functional role in the disease, such as CELF1, MADD, MYBPC3, NR1H3, NUP160, SPI1, and TOMM40. Interestingly, eight of these variants are located within long non-coding RNA (lncRNA) genes that have not been previously investigated regarding AD. Some of these polymorphisms can result in changes in these lncRNAs' secondary structures, leading to either loss or gain of microRNA (miRNA)-binding sites, deregulating downstream pathways. Our pioneering work not only replicated LOAD association with polymorphisms not yet associated in the Brazilian population but also identified six possible lncRNAs that may interfere in LOAD development. The results lead us to emphasize the importance of functional exploration of associations found in large-scale association studies in different populations to base personalized and inclusive medicine in the future.

The BIN1 rs744373 Alzheimer's disease risk SNP is associated with faster Aβ-associated tau accumulation and cognitive decline

INTRODUCTION

The BIN1 rs744373 single nucleotide polymorphism (SNP) is a key genetic risk locus for Alzheimer's disease (AD) associated with tau pathology. Because tau typically accumulates in response to amyloid beta (Aβ), we tested whether BIN1 rs744373 accelerates Aβ-related tau accumulation.

METHODS

We included two samples (Alzheimer's Disease Neuroimaging Initiative [ADNI], n = 153; Biomarkers for Identifying Neurodegenerative Disorders Early and Reliably [BioFINDER], n = 63) with longitudinal ¹⁸ F-Flortaucipir positron emission tomography (PET), Aβ biomarkers, and longitudinal cognitive assessments. We assessed whether BIN1 rs744373 was associated with faster tau-PET accumulation at a given level of Aβ and whether faster BIN1 rs744373-associated tau-PET accumulation mediated cognitive decline.

RESULTS

BIN1 rs744373 risk-allele carriers showed faster global tau-PET accumulation (ADNI/BioFINDER, P < .001/P < .001). We found significant Aβ by rs744373 interactions on global tau-PET change (ADNI: β/standard error [SE] = 0.42/0.14, P = 0.002; BioFINDER: β/SE = -0.35/0.15, P = .021), BIN1 risk-allele carriers showed accelerated tau-PET accumulation at higher Aβ levels. In ADNI, rs744373 effects on cognitive decline were mediated by faster global tau-PET accumulation (β/SE = 0.20/0.07, P = .005).

DISCUSSION

BIN1-associated AD risk is potentially driven by accelerated tau accumulation in the face of Aβ.

Genetic Predisposition to Alzheimer's Disease Is Associated with Enlargement of Perivascular Spaces in Centrum Semiovale Region

This study investigated whether genetic factors involved in Alzheimer’s disease (AD) are associated with enlargement of Perivascular Spaces (ePVS) in the brain. A total of 680 participants with T2-weighted MRI scans and genetic information were acquired from the ALFA study. ePVS in the basal ganglia (BG) and the centrum semiovale (CS) were assessed based on a validated visual rating scale. We used univariate and multivariate logistic regression models to investigate associations between ePVS in BG and CS with BIN1-rs744373, as well as APOE genotypes. We found a significant association of the BIN1-rs744373 polymorphism in the CS subscale (p value = 0.019; OR = 2.564), suggesting that G allele carriers have an increased risk of ePVS in comparison with A allele carriers. In stratified analysis by APOE-ε4 status (carriers vs. non-carriers), these results remained significant only for ε4 carriers (p value = 0.011; OR = 1.429). To our knowledge, the present study is the first suggesting that genetic predisposition for AD is associated with ePVS in CS. These findings provide evidence that underlying biological processes affecting AD may influence CS-ePVS.

Role of Microglia in Regulating Cholesterol and Tau Pathology in Alzheimer's Disease

Cholesterol, a principal constituent of the cell membrane, plays a crucial role in the brain by regulating the synaptic transmission, neuronal signaling, as well as neurodegenerative diseases. Defects in the cholesterol trafficking are associated with enhanced generation of hyperphosphorylated Tau and Amyloid-β protein. Tau, a major microtubule-associated protein in the brain, is the key regulator of the mature neuron. Abnormally hyperphosphorylated Tau hampers the major functions related to microtubule assembly by promoting neurofibrillary tangles of paired helical filaments, twisted ribbons, and straight filaments. The observed pathological changes due to impaired cholesterol and Tau protein accumulation cause Alzheimer's disease. Thus, in order to regulate the pathogenesis of Alzheimer's disease, regulation of cholesterol metabolism, as well as Tau phosphorylation, is essential. The current review provides an overview of (1) cholesterol synthesis in the brain, neurons, astrocytes, and microglia; (2) the mechanism involved in modulating cholesterol concentration between the astrocytes and brain; (3) major mechanisms involved in the hyperphosphorylation of Tau and amyloid-β protein; and (4) microglial involvement in its regulation. Thus, the answering key questions will provide an in-depth information on microglia involvement in managing the pathogenesis of cholesterol-modulated hyperphosphorylated Tau protein.

Animal and Cellular Models of Alzheimer's Disease: Progress, Promise, and Future Approaches

Alzheimer's disease (AD) is an incurable neurodegenerative disease affecting over 45 million people worldwide. Transgenic mouse models have made remarkable contributions toward clarifying the pathophysiological mechanisms behind the clinical manifestations of AD. However, the limited ability of these in vivo models to accurately replicate the biology of the human disease have precluded the translation of promising preclinical therapies to the clinic. In this review, we highlight several major pathogenic mechanisms of AD that were discovered using transgenic mouse models. Moreover, we discuss the shortcomings of current animal models and the need to develop reliable models for the sporadic form of the disease, which accounts for the majority of AD cases, as well as human cellular models to improve success in translating results into human treatments.

An Analysis of the Neurological and Molecular Alterations Underlying the Pathogenesis of Alzheimer's Disease

Alzheimer’s disease (AD) is a neurodegenerative disorder characterized by amyloid beta (Aβ) plaques, neurofibrillary tangles, and neuronal loss. Unfortunately, despite decades of studies being performed on these histological alterations, there is no effective treatment or cure for AD. Identifying the molecular characteristics of the disease is imperative to understanding the pathogenesis of AD. Furthermore, uncovering the key causative alterations of AD can be valuable in developing models for AD treatment. Several alterations have been implicated in driving this disease, including blood–brain barrier dysfunction, hypoxia, mitochondrial dysfunction, oxidative stress, glucose hypometabolism, and altered heme homeostasis. Although these alterations have all been associated with the progression of AD, the root cause of AD has not been identified. Intriguingly, recent studies have pinpointed dysfunctional heme metabolism as a culprit of the development of AD. Heme has been shown to be central in neuronal function, mitochondrial respiration, and oxidative stress. Therefore, dysregulation of heme homeostasis may play a pivotal role in the manifestation of AD and its various alterations. This review will discuss the most common neurological and molecular alterations associated with AD and point out the critical role heme plays in the development of this disease.

Coupling of Co-expression Network Analysis and Machine Learning Validation Unearthed Potential Key Genes Involved in Rheumatoid Arthritis

Rheumatoid arthritis (RA) is an incurable disease that afflicts 0.5-1.0% of the global population though it is less threatening at its early stage. Therefore, improved diagnostic efficiency and prognostic outcome are critical for confronting RA. Although machine learning is considered a promising technique in clinical research, its potential in verifying the biological significance of gene was not fully exploited. The performance of a machine learning model depends greatly on the features used for model training; therefore, the effectiveness of prediction might reflect the quality of input features. In the present study, we used weighted gene co-expression network analysis (WGCNA) in conjunction with differentially expressed gene (DEG) analysis to select the key genes that were highly associated with RA phenotypes based on multiple microarray datasets of RA blood samples, after which they were used as features in machine learning model validation. A total of six machine learning models were used to validate the biological significance of the key genes based on gene expression, among which five models achieved good performances [area under curve (AUC) >0.85], suggesting that our currently identified key genes are biologically significant and highly representative of genes involved in RA. Combined with other biological interpretations including Gene Ontology (GO) analysis, protein-protein interaction (PPI) network analysis, as well as inference of immune cell composition, our current study might shed a light on the in-depth study of RA diagnosis and prognosis.

Pursuing sources of heterogeneity in modeling clustered population

Researchers often have to deal with heterogeneous population with mixed regression relationships, increasingly so in the era of data explosion. In such problems, when there are many candidate predictors, it is not only of interest to identify the predictors that are associated with the outcome, but also to distinguish the true sources of heterogeneity, that is, to identify the predictors that have different effects among the clusters and thus are the true contributors to the formation of the clusters. We clarify the concepts of the source of heterogeneity that account for potential scale differences of the clusters and propose a regularized finite mixture effects regression to achieve heterogeneity pursuit and feature selection simultaneously. We develop an efficient algorithm and show that our approach can achieve both estimation and selection consistency. Simulation studies further demonstrate the effectiveness of our method under various practical scenarios. Three applications are presented, namely, an imaging genetics study for linking genetic factors and brain neuroimaging traits in Alzheimer's disease, a public health study for exploring the association between suicide risk among adolescents and their school district characteristics, and a sport analytics study for understanding how the salary levels of baseball players are associated with their performance and contractual status.

The biological pathways of Alzheimer disease: a review

Alzheimer disease is a progressive neurodegenerative disorder, mainly affecting older people, which severely impairs patients' quality of life. In the recent years, the number of affected individuals has seen a rapid increase. It is estimated that up to 107 million subjects will be affected by 2050 worldwide. Research in this area has revealed a lot about the biological and environmental underpinnings of Alzheimer, especially its correlation with β-Amyloid and Tau related mechanics; however, the precise molecular events and biological pathways behind the disease are yet to be discovered. In this review, we focus our attention on the biological mechanics that may lie behind Alzheimer development. In particular, we briefly describe the genetic elements and discuss about specific biological processes potentially associated with the disease.

scTenifoldNet: A Machine Learning Workflow for Constructing and Comparing Transcriptome-wide Gene Regulatory Networks from Single-Cell Data

We present scTenifoldNet-a machine learning workflow built upon principal-component regression, low-rank tensor approximation, and manifold alignment-for constructing and comparing single-cell gene regulatory networks (scGRNs) using data from single-cell RNA sequencing. scTenifoldNet reveals regulatory changes in gene expression between samples by comparing the constructed scGRNs. With real data, scTenifoldNet identifies specific gene expression programs associated with different biological processes, providing critical insights into the underlying mechanism of regulatory networks governing cellular transcriptional activities.

The Differential Influence of Immune, Endocytotic, and Lipid Metabolism Genes on Amyloid Deposition and Neurodegeneration in Subjects at Risk of Alzheimer's Disease

BACKGROUND

Over 20 single-nucleotide polymorphisms (SNPs) are associated with increased risk of Alzheimer's disease (AD). We categorized these loci into immunity, lipid metabolism, and endocytosis pathways, and associated the polygenic risk scores (PRS) calculated, with AD biomarkers in mild cognitive impairment (MCI) subjects.

OBJECTIVE

The aim of this study was to identify associations between pathway-specific PRS and AD biomarkers in patients with MCI and healthy controls.

METHODS

AD biomarkers ([18F]Florbetapir-PET SUVR, FDG-PET SUVR, hippocampal volume, CSF tau and amyloid-β levels) and neurocognitive tests scores were obtained in 258 healthy controls and 451 MCI subjects from the ADNI dataset at baseline and at 24-month follow up. Pathway-related (immunity, lipid metabolism, and endocytosis) and total polygenic risk scores were calculated from 20 SNPs. Multiple linear regression analysis was used to test predictive value of the polygenic risk scores over longitudinal biomarker and cognitive changes.

RESULTS

Higher immune risk score was associated with worse cognitive measures and reduced glucose metabolism. Higher lipid risk score was associated with increased amyloid deposition and cortical hypometabolism. Total, immune, and lipid scores were associated with significant changes in cognitive measures, amyloid deposition, and brain metabolism.

CONCLUSION

Polygenic risk scores highlights the influence of specific genes on amyloid-dependent and independent pathways; and these pathways could be differentially influenced by lipid and immune scores respectively.

Genetic Risk, Vascular Function, and Subjective Cognitive Complaints Predict Objective Cognitive Function in Healthy Older Adults: Results From the Brain in Motion Study

Aging is associated with subjective memory complaints. Approximately half of those with subjective memory complaints have objective cognitive impairment. Previous studies have provided evidence of an association between genetic risk for Alzheimer’s disease (AD) and dementia progression. Also, aging is a significant risk factor for vascular pathology that may underlie at least some of the cognitive changes. This study investigates the relative contribution of subjective cognitive complaints (SCC), vascular function, and genetic risk for dementia in predicting objective cognitive performance. Multiple regression and relative importance analysis were used to investigate the relative contribution of vascular function, self-reported SCC, and dementia genetic risk, in predicting objective cognition in a sample of 238 healthy community-dwelling older adults. Age, sex, premorbid cognitive abilities, subjective verbal memory complaints, higher cerebrovascular blood flow during submaximal exercise, and certain dementia risk alleles were significant predictors of worse objective verbal memory performance (p < 0.001, R² = 35.2–36.4%). Using relative importance analysis, subjective verbal memory complaints, and certain dementia risk alleles contributed more variance than cerebrovascular measures. These results suggest that age-related changes in memory in healthy older adults can be predicted by subjective memory complaints, genetic risk, and to a lesser extent, cerebrovascular function.

Hippocampal and cortical tissue-specific epigenetic clocks indicate an increased epigenetic age in a mouse model for Alzheimer's disease

Epigenetic clocks are based on age-associated changes in DNA methylation of CpG-sites, which can accurately measure chronological age in different species. Recently, several studies have indicated that the difference between chronological and epigenetic age, defined as the age acceleration, could reflect biological age indicating functional decline and age-associated diseases. In humans, an epigenetic clock associated Alzheimer's disease (AD) pathology with an acceleration of the epigenetic age. In this study, we developed and validated two mouse brain region-specific epigenetic clocks from the C57BL/6J hippocampus and cerebral cortex. Both clocks, which could successfully estimate chronological age, were further validated in a widely used mouse model for AD, the triple transgenic AD (3xTg-AD) mouse. We observed an epigenetic age acceleration indicating an increased biological age for the 3xTg-AD mice compared to non-pathological C57BL/6J mice, which was more pronounced in the cortex as compared to the hippocampus. Genomic region enrichment analysis revealed that age-dependent CpGs were enriched in genes related to developmental, aging-related, neuronal and neurodegenerative functions. Due to the limited access of human brain tissues, these epigenetic clocks specific for mouse cortex and hippocampus might be important in further unravelling the role of epigenetic mechanisms underlying AD pathology or brain aging in general.

The dark side of Alzheimer's disease: unstructured biology of proteins from the amyloid cascade signaling pathway

Alzheimer's disease (AD) is a leading cause of age-related dementia worldwide. Despite more than a century of intensive research, we are not anywhere near the discovery of a cure for this disease or a way to prevent its progression. Among the various molecular mechanisms proposed for the description of the pathogenesis and progression of AD, the amyloid cascade hypothesis, according to which accumulation of a product of amyloid precursor protein (APP) cleavage, amyloid β (Aβ) peptide, induces pathological changes in the brain observed in AD, occupies a unique niche. Although multiple proteins have been implicated in this amyloid cascade signaling pathway, their structure-function relationships are mostly unexplored. However, it is known that two major proteins related to AD pathology, Aβ peptide, and microtubule-associated protein tau belong to the category of intrinsically disordered proteins (IDPs), which are the functionally important proteins characterized by a lack of fixed, ordered three-dimensional structure. IDPs and intrinsically disordered protein regions (IDPRs) play numerous vital roles in various cellular processes, such as signaling, cell cycle regulation, macromolecular recognition, and promiscuous binding. However, the deregulation and misfolding of IDPs may lead to disturbed signaling, interactions, and disease pathogenesis. Often, molecular recognition-related IDPs/IDPRs undergo disorder-to-order transition upon binding to their biological partners and contain specific disorder-based binding motifs, known as molecular recognition features (MoRFs). Knowing the intrinsic disorder status and disorder-based functionality of proteins associated with amyloid cascade signaling pathway may help to untangle the mechanisms of AD pathogenesis and help identify therapeutic targets. In this paper, we have used multiple computational tools to evaluate the presence of intrinsic disorder and MoRFs in 27 proteins potentially relevant to the amyloid cascade signaling pathway. Among these, BIN1, APP, APOE, PICALM, PSEN1 and CD33 were found to be highly disordered. Furthermore, their disorder-based binding regions and associated short linear motifs have also been identified. These findings represent important foundation for the future research, and experimental characterization of disordered regions in these proteins is required to better understand their roles in AD pathogenesis.

CoMM-S2: a collaborative mixed model using summary statistics in transcriptome-wide association studies

MOTIVATION

Although genome-wide association studies (GWAS) have deepened our understanding of the genetic architecture of complex traits, the mechanistic links that underlie how genetic variants cause complex traits remains elusive. To advance our understanding of the underlying mechanistic links, various consortia have collected a vast volume of genomic data that enable us to investigate the role that genetic variants play in gene expression regulation. Recently, a collaborative mixed model (CoMM) was proposed to jointly interrogate genome on complex traits by integrating both the GWAS dataset and the expression quantitative trait loci (eQTL) dataset. Although CoMM is a powerful approach that leverages regulatory information while accounting for the uncertainty in using an eQTL dataset, it requires individual-level GWAS data and cannot fully make use of widely available GWAS summary statistics. Therefore, statistically efficient methods that leverages transcriptome information using only summary statistics information from GWAS data are required.

RESULTS

In this study, we propose a novel probabilistic model, CoMM-S2, to examine the mechanistic role that genetic variants play, by using only GWAS summary statistics instead of individual-level GWAS data. Similar to CoMM which uses individual-level GWAS data, CoMM-S2 combines two models: the first model examines the relationship between gene expression and genotype, while the second model examines the relationship between the phenotype and the predicted gene expression from the first model. Distinct from CoMM, CoMM-S2 requires only GWAS summary statistics. Using both simulation studies and real data analysis, we demonstrate that even though CoMM-S2 utilizes GWAS summary statistics, it has comparable performance as CoMM, which uses individual-level GWAS data.

AVAILABILITY AND IMPLEMENTATION

The implement of CoMM-S2 is included in the CoMM package that can be downloaded from https://github.com/gordonliu810822/CoMM.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

A novel role for the late-onset Alzheimer's disease (LOAD)-associated protein Bin1 in regulating postsynaptic trafficking and glutamatergic signaling

Postsynaptic trafficking plays a key role in regulating synapse structure and function. While spiny excitatory synapses can be stable throughout adult life, their morphology and function is impaired in Alzheimer's disease (AD). However, little is known about how AD risk genes impact synaptic function. Here we used structured superresolution illumination microscopy (SIM) to study the late-onset Alzheimer's disease (LOAD) risk factor BIN1, and show that this protein is abundant in postsynaptic compartments, including spines. While postsynaptic Bin1 shows colocalization with clathrin, a major endocytic protein, it also colocalizes with the small GTPases Rab11 and Arf6, components of the exocytic pathway. Bin1 participates in protein complexes with Arf6 and GluA1, and manipulations of Bin1 lead to changes in spine morphology, AMPA receptor surface expression and trafficking, and AMPA receptor-mediated synaptic transmission. Our data provide new insights into the mesoscale architecture of postsynaptic trafficking compartments and their regulation by a major LOAD risk factor.

The role of innate immunity in Alzheimer's disease

The amyloid hypothesis has dominated Alzheimer's disease (AD) research for almost 30 years. This hypothesis hinges on the predominant clinical role of the amyloid beta (Aβ) peptide in propagating neurofibrillary tangles (NFTs) and eventual cognitive impairment in AD. Recent research in the AD field has identified the brain-resident macrophages, known as microglia, and their receptors as integral regulators of both the initiation and propagation of inflammation, Aβ accumulation, neuronal loss, and memory decline in AD. Emerging studies have also begun to reveal critical roles for distinct innate immune pathways in AD pathogenesis, which has led to great interest in harnessing the innate immune response as a therapeutic strategy to treat AD. In this review, we will highlight recent advancements in our understanding of innate immunity and inflammation in AD onset and progression. Additionally, there has been mounting evidence suggesting pivotal contributions of environmental factors and lifestyle choices in AD pathogenesis. Therefore, we will also discuss recent findings, suggesting that many of these AD risk factors influence AD progression via modulation of microglia and immune responses.

PICALM rescues glutamatergic neurotransmission, behavioural function and survival in a Drosophila model of Aβ42 toxicity

Alzheimer's disease (AD) is the most common form of dementia and the most prevalent neurodegenerative disease. Genome-wide association studies have linked PICALM to AD risk. PICALM has been implicated in Aβ42 production and turnover, but whether it plays a direct role in modulating Aβ42 toxicity remains unclear. We found that increased expression of the Drosophila PICALM orthologue lap could rescue Aβ42 toxicity in an adult-onset model of AD, without affecting Aβ42 level. Imbalances in the glutamatergic system, leading to excessive, toxic stimulation, have been associated with AD. We found that Aβ42 caused the accumulation of presynaptic vesicular glutamate transporter (VGlut) and increased spontaneous glutamate release. Increased lap expression reversed these phenotypes back to control levels, suggesting that lap may modulate glutamatergic transmission. We also found that lap modulated the localization of amphiphysin (Amph), the homologue of another AD risk factor BIN1, and that Amph itself modulated postsynaptic glutamate receptor (GluRII) localization. We propose a model where PICALM modulates glutamatergic transmission, together with BIN1, to ameliorate synaptic dysfunction and disease progression.

Differential Methylation Levels in CpGs of the BIN1 Gene in Individuals With Alzheimer Disease

INTRODUCTION

Late-onset Alzheimer disease (LOAD) is the most common dementia worldwide. APOE-[Latin Small Letter Open E]4 and BIN1 (Bridging Integrator 1) have been implicated in the pathogenesis of this disease, but, although DNA methylation of dinucleotide CpGs in the BIN1 gene influences alterations, it has not been studied in Hispanics.

OBJECTIVE

The objective of this study was to evaluate the BIN1 3' intergenic region DNA methylation patterns in a Colombian sample of LOAD patients.

METHODS

A case-control study was conducted in 50 individuals with LOAD and 50 age-sex matched controls to determine associations of LOAD with DNA methylation. DNA was isolated from peripheral blood, and methylation levels of 8 CpGs were estimated by bisulfite conversion followed by Sanger sequencing with direct PCR analysis. Logistic regression models adjusted by age, sex, and APOE were used to calculate risk associations between methylation levels and LOAD.

RESULTS

Overall, participants with LOAD had significantly lower methylation levels on CpG26 (0.86±0.11 vs. 0.95±0.05; P>0.001), CpG44 (0.84±0.09 vs. 0.94±0.06; P=0.001), and CpG87 (0.64±0.12 vs. 0.82±0.10; P>0.001). Adjusted regression models showed that decreased methylation levels of these CpGs remained as risk factors for LOAD (P<0.05).

CONCLUSIONS

Hypomethylation of CpGs in BIN1 might play an important role in the expression of BIN1 and may be a biomarker for identifying individuals at high risk of developing LOAD.