Systematic meta-analyses of Alzheimer disease genetic association studies: the AlzGene database

Systematic Review and Phenome-Wide Scans of Genetic Associations with Vascular Cognitive Impairment

Vascular cognitive impairment (VCI) is a heterogenous form of cognitive impairment that results from cerebrovascular disease. It is a result of both genetic and non-genetic factors. Although much research has been conducted on the genetic contributors to other forms of cognitive impairment (e.g. Alzheimer's disease), knowledge is lacking on the genetic factors associated with VCI. A better understanding of the genetics of VCI will be critical for prevention and treatment. To begin to fill this gap, the genetic contributors are reviewed with VCI from the literature. Phenome-wide scans of the identified genes are conducted and genetic variants identified in the review in large-scale resources displaying genetic variant-trait association information. Gene set are also carried out enrichment analysis using the genes identified from the review. Thirty one articles are identified meeting the search criteria and filters, from which 107 unique protein-coding genes are noted related to VCI. The phenome-wide scans and gene set enrichment analysis identify pathways associated with a diverse set of biological systems. This results indicate that genes with evidence of involvement in VCI are involved in a diverse set of biological functions. This information can facilitate downstream research to better dissect possible shared biological mechanisms for future therapies.

Mitochondrial alterations in fibroblasts from sporadic Alzheimer's disease (AD) patients correlate with AD-related clinical hallmarks

Mitochondrial dysfunctions are key features of Alzheimer's disease (AD). The occurrence of these disturbances in the peripheral cells of AD patients and their potential correlation with disease progression are underinvestigated. We studied mitochondrial structure, function and mitophagy in fibroblasts from healthy volunteers and AD patients at the prodromal (AD-MCI) or demented (AD-D) stages. We carried out correlation studies with clinical cognitive scores, namely, (i) Mini-Mental State Examination (MMSE) and (ii) Dementia Rating-Scale Sum of Boxes (CDR-SOB), and with (iii) amyloid beta (Aβ) plaque burden (PiB-PET imaging) and (iv) the accumulation of peripheral amyloid precursor protein C-terminal fragments (APP-CTFs). We revealed alterations in mitochondrial structure as well as specific mitochondrial dysfunction signatures in AD-MCI and AD-D fibroblasts and revealed that defective mitophagy and autophagy are linked to impaired lysosomal activity in AD-D fibroblasts. We reported significant correlations of a subset of these dysfunctions with cognitive decline, AD-related clinical hallmarks and peripheral APP-CTFs accumulation. This study emphasizes the potential use of peripheral cells for investigating AD pathophysiology.

Classifying Alzheimer's disease and normal subjects using machine learning techniques and genetic-environmental features

BACKGROUND

Alzheimer's disease (AD) is complicated by multiple environmental and polygenetic factors. The accuracy of artificial neural networks (ANNs) incorporating the common factors for identifying AD has not been evaluated.

METHODS

A total of 184 probable AD patients and 3773 healthy individuals aged 65 and over were enrolled. AD-related genes (51 SNPs) and 8 environmental factors were selected as features for multilayer ANN modeling. Random Forest (RF) and Support Vector Machine with RBF kernel (SVM) were also employed for comparison. Model results were verified using traditional statistics.

RESULTS

The ANN achieved high accuracy (0.98), sensitivity (0.95), and specificity (0.96) in the intrinsic test for AD classification. Excluding age and genetic data still yielded favorable results (accuracy: 0.97, sensitivity: 0.94, specificity: 0.96). The assigned weights to ANN features highlighted the importance of mental evaluation, years of education, and specific genetic variations (CASS4 rs7274581, PICALM rs3851179, and TOMM40 rs2075650) for AD classification. Receiver operating characteristic analysis revealed AUC values of 0.99 (intrinsic test), 0.60 (TWB-GWA), and 0.72 (CG-WGS), with slightly lower AUC values (0.96, 0.80, 0.52) when excluding age in ANN. The performance of the ANN model in AD classification was comparable to RF, SVM (linear kernel), and SVM (RBF kernel).

CONCLUSION

The ANN model demonstrated good sensitivity, specificity, and accuracy in AD classification. The top-weighted SNPs for AD prediction were CASS4 rs7274581, PICALM rs3851179, and TOMM40 rs2075650. The ANN model performed similarly to RF and SVM, indicating its capability to handle the complexity of AD as a disease entity.

Learning semi-supervised enrichment of longitudinal imaging-genetic data for improved prediction of cognitive decline

BACKGROUND

Alzheimer's Disease (AD) is a progressive memory disorder that causes irreversible cognitive decline. Given that there is currently no cure, it is critical to detect AD in its early stage during the disease progression. Recently, many statistical learning methods have been presented to identify cognitive decline with temporal data, but few of these methods integrate heterogeneous phenotype and genetic information together to improve the accuracy of prediction. In addition, many of these models are often unable to handle incomplete temporal data; this often manifests itself in the removal of records to ensure consistency in the number of records across participants.

RESULTS

To address these issues, in this work we propose a novel approach to integrate the genetic data and the longitudinal phenotype data to learn a fixed-length "enriched" biomarker representation derived from the temporal heterogeneous neuroimaging records. Armed with this enriched representation, as a fixed-length vector per participant, conventional machine learning models can be used to predict clinical outcomes associated with AD.

CONCLUSION

The proposed method shows improved prediction performance when applied to data derived from Alzheimer's Disease Neruoimaging Initiative cohort. In addition, our approach can be easily interpreted to allow for the identification and validation of biomarkers associated with cognitive decline.

The Neurodegenerative Disease Knowledge Portal: Propelling Discovery Through the Sharing of Neurodegenerative Disease Genomic Resources

Although large-scale genetic association studies have proven opportunistic for the delineation of neurodegenerative disease processes, we still lack a full understanding of the pathological mechanisms of these diseases, resulting in few appropriate treatment options and diagnostic challenges. To mitigate these gaps, the Neurodegenerative Disease Knowledge Portal (NDKP) was created as an open-science initiative with the aim to aggregate, enable analysis, and display all available genomic datasets of neurodegenerative disease, while protecting the integrity and confidentiality of the underlying datasets. The portal contains 218 genomic datasets, including genotyping and sequencing studies, of individuals across ten different phenotypic groups, including neurological conditions such as Alzheimer's disease, amyotrophic lateral sclerosis, Lewy body dementia, and Parkinson's disease. In addition to securely hosting large genomic datasets, the NDKP provides accessible workflows and tools to effectively utilize the datasets and assist in the facilitation of customized genomic analyses. Here, we summarize the genomic datasets currently included within the portal, the bioinformatics processing of the datasets, and the variety of phenotypes captured. We also present example use-cases of the various user interfaces and integrated analytic tools to demonstrate their extensive utility in enabling the extraction of high-quality results at the source, for both genomics experts and those in other disciplines. Overall, the NDKP promotes open-science and collaboration, maximizing the potential for discovery from the large-scale datasets researchers and consortia are expending immense resources to produce and resulting in reproducible conclusions to improve diagnostic and therapeutic care for neurodegenerative disease patients.

Gene networks and systems biology in Alzheimer's disease: Insights from multi-omics approaches

Despite numerous studies in the field of dementia and Alzheimer's disease (AD), a comprehensive understanding of this devastating disease remains elusive. Bulk transcriptomics have provided insights into the underlying genetic factors at a high level. Subsequent technological advancements have focused on single-cell omics, encompassing techniques such as single-cell RNA sequencing and epigenomics, enabling the capture of RNA transcripts and chromatin states at a single cell or nucleus resolution. Furthermore, the emergence of spatial omics has allowed the study of gene responses in the vicinity of amyloid beta plaques or across various brain regions. With the vast amount of data generated, utilizing gene regulatory networks to comprehensively study this disease has become essential. This review delves into some techniques employed in the field of AD, explores the discoveries made using these techniques, and provides insights into the future of the field.

Apolipoprotein E2 Expression Alters Endosomal Pathways in a Mouse Model With Increased Brain Exosome Levels During Aging

The polymorphic APOE gene is the greatest genetic determinant of sporadic Alzheimer's disease risk: the APOE4 allele increases risk, while the APOE2 allele is neuroprotective compared with the risk-neutral APOE3 allele. The neuronal endosomal system is inherently vulnerable during aging, and APOE4 exacerbates this vulnerability by driving an enlargement of early endosomes and reducing exosome release in the brain of humans and mice. We hypothesized that the protective effects of APOE2 are, in part, mediated through the endosomal pathway. Messenger RNA analyses showed that APOE2 leads to an enrichment of endosomal pathways in the brain when compared with both APOE3 and APOE4. Moreover, we show age-dependent alterations in the recruitment of key endosomal regulatory proteins to vesicle compartments when comparing APOE2 to APOE3. In contrast to the early endosome enlargement previously shown in Alzheimer's disease and APOE4 models, we detected similar morphology and abundance of early endosomes and retromer-associated vesicles within cortical neurons of aged APOE2 targeted-replacement mice compared with APOE3. Additionally, we observed increased brain extracellular levels of endosome-derived exosomes in APOE2 compared with APOE3 mice during aging, consistent with enhanced endosomal cargo clearance by exosomes to the extracellular space. Our findings thus demonstrate that APOE2 enhances an endosomal clearance pathway, which has been shown to be impaired by APOE4 and which may be protective due to APOE2 expression during brain aging.

On the effect heterogeneity of established disease susceptibility loci for Alzheimer's disease across different genetic ancestries

INTRODUCTION

Genome-wide association studies have identified numerous disease susceptibility loci (DSLs) for Alzheimer's disease (AD). However, only a limited number of studies have investigated the dependence of the genetic effect size of established DSLs on genetic ancestry.

METHODS

We utilized the whole genome sequencing data from the Alzheimer's Disease Sequencing Project (ADSP) including 35,569 participants. A total of 25,459 subjects in four distinct populations (African ancestry, non-Hispanic White, admixed Hispanic, and Asian) were analyzed.

RESULTS

We found that nine DSLs showed significant heterogeneity across populations. Single nucleotide polymorphism (SNP) rs2075650 in translocase of outer mitochondrial membrane 40 (TOMM40) showed the largest heterogeneity (Cochran's Q = 0.00, I2 = 90.08), followed by other SNPs in apolipoprotein C1 (APOC1) and apolipoprotein E (APOE). Two additional loci, signal-induced proliferation-associated 1 like 2 (SIPA1L2) and solute carrier 24 member 4 (SLC24A4), showed significant heterogeneity across populations.

DISCUSSION

We observed substantial heterogeneity for the APOE-harboring 19q13.32 region with TOMM40/APOE/APOC1 genes. The largest risk effect was seen among African Americans, while Asians showed a surprisingly small risk effect.

Statistical and Machine Learning Analysis in Brain-Imaging Genetics: A Review of Methods

Brain-imaging-genetic analysis is an emerging field of research that aims at aggregating data from neuroimaging modalities, which characterize brain structure or function, and genetic data, which capture the structure and function of the genome, to explain or predict normal (or abnormal) brain performance. Brain-imaging-genetic studies offer great potential for understanding complex brain-related diseases/disorders of genetic etiology. Still, a combined brain-wide genome-wide analysis is difficult to perform as typical datasets fuse multiple modalities, each with high dimensionality, unique correlational landscapes, and often low statistical signal-to-noise ratios. In this review, we outline the progress in brain-imaging-genetic methodologies starting from early massive univariate to current deep learning approaches, highlighting each approach's strengths and weaknesses and elongating it with the field's development. We conclude by discussing selected remaining challenges and prospects for the field.

Poor statistical power in population-based association study of gene interaction

BACKGROUND

Statistical epistasis, or "gene-gene interaction" in genetic association studies, means the nonadditive effects between the polymorphic sites on two different genes affecting the same phenotype. In the genetic association analysis of complex traits, nevertheless, the researchers haven't found enough clues of statistical epistasis so far.

METHODS

We developed a statistical model where the statistical epistasis was presented as an extra linkage disequilibrium between the polymorphic sites of different risk genes. The power of statistical test for identifying the gene-gene interaction was calculated and then compared in different hypothesis scenarios.

RESULTS

Our results show the statistical power increases with the increasing of interaction coefficient, relative risk, and linkage disequilibrium with genetic markers. However, the power of interaction discovery is much lower than that of regular single-site association test. When rigorous criteria were employed in statistical tests, the identification of gene-gene interaction became a very difficult task. Since the criterion of significance was given to be p-value ≤ 5.0 × 10-8, the same as that of many genome-wide association studies, there is little chance to identify the gene-gene interaction in all kind of circumstances.

CONCLUSIONS

The lack of epistasis tends to be an inevitable result caused by the statistical principles of methods in the genetic association studies and therefore is the inherent characteristic of the research itself.

Epigenetic dysregulation in Alzheimer's disease peripheral immunity

The peripheral immune system in Alzheimer's disease (AD) has not been thoroughly studied with modern sequencing methods. To investigate epigenetic and transcriptional alterations to the AD peripheral immune system, we used single-cell sequencing strategies, including assay for transposase-accessible chromatin and RNA sequencing. We reveal a striking amount of open chromatin in peripheral immune cells in AD. In CD8 T cells, we uncover a cis-regulatory DNA element co-accessible with the CXC motif chemokine receptor 3 gene promoter. In monocytes, we identify a novel AD-specific RELA transcription factor binding site adjacent to an open chromatin region in the nuclear factor kappa B subunit 2 gene. We also demonstrate apolipoprotein E genotype-dependent epigenetic changes in monocytes. Surprisingly, we also identify differentially accessible chromatin regions in genes associated with sporadic AD risk. Our findings provide novel insights into the complex relationship between epigenetics and genetic risk factors in AD peripheral immunity.

PheSeq, a Bayesian deep learning model to enhance and interpret the gene-disease association studies

Despite the abundance of genotype-phenotype association studies, the resulting association outcomes often lack robustness and interpretations. To address these challenges, we introduce PheSeq, a Bayesian deep learning model that enhances and interprets association studies through the integration and perception of phenotype descriptions. By implementing the PheSeq model in three case studies on Alzheimer's disease, breast cancer, and lung cancer, we identify 1024 priority genes for Alzheimer's disease and 818 and 566 genes for breast cancer and lung cancer, respectively. Benefiting from data fusion, these findings represent moderate positive rates, high recall rates, and interpretation in gene-disease association studies.

Florbetapir PET-assessed demyelination is associated with faster tau accumulation in an APOE ε4-dependent manner

PURPOSE

The main objectives were to test whether (1) a decrease in myelin is associated with enhanced rate of fibrillar tau accumulation and cognitive decline in Alzheimer's disease, and (2) whether apolipoprotein E (APOE) ε4 genotype is associated with worse myelin decrease and thus tau accumulation.

METHODS

To address our objectives, we repurposed florbetapir-PET as a marker of myelin in the white matter (WM) based on previous validation studies showing that beta-amyloid (Aβ) PET tracers bind to WM myelin. We assessed 43 Aβ-biomarker negative (Aβ-) cognitively normal participants and 108 Aβ+ participants within the AD spectrum with florbetapir-PET at baseline and longitudinal flortaucipir-PET as a measure of fibrillar tau (tau-PET) over ~ 2 years. In linear regression analyses, we tested florbetapir-PET in the whole WM and major fiber tracts as predictors of tau-PET accumulation in a priori defined regions of interest (ROIs) and fiber-tract projection areas. In mediation analyses we tested whether tau-PET accumulation mediates the effect of florbetapir-PET in the whole WM on cognition. Finally, we assessed the role of myelin alteration on the association between APOE and tau-PET accumulation.

RESULTS

Lower florbetapir-PET in the whole WM or at a given fiber tract was predictive of faster tau-PET accumulation in Braak stages or the connected grey matter areas in Aβ+ participants. Faster tau-PET accumulation in higher cortical brain areas mediated the association between a decrease in florbetapir-PET in the WM and a faster rate of decline in global cognition and episodic memory. APOE ε4 genotype was associated with a worse decrease in the whole WM florbetapir-PET and thus enhanced tau-PET accumulation.

CONCLUSION

Myelin alterations are associated in an APOE ε4 dependent manner with faster tau progression and cognitive decline, and may therefore play a role in the etiology of AD.

A review and analysis of key biomarkers in Alzheimer's disease

Alzheimer's disease (AD) is a progressive neurodegenerative disorder that affects over 50 million elderly individuals worldwide. Although the pathogenesis of AD is not fully understood, based on current research, researchers are able to identify potential biomarker genes and proteins that may serve as effective targets against AD. This article aims to present a comprehensive overview of recent advances in AD biomarker identification, with highlights on the use of various algorithms, the exploration of relevant biological processes, and the investigation of shared biomarkers with co-occurring diseases. Additionally, this article includes a statistical analysis of key genes reported in the research literature, and identifies the intersection with AD-related gene sets from databases such as AlzGen, GeneCard, and DisGeNet. For these gene sets, besides enrichment analysis, protein-protein interaction (PPI) networks utilized to identify central genes among the overlapping genes. Enrichment analysis, protein interaction network analysis, and tissue-specific connectedness analysis based on GTEx database performed on multiple groups of overlapping genes. Our work has laid the foundation for a better understanding of the molecular mechanisms of AD and more accurate identification of key AD markers.

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.

Whole-Genome Sequencing Analysis Reveals New Susceptibility Loci and Structural Variants Associated with Progressive Supranuclear Palsy

Background

Progressive supranuclear palsy (PSP) is a rare neurodegenerative disease characterized by the accumulation of aggregated tau proteins in astrocytes, neurons, and oligodendrocytes. Previous genome-wide association studies for PSP were based on genotype array, therefore, were inadequate for the analysis of rare variants as well as larger mutations, such as small insertions/deletions (indels) and structural variants (SVs).

Method

In this study, we performed whole genome sequencing (WGS) and conducted association analysis for single nucleotide variants (SNVs), indels, and SVs, in a cohort of 1,718 cases and 2,944 controls of European ancestry. Of the 1,718 PSP individuals, 1,441 were autopsy-confirmed and 277 were clinically diagnosed.

Results

Our analysis of common SNVs and indels confirmed known genetic loci at MAPT, MOBP, STX6, SLCO1A2, DUSP10, and SP1, and further uncovered novel signals in APOE, FCHO1/MAP1S, KIF13A, TRIM24, TNXB, and ELOVL1. Notably, in contrast to Alzheimer's disease (AD), we observed the APOE ε2 allele to be the risk allele in PSP. Analysis of rare SNVs and indels identified significant association in ZNF592 and further gene network analysis identified a module of neuronal genes dysregulated in PSP. Moreover, seven common SVs associated with PSP were observed in the H1/H2 haplotype region (17q21.31) and other loci, including IGH, PCMT1, CYP2A13, and SMCP. In the H1/H2 haplotype region, there is a burden of rare deletions and duplications (P = 6.73×10-3) in PSP.

Conclusions

Through WGS, we significantly enhanced our understanding of the genetic basis of PSP, providing new targets for exploring disease mechanisms and therapeutic interventions.

Cognitive Dysfunction and Exercise: From Epigenetic to Genetic Molecular Mechanisms

Maintaining good health is crucial, and exercise plays a vital role in achieving this goal. It offers a range of positive benefits for cognitive function, regardless of age. However, as our population ages and life expectancy increases, cognitive impairment has become a prevalent issue, often coexisting with age-related neurodegenerative conditions. This can result in devastating consequences such as memory loss, difficulty speaking, and confusion, greatly hindering one's ability to lead an ordinary life. In addition, the decrease in mental capacity has a significant effect on an individual's physical and emotional well-being, greatly reducing their overall level of contentment and causing a significant financial burden for communities. While most current approaches aim to slow the decline of cognition, exercise offers a non-pharmacological, safe, and accessible solution. Its effects on cognition are intricate and involve changes in the brain's neural plasticity, mitochondrial stability, and energy metabolism. Moreover, exercise triggers the release of cytokines, playing a significant role in the body-brain connection and its impact on cognition. Additionally, exercise can influence gene expression through epigenetic mechanisms, leading to lasting improvements in brain function and behavior. Herein, we summarized various genetic and epigenetic mechanisms that can be modulated by exercise in cognitive dysfunction.

On-Tissue Spatial Proteomics Integrating MALDI-MS Imaging with Shotgun Proteomics Reveals Soy Consumption-Induced Protein Changes in a Fragile X Syndrome Mouse Model

Fragile X syndrome (FXS), the leading cause of inherited intellectual disability and autism, is caused by the transcriptional silencing of the FMR1 gene, which encodes the fragile X messenger ribonucleoprotein (FMRP). FMRP interacts with numerous brain mRNAs that are involved in synaptic plasticity and implicated in autism spectrum disorders. Our published studies indicate that single-source, soy-based diets are associated with increased seizures and autism. Thus, there is an acute need for an unbiased protein marker identification in FXS in response to soy consumption. Herein, we present a spatial proteomics approach integrating mass spectrometry imaging with label-free proteomics in the FXS mouse model to map the spatial distribution and quantify levels of proteins in the hippocampus and hypothalamus brain regions. In total, 1250 unique peptides were spatially resolved, demonstrating the diverse array of peptidomes present in the tissue slices and the broad coverage of the strategy. A group of proteins that are known to be involved in glycolysis, synaptic transmission, and coexpression network analysis suggest a significant association between soy proteins and metabolic and synaptic processes in the Fmr1KO brain. Ultimately, this spatial proteomics work represents a crucial step toward identifying potential candidate protein markers and novel therapeutic targets for FXS.

Drug repositioning with adaptive graph convolutional networks

MOTIVATION

Drug repositioning is an effective strategy to identify new indications for existing drugs, providing the quickest possible transition from bench to bedside. With the rapid development of deep learning, graph convolutional networks (GCNs) have been widely adopted for drug repositioning tasks. However, prior GCNs based methods exist limitations in deeply integrating node features and topological structures, which may hinder the capability of GCNs.

RESULTS

In this study, we propose an adaptive GCNs approach, termed AdaDR, for drug repositioning by deeply integrating node features and topological structures. Distinct from conventional graph convolution networks, AdaDR models interactive information between them with adaptive graph convolution operation, which enhances the expression of model. Concretely, AdaDR simultaneously extracts embeddings from node features and topological structures and then uses the attention mechanism to learn adaptive importance weights of the embeddings. Experimental results show that AdaDR achieves better performance than multiple baselines for drug repositioning. Moreover, in the case study, exploratory analyses are offered for finding novel drug-disease associations.

AVAILABILITY AND IMPLEMENTATION

The soure code of AdaDR is available at: https://github.com/xinliangSun/AdaDR.

The Contributions of the Endolysosomal Compartment and Autophagy to APOEɛ4 Allele-Mediated Increase in Alzheimer's Disease Risk

Apolipoprotein E4 (APOE4), although yet-to-be fully understood, increases the risk and lowers the age of onset of Alzheimer's disease (AD), which is the major cause of dementia among elderly individuals. The endosome-lysosome and autophagy pathways, which are necessary for homeostasis in both neurons and glia, are dysregulated even in early AD. Nonetheless, the contributory roles of these pathways to developing AD-related pathologies in APOE4 individuals and models are unclear. Therefore, this review summarizes the dysregulations in the endosome-lysosome and autophagy pathways in APOE4 individuals and non-human models, and how these anomalies contribute to developing AD-relevant pathologies. The available literature suggests that APOE4 causes endosomal enlargement, increases endosomal acidification, impairs endosomal recycling, and downregulates exosome production. APOE4 impairs autophagy initiation and inhibits basal autophagy and autophagy flux. APOE4 promotes lysosome formation and trafficking and causes ApoE to accumulate in lysosomes. APOE4-mediated changes in the endosome, autophagosome and lysosome could promote AD-related features including Aβ accumulation, tau hyperphosphorylation, glial dysfunction, lipid dyshomeostasis, and synaptic defects. ApoE4 protein could mediate APOE4-mediated endosome-lysosome-autophagy changes. ApoE4 impairs vesicle recycling and endosome trafficking, impairs the synthesis of autophagy genes, resists being dissociated from its receptors and degradation, and forms a stable folding intermediate that could disrupt lysosome structure. Drugs such as molecular correctors that target ApoE4 molecular structure and enhance autophagy may ameliorate the endosome-lysosome-autophagy-mediated increase in AD risk in APOE4 individuals.

Investigation of sex differences in mutation carriers of the Dominantly Inherited Alzheimer Network

INTRODUCTION

Studies suggest distinct differences in the development, presentation, progression, and response to treatment of Alzheimer's disease (AD) between females and males. We investigated sex differences in cognition, neuroimaging, and fluid biomarkers in dominantly inherited AD (DIAD).

METHODS

Three hundred twenty-five mutation carriers (55% female) and one hundred eighty-six non-carriers (58% female) of the Dominantly Inherited Alzheimer Network Observational Study were analyzed. Linear mixed models and Spearman's correlation explored cross-sectional sex differences in cognition, cerebrospinal fluid (CSF) biomarkers, Pittsburgh compound B positron emission tomography (11 C-PiB PET) and structural magnetic resonance imaging (MRI).

RESULTS

Female carriers performed better than males on delayed recall and processing speed despite similar hippocampal volumes. As the disease progressed, symptomatic females revealed higher increases in MRI markers of neurodegeneration and memory impairment. PiB PET and established CSF AD markers revealed no sex differences.

DISCUSSION

Our findings suggest an initial cognitive reserve in female carriers followed by a pronounced increase in neurodegeneration coupled with worse performance on delayed recall at later stages of DIAD.

CCR5 deficiency: Decreased neuronal resilience to oxidative stress and increased risk of vascular dementia

INTRODUCTION

As the chemokine receptor5 (CCR5) may play a role in ischemia, we studied the links between CCR5 deficiency, the sensitivity of neurons to oxidative stress, and the development of dementia.

METHODS

Logistic regression models with CCR5/apolipoprotein E (ApoE) polymorphisms were applied on a sample of 205 cognitively normal individuals and 189 dementia patients from Geneva. The impact of oxidative stress on Ccr5 expression and cell death was assessed in mice neurons.

RESULTS

CCR5-Δ32 allele synergized with ApoEε4 as risk factor for dementia and specifically for dementia with a vascular component. We confirmed these results in an independent cohort from Italy (157 cognitively normal and 620 dementia). Carriers of the ApoEε4/CCR5-Δ32 genotype aged ≥80 years have an 11-fold greater risk of vascular-and-mixed dementia. Oxidative stress-induced cell death in Ccr5-/- mice neurons.

DISCUSSION

We propose the vulnerability of CCR5-deficient neurons in response to oxidative stress as possible mechanisms contributing to dementia.

Association between APOE-ε4 allele and cognitive function is mediated by Alzheimer's disease pathology: a population-based autopsy study in an admixed sample

BACKGROUND

Apolipoprotein E ε4 allele (APOE-ε4) is the main genetic risk factor for late-onset Alzheimer's disease (AD) and may impact cognitive function also via other neuropathological lesions. However, there is limited evidence available from diverse populations, as APOE associations with dementia seem to differ by race. Therefore, we aimed to evaluate the pathways linking APOE-ε4 to cognitive abilities through AD and non-AD neuropathology in an autopsy study with an admixed sample.

METHODS

Neuropathological lesions were evaluated following international criteria using immunohistochemistry. Participants were classified into APOE-ε4 carriers (at least one ε4 allele) and non-carriers. Cognitive abilities were evaluated by the Clinical Dementia Rating Scale sum of boxes. Mediation analyses were conducted to assess the indirect association of APOE-ε4 with cognition through AD-pathology, lacunar infarcts, hyaline arteriosclerosis, cerebral amyloid angiopathy (CAA), Lewy body disease (LBD), and TAR DNA-binding protein 43 (TDP-43).

RESULTS

We included 648 participants (mean age 75 ± 12 years old, mean education 4.4 ± 3.7 years, 52% women, 69% White, and 28% APOE-ε4 carriers). The association between APOE-ε4 and cognitive abilities was mediated by neurofibrillary tangles (β = 0.88, 95% CI = 0.45; 1.38, p < 0.001) and neuritic plaques (β = 1.36, 95% CI = 0.86; 1.96, p < 0.001). Lacunar infarcts, hyaline arteriosclerosis, CAA, LBD, and TDP-43 were not mediators in the pathway from APOE-ε4 to cognition.

CONCLUSION

The association between APOE-ε4 and cognitive abilities was partially mediated by AD-pathology. On the other hand, cerebrovascular lesions and other neurodegenerative diseases did not mediate the association between APOE-ε4 and cognition.

Association of biological age with health outcomes and its modifiable factors

Identifying the clinical implications and modifiable and unmodifiable factors of aging requires the measurement of biological age (BA) and age gap. Leveraging the biomedical traits involved with physical measures, biochemical assays, genomic data, and cognitive functions from the healthy participants in the UK Biobank, we establish an integrative BA model consisting of multi-dimensional indicators. Accelerated aging (age gap >3.2 years) at baseline is associated incident circulatory diseases, related chronic disorders, all-cause, and cause-specific mortality. We identify 35 modifiable factors for age gap (p < 4.81 × 10-4 ), where pulmonary functions, body mass, hand grip strength, basal metabolic rate, estimated glomerular filtration rate, and C-reactive protein show the most significant associations. Genetic analyses replicate the possible associations between age gap and health-related outcomes and further identify CST3 as an essential gene for biological aging, which is highly expressed in the brain and is associated with immune and metabolic traits. Our study profiles the landscape of biological aging and provides insights into the preventive strategies and therapeutic targets for aging.

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.

Artificial intelligence for neurodegenerative experimental models

INTRODUCTION

Experimental models are essential tools in neurodegenerative disease research. However, the translation of insights and drugs discovered in model systems has proven immensely challenging, marred by high failure rates in human clinical trials.

METHODS

Here we review the application of artificial intelligence (AI) and machine learning (ML) in experimental medicine for dementia research.

RESULTS

Considering the specific challenges of reproducibility and translation between other species or model systems and human biology in preclinical dementia research, we highlight best practices and resources that can be leveraged to quantify and evaluate translatability. We then evaluate how AI and ML approaches could be applied to enhance both cross-model reproducibility and translation to human biology, while sustaining biological interpretability.

DISCUSSION

AI and ML approaches in experimental medicine remain in their infancy. However, they have great potential to strengthen preclinical research and translation if based upon adequate, robust, and reproducible experimental data.

HIGHLIGHTS

There are increasing applications of AI in experimental medicine. We identified issues in reproducibility, cross-species translation, and data curation in the field. Our review highlights data resources and AI approaches as solutions. Multi-omics analysis with AI offers exciting future possibilities in drug discovery.

Genome-wide association study in Alzheimer's disease: a bibliometric and visualization analysis

BACKGROUND

Thousands of research studies concerning genome-wide association studies (GWAS) in Alzheimer's disease (AD) have been published in the last decades. However, a comprehensive understanding of the current research status and future development trends of GWAS in AD have not been clearly shown. In this study, we tried to gain a systematic overview of GWAS in AD by bibliometric and visualization analysis.

METHODS

The literature search terms are: ("genome-wide analysis" or "genome-wide association study" or "whole-genome analysis") AND ("Alzheimer's Disease" or "Alzheimer Disease"). Relevant publications were extracted from the Web of Science Core Collection (WoSCC) database. Collected data were further analyzed using VOSviewer, CiteSpace and R package Bibliometrix. The countries, institutions, authors and scholar collaborations were investigated. The co-citation analysis of publications was visualized. In addition, research hotspots and fronts were examined.

RESULTS

A total of 1,350 publications with 59,818 citations were identified. The number of publications and citations presented a significant rising trend since 2013. The United States was the leading country with an overwhelming number of publications (775) and citations (42,237). The University of Washington and Harvard University were the most prolific institutions with 101 publications each. Bennett DA was the most influential researcher with the highest local H-index. Neurobiology of Aging was the journal with the highest number of publications. Aβ, tau, immunity, microglia and DNA methylation were research hotspots. Disease and causal variants were research fronts.

CONCLUSION

The most frequently studied AD pathogenesis and research hotspots are (1) Aβ and tau, (2) immunity and microglia, with TREM2 as a potential immunotherapy target, and (3) DNA methylation. The research fronts are (1) looking for genetic similarities between AD and other neurological diseases and syndromes, and (2) searching for causal variants of AD. These hotspots suggest noteworthy directions for future studies on AD pathogenesis and genetics, in which basic research regarding immunity is promising for clinical conversion. The current under-researched directions are (1) GWAS in AD biomarkers based on large sample sizes, (2) studies of causal variants of AD, and (3) GWAS in AD based on non-European populations, which need to be strengthened in the future.

Brain apolipoprotein E levels in mice challenged by a Western diet increase in an allele-dependent manner

Human apolipoprotein E (APOE) is the greatest determinant of genetic risk for memory deficits and Alzheimer's disease (AD). While APOE4 drives memory loss and high AD risk, APOE2 leads to healthy brain aging and reduced AD risk compared to the common APOE3 variant. We examined brain APOE protein levels in humanized mice homozygous for these alleles and found baseline levels to be age- and isoform-dependent: APOE2 levels were greater than APOE3, which were greater than APOE4. Despite the understanding that APOE lipoparticles do not traverse the blood-brain barrier, we show that brain APOE levels are responsive to dietary fat intake. Challenging mice for 6 months on a Western diet high in fat and cholesterol increased APOE protein levels in an allele-dependent fashion with a much greater increase within blood plasma than within the brain. In the brain, APOE2 levels responded most to the Western diet challenge, increasing by 20 % to 30 %. While increased lipoparticles are generally deleterious in the periphery, we propose that higher brain APOE2 levels may represent a readily available pool of beneficial lipid particles for neurons.

Profiling baseline performance on the Longitudinal Early-Onset Alzheimer's Disease Study (LEADS) cohort near the midpoint of data collection

OBJECTIVE

The Longitudinal Early-Onset Alzheimer's Disease Study (LEADS) seeks to provide comprehensive understanding of early-onset Alzheimer's disease (EOAD; onset <65 years), with the current study profiling baseline clinical, cognitive, biomarker, and genetic characteristics of the cohort nearing the data-collection mid-point.

METHODS

Data from 371 LEADS participants were compared based on diagnostic group classification (cognitively normal [n = 89], amyloid-positive EOAD [n = 212], and amyloid-negative early-onset non-Alzheimer's disease [EOnonAD; n = 70]).

RESULTS

Cognitive performance was worse for EOAD than other groups, and EOAD participants were apolipoprotein E (APOE) ε4 homozygotes at higher rates. An amnestic presentation was common among impaired participants (81%), with several clinical phenotypes present. LEADS participants generally consented at high rates to optional trial procedures.

CONCLUSIONS

We present the most comprehensive baseline characterization of sporadic EOAD in the United States to date. EOAD presents with widespread cognitive impairment within and across clinical phenotypes, with differences in APOE ε4 allele carrier status appearing to be relevant.

HIGHLIGHTS

Findings represent the most comprehensive baseline characterization of sporadic early-onset Alzheimer's disease (EOAD) to date. Cognitive impairment was widespread for EOAD participants and more severe than other groups. EOAD participants were homozygous apolipoprotein E (APOE) ε4 carriers at higher rates than the EOnonAD group. Amnestic presentation predominated in EOAD and EOnonAD participants, but other clinical phenotypes were present.

Clinical and neurochemical correlates of the APOE genotype in early-stage Parkinson's disease

Emerging evidence indicates that apolipoprotein E (APOE) genotype may influence Parkinson's disease (PD) course, although clinical and neurochemical correlates have not been completely established. This study aimed to determine the associations of APOE genotypes (ε4 vs. non-ε4) with cerebrospinal fluid (CSF) neurodegeneration biomarkers and clinical parameters in early-stage PD patients. One hundred and seventy-five PD patients and 89 non-neurodegenerative controls grouped in APOE-ε4 carriers (28 PD; 12 controls) and non-APOE-ε4 carriers (147 PD; 78 controls) were enrolled. CSF levels of amyloid-β-42, amyloid-β-40, total and 181-phosphorylated tau, and clinical scores were compared among groups adjusting for main covariates. APOE genotypes prevalence was similar in PD and controls. PD APOE-ε4 carriers had lower amyloid-β-42 CSF levels than PD non-APOE-ε4 carriers and controls, independently from age. PD APOE-ε4 carriers also had higher total and "item 5" (attention and memory) non-motor symptoms scale scores than PD non-APOE-ε4 carriers, independently from confounding factors. APOE-ε4 genotype might thus account for a more vulnerable PD subtype characterized by prominent amyloidopathy and a greater burden of non-motor symptoms in the early disease stages. DATA AVAILABILITY: Data are available upon reasonable request.

Cognitive impairment in long-living adults: a genome-wide association study, polygenic risk score model and molecular modeling of the APOE protein

Background

Cognitive impairment is an irreversible, aging-associated condition that robs people of their independence. The purpose of this study was to investigate possible causes of this condition and propose preventive options.

Methods

We assessed cognitive status in long-living adults aged 90+ (n = 2,559) and performed a genome wide association study using two sets of variables: Mini-Mental State Examination scores as a continuous variable (linear regression) and cognitive status as a binary variable (> 24, no cognitive impairment; <10, impairment) (logistic regression).

Results

Both variations yielded the same polymorphisms, including a well-known marker of dementia, rs429358in the APOE gene. Molecular dynamics simulations showed that this polymorphism leads to changes in the structure of alpha helices and the mobility of the lipid-binding domain in the APOE protein.

Conclusion

These changes, along with higher LDL and total cholesterol levels, could be the mechanism underlying the development of cognitive impairment in older adults. However, this polymorphism is not the only determining factor in cognitive impairment. The polygenic risk score model included 45 polymorphisms (ROC AUC 69%), further confirming the multifactorial nature of this condition. Our findings, particularly the results of PRS modeling, could contribute to the development of early detection strategies for predisposition to cognitive impairment in older adults.

COVID-19 and the impact on Alzheimer's disease pathology

Coronavirus disease 2019 (COVID-19) has rapidly escalated into a global pandemic that primarily affects older and immunocompromised individuals due to underlying clinical conditions and suppressed immune responses. Furthermore, COVID-19 patients exhibit a spectrum of neurological symptoms, indicating that COVID-19 can affect the brain in a variety of manners. Many studies, past and recent, suggest a connection between viral infections and an increased risk of neurodegeneration, raising concerns about the neurological effects of COVID-19 and the possibility that it may contribute to Alzheimer's disease (AD) onset or worsen already existing AD pathology through inflammatory processes given that both COVID-19 and AD share pathological features and risk factors. This leads us to question whether COVID-19 is a risk factor for AD and how these two conditions might influence each other. Considering the extensive reach of the COVID-19 pandemic and the devastating impact of the ongoing AD pandemic, their combined effects could have significant public health consequences worldwide.

Sex differences in associations between APOE ε2 and longitudinal cognitive decline

INTRODUCTION

We examined whether sex modifies the association between APOE ε2 and cognitive decline in two independent samples.

METHODS

We used observational data from cognitively unimpaired non-Hispanic White (NHW) and non-Hispanic Black (NHB) adults. Linear mixed models examined interactive associations of APOE genotype (ε2 or ε4 carrier vs. ε3/ε3) and sex on cognitive decline in NHW and NHB participants separately.

RESULTS

In both Sample 1 (N = 9766) and Sample 2 (N = 915), sex modified the association between APOE ε2 and cognitive decline in NHW participants. Specifically, relative to APOE ε3/ε3, APOE ε2 protected against cognitive decline in men but not women. Among APOE ε2 carriers, men had slower decline than women. Among APOE ε3/ε3 carriers, cognitive trajectories did not differ between sexes. There were no sex-specific associations of APOE ε2 with cognition in NHB participants (N = 2010).

DISCUSSION

In NHW adults, APOE ε2 may protect men but not women against cognitive decline.

HIGHLIGHTS

We studied sex-specific apolipoprotein E (APOE) ε2 effects on cognitive decline. In non-Hispanic White (NHW) adults, APOE ε2 selectively protects men against decline. Among men, APOE ε2 was more protective than APOE ε3/ε3. In women, APOE ε2 was no more protective than APOE ε3/ε3. Among APOE ε2 carriers, men had slower decline than women. There were no sex-specific APOE ε2 effects in non-Hispanic Black (NHB) adults.

Amyloid Precursor Protein and Alzheimer's Disease

Alzheimer's disease (AD) is one of the most common neurodegenerative disorders associated with age or inherited mutations. It is characterized by severe dementia in the late stages that affect memory, cognitive functions, and daily life overall. AD progression is linked to the accumulation of cytotoxic amyloid beta (Aβ) and hyperphosphorylated tau protein combined with other pathological features such as synaptic loss, defective energy metabolism, imbalances in protein, and metal homeostasis. Several treatment options for AD are under investigation, including antibody-based therapy and stem cell transplantation. Amyloid precursor protein (APP) is a membrane protein considered to play a main role in AD pathology. It is known that APP in physiological conditions follows a non-amyloidogenic pathway; however, it can proceed to an amyloidogenic scenario, which leads to the generation of extracellular deleterious Aβ plaques. Not all steps of APP biogenesis are clear so far, and these questions should be addressed in future studies. AD is a complex chronic disease with many factors that contribute to disease progression.

Multi-omic atlas of the parahippocampal gyrus in Alzheimer's disease

Alzheimer's disease (AD) is the most common form of dementia worldwide, with a projection of 151 million cases by 2050. Previous genetic studies have identified three main genes associated with early-onset familial Alzheimer's disease, however this subtype accounts for less than 5% of total cases. Next-generation sequencing has been well established and holds great promise to assist in the development of novel therapeutics as well as biomarkers to prevent or slow the progression of this devastating disease. Here we present a public resource of functional genomic data from the parahippocampal gyrus of 201 postmortem control, mild cognitively impaired (MCI) and AD individuals from the Mount Sinai brain bank, of which whole-genome sequencing (WGS), and bulk RNA sequencing (RNA-seq) were previously published. The genomic data include bulk proteomics and DNA methylation, as well as cell-type-specific RNA-seq and assay for transposase-accessible chromatin with high-throughput sequencing (ATAC-seq) data. We have performed extensive preprocessing and quality control, allowing the research community to access and utilize this public resource available on the Synapse platform at https://doi.org/10.7303/syn51180043.2 .

Association of Common and Rare Variants with Alzheimer's Disease in over 13,000 Diverse Individuals with Whole-Genome Sequencing from the Alzheimer's Disease Sequencing Project

Alzheimer's Disease (AD) is a common disorder of the elderly that is both highly heritable and genetically heterogeneous. Here, we investigated the association between AD and both common variants and aggregates of rare coding and noncoding variants in 13,371 individuals of diverse ancestry with whole genome sequence (WGS) data. Pooled-population analyses identified genetic variants in or near APOE, BIN1, and LINC00320 significantly associated with AD (p < 5×10-8). Population-specific analyses identified a haplotype on chromosome 14 including PSEN1 associated with AD in Hispanics, further supported by aggregate testing of rare coding and noncoding variants in this region. Finally, we observed suggestive associations (p < 5×10-5) of aggregates of rare coding rare variants in ABCA7 among non-Hispanic Whites (p=5.4×10-6), and rare noncoding variants in the promoter of TOMM40 distinct of APOE in pooled-population analyses (p=7.2×10-8). Complementary pooled-population and population-specific analyses offered unique insights into the genetic architecture of AD.

A plasma protein signature associated with cognitive function in men without severe cognitive impairment

BACKGROUND

A minimally invasive blood-based assessment of cognitive function could be a promising screening strategy to identify high-risk groups for the incidence of Alzheimer's disease.

METHODS

The study included 448 cognitively unimpaired men (mean age 64.1 years) drawn from the Geelong Osteoporosis Study. A targeted mass spectrometry-based proteomic assay was performed to measure the abundance levels of 269 plasma proteins followed by linear regression analyses adjusted for age and APOE ε4 carrier status to identify the biomarkers related to overall cognitive function. Furthermore, two-way interactions were conducted to see whether Alzheimer's disease-linked genetic variants or health conditions modify the association between biomarkers and cognitive function.

RESULTS

Ten plasma proteins showed an association with overall cognitive function. This association was modified by allelic variants in genes ABCA7, CLU, BDNF and MS4A6A that have been previously linked to Alzheimer's disease. Modifiable health conditions such as mood disorders and poor bone health, which are postulated to be risk factors for Alzheimer's disease, also impacted the relationship observed between protein marker levels and cognition. In addition to the univariate analyses, an 11-feature multianalyte model was created using the least absolute shrinkage and selection operator regression that identified 10 protein features and age associated with cognitive function.

CONCLUSIONS

Overall, the present study revealed plasma protein candidates that may contribute to the development of a blood-based screening test for identifying early cognitive changes. This study also highlights the importance of considering other risk factors in elucidating the relationship between biomarkers and cognition, an area that remains largely unexplored.

Loss-of-function variant in the ovine TMCO6 gene in North Country Cheviot sheep with motor neuron disease

In North Country Cheviot lambs with early-onset progressive ataxia and motor neuron degeneration, whole-genome sequencing identified a homozygous loss-of-function variant in the ovine transmembrane and coiled-coil domains (TMCO6) gene. The familial recessive form of motor neuron disease in sheep is due to a pathogenic 4 bp deletion leading to a 50% protein truncation that is assumed to result in the absence of a functional TMCO6. This uncharacterised protein is proposed to interact with ubiquilin 1 which is associated with Alzheimer's disease, whereas sporadic forms of amyotrophic lateral sclerosis are caused by variants in UBQLN2. Our findings provide a first spontaneous animal model for TMCO6, which could have implications in the studies of other comparative neurodegenerative diseases. In addition, these results will allow the design of a genetic test to prevent the occurrence of this fatal disease in the affected sheep population.

The role of sperm-specific glyceraldehyde-3-phosphate dehydrogenase in the development of pathologies-from asthenozoospermia to carcinogenesis

The review considers various aspects of the influence of the glycolytic enzyme, sperm-specific glyceraldehyde-3-phosphate dehydrogenase (GAPDS) on the energy metabolism of spermatozoa and on the occurrence of several pathologies both in spermatozoa and in other cells. GAPDS is a unique enzyme normally found only in mammalian spermatozoa. GAPDS provides movement of the sperm flagellum through the ATP formation in glycolytic reactions. Oxidation of cysteine residues in GAPDS results in inactivation of the enzyme and decreases sperm motility. In particular, reduced sperm motility in diabetes can be associated with GAPDS oxidation by superoxide anion produced during glycation reactions. Mutations in GAPDS gene lead in the loss of motility, and in some cases, disrupts the formation of the structural elements of the sperm flagellum, in which the enzyme incorporates during spermiogenesis. GAPDS activation can be used to increase the spermatozoa fertility, and inhibitors of this enzyme are being tried as contraceptives. A truncated GAPDS lacking the N-terminal fragment of 72 amino acids that attaches the enzyme to the sperm flagellum was found in melanoma cell lines and then in specimens of melanoma and other tumors. Simultaneous production of the somatic form of GAPDH and sperm-specific GAPDS in cancer cells leads to a reorganization of their energy metabolism, which is accompanied by a change in the efficiency of metastasis of certain forms of cancer. Issues related to the use of GAPDS for the diagnosis of cancer, as well as the possibility of regulating the activity of this enzyme to prevent metastasis, are discussed.

Intervention of next-generation sequencing in diagnosis of Alzheimer's disease: challenges and future prospects

Clinical diagnosis of several neurodegenerative disorders based on clinical phenotype is challenging due to its heterogeneous nature and overlapping disease manifestations. Therefore, the identification of underlying genetic mechanisms is of paramount importance for better diagnosis and therapeutic regimens. With the emergence of next-generation sequencing, it becomes easier to identify all gene variants in the genome simultaneously, with a system-wide and unbiased approach. Presently various bioinformatics databases are maintained on discovered gene variants and phenotypic indications are available online. Since individuals are unique in their genome, evaluation based on their genetic makeup helps evolve the diagnosis, counselling, and treatment process at the personal level. This article aims to briefly summarize the utilization of next-generation sequencing in deciphering the genetic causes of Alzheimer's disease and address the limitations of whole genome and exome sequencing.

Genetic Phenotypes of Alzheimer's Disease: Mechanisms and Potential Therapy

Years of intensive research has brought us extensive knowledge on the genetic and molecular factors involved in Alzheimer's disease (AD). In addition to the mutations in the three main causative genes of familial AD (FAD) including presenilins and amyloid precursor protein genes, studies have identified several genes as the most plausible genes for the onset and progression of FAD, such as triggering receptor expressed on myeloid cells 2, sortilin-related receptor 1, and adenosine triphosphate-binding cassette transporter subfamily A member 7. The apolipoprotein E ε4 allele is reported to be the strongest genetic risk factor for sporadic AD (SAD), and it also plays an important role in FAD. Here, we reviewed recent developments in genetic and molecular studies that contributed to the understanding of the genetic phenotypes of FAD and compared them with SAD. We further reviewed the advancements in AD gene therapy and discussed the future perspectives based on the genetic phenotypes.

Obesity impacts the expression of Alzheimer's disease-related genes: The Framingham Heart Study

INTRODUCTION

We investigated associations of obesity with the expression of Alzheimer's disease (AD)-related genes in a large community-based cohort.

METHODS

The sample consisted of 5619 participants from the Framingham Heart Study. Obesity metrics included body mass index (BMI) and waist-to-hip ratio (WHR). Gene expression was measured for a set of 74 AD-related genes, derived by integrating genome-wide association study results with functional genomics data.

RESULTS

Obesity metrics were associated with the expression of 21 AD-related genes. The strongest associations were observed with CLU, CD2AP, KLC3, and FCER1G. Unique associations were noted with TSPAN14, SLC24A4 for BMI, and ZSCAN21, BCKDK for WHR. After adjustment for cardiovascular risk factors, 13 associations remained significant for BMI and 8 for WHR. Dichotomous obesity metrics exhibited unique associations with EPHX2 for BMI, and with TSPAN14 for WHR.

DISCUSSION

Obesity was associated with AD-related gene expression; these findings shed light on the molecular pathways linking obesity to AD.

Prioritizing genes associated with brain disorders by leveraging enhancer-promoter interactions in diverse neural cells and tissues

BACKGROUND

Prioritizing genes that underlie complex brain disorders poses a considerable challenge. Despite previous studies have found that they shared symptoms and heterogeneity, it remained difficult to systematically identify the risk genes associated with them.

METHODS

By using the CAGE (Cap Analysis of Gene Expression) read alignment files for 439 human cell and tissue types (including primary cells, tissues and cell lines) from FANTOM5 project, we predicted enhancer-promoter interactions (EPIs) of 439 cell and tissue types in human, and examined their reliability. Then we evaluated the genetic heritability of 17 diverse brain disorders and behavioral-cognitive phenotypes in each neural cell type, brain region, and developmental stage. Furthermore, we prioritized genes associated with brain disorders and phenotypes by leveraging the EPIs in each neural cell and tissue type, and analyzed their pleiotropy and functionality for different categories of disorders and phenotypes. Finally, we characterized the spatiotemporal expression dynamics of these associated genes in cells and tissues.

RESULTS

We found that identified EPIs showed activity specificity and network aggregation in cell and tissue types, and enriched TF binding in neural cells played key roles in synaptic plasticity and nerve cell development, i.e., EGR1 and SOX family. We also discovered that most neurological disorders exhibit heritability enrichment in neural stem cells and astrocytes, while psychiatric disorders and behavioral-cognitive phenotypes exhibit enrichment in neurons. Furthermore, our identified genes recapitulated well-known risk genes, which exhibited widespread pleiotropy between psychiatric disorders and behavioral-cognitive phenotypes (i.e., FOXP2), and indicated expression specificity in neural cell types, brain regions, and developmental stages associated with disorders and phenotypes. Importantly, we showed the potential associations of brain disorders with brain regions and developmental stages that have not been well studied.

CONCLUSIONS

Overall, our study characterized the gene-enhancer regulatory networks and genetic mechanisms in the human neural cells and tissues, and illustrated the value of reanalysis of publicly available genomic datasets.

PINNet: a deep neural network with pathway prior knowledge for Alzheimer's disease

Introduction

Identification of Alzheimer's Disease (AD)-related transcriptomic signatures from blood is important for early diagnosis of the disease. Deep learning techniques are potent classifiers for AD diagnosis, but most have been unable to identify biomarkers because of their lack of interpretability.

Methods

To address these challenges, we propose a pathway information-based neural network (PINNet) to predict AD patients and analyze blood and brain transcriptomic signatures using an interpretable deep learning model. PINNet is a deep neural network (DNN) model with pathway prior knowledge from either the Gene Ontology or Kyoto Encyclopedia of Genes and Genomes databases. Then, a backpropagation-based model interpretation method was applied to reveal essential pathways and genes for predicting AD.

Results

The performance of PINNet was compared with a DNN model without a pathway. Performances of PINNet outperformed or were similar to those of DNN without a pathway using blood and brain gene expressions, respectively. Moreover, PINNet considers more AD-related genes as essential features than DNN without a pathway in the learning process. Pathway analysis of protein-protein interaction modules of highly contributed genes showed that AD-related genes in blood were enriched with cell migration, PI3K-Akt, MAPK signaling, and apoptosis in blood. The pathways enriched in the brain module included cell migration, PI3K-Akt, MAPK signaling, apoptosis, protein ubiquitination, and t-cell activation.

Discussion

By integrating prior knowledge about pathways, PINNet can reveal essential pathways related to AD. The source codes are available at https://github.com/DMCB-GIST/PINNet.

Cognitive trajectories diverge by genetic risk in a preclinical longitudinal cohort

INTRODUCTION

We sought to characterize the timing of changes in cognitive trajectories related to genetic risk using the apolipoprotein E (APOE) score, a continuous measure of Alzheimer's disease (AD) risk. We also aimed to determine whether that timing was different when genetic risk was measured using an AD polygenic risk score (PRS) that contains APOE.

METHODS

We analyzed trajectories (N ≈1135) for four neuropsychological composite scores using mixed effects regression for longitudinal change across APOE scores and PRS of participants in the Wisconsin Registry for Alzheimer's Prevention, a longitudinal study of adults aged 40 to 70 at baseline, with a median participant follow-up time of 7.8 years.

RESULTS

We found a significant non-linear age-by-APOE score interaction in predicting cognitive decline. Cognitive trajectories diverged by APOE score at approximately 65 years of age. A 0.5 standard deviation difference in cognition between extreme percentiles of the PRS was predicted to occur 1 to 2 years before that of the APOE score.

DISCUSSION

Cognitive decline differs across time and APOE score. Estimates did not substantially shift with the AD PRS.

HIGHLIGHTS

The apolipoprotein E (APOE) score, a continuous measure, accounts for non-linear genetic risk of Alzheimer's disease. Non-linear age interacts with the APOE score to affect cognition. Cognitive decline starts to differ by APOE score levels at approximately age 65. Cognitive decline timing by polygenic risk (including APOE) is similar to APOE alone.

Step by step: towards a better understanding of the genetic architecture of Alzheimer's disease

Alzheimer's disease (AD) is considered to have a large genetic component. Our knowledge of this component has progressed over the last 10 years, thanks notably to the advent of genome-wide association studies and the establishment of large consortia that make it possible to analyze hundreds of thousands of cases and controls. The characterization of dozens of chromosomal regions associated with the risk of developing AD and (in some loci) the causal genes responsible for the observed disease signal has confirmed the involvement of major pathophysiological pathways (such as amyloid precursor protein metabolism) and opened up new perspectives (such as the central role of microglia and inflammation). Furthermore, large-scale sequencing projects are starting to reveal the major impact of rare variants - even in genes like APOE - on the AD risk. This increasingly comprehensive knowledge is now being disseminated through translational research; in particular, the development of genetic risk/polygenic risk scores is helping to identify the subpopulations more at risk or less at risk of developing AD. Although it is difficult to assess the efforts still needed to comprehensively characterize the genetic component of AD, several lines of research can be improved or initiated. Ultimately, genetics (in combination with other biomarkers) might help to redefine the boundaries and relationships between various neurodegenerative diseases.

The effects of enhancing angiotensin converting enzyme in myelomonocytes on ameliorating Alzheimer's-related disease and preserving cognition

This review examines the role of angiotensin-converting enzyme (ACE) in the context of Alzheimer's disease (AD) and its potential therapeutic value. ACE is known to degrade the neurotoxic 42-residue long alloform of amyloid β-protein (Aβ42), a peptide strongly associated with AD. Previous studies in mice, demonstrated that targeted overexpression of ACE in CD115+ myelomonocytic cells (ACE10 models) improved their immune responses to effectively reduce viral and bacterial infection, tumor growth, and atherosclerotic plaque. We further demonstrated that introducing ACE10 myelomonocytes (microglia and peripheral monocytes) into the double transgenic APPSWE/PS1ΔE9 murine model of AD (AD+ mice), diminished neuropathology and enhanced the cognitive functions. These beneficial effects were dependent on ACE catalytic activity and vanished when ACE was pharmacologically blocked. Moreover, we revealed that the therapeutic effects in AD+ mice can be achieved by enhancing ACE expression in bone marrow (BM)-derived CD115+ monocytes alone, without targeting central nervous system (CNS) resident microglia. Following blood enrichment with CD115+ ACE10-monocytes versus wild-type (WT) monocytes, AD+ mice had reduced cerebral vascular and parenchymal Aβ burden, limited microgliosis and astrogliosis, as well as improved synaptic and cognitive preservation. CD115+ ACE10-versus WT-monocyte-derived macrophages (Mo/MΦ) were recruited in higher numbers to the brains of AD+ mice, homing to Aβ plaque lesions and exhibiting a highly Aβ-phagocytic and anti-inflammatory phenotype (reduced TNFα/iNOS and increased MMP-9/IGF-1). Moreover, BM-derived ACE10-Mo/MΦ cultures had enhanced capability to phagocytose Aβ42 fibrils, prion-rod-like, and soluble oligomeric forms that was associated with elongated cell morphology and expression of surface scavenger receptors (i.e., CD36, Scara-1). This review explores the emerging evidence behind the role of ACE in AD, the neuroprotective properties of monocytes overexpressing ACE and the therapeutic potential for exploiting this natural mechanism for ameliorating AD pathogenesis.

Sex specific molecular networks and key drivers of Alzheimer's disease

BACKGROUND

Alzheimer's disease (AD) is a progressive and age-associated neurodegenerative disorder that affects women disproportionally. However, the underlying mechanisms are poorly characterized. Moreover, while the interplay between sex and ApoE genotype in AD has been investigated, multi-omics studies to understand this interaction are limited. Therefore, we applied systems biology approaches to investigate sex-specific molecular networks of AD.

METHODS

We integrated large-scale human postmortem brain transcriptomic data of AD from two cohorts (MSBB and ROSMAP) via multiscale network analysis and identified key drivers with sexually dimorphic expression patterns and/or different responses to APOE genotypes between sexes. The expression patterns and functional relevance of the top sex-specific network driver of AD were further investigated using postmortem human brain samples and gene perturbation experiments in AD mouse models.

RESULTS

Gene expression changes in AD versus control were identified for each sex. Gene co-expression networks were constructed for each sex to identify AD-associated co-expressed gene modules shared by males and females or specific to each sex. Key network regulators were further identified as potential drivers of sex differences in AD development. LRP10 was identified as a top driver of the sex differences in AD pathogenesis and manifestation. Changes of LRP10 expression at the mRNA and protein levels were further validated in human AD brain samples. Gene perturbation experiments in EFAD mouse models demonstrated that LRP10 differentially affected cognitive function and AD pathology in sex- and APOE genotype-specific manners. A comprehensive mapping of brain cells in LRP10 over-expressed (OE) female E4FAD mice suggested neurons and microglia as the most affected cell populations. The female-specific targets of LRP10 identified from the single cell RNA-sequencing (scRNA-seq) data of the LRP10 OE E4FAD mouse brains were significantly enriched in the LRP10-centered subnetworks in female AD subjects, validating LRP10 as a key network regulator of AD in females. Eight LRP10 binding partners were identified by the yeast two-hybrid system screening, and LRP10 over-expression reduced the association of LRP10 with one binding partner CD34.

CONCLUSIONS

These findings provide insights into key mechanisms mediating sex differences in AD pathogenesis and will facilitate the development of sex- and APOE genotype-specific therapies for AD.

Microglia in Alzheimer's disease: pathogenesis, mechanisms, and therapeutic potentials

Alzheimer's disease (AD) is a neurodegenerative disorder characterized by protein aggregation in the brain. Recent studies have revealed the critical role of microglia in AD pathogenesis. This review provides a comprehensive summary of the current understanding of microglial involvement in AD, focusing on genetic determinants, phenotypic state, phagocytic capacity, neuroinflammatory response, and impact on synaptic plasticity and neuronal regulation. Furthermore, recent developments in drug discovery targeting microglia in AD are reviewed, highlighting potential avenues for therapeutic intervention. This review emphasizes the essential role of microglia in AD and provides insights into potential treatments.

Monitoring clusterin and fibrillar structures in aging and dementia

Objective

Clusterin is involved in a variety of physiological processes, including proteostasis. Several clusterin polymorphisms were associated with an increased risk of developing Alzheimer's disease, the world-leading cause of dementia. Herein, the effect of a clusterin polymorphism, aging and dementia in the levels of clusterin in human plasma were analysed in a primary care-based cohort, and the association of this chaperone with fibrillar structures discussed.

Methods

64 individuals with dementia (CDR≥1) and 64 age- and sex-matched Controls from a Portuguese cohort were genotyped for CLU rs1136000 polymorphism, and the plasma levels of clusterin and fibrils were assessed.

Results

An increased prevalence of the CC genotype was observed for the dementia group, although no significant robustness was achieved. CLU rs11136000 SNP did not significantly change plasma clusterin levels in demented individuals. Instead, clusterin levels decreased with aging and even more in individuals with dementia. Importantly, plasma clusterin levels correlated with the presence of fibrillar structures in Control individuals, but not in those with dementia.

Conclusion

This study reveals a significant decrease in plasma clusterin in demented individuals with aging, which related to altered clusterin-fibrils dynamics. Potentially, plasma clusterin and its association with fibrillar structures can be used to monitor dementia progression along aging.