The role of ABCA7 in Alzheimer's disease: evidence from genomics, transcriptomics and methylomics

Utilizing Machine Learning to Identify Biomarkers of Endoplasmic Reticulum Stress and Analyze Immune Cell Infiltration in Parkinson's Disease

The neurodegenerative disorder known as Parkinson's disease (PD) affects many people. The objective of this investigation was to examine the relationship between immune system infiltration, ATP-binding cassette transporter subfamily A member 7 (ABCA7) and TBL2 as well as potential therapeutic targets for the identification of PD associated to endoplasmic reticulum (ER) stress. First, we obtained PD data through GEO and divided it into two sets: a training set (GSE8397) plus a set for validation (GSE7621). Functional enrichment analysis was performed on a set of DEGs that overlapped with genes involved in endoplasmic reticulum stress. To identify genes of PD linked with endoplasmic reticulum stress, we employed random forest (RF) along with the least absolute shrinkage and selection operator (LASSO) logistic regression. Spearman's rank correlation analysis was then used to find associations among diagnostic markers with immune cell penetration. A grand total of 2 stress-related endoplasmic reticulum signature transcripts were identified. ABCA7 and TBL2 were shown to have diagnostic potential for PD and immune infiltrating cells have a role in the etiology of the disease. Additionally, resting CD4 memory, plasma cells, and NK cells overall exhibited positive associations with ABCA7, whereas triggered macrophages, T cells with active CD4 memory, activating NK cells, T cells with activated CD4 naive, engaged NK cells, and neutrophils all had adverse interactions with ABCA7. Overall, ABCA7 together with TBL2 have diagnostic utility for PD, and several types of immune cells, especially macrophages, may be involved in the development and progression of the disease.

Systematic review and meta-analysis of the association between ABCA7 common variants and Alzheimer's disease in non-Hispanic White and Asian cohorts

Background and aims

The relationship between the ABCA7 gene and Alzheimer's disease (AD) has been widely studied across various populations. However, the results have been inconsistent. This meta-analysis aimed to evaluate the association of ABCA7 polymorphisms with AD risk, including specific subtypes such as late-onset Alzheimer's disease (LOAD).

Methods

Relevant studies were identified through comprehensive database searches, and the quality of each study was assessed using the Newcastle-Ottawa Scale (NOS). Allele and genotype frequencies were extracted from the included studies. The pooled odds ratios (OR) with corresponding 95% confidence intervals (CI) were calculated using random-effects or fixed-effects models. Multiple testing corrections were conducted using the false discovery rate (FDR) method. The Cochran Q statistic and I2 metric were used to evaluate heterogeneity between studies, while Egger's test and funnel plots were employed to assess publication bias.

Results

A total of 36 studies, covering 21 polymorphisms and involving 31,809 AD cases and 44,994 controls, were included in this meta-analysis. NOS scores ranged from 7 to 9, indicating high-quality studies. A total of 11 SNPs (rs3764650, rs3752246, rs4147929, rs3752232, rs3752243, rs3764645, rs4147934, rs200538373, rs4147914, rs4147915, and rs115550680) in ABCA7 were significantly associated with AD risk. Among these SNPs, two (rs3764650 and rs3752246) were also found to be related to the late-onset AD (LOAD) subtype. In addition, two SNPs (rs4147929 and rs4147934) were associated with the susceptibility to AD only in non-Hispanic White populations. A total of 10 SNPs (rs3764647, rs3752229, rs3752237, rs4147932, rs113809142, rs3745842, rs3752239, rs4147918, rs74176364, and rs117187003) showed no significant relationship with AD risk. Sensitivity analyses confirmed the reliability of the original results, and heterogeneity was largely attributed to deviations from Hardy-Weinberg equilibrium, ethnicity, and variations between individual studies.

Conclusion

The available evidence suggests that specific ABCA7 SNPs may be associated with AD risk. Future studies with larger sample sizes will be necessary to confirm these results.

Systematic review registration

https://www.crd.york.ac.uk/prospero/, identifier: CRD42024540539.

Network dynamics-based subtyping of Alzheimer's disease with microglial genetic risk factors

BACKGROUND

The potential of microglia as a target for Alzheimer's disease (AD) treatment is promising, yet the clinical and pathological diversity within microglia, driven by genetic factors, poses a significant challenge. Subtyping AD is imperative to enable precise and effective treatment strategies. However, existing subtyping methods fail to comprehensively address the intricate complexities of AD pathogenesis, particularly concerning genetic risk factors. To address this gap, we have employed systems biology approaches for AD subtyping and identified potential therapeutic targets.

METHODS

We constructed patient-specific microglial molecular regulatory network models by utilizing existing literature and single-cell RNA sequencing data. The combination of large-scale computer simulations and dynamic network analysis enabled us to subtype AD patients according to their distinct molecular regulatory mechanisms. For each identified subtype, we suggested optimal targets for effective AD treatment.

RESULTS

To investigate heterogeneity in AD and identify potential therapeutic targets, we constructed a microglia molecular regulatory network model. The network model incorporated 20 known risk factors and crucial signaling pathways associated with microglial functionality, such as inflammation, anti-inflammation, phagocytosis, and autophagy. Probabilistic simulations with patient-specific genomic data and subsequent dynamics analysis revealed nine distinct AD subtypes characterized by core feedback mechanisms involving SPI1, CASS4, and MEF2C. Moreover, we identified PICALM, MEF2C, and LAT2 as common therapeutic targets among several subtypes. Furthermore, we clarified the reasons for the previous contradictory experimental results that suggested both the activation and inhibition of AKT or INPP5D could activate AD through dynamic analysis. This highlights the multifaceted nature of microglial network regulation.

CONCLUSIONS

These results offer a means to classify AD patients by their genetic risk factors, clarify inconsistent experimental findings, and advance the development of treatments tailored to individual genotypes for AD.

Sex differences in DNA methylation variations according to ART conception-evidence from the Norwegian mother, father, and child cohort study

Previous studies have shown cord-blood DNA methylation differences in newborns conceived using assisted reproductive technologies (ART) compared to those conceived naturally. However, whether these ART-related DNA methylation differences vary with children's sex is unknown. We hypothesize that the DNA methylation differences in cord blood between ART-conceived and naturally conceived newborns also varies by the sex of the child, with distinct patterns of differential methylation present in males and females. We investigated sex differences in cord-blood DNA methylation variation according to conception by ART using the Illumina MethylationEPIC platform, comparing 456 ART-conceived versus 507 naturally-conceived girls, and 503 ART-conceived and 473 naturally-conceived boys. We identified 37 differentially methylated CpGs according to ART-conception among girls, and 70 differentially methylated CpGs according to ART-conception among boys, when we used a 1% false discovery rate to account for multiple testing. Ten CpGs were differentially methylated according to conception by ART in both sexes. Among the genes that were associated with these CpGs, we found the BRCA1; NBR2 gene (two CpGs) was hypermethylated in girls while the APC2 (two CpGs) and NECAB3;ACTL10, (four CpGs) related to cellular signaling were hypomethylated in boys. These findings confirm the presence of sex-specific epigenetic differences, illustrating the nuanced impact of ART on the fetal epigenome. There is a need for further explorations into the implications for sex-specific developmental trajectories and health outcomes in ART-conceived children.

Very low levels of ABCA7 in the cerebrum and Alzheimer's disease onset between the ages of 60 and 80 independently of APOE

This cross-sectional study addressed the ABCA7-Alzheimer's disease (AD) association. ABCA7 protein levels were quantified in 3 cerebral regions of brain donors with Braak neurofibrillary tangle (NFT) stages 0-V. Ordinal regression models were implemented to estimate the effect of ABCA7 on stopping in an earlier Braak NFT stage versus progressing to the later stages in 2 prespecified age segments. In the final model, high ABCA7 levels in the parietal cortex increased the odds of remaining cognitively healthy (ie, in stages 0/I) versus experiencing AD onset (ie, progressing to stages II-V) in the 61-80 age segment (OR = 2.87, adj 95% CI = 1.41-7.86, adj P = .007, n = 109), after controlling for APOE and other covariates. No ABCA7-AD association was found in the 81-98 age segment (n = 113). Parietal ABCA7 levels in 61-80-year-old with stages II-V were very low, even significantly lower than in 81-98-year-old with stages II-V. ABCA7 levels in the prefrontal cortex and hippocampus predicted AD onset in the 61-80 age segment after adjustment for APOE. ABCA7 levels were also the lowest in 61-80-year-old with frequent neuritic plaques. Thus, very low ABCA7 levels in the cerebrum are associated with AD onset in the 7th-8th decade of life.

Identification of Genetic Variants in Progressive Supranuclear Palsy in Southeast Asia

BACKGROUND

Progressive supranuclear palsy (PSP) is largely a sporadic disease with few reported familial cases. Genome-wide association studies (GWAS) in sporadic PSP in Caucasian populations have identified MAPT as the most commonly associated genetic risk locus with the strongest effect size. At present there are limited data on genetic factors associated with PSP in Asian populations.

OBJECTIVES

Our goal was to investigate the genetic factors associated with PSP in Southeast Asian PSP patients.

METHODS

Next-generation sequencing (whole-exome, whole-genome and targeted sequencing) was performed in two Asian cohorts, comprising 177 PSP patients.

RESULTS

We identified 17 pathogenic or likely pathogenic variants in 16 PSP patients (9%), eight of which were novel. The most common relevant genetic variants identified were in MAPT, GBA1, OPTN, SYNJ1, and SQSTM1. Other variants detected were in TBK1, PRNP, and ABCA7-genes that have been implicated in other neurodegenerative diseases. Eighteen patients had a positive family history, of whom two carried pathogenic MAPT variants, and one carried a likely pathogenic GBA1 variant. None of the patients had expanded repeats in C9orf72. Furthermore, we found 16 different variants of uncertain significance in 21 PSP patients in PSEN2, ABCA7, SMPD1, MAPT, ATP13A2, OPTN, SQSTM1, CYLD, and BSN.

CONCLUSIONS

The genetic findings in our PSP cohorts appear to be somewhat distinct from those in Western populations, and also suggest an overlap of the genetic architecture between PSP and other neurodegenerative diseases. Further functional studies and validation in independent Asian cohorts will be useful for improving our understanding of PSP genetics and guiding genetic screening strategies in these populations. © 2024 International Parkinson and Movement Disorder Society.

ABCA7-dependent induction of neuropeptide Y is required for synaptic resilience in Alzheimer's disease through BDNF/NGFR signaling

Genetic variants in ABCA7, an Alzheimer's disease (AD)-associated gene, elevate AD risk, yet its functional relevance to the etiology is unclear. We generated a CRISPR-Cas9-mediated abca7 knockout zebrafish to explore ABCA7's role in AD. Single-cell transcriptomics in heterozygous abca7+/- knockout combined with Aβ42 toxicity revealed that ABCA7 is crucial for neuropeptide Y (NPY), brain-derived neurotrophic factor (BDNF), and nerve growth factor receptor (NGFR) expressions, which are crucial for synaptic integrity, astroglial proliferation, and microglial prevalence. Impaired NPY induction decreased BDNF and synaptic density, which are rescuable with ectopic NPY. In induced pluripotent stem cell-derived human neurons exposed to Aβ42, ABCA7-/- suppresses NPY. Clinical data showed reduced NPY in AD correlated with elevated Braak stages, genetic variants in NPY associated with AD, and epigenetic changes in NPY, NGFR, and BDNF promoters linked to ABCA7 variants. Therefore, ABCA7-dependent NPY signaling via BDNF-NGFR maintains synaptic integrity, implicating its impairment in increased AD risk through reduced brain resilience.

New insights in lipid metabolism: potential therapeutic targets for the treatment of Alzheimer's disease

Alzheimer's disease (AD) is increasingly recognized as being intertwined with the dysregulation of lipid metabolism. Lipids are a significant class of nutrients vital to all organisms, playing crucial roles in cellular structure, energy storage, and signaling. Alterations in the levels of various lipids in AD brains and dysregulation of lipid pathways and transportation have been implicated in AD pathogenesis. Clinically, evidence for a high-fat diet firmly links disrupted lipid metabolism to the pathogenesis and progression of AD, although contradictory findings warrant further exploration. In view of the significance of various lipids in brain physiology, the discovery of complex and diverse mechanisms that connect lipid metabolism with AD-related pathophysiology will bring new hope for patients with AD, underscoring the importance of lipid metabolism in AD pathophysiology, and promising targets for therapeutic intervention. Specifically, cholesterol, sphingolipids, and fatty acids have been shown to influence amyloid-beta (Aβ) accumulation and tau hyperphosphorylation, which are hallmarks of AD pathology. Recent studies have highlighted the potential therapeutic targets within lipid metabolism, such as enhancing apolipoprotein E lipidation, activating liver X receptors and retinoid X receptors, and modulating peroxisome proliferator-activated receptors. Ongoing clinical trials are investigating the efficacy of these strategies, including the use of ketogenic diets, statin therapy, and novel compounds like NE3107. The implications of these findings suggest that targeting lipid metabolism could offer new avenues for the treatment and management of AD. By concentrating on alterations in lipid metabolism within the central nervous system and their contribution to AD development, this review aims to shed light on novel research directions and treatment approaches for combating AD, offering hope for the development of more effective management strategies.

Alzheimer's Disease and Effects of ABCA7 Polymorphisms: A Review

Alzheimer's Disease (AD) is a progressive neurodegenerative disease and the main cause of dementia. Its etiology remains largely unclear, though genetic and environmental factors appear to confer susceptibility to AD development. This study assessed the role of ATP-binding Cassette A Subfamily 7 (ABCA7) genetic polymorphisms, as ongoing research suggests they have a role in the development of AD. We conducted a PubMed, Google Scholar, and Scopus search to identify and assess all AD studies examining ABCA7 variants in different populations and ethnicities. The last search was conducted on February 8, 2023. Inclusion and exclusion criteria were applied and only the studies that met the inclusion criteria were included in this review. Seventeen studies were finally included. According to the results, ABCA7 variants infer different risks for AD among populations with different ancestries. African American populations show a higher risk for AD, carrying the five novel variants rs115550680, rs142076058, rs10405305, rs3764647, and rs567222111. Asian populations also have an increased risk for AD, harboring three variants. ABCA7 genetic variability contributes to AD development and shows racial disparities. African American and Asian populations seem to be at greater risk of developing AD. These results may assist future research efforts for the early and accurate diagnosis of AD. Moreover, further exploration of the mechanisms of ABCA7 in the context of AD could identify potential therapeutic targets.

Therapeutic potential of plant-derived natural compounds in Alzheimer's disease: Targeting microglia-mediated neuroinflammation

Microglia are resident immune cells of the central nervous system (CNS) with roles in sensing, housekeeping, and defense. Exploring the role of microglia in the occurrence and development of Alzheimer's disease (AD) and the possible therapeutic mechanism of plant-derived natural compounds (PDNCs) that regulate microglia-associated neuroinflammation may potentially help in elucidating the pathogenesis of AD and provide novel insights for its treatment. This review explores the role of abnormal microglial activation and its dominant neuroinflammatory response, as well as the activation of their target receptors and signaling pathways in AD pathogenesis. Additionally, we report an update on the potential pharmacological mechanisms of multiple PDNCs in modulating microglia-associated neuroinflammation in AD treatment. Dysregulated activation of microglial receptors and their downstream pathways impaired immune homeostasis in animal models of AD. Multiple signaling pathways, such as mitogen-activated protein kinase (MAPK), nuclear factor kappa light chain enhancer of activated B cells (NF-κB), and Toll-like receptors, play important roles in microglial activation and can exacerbate microglia-mediated neuroinflammation. PDNCs, such as magnolol, stigmasterol, matrine, naringenin, naringin, and resveratrol, can delay the progression of AD by inhibiting the proinflammatory receptors of microglia, activating its anti-inflammatory receptors, regulating the receptors related to β-amyloid (Aβ) clearance, reversing immune dysregulation, and maintaining the immune homeostasis of microglial downstream pathways. This review summarizes the mechanisms by which microglia cause chronic inflammation in AD and evaluates the beneficial effects of PDNCs on immune regulation in AD by regulating microglial receptors and their downstream pathways.

Tracking neuroinflammatory biomarkers in Alzheimer's disease: a strategy for individualized therapeutic approaches?

BACKGROUND

Recent trials of anti-amyloid-β (Aβ) monoclonal antibodies, including lecanemab and donanemab, in early Alzheimer disease (AD) showed that these drugs have limited clinical benefits and their use comes with a significant risk of serious adverse events. Thus, it seems crucial to explore complementary therapeutic approaches. Genome-wide association studies identified robust associations between AD and several AD risk genes related to immune response, including but not restricted to CD33 and TREM2. Here, we critically reviewed the current knowledge on candidate neuroinflammatory biomarkers and their role in characterizing the pathophysiology of AD.

MAIN BODY

Neuroinflammation is recognized to be a crucial and contributing component of AD pathogenesis. The fact that neuroinflammation is most likely present from earliest pre-stages of AD and co-occurs with the deposition of Aβ reinforces the need to precisely define the sequence and nature of neuroinflammatory events. Numerous clinical trials involving anti-inflammatory drugs previously yielded unfavorable outcomes in early and mild-to-moderate AD. Although the reasons behind these failures remain unclear, these may include the time and the target selected for intervention. Indeed, in our review, we observed a stage-dependent neuroinflammatory process in the AD brain. While the initial activation of glial cells counteracts early brain Aβ deposition, the downregulation in the functional state of microglia occurs at more advanced disease stages. To address this issue, personalized neuroinflammatory modulation therapy is required. The emergence of reliable blood-based neuroinflammatory biomarkers, particularly glial fibrillary acidic protein, a marker of reactive astrocytes, may facilitate the classification of AD patients based on the ATI(N) biomarker framework. This expands upon the traditional classification of Aβ ("A"), tau ("T"), and neurodegeneration ("N"), by incorporating a novel inflammatory component ("I").

CONCLUSIONS

The present review outlines the current knowledge on potential neuroinflammatory biomarkers and, importantly, emphasizes the role of longitudinal analyses, which are needed to accurately monitor the dynamics of cerebral inflammation. Such a precise information on time and place will be required before anti-inflammatory therapeutic interventions can be considered for clinical evaluation. We propose that an effective anti-neuroinflammatory therapy should specifically target microglia and astrocytes, while considering the individual ATI(N) status of patients.

The Abca7V1613M variant reduces Aβ generation, plaque load, and neuronal damage

BACKGROUND

Variants in ABCA7, a member of the ABC transporter superfamily, have been associated with increased risk for developing late onset Alzheimer's disease (LOAD).

METHODS

CRISPR-Cas9 was used to generate an Abca7V1613M variant in mice, modeling the homologous human ABCA7V1599M variant, and extensive characterization was performed.

RESULTS

Abca7V1613M microglia show differential gene expression profiles upon lipopolysaccharide challenge and increased phagocytic capacity. Homozygous Abca7V1613M mice display elevated circulating cholesterol and altered brain lipid composition. When crossed with 5xFAD mice, homozygous Abca7V1613M mice display fewer Thioflavin S-positive plaques, decreased amyloid beta (Aβ) peptides, and altered amyloid precursor protein processing and trafficking. They also exhibit reduced Aβ-associated inflammation, gliosis, and neuronal damage.

DISCUSSION

Overall, homozygosity for the Abca7V1613M variant influences phagocytosis, response to inflammation, lipid metabolism, Aβ pathology, and neuronal damage in mice. This variant may confer a gain of function and offer a protective effect against Alzheimer's disease-related pathology.

HIGHLIGHTS

ABCA7 recognized as a top 10 risk gene for developing Alzheimer's disease. Loss of function mutations result in increased risk for LOAD. V1613M variant reduces amyloid beta plaque burden in 5xFAD mice. V1613M variant modulates APP processing and trafficking in 5xFAD mice. V1613M variant reduces amyloid beta-associated damage in 5xFAD mice.

Single-cell atlas of ABCA7 loss-of-function reveals impaired neuronal respiration via choline-dependent lipid imbalances

Loss-of-function (LoF) variants in the lipid transporter ABCA7 significantly increase the risk of Alzheimer's disease (odds ratio ∼2), yet the pathogenic mechanisms and the neural cell types affected by these variants remain largely unknown. Here, we performed single-nuclear RNA sequencing of 36 human post-mortem samples from the prefrontal cortex of 12 ABCA7 LoF carriers and 24 matched non-carrier control individuals. ABCA7 LoF was associated with gene expression changes in all major cell types. Excitatory neurons, which expressed the highest levels of ABCA7, showed transcriptional changes related to lipid metabolism, mitochondrial function, cell cycle-related pathways, and synaptic signaling. ABCA7 LoF-associated transcriptional changes in neurons were similarly perturbed in carriers of the common AD missense variant ABCA7 p.Ala1527Gly (n = 240 controls, 135 carriers), indicating that findings from our study may extend to large portions of the at-risk population. Consistent with ABCA7's function as a lipid exporter, lipidomic analysis of isogenic iPSC-derived neurons (iNs) revealed profound intracellular triglyceride accumulation in ABCA7 LoF, which was accompanied by a relative decrease in phosphatidylcholine abundance. Metabolomic and biochemical analyses of iNs further indicated that ABCA7 LoF was associated with disrupted mitochondrial bioenergetics that suggested impaired lipid breakdown by uncoupled respiration. Treatment of ABCA7 LoF iNs with CDP-choline (a rate-limiting precursor of phosphatidylcholine synthesis) reduced triglyceride accumulation and restored mitochondrial function, indicating that ABCA7 LoF-induced phosphatidylcholine dyshomeostasis may directly disrupt mitochondrial metabolism of lipids. Treatment with CDP-choline also rescued intracellular amyloid β -42 levels in ABCA7 LoF iNs, further suggesting a link between ABCA7 LoF metabolic disruptions in neurons and AD pathology. This study provides a detailed transcriptomic atlas of ABCA7 LoF in the human brain and mechanistically links ABCA7 LoF-induced lipid perturbations to neuronal energy dyshomeostasis. In line with a growing body of evidence, our study highlights the central role of lipid metabolism in the etiology of Alzheimer's disease.

Comprehensive Overview of Alzheimer's Disease: Etiological Insights and Degradation Strategies

Alzheimer's disease (AD) is the most prevalent neurodegenerative disorder and affects millions of individuals globally. AD is associated with cognitive decline and memory loss that worsens with aging. A statistical report using U.S. data on AD estimates that approximately 6.9 million individuals suffer from AD, a number projected to surge to 13.8 million by 2060. Thus, there is a critical imperative to pinpoint and address AD and its hallmark tau protein aggregation early to prevent and manage its debilitating effects. Amyloid-β and tau proteins are primarily associated with the formation of plaques and neurofibril tangles in the brain. Current research efforts focus on degrading amyloid-β and tau or inhibiting their synthesis, particularly targeting APP processing and tau hyperphosphorylation, aiming to develop effective clinical interventions. However, navigating this intricate landscape requires ongoing studies and clinical trials to develop treatments that truly make a difference. Genome-wide association studies (GWASs) across various cohorts identified 40 loci and over 300 genes associated with AD. Despite this wealth of genetic data, much remains to be understood about the functions of these genes and their role in the disease process, prompting continued investigation. By delving deeper into these genetic associations, novel targets such as kinases, proteases, cytokines, and degradation pathways, offer new directions for drug discovery and therapeutic intervention in AD. This review delves into the intricate biological pathways disrupted in AD and identifies how genetic variations within these pathways could serve as potential targets for drug discovery and treatment strategies. Through a comprehensive understanding of the molecular underpinnings of AD, researchers aim to pave the way for more effective therapies that can alleviate the burden of this devastating disease.

An interpretable generative multimodal neuroimaging-genomics framework for decoding Alzheimer's disease

Alzheimer's disease (AD) is the most prevalent form of dementia, affecting millions worldwide with a progressive decline in cognitive abilities. The AD continuum encompasses a prodormal stage known as Mild Cognitive Impairment (MCI), where patients may either progress to AD (MCIc) or remain stable (MCInc). Understanding the underlying mechanisms of AD requires complementary analysis derived from different data sources, leading to the development of multimodal deep learning models. In this study, we leveraged structural and functional Magnetic Resonance Imaging (sMRI/fMRI) to investigate the disease-induced grey matter and functional network connectivity changes. Moreover, considering AD's strong genetic component, we introduce Single Nucleotide Polymorphisms (SNPs) as a third channel. Given such diverse inputs, missing one or more modalities is a typical concern of multimodal methods. We hence propose a novel deep learning based classification framework where generative module employing Cycle Generative Adversarial Networks (cGAN) was adopted to impute missing data within the latent space. Additionally, we adopted an Explainable Artificial Intelligence (XAI) method, Integrated Gradients (IG), to extract input features relevance, enhancing our understanding of the learned representations. Two critical tasks were addressed: AD detection and MCI conversion prediction. Experimental results showed that our framework was able to reach the state-of-the-art in the classification of CN vs AD reaching an average test accuracy of 0.926 ± 0.02. For the MCInc vs MCIc task, we achieved an average prediction accuracy of 0.711 ± 0.01 using the pre-trained model for CN and AD. The interpretability analysis revealed that the classification performance was led by significant grey matter modulations in cortical and subcortical brain areas well known for their association with AD. Moreover, impairments in sensory-motor and visual resting state network connectivity along the disease continuum, as well as mutations in SNPs defining biological processes linked to amyloid-beta and cholesterol formation clearance and regulation, were identified as contributors to the achieved performance. Overall, our integrative deep learning approach shows promise for AD detection and MCI prediction, while shading light on important biological insights.

Brain cholesterol and Alzheimer's disease: challenges and opportunities in probe and drug development

Cholesterol homeostasis is impaired in Alzheimer's disease; however, attempts to modulate brain cholesterol biology have not translated into tangible clinical benefits for patients to date. Several recent milestone developments have substantially improved our understanding of how excess neuronal cholesterol contributes to the pathophysiology of Alzheimer's disease. Indeed, neuronal cholesterol was linked to the formation of amyloid-β and neurofibrillary tangles through molecular pathways that were recently delineated in mechanistic studies. Furthermore, remarkable advances in translational molecular imaging have now made it possible to probe cholesterol metabolism in the living human brain with PET, which is an important prerequisite for future clinical trials that target the brain cholesterol machinery in Alzheimer's disease patients-with the ultimate aim being to develop disease-modifying treatments. This work summarizes current concepts of how the biosynthesis, transport and clearance of brain cholesterol are affected in Alzheimer's disease. Further, current strategies to reverse these alterations by pharmacotherapy are critically discussed in the wake of emerging translational research tools that support the assessment of brain cholesterol biology not only in animal models but also in patients with Alzheimer's disease.

Emerging Role of ABC Transporters in Glia Cells in Health and Diseases of the Central Nervous System

ATP-binding cassette (ABC) transporters play a crucial role for the efflux of a wide range of substrates across different cellular membranes. In the central nervous system (CNS), ABC transporters have recently gathered significant attention due to their pivotal involvement in brain physiology and neurodegenerative disorders, such as Alzheimer's disease (AD). Glial cells are fundamental for normal CNS function and engage with several ABC transporters in different ways. Here, we specifically highlight ABC transporters involved in the maintenance of brain homeostasis and their implications in its metabolic regulation. We also show new aspects related to ABC transporter function found in less recognized diseases, such as Huntington's disease (HD) and experimental autoimmune encephalomyelitis (EAE), as a model for multiple sclerosis (MS). Understanding both their impact on the physiological regulation of the CNS and their roles in brain diseases holds promise for uncovering new therapeutic options. Further investigations and preclinical studies are warranted to elucidate the complex interplay between glial ABC transporters and physiological brain functions, potentially leading to effective therapeutic interventions also for rare CNS disorders.

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

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

Generation of an induced pluripotent stem cell line (UMi043-A) from an African American patient with Alzheimer's disease carrying an ABCA7 deletion (p.Arg578Alafs)

The ATP-binding cassette, subfamily A (ABC1), member 7 (ABCA7) gene is associated with Alzheimer's disease (AD) risk in populations of African, Asian, and European ancestry1-5. Numerous ABCA7 mutations contributing to risk have been identified, including a 44 base pair deletion (rs142076058) specific to individuals of African ancestry and predicted to cause a frameshift mutation (p.Arg578Alafs) (Cukier et al., 2016). The UMi043-A human induced pluripotent stem cell line was derived from an African American individual with AD who is heterozygous for this deletion and is a resource to further investigate ABCA7 and how this African-specific deletion may influence disease pathology.

Predicting long-term progression of Alzheimer's disease using a multimodal deep learning model incorporating interaction effects

BACKGROUND

Identifying individuals with mild cognitive impairment (MCI) at risk of progressing to Alzheimer's disease (AD) provides a unique opportunity for early interventions. Therefore, accurate and long-term prediction of the conversion from MCI to AD is desired but, to date, remains challenging. Here, we developed an interpretable deep learning model featuring a novel design that incorporates interaction effects and multimodality to improve the prediction accuracy and horizon for MCI-to-AD progression.

METHODS

This multi-center, multi-cohort retrospective study collected structural magnetic resonance imaging (sMRI), clinical assessments, and genetic polymorphism data of 252 patients with MCI at baseline from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Our deep learning model was cross-validated on the ADNI-1 and ADNI-2/GO cohorts and further generalized in the ongoing ADNI-3 cohort. We evaluated the model performance using the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, specificity, and F1 score.

RESULTS

On the cross-validation set, our model achieved superior results for predicting MCI conversion within 4 years (AUC, 0.962; accuracy, 92.92%; sensitivity, 88.89%; specificity, 95.33%) compared to all existing studies. In the independent test, our model exhibited consistent performance with an AUC of 0.939 and an accuracy of 92.86%. Integrating interaction effects and multimodal data into the model significantly increased prediction accuracy by 4.76% (P = 0.01) and 4.29% (P = 0.03), respectively. Furthermore, our model demonstrated robustness to inter-center and inter-scanner variability, while generating interpretable predictions by quantifying the contribution of multimodal biomarkers.

CONCLUSIONS

The proposed deep learning model presents a novel perspective by combining interaction effects and multimodality, leading to more accurate and longer-term predictions of AD progression, which promises to improve pre-dementia patient care.

Multi-class Modeling Identifies Shared Genetic Risk for Late-onset Epilepsy and Alzheimer's Disease

Background

Previous studies have established a strong link between late-onset epilepsy (LOE) and Alzheimer's disease (AD). However, their shared genetic risk beyond the APOE gene remains unclear. Our study sought to examine the shared genetic factors of AD and LOE, interpret the biological pathways involved, and evaluate how AD onset may be mediated by LOE and shared genetic risks.

Methods

We defined phenotypes using phecodes mapped from diagnosis codes, with patients' records aged 60-90. A two-step Least Absolute Shrinkage and Selection Operator (LASSO) workflow was used to identify shared genetic variants based on prior AD GWAS integrated with functional genomic data. We calculated an AD-LOE shared risk score and used it as a proxy in a causal mediation analysis. We used electronic health records from an academic health center (UCLA Health) for discovery analyses and validated our findings in a multi-institutional EHR database (All of Us).

Results

The two-step LASSO method identified 34 shared genetic loci between AD and LOE, including the APOE region. These loci were mapped to 65 genes, which showed enrichment in molecular functions and pathways such as tau protein binding and lipoprotein metabolism. Individuals with high predicted shared risk scores have a higher risk of developing AD, LOE, or both in their later life compared to those with low-risk scores. LOE partially mediates the effect of AD-LOE shared genetic risk on AD (15% proportion mediated on average). Validation results from All of Us were consistent with findings from the UCLA sample.

Conclusions

We employed a machine learning approach to identify shared genetic risks of AD and LOE. In addition to providing substantial evidence for the significant contribution of the APOE-TOMM40-APOC1 gene cluster to shared risk, we uncovered novel genes that may contribute. Our study is one of the first to utilize All of Us genetic data to investigate AD, and provides valuable insights into the potential common and disease-specific mechanisms underlying AD and LOE, which could have profound implications for the future of disease prevention and the development of targeted treatment strategies to combat the co-occurrence of these two diseases.

14-Week exercise training modifies the DNA methylation levels at gene sites in non-Alzheimer's disease women aged 50 to 70 years

Exercise training emerges as a key strategy in lifestyle modification, capable of reducing the risk of developing Alzheimer's disease (AD) due to risk factors such as age, family history, genetics and low level of education associated with AD. We aim to analyze the effect of a 14-week combined exercise training (CT) on the methylation of genes associated with AD in non-alzheimer's disease women. CT sessions lasted 60 min, occurring three times a week for 14 weeks. Forty non-Alzheimer's disease women aged 50 to 70 years (60.7 ± 4.1 years) with a mean height of 1.6 ± 0.1 m, mean weight of 73.12 ± 9.0 kg and a mean body mass index of 29.69 ± 3.5 kg/m2, underwent two physical assessments: pre and post the 14 weeks. DNA methylation assays utilized the EPIC Infinium Methylation BeadChip from Illumina. We observed that 14 weeks of CT led to reductions in systolic (p = 0.001) and diastolic (p = 0.017) blood pressure and improved motor skills post-intervention. Among 25 genes linked to AD, CT induced differentially methylated sites in 12 genes, predominantly showing hypomethylated sites (negative β values). Interestingly, despite hypomethylated sites, some genes exhibited hypermethylated sites (positive β values), such as ABCA7, BDNF, and WWOX. A 14-week CT regimen was adequate to induce differential methylation in 12 CE-related genes in healthy older women, alongside improvements in motor skills and blood pressure. In conclusion, this study suggest that combined training can be a strategy to improve physical fitness in older individuals, especially able to induce methylation alterations in genes sites related to development of AD. It is important to highlight that training should act as protective factor in older adults.

Blood-brain barrier transporters: An overview of function, dysfunction in Alzheimer's disease and strategies for treatment

The blood-brain-barrier (BBB) has a major function in maintaining brain homeostasis by regulating the entry of molecules from the blood to the brain. Key players in BBB function are BBB transporters which are highly expressed in brain endothelial cells (BECs) and critical in mediating the exchange of nutrients and waste products. BBB transporters can also influence drug delivery into the brain by inhibiting or facilitating the entry of brain targeting therapeutics for the treatment of brain disorders, such as Alzheimer's disease (AD). Recent studies have shown that AD is associated with a disrupted BBB and transporter dysfunction, although their roles in the development in AD are not fully understand. Modulation of BBB transporter activity may pose a novel approach to enhance the delivery of drugs to the brain for enhanced treatment of AD. In this review, we will give an overview of key functions of BBB transporters and known changes in AD. In addition, we will discuss current strategies for transporter modulation for enhanced drug delivery into the brain.

Accounting for network noise in graph-guided Bayesian modeling of structured high-dimensional data

There is a growing body of literature on knowledge-guided statistical learning methods for analysis of structured high-dimensional data (such as genomic and transcriptomic data) that can incorporate knowledge of underlying networks derived from functional genomics and functional proteomics. These methods have been shown to improve variable selection and prediction accuracy and yield more interpretable results. However, these methods typically use graphs extracted from existing databases or rely on subject matter expertise, which are known to be incomplete and may contain false edges. To address this gap, we propose a graph-guided Bayesian modeling framework to account for network noise in regression models involving structured high-dimensional predictors. Specifically, we use 2 sources of network information, including the noisy graph extracted from existing databases and the estimated graph from observed predictors in the dataset at hand, to inform the model for the true underlying network via a latent scale modeling framework. This model is coupled with the Bayesian regression model with structured high-dimensional predictors involving an adaptive structured shrinkage prior. We develop an efficient Markov chain Monte Carlo algorithm for posterior sampling. We demonstrate the advantages of our method over existing methods in simulations, and through analyses of a genomics dataset and another proteomics dataset for Alzheimer's disease.

Insights into the Neuroprotective Potential of Epicatechin: Effects against Aβ-Induced Toxicity in Caenorhabditis elegans

Medical therapies to avoid the progression of Alzheimer's disease (AD) are limited to date. Certain diets have been associated with a lower incidence of neurodegenerative diseases. In particular, the regular intake of foods rich in polyphenols, such as epicatechin (EC), could help prevent or mitigate AD progression. This work aims to explore the neuroprotective effects of EC using different transgenic strains of Caenorhabditis elegans, which express human Aβ1-42 peptides and contribute to elucidating the mechanisms involved in the effects of EC in AD. The performed assays indicate that this flavan-3-ol was able to reduce the signs of β-amyloid accumulation in C. elegans, improving motility and chemotaxis and increasing survival in transgenic strain peptide producers compared to nematodes not treated with EC. The neuroprotective effects exhibited by EC in C. elegans could be explained by the modulation of inflammation and stress-associated genes, as well as autophagy, microgliosis, and heat shock signaling pathways, involving the regulation of cpr-5, epg-8, ced-7, ZC239.12, and hsp-16 genes. Overall, the results obtained in this study support the protective effects of epicatechin against Aβ-induced toxicity.

ABCA7-dependent Neuropeptide-Y signalling is a resilience mechanism required for synaptic integrity in Alzheimer's disease

Alzheimer's disease (AD) remains a complex challenge characterized by cognitive decline and memory loss. Genetic variations have emerged as crucial players in the etiology of AD, enabling hope for a better understanding of the disease mechanisms; yet the specific mechanism of action for those genetic variants remain uncertain. Animal models with reminiscent disease pathology could uncover previously uncharacterized roles of these genes. Using CRISPR/Cas9 gene editing, we generated a knockout model for abca7, orthologous to human ABCA7 - an established AD-risk gene. The abca7 +/- zebrafish showed reduced astroglial proliferation, synaptic density, and microglial abundance in response to amyloid beta 42 (Aβ42). Single-cell transcriptomics revealed abca7 -dependent neuronal and glial cellular crosstalk through neuropeptide Y (NPY) signaling. The abca7 knockout reduced the expression of npy, bdnf and ngfra , which are required for synaptic integrity and astroglial proliferation. With clinical data in humans, we showed reduced NPY in AD correlates with elevated Braak stage, predicted regulatory interaction between NPY and BDNF , identified genetic variants in NPY associated with AD, found segregation of variants in ABCA7, BDNF and NGFR in AD families, and discovered epigenetic changes in the promoter regions of NPY, NGFR and BDNF in humans with specific single nucleotide polymorphisms in ABCA7 . These results suggest that ABCA7-dependent NPY signaling is required for synaptic integrity, the impairment of which generates a risk factor for AD through compromised brain resilience.

Abstract Figure

Codon Pattern and Context Analysis in Genes Triggering Alzheimer's Disease and Latent Tau Protein Aggregation Post-Anesthesia Exhibited Unique Molecular Patterns Associated with Functional Aspects

Background

Previous reports have demonstrated post-operative dementia and Alzheimer's disease (AD), and increased amyloid-β levels and tau hyperphosphorylation have been observed in animal models post-anesthesia.

Objective

After surgical interventions, loss in memory has been observed that has been found linked with genes modulated after anesthesia. Present study aimed to study molecular pattern present in genes modulated post anesthesia and involved in characters progressing towards AD.

Methods

In the present study, 17 transcript variants belonging to eight genes, which have been found to modulate post-anesthesia and contribute to AD progression, were envisaged for their compositional features, molecular patterns, and codon and codon context-associated studies.

Results

The sequences' composition was G/C rich, influencing dinucleotide preference, codon preference, codon usage, and codon context. The G/C nucleotides being highly occurring nucleotides, CpGdinucleotides were also preferred; however, CpG was highly disfavored at p3-1 at the codon junction. The nucleotide composition of Cytosine exhibited a unique feature, and unlike other nucleotides, it did not correlate with codon bias. Contrarily, it correlated with the sequence lengths. The sequences were leucine-rich, and multiple leucine repeats were present, exhibiting the functional role of neuroprotection from neuroinflammation post-anesthesia.

Conclusions

The analysis pave the way to elucidate unique molecular patterns in genes modulated during anesthetic treatment and might help ameliorate the ill effects of anesthetics in the future.

Association of Blood-Based DNA Methylation Markers With Late-Onset Alzheimer Disease: A Potential Diagnostic Approach

BACKGROUND AND OBJECTIVES

There is an urgent need to identify novel noninvasive biomarkers for Alzheimer disease (AD) diagnosis. Recent advances in blood-based measurements of phosphorylated tau (pTau) species are promising but still insufficient to address clinical needs. Epigenetics has been shown to be helpful to better understand AD pathogenesis. Epigenetic biomarkers have been successfully implemented in other medical disciplines, such as oncology. The objective of this study was to explore the diagnostic accuracy of a blood-based DNA methylation marker panel as a noninvasive tool to identify patients with late-onset Alzheimer compared with age-matched controls.

METHODS

A case-control study was performed. Blood DNA methylation levels at 46 cytosine-guanine sites (21 genes selected after a comprehensive literature search) were measured by bisulfite pyrosequencing in patients with "probable AD dementia" following National Institute on Aging and the Alzheimer's Association guidelines (2011) and age-matched and sex-matched controls recruited at Neurology Department-University Hospital of Navarre, Spain, selected by convenience sampling. Plasma pTau181 levels were determined by Simoa technology. Multivariable logistic regression analysis was performed to explore the optimal model to discriminate patients with AD from controls. Furthermore, we performed a stratified analysis by sex.

RESULTS

The final study cohort consisted of 80 patients with AD (age: median [interquartile range] 79 [11] years; 58.8% female) and 100 cognitively healthy controls (age 77 [10] years; 58% female). A panel including DNA methylation levels at NXN, ABCA7, and HOXA3 genes and plasma pTau181 significantly improved (area under the receiver operating characteristic curve 0.93, 95% CI 0.89-0.97) the diagnostic performance of a single pTau181-based model, adjusted for age, sex, and APOE ɛ4 genotype. The sensitivity and specificity of this panel were 83.30% and 90.00%, respectively. After sex-stratified analysis, HOXA3 DNA methylation levels showed consistent association with AD.

DISCUSSION

These results highlight the potential translational value of blood-based DNA methylation biomarkers for noninvasive diagnosis of AD.

REGISTRATION INFORMATION

Research Ethics Committee of the University Hospital of Navarre (PI17/02218).

CSF biomarker analysis of ABCA7 mutation carriers suggests altered APP processing and reduced inflammatory response

BACKGROUND

The Alzheimer's disease (AD) risk gene ABCA7 has suggested functions in lipid metabolism and the immune system. Rare premature termination codon (PTC) mutations and an expansion of a variable number of tandem repeats (VNTR) polymorphism in the gene, both likely cause a lower ABCA7 expression and hereby increased risk for AD. However, the exact mechanism of action remains unclear. By studying CSF biomarkers reflecting different types of AD-related pathological processes, we aim to get a better insight in those processes and establish a biomarker profile of mutation carriers.

METHODS

The study population consisted of 229 AD patients for whom CSF was available and ABCA7 sequencing and VNTR genotyping had been performed. This included 28 PTC mutation and 16 pathogenic expansion carriers. CSF levels of Aβ1-42, Aβ1-40, P-tau181, T-tau, sAPPα, sAPPβ, YKL-40, and hFABP were determined using ELISA and Meso Scale Discovery assays. We compared differences in levels of these biomarkers and the Aβ ratio between AD patients with or without an ABCA7 PTC mutation or expansion using linear regression on INT-transformed data with APOE-status, age and sex as covariates.

RESULTS

Carriers of ABCA7 expansion mutations had significantly lower Aβ1-42 levels (P = 0.022) compared with non-carrier patients. The effect of the presence of ABCA7 mutations on CSF levels was especially pronounced in APOE ε4-negative carriers. In addition, VNTR expansion carriers had reduced Aβ1-40 (P = 0.023), sAPPα (P = 0.047), sAPPβ (P = 0.016), and YKL-40 (P = 0.0036) levels.

CONCLUSIONS

Our results are suggestive for an effect on APP processing by repeat expansions given the changes in the amyloid-related CSF biomarkers that were found in carriers. The decrease in YKL-40 levels in expansion carriers moreover suggests that these patients potentially have a reduced inflammatory response to AD damage. Moreover, our findings suggest the existence of a mechanism, independent of lowered expression, affecting neuropathology in expansion carriers.

Pharmacogenomics of Dementia: Personalizing the Treatment of Cognitive and Neuropsychiatric Symptoms

Dementia is a syndrome of global and progressive deterioration of cognitive skills, especially memory, learning, abstract thinking, and orientation, usually affecting the elderly. The most common forms are Alzheimer's disease, vascular dementia, and other (frontotemporal, Lewy body disease) dementias. The etiology of these multifactorial disorders involves complex interactions of various environmental and (epi)genetic factors and requires multiple forms of pharmacological intervention, including anti-dementia drugs for cognitive impairment, antidepressants, antipsychotics, anxiolytics and sedatives for behavioral and psychological symptoms of dementia, and other drugs for comorbid disorders. The pharmacotherapy of dementia patients has been characterized by a significant interindividual variability in drug response and the development of adverse drug effects. The therapeutic response to currently available drugs is partially effective in only some individuals, with side effects, drug interactions, intolerance, and non-compliance occurring in the majority of dementia patients. Therefore, understanding the genetic basis of a patient's response to pharmacotherapy might help clinicians select the most effective treatment for dementia while minimizing the likelihood of adverse reactions and drug interactions. Recent advances in pharmacogenomics may contribute to the individualization and optimization of dementia pharmacotherapy by increasing its efficacy and safety via a prediction of clinical outcomes. Thus, it can significantly improve the quality of life in dementia patients.

ABCA7-Associated Clinical Features and Molecular Mechanisms in Alzheimer's Disease

Alzheimer's disease (AD) is the most common type of neurodegenerative disease and its pathogenesis is still unclear. Genetic factors are thought to account for a large proportion of the overall AD phenotypes. ATP-binding cassette transporter A7 (ABCA7) is one of the most important risk gene for AD. Multiple forms of ABCA7 variants significantly increase the risk of AD, such as single-nucleotide polymorphisms, premature termination codon variants, missense variants, variable number tandem repeat, mutations, and alternative splicing. AD patients with ABCA7 variants usually exhibit typical clinical and pathological features of traditional AD with a wide age of onset range. ABCA7 variants can alter ABCA7 protein expression levels and protein structure to affect protein functions such as abnormal lipid metabolism, amyloid precursor protein (APP) processing, and immune cell function. Specifically, ABCA7 deficiency can cause neuronal apoptosis by inducing endoplasmic reticulum stress through the PERK/eIF2α pathway. Second, ABCA7 deficiency can increase Aβ production by upregulating the SREBP2/BACE1 pathway and promoting APP endocytosis. In addition, the ability of microglia to phagocytose and degrade Aβ is destroyed by ABCA7 deficiency, leading to reduced clearance of Aβ. Finally, disturbance of lipid metabolism may also be an important method by which ABCA7 variants influence the incidence rate of AD. In the future, more attention should be given to different ABCA7 variants and ABCA7 targeted therapies for AD.

Down-Regulation of ABCA7 in Human Microglia, Astrocyte and THP-1 Cell Lines by Cholesterol Depletion, IL-1β and TNFα, or PMA

Adenosine triphosphate-binding cassette transporter subfamily A member 7 (ABCA7) is a major risk factor for Alzheimer's disease. Human neural cell lines were used to investigate the regulation of ABCA7 expression by cholesterol and pro-inflammatory cytokines. Cholesterol was depleted by methyl-β-cyclodextrin, followed by treatment with rosuvastatin to suppress de novo synthesis, while the cells underwent adjustment to low cholesterol. Cholesterol depletion by 50-76% decreased ABCA7 expression by ~40% in C20 microglia and ~21% in A172 astrocytes but had no effect on the protein in SK-N-SH neurons. Cholesterol depletion also suppressed ABCA7 in HMC3 microglia. Previously, cholesterol loss was reported to up-regulate ABCA7 in murine macrophages. ABCA7 was down-regulated during PMA-induced differentiation of human THP-1 monocytes to macrophages. But, cholesterol depletion in THP-1 macrophages by ~71% had no effect on ABCA7. IL-1β and TNFα reduced ABCA7 expression in C20 and HMC3 microglia but not in A172 astrocytes or SK-N-SH neurons. IL-6 did not affect ABCA7 in the neural cells. These findings suggest that ABCA7 is active in regular homeostasis in human neural cells, is regulated by cholesterol in a cell type-dependent manner, i.e., cholesterol depletion down-regulates it in human neuroglia but not neurons, and is incompatible with IL-1β and TNFα inflammatory responses in human microglia.

Interaction Analysis Reveals Complex Genetic Associations with Alzheimer's Disease in the CLU and ABCA7 Gene Regions

Sporadic Alzheimer's disease (AD) is a polygenic neurodegenerative disorder. Single-nucleotide polymorphisms (SNPs) in multiple genes (e.g., CLU and ABCA7) have been associated with AD. However, none of them were characterized as causal variants that indicate the complex genetic architecture of AD, which is likely affected by individual variants and their interactions. We performed a meta-analysis of four independent cohorts to examine associations of 32 CLU and 50 ABCA7 polymorphisms as well as their 496 and 1225 pair-wise interactions with AD. The single SNP analyses revealed that six CLU and five ABCA7 SNPs were associated with AD. Ten of them were previously not reported. The interaction analyses identified AD-associated compound genotypes for 25 CLU and 24 ABCA7 SNP pairs, whose comprising SNPs were not associated with AD individually. Three and one additional CLU and ABCA7 pairs composed of the AD-associated SNPs showed partial interactions as the minor allele effect of one SNP in each pair was intensified in the absence of the minor allele of the other SNP. The interactions identified here may modulate associations of the CLU and ABCA7 variants with AD. Our analyses highlight the importance of the roles of combinations of genetic variants in AD risk assessment.

Intersectionality in Alzheimer's Disease: The Role of Female Sex and Black American Race in the Development and Prevalence of Alzheimer's Disease

It is well known that vascular factors and specific social determinants of health contribute to dementia risk and that the prevalence of these risk factors differs according to race and sex. In this review, we discuss the intersection of sex and race, particularly female sex and Black American race. Women, particularly Black women, have been underrepresented in Alzheimer's disease clinical trials and research. However, in recent years, the number of women participating in clinical research has steadily increased. A greater prevalence of vascular risk factors such as hypertension and type 2 diabetes, coupled with unique social and environmental pressures, puts Black American women particularly at risk for the development of Alzheimer's disease and related dementias. Female sex hormones and the use of hormonal birth control may offer some protective benefits, but results are mixed, and studies do not consistently report the demographics of their samples. We argue that as a research community, greater efforts should be made to not only recruit this vulnerable population, but also report the demographic makeup of samples in research to better target those at greatest risk for the disease.

Identification of highly reliable risk genes for Alzheimer's disease through joint-tissue integrative analysis

Numerous genetic variants associated with Alzheimer's disease (AD) have been identified through genome-wide association studies (GWAS), but their interpretation is hindered by the strong linkage disequilibrium (LD) among the variants, making it difficult to identify the causal variants directly. To address this issue, the transcriptome-wide association study (TWAS) was employed to infer the association between gene expression and a trait at the genetic level using expression quantitative trait locus (eQTL) cohorts. In this study, we applied the TWAS theory and utilized the improved Joint-Tissue Imputation (JTI) approach and Mendelian Randomization (MR) framework (MR-JTI) to identify potential AD-associated genes. By integrating LD score, GTEx eQTL data, and GWAS summary statistic data from a large cohort using MR-JTI, a total of 415 AD-associated genes were identified. Then, 2873 differentially expressed genes from 11 AD-related datasets were used for the Fisher test of these AD-associated genes. We finally obtained 36 highly reliable AD-associated genes, including APOC1, CR1, ERBB2, and RIN3. Moreover, the GO and KEGG enrichment analysis revealed that these genes are primarily involved in antigen processing and presentation, amyloid-beta formation, tau protein binding, and response to oxidative stress. The identification of these potential AD-associated genes not only provides insights into the pathogenesis of AD but also offers biomarkers for early diagnosis of the disease.

Comprehensive genetic screening of early-onset dementia patients in an Austrian cohort-suggesting new disease-contributing genes

Early-onset dementia (EOD), with symptom onset before age 65, has a strong genetic burden. Due to genetic and clinical overlaps between different types of dementia, whole-exome sequencing (WES) has emerged as an appropriate screening method for diagnostic testing and novel gene-finding approaches. We performed WES and C9orf72 repeat testing in 60 well-defined Austrian EOD patients. Seven patients (12%) carried likely disease-causing variants in monogenic genes, PSEN1, MAPT, APP, and GRN. Five patients (8%) were APOE4 homozygote carriers. Definite and possible risk variants were detected in the genes TREM2, SORL1, ABCA7 and TBK1. In an explorative approach, we cross-checked rare gene variants in our cohort with a curated neurodegeneration candidate gene list and identified DCTN1, MAPK8IP3, LRRK2, VPS13C and BACE1 as promising candidate genes. Conclusively, 12 cases (20%) carried variants relevant to patient counseling, comparable to previously reported studies, and can thus be considered genetically resolved. Reduced penetrance, oligogenic inheritance and not yet identified high-risk genes might explain the high number of unresolved cases. To address this issue, we provide complete genetic and phenotypic information (uploaded to the European Genome-phenome Archive), enabling other researchers to cross-check variants. Thereby, we hope to increase the chance of independently finding the same gene/variant-hit in other well-defined EOD patient cohorts, thus confirming new genetic risk variants or variant combinations.

Aberrant DNA Methylation, Expression, and Occurrence of Transcript Variants of the ABC Transporter ABCA7 in Breast Cancer

The ABC transporter ABCA7 has been found to be aberrantly expressed in a variety of cancer types, including breast cancer. We searched for specific epigenetic and genetic alterations and alternative splicing variants of ABCA7 in breast cancer and investigated whether these alterations are associated with ABCA7 expression. By analyzing tumor tissues from breast cancer patients, we found CpGs at the exon 5-intron 5 boundary aberrantly methylated in a molecular subtype-specific manner. The detection of altered DNA methylation in tumor-adjacent tissues suggests epigenetic field cancerization. In breast cancer cell lines, DNA methylation levels of CpGs in promoter-exon 1, intron 1, and at the exon 5-intron 5 boundary were not correlated with ABCA7 mRNA levels. By qPCR involving intron-specific and intron-flanking primers, we identified intron-containing ABCA7 mRNA transcripts. The occurrence of intron-containing transcripts was neither molecular subtype-specific nor directly correlated with DNA methylation at the respective exon-intron boundaries. Treatment of breast cancer cell lines MCF-7, BT-474, SK-BR3, and MDA-MB-231 with doxorubicin or paclitaxel for 72 h resulted in altered ABCA7 intron levels. Shotgun proteomics revealed that an increase in intron-containing transcripts was associated with significant dysregulation of splicing factors linked to alternative splicing.

Structure and Mechanism of Human ABC Transporters

ABC transporters are essential for cellular physiology. Humans have 48 ABC genes organized into seven distinct families. Of these genes, 44 (in five distinct families) encode for membrane transporters, of which several are involved in drug resistance and disease pathways resulting from transporter dysfunction. Over the last decade, advances in structural biology have vastly expanded our mechanistic understanding of human ABC transporter function, revealing details of their molecular arrangement, regulation, and interactions, facilitated in large part by advances in cryo-EM that have rendered hitherto inaccessible targets amenable to high-resolution structural analysis. As a result, experimentally determined structures of multiple members of each of the five families of ABC transporters in humans are now available. Here we review this recent progress, highlighting the physiological relevance of human ABC transporters and mechanistic insights gleaned from their direct structure determination. We also discuss the impact and limitations of model systems and structure prediction methods in understanding human ABC transporters and discuss current challenges and future research directions.

Large multi-ethnic genetic analyses of amyloid imaging identify new genes for Alzheimer disease

Amyloid PET imaging has been crucial for detecting the accumulation of amyloid beta (Aβ) deposits in the brain and to study Alzheimer's disease (AD). We performed a genome-wide association study on the largest collection of amyloid imaging data (N = 13,409) to date, across multiple ethnicities from multicenter cohorts to identify variants associated with brain amyloidosis and AD risk. We found a strong APOE signal on chr19q.13.32 (top SNP: APOE ɛ4; rs429358; β = 0.35, SE = 0.01, P = 6.2 × 10-311, MAF = 0.19), driven by APOE ɛ4, and five additional novel associations (APOE ε2/rs7412; rs73052335/rs5117, rs1081105, rs438811, and rs4420638) independent of APOE ɛ4. APOE ɛ4 and ε2 showed race specific effect with stronger association in Non-Hispanic Whites, with the lowest association in Asians. Besides the APOE, we also identified three other genome-wide loci: ABCA7 (rs12151021/chr19p.13.3; β = 0.07, SE = 0.01, P = 9.2 × 10-09, MAF = 0.32), CR1 (rs6656401/chr1q.32.2; β = 0.1, SE = 0.02, P = 2.4 × 10-10, MAF = 0.18) and FERMT2 locus (rs117834516/chr14q.22.1; β = 0.16, SE = 0.03, P = 1.1 × 10-09, MAF = 0.06) that all colocalized with AD risk. Sex-stratified analyses identified two novel female-specific signals on chr5p.14.1 (rs529007143, β = 0.79, SE = 0.14, P = 1.4 × 10-08, MAF = 0.006, sex-interaction P = 9.8 × 10-07) and chr11p.15.2 (rs192346166, β = 0.94, SE = 0.17, P = 3.7 × 10-08, MAF = 0.004, sex-interaction P = 1.3 × 10-03). We also demonstrated that the overall genetic architecture of brain amyloidosis overlaps with that of AD, Frontotemporal Dementia, stroke, and brain structure-related complex human traits. Overall, our results have important implications when estimating the individual risk to a population level, as race and sex will needed to be taken into account. This may affect participant selection for future clinical trials and therapies.

Lipid Mediated Brain Disorders: A Perspective

The brain, one of the most resilient organs of the body is highly enriched in lipid content, suggesting the essential role of lipids in brain physiological activities. Lipids constitute an important structural part of the brain and act as a rich source of metabolic energy. Besides, lipids in their bioactive form (known as bioactive lipids) play an essential signaling and regulatory role, facilitating neurogenesis, synaptogenesis, and cell-cell communication. Brain lipid metabolism is thus a tightly regulated process. Any alteration/dysregulation of lipid metabolism greatly impact brain health and activity. Moreover, since central nervous system (CNS) is the most metabolically active system and lacks an efficient antioxidative defence system, it acts as a hub for the production of reactive oxygen species (ROS) and subsequent lipid peroxidation. These peroxidation events are reported during pathological changes such as neuronal tissue injury and inflammation. Present review is a modest attempt to gain insights into the role of dysregulated bioactive lipid levels and lipid oxidation status in the pathogenesis and progression of neurodegenerative disorders. This may open up new avenues exploiting lipids as the therapeutic targets for improving brain health, and treatment of nervous system disorders.

Expression of the primate-specific LINC00473 RNA in mouse neurons promotes excitability and CREB-regulated transcription

The LINC00473 (Lnc473) gene has previously been shown to be associated with cancer and psychiatric disorders. Its expression is elevated in several types of tumors and decreased in the brains of patients diagnosed with schizophrenia or major depression. In neurons, Lnc473 transcription is strongly responsive to synaptic activity, suggesting a role in adaptive, plasticity-related mechanisms. However, the function of Lnc473 is largely unknown. Here, using a recombinant adeno-associated viral vector, we introduced a primate-specific human Lnc473 RNA into mouse primary neurons. We show that this resulted in a transcriptomic shift comprising downregulation of epilepsy-associated genes and a rise in cAMP response element binding protein (CREB) activity, which was driven by augmented CREB-regulated transcription coactivator 1 (CRTC1) nuclear localization. Moreover, we demonstrate that ectopic Lnc473 expression increased neuronal excitability as well as network excitability. These findings suggest that primates may possess a lineage-specific activity-dependent modulator of CREB-regulated neuronal excitability.

Application of orthogonal sparse joint non-negative matrix factorization based on connectivity in Alzheimer's disease research

Based on the mining of micro- and macro-relationships of genetic variation and brain imaging data, imaging genetics has been widely applied in the early diagnosis of Alzheimer's disease (AD). However, effective integration of prior knowledge remains a barrier to determining the biological mechanism of AD. This paper proposes a new connectivity-based orthogonal sparse joint non-negative matrix factorization (OSJNMF-C) method based on integrating the structural magnetic resonance image, single nucleotide polymorphism and gene expression data of AD patients; the correlation information, sparseness, orthogonal constraint and brain connectivity information between the brain image data and genetic data are designed as constraints in the proposed algorithm, which efficiently improved the accuracy and convergence through multiple iterative experiments. Compared with the competitive algorithm, OSJNMF-C has significantly smaller related errors and objective function values than the competitive algorithm, showing its good anti-noise performance. From the biological point of view, we have identified some biomarkers and statistically significant relationship pairs of AD/mild cognitive impairment (MCI), such as rs75277622 and BCL7A, which may affect the function and structure of multiple brain regions. These findings will promote the prediction of AD/MCI.

Gene Expression Profiling as a Novel Diagnostic Tool for Neurodegenerative Disorders

There is a lack of effective diagnostic biomarkers for neurodegenerative disorders (NDDs). Here, we established gene expression profiles for diagnosing Alzheimer’s disease (AD), Parkinson’s disease (PD), and vascular (VaD)/mixed dementia. Patients with AD had decreased APOE, PSEN1, and ABCA7 mRNA expression. Subjects with VaD/mixed dementia had 98% higher PICALM mRNA levels, but 75% lower ABCA7 mRNA expression than healthy individuals. Patients with PD and PD-related disorders showed increased SNCA mRNA levels. There were no differences in mRNA expression for OPRK1, NTRK2, and LRRK2 between healthy subjects and NDD patients. APOE mRNA expression had high diagnostic accuracy for AD, and moderate accuracy for PD and VaD/mixed dementia. PSEN1 mRNA expression showed promising accuracy for AD. PICALM mRNA expression was less accurate as a biomarker for AD. ABCA7 and SNCA mRNA expression showed high-to-excellent diagnostic accuracy for AD and PD, and moderate-to-high accuracy for VaD/mixed dementia. The APOE E4 allele reduced APOE expression in patients with different APOE genotypes. There was no association between PSEN1, PICALM, ABCA7, and SNCA gene polymorphisms and expression. Our study suggests that gene expression analysis has diagnostic value for NDDs and provides a liquid biopsy alternative to current diagnostic methods.

Controlling the Impact of Helicobacter pylori-Related Hyperhomocysteinemia on Neurodegeneration

Helicobacter pylori infection consists a high global burden affecting more than 50% of the world’s population. It is implicated, beyond substantiated local gastric pathologies, i.e., peptic ulcers and gastric cancer, in the pathophysiology of several neurodegenerative disorders, mainly by inducing hyperhomocysteinemia-related brain cortical thinning (BCT). BCT has been advocated as a possible biomarker associated with neurodegenerative central nervous system disorders such as Alzheimer’s disease, Parkinson’s disease, multiple sclerosis, and/or glaucoma, termed as “ocular Alzheimer’s disease”. According to the infection hypothesis in relation to neurodegeneration, Helicobacter pylori as non-commensal gut microbiome has been advocated as trigger and/or mediator of neurodegenerative diseases, such as the development of Alzheimer’s disease. Among others, Helicobacter pylori-related inflammatory mediators, defensins, autophagy, vitamin D, dietary factors, role of probiotics, and some pathogenetic considerations including relevant involved genes are discussed within this opinion article. In conclusion, by controlling the impact of Helicobacter pylori-related hyperhomocysteinemia on neurodegenerative disorders might offer benefits, and additional research is warranted to clarify this crucial topic currently representing a major worldwide burden.

Lipid metabolism and Alzheimer's disease: clinical evidence, mechanistic link and therapeutic promise

Alzheimer's disease (AD) is an age-associated neurodegenerative disorder with multifactorial etiology, intersecting genetic and environmental risk factors, and a lack of disease-modifying therapeutics. While the abnormal accumulation of lipids was described in the very first report of AD neuropathology, it was not until recent decades that lipid dyshomeostasis became a focus of AD research. Clinically, lipidomic and metabolomic studies have consistently shown alterations in the levels of various lipid classes emerging in early stages of AD brains. Mechanistically, decades of discovery research have revealed multifaceted interactions between lipid metabolism and key AD pathogenic mechanisms including amyloidogenesis, bioenergetic deficit, oxidative stress, neuroinflammation, and myelin degeneration. In the present review, converging evidence defining lipid dyshomeostasis in AD is summarized, followed by discussions on mechanisms by which lipid metabolism contributes to pathogenesis and modifies disease risk. Furthermore, lipid-targeting therapeutic strategies, and the modification of their efficacy by disease stage, ApoE status, and metabolic and vascular profiles, are reviewed.

Co-occurring pathogenic variants in 6q27 associated with dementia spectrum disorders in a Peruvian family

Evidence suggests that there may be racial differences in risk factors associated with the development of Alzheimer's disease and related dementia (ADRD). We used whole-genome sequencing analysis and identified a novel combination of three pathogenic variants in the heterozygous state (UNC93A: rs7739897 and WDR27: rs61740334; rs3800544) in a Peruvian family with a strong clinical history of ADRD. Notably, the combination of these variants was present in two generations of affected individuals but absent in healthy members of the family. In silico and in vitro studies have provided insights into the pathogenicity of these variants. These studies predict that the loss of function of the mutant UNC93A and WDR27 proteins induced dramatic changes in the global transcriptomic signature of brain cells, including neurons, astrocytes, and especially pericytes and vascular smooth muscle cells, indicating that the combination of these three variants may affect the neurovascular unit. In addition, known key molecular pathways associated with dementia spectrum disorders were enriched in brain cells with low levels of UNC93A and WDR27. Our findings have thus identified a genetic risk factor for familial dementia in a Peruvian family with an Amerindian ancestral background.

Alzheimer's Disease: An Updated Overview of Its Genetics

Alzheimer's disease (AD) is the most common neurodegenerative disease in the world. It is classified as familial and sporadic. The dominant familial or autosomal presentation represents 1-5% of the total number of cases. It is categorized as early onset (EOAD; <65 years of age) and presents genetic mutations in presenilin 1 (PSEN1), presenilin 2 (PSEN2), or the Amyloid precursor protein (APP). Sporadic AD represents 95% of the cases and is categorized as late-onset (LOAD), occurring in patients older than 65 years of age. Several risk factors have been identified in sporadic AD; aging is the main one. Nonetheless, multiple genes have been associated with the different neuropathological events involved in LOAD, such as the pathological processing of Amyloid beta (Aβ) peptide and Tau protein, as well as synaptic and mitochondrial dysfunctions, neurovascular alterations, oxidative stress, and neuroinflammation, among others. Interestingly, using genome-wide association study (GWAS) technology, many polymorphisms associated with LOAD have been identified. This review aims to analyze the new genetic findings that are closely related to the pathophysiology of AD. Likewise, it analyzes the multiple mutations identified to date through GWAS that are associated with a high or low risk of developing this neurodegeneration. Understanding genetic variability will allow for the identification of early biomarkers and opportune therapeutic targets for AD.

Cryo-EM structures of human ABCA7 provide insights into its phospholipid translocation mechanisms

Phospholipid extrusion by ABC subfamily A (ABCA) exporters is central to cellular physiology, although the specifics of the underlying substrate interactions and transport mechanisms remain poorly resolved at the molecular level. Here we report cryo-EM structures of lipid-embedded human ABCA7 in an open state and in a nucleotide-bound, closed state at resolutions between 3.6 and 4.0 Å. The former reveals an ordered patch of bilayer lipids traversing the transmembrane domain (TMD), while the latter reveals a lipid-free, closed TMD with a small extracellular opening. These structures offer a structural framework for both substrate entry and exit from the ABCA7 TMD and highlight conserved rigid-body motions that underlie the associated conformational transitions. Combined with functional analysis and molecular dynamics (MD) simulations, our data also shed light on lipid partitioning into the ABCA7 TMD and localized membrane perturbations that underlie ABCA7 function and have broader implications for other ABCA family transporters.

PSEN2 and ABCA7 variants causing early-onset preclinical pathological changes in Alzheimer's disease: a case report and literature review

BACKGROUND

Alzheimer's disease (AD) is a debilitating and highly heritable neurodegenerative disease. Early-onset AD (EOAD) was defined as AD occurring before age 65. Although it has a high genetic risk, EOAD due to PSEN2 variation is very rare. ABCA7 is an important risk gene for AD. Previously reported cases mainly carried variations in a single pathogenic or risk gene. METHODS AND RESULTS: In this study, we report a 35-year-old female carrying variants in both the PSEN2 gene (c.640G > T p.V214L) and ABCA7 gene (c.2848G > A p.V950M). Four previously reported cases carried PSEN2 V214L, and no reported cases carried ABCA7 V950M. She had a history of migraine, patent foramen ovale, spontaneous subarachnoid hemorrhage without aneurysm, and multiple cerebral microhemorrhages. Her MMSE score was 24/30, and her MoCA score was 22/30. The concentration of Aβ42 and the ratio of Aβ42 to Aβ40 in cerebral spinal fluid were obviously decreased. Published variants of PSEN2 and ABCA7 in PubMed were reviewed, and the patients' characteristics were summarized and compared to provide information for the clinical diagnosis of AD.

CONCLUSIONS

It is necessary to conduct genetic screening in cases with atypical manifestations.

Discovery of an evodiamine derivative for PI3K/AKT/GSK3β pathway activation and AD pathology improvement in mouse models

Alzheimer's disease (AD) is a neurodegenerative disease characterized by progressive neurodegeneration and cognitive decline. Evodiamine, a main component in Chinese medicine, was found to improve cognitive impairment in AD model mice based on several intensive studies. However, evodiamine has high cytotoxicity and poor bioactivity. In this study, several evodiamine derivatives were synthesized via heterocyclic substitution and amide introduction and screened for cytotoxicity and antioxidant capacity. Under the same concentrations, compound 4c was found to exhibit lower cytotoxicity and higher activity against H₂O₂ and amyloid β oligomers (AβOs) than evodiamine in vitro and significantly improve the working memory and spatial memory of 3 x Tg and APP/PS1 AD mice. Subsequent RNA sequencing and pathway enrichment analysis showed that 4c affected AD-related genes and the AMPK and insulin signaling pathways. Furthermore, we confirmed that 4c recovered PI3K/AKT/GSK3β/Tau dysfunction in vivo and in vitro. In conclusion, 4c represents a potential lead compound for AD therapy based on the recovery of PI3K/AKT/GSK3β pathway dysfunction.