Role of genes and environments for explaining Alzheimer disease

Ginkgo biloba extract mitigates the neurotoxicity of AlCl3 in alzheimer rat's model: role of apolipoprotein E4 and clusterin genes in stimulating ROS generation and apoptosis

PURPOSE

Alzheimer's disease (AD) appears as a result of an increase in the accumulation of amyloid beta peptide (Aβ) and a decrease in neurotransmitters (acetylcholine) within the brain cells which may be due to increase in acetylcholinesterase (AchE) activity and change in expression of Apolipoprotein E4 (ApoE4) and Clusterin (Clu) genes. The aim of the present study was using natural products such as Ginkgo biloba (G. biloba) extract that has the potential to reduce Aβ formation and increase AchE inhibition with its ability to save neuronal DNA from damage.

METHODS

Sixty male aged rats were divided into six experimental groups exposed to AlCl3 to induce AD model and were treated with G. biloba extract. Collected brain tissues were used to assess the apoptosis rate, reactive oxygen species (ROS) generation, AchE inhibitory activity, expression alteration in ApoE4 and Clu genes, DNA fragmentations and gutathione peroxidase (GPx) activity.Results: The results exhibited that rats exposed to AlCl3 increased significantly rate of apoptosis, ROS formation, DNA fragmentation, up-regulation of ApoE4 and Clu genes as well as decrease of AchE inhibitory activity and GPx activity compared with those in control rats. However, treatment of AlCl3-rats with G. biloba extract improved the above neurotoxicity results induced by AlCl3 exposure.

CONCLUSIONS

It is therefore likely that G. biloba extract's protective properties against AD are due to its ability to activate the response against oxidative stress.

Bayesian genome-wide TWAS with reference transcriptomic data of brain and blood tissues identified 141 risk genes for Alzheimer's disease dementia

BACKGROUND

Transcriptome-wide association study (TWAS) is an influential tool for identifying genes associated with complex diseases whose genetic effects are likely mediated through transcriptome. TWAS utilizes reference genetic and transcriptomic data to estimate effect sizes of genetic variants on gene expression (i.e., effect sizes of a broad sense of expression quantitative trait loci, eQTL). These estimated effect sizes are employed as variant weights in gene-based association tests, facilitating the mapping of risk genes with genome-wide association study (GWAS) data. However, most existing TWAS of Alzheimer's disease (AD) dementia are limited to studying only cis-eQTL proximal to the test gene. To overcome this limitation, we applied the Bayesian Genome-wide TWAS (BGW-TWAS) method to leveraging both cis- and trans- eQTL of brain and blood tissues, in order to enhance mapping risk genes for AD dementia.

METHODS

We first applied BGW-TWAS to the Genotype-Tissue Expression (GTEx) V8 dataset to estimate cis- and trans- eQTL effect sizes of the prefrontal cortex, cortex, and whole blood tissues. Estimated eQTL effect sizes were integrated with the summary data of the most recent GWAS of AD dementia to obtain BGW-TWAS (i.e., gene-based association test) p-values of AD dementia per gene per tissue type. Then we used the aggregated Cauchy association test to combine TWAS p-values across three tissues to obtain omnibus TWAS p-values per gene.

RESULTS

We identified 85 significant genes in prefrontal cortex, 82 in cortex, and 76 in whole blood that were significantly associated with AD dementia. By combining BGW-TWAS p-values across these three tissues, we obtained 141 significant risk genes including 34 genes primarily due to trans-eQTL and 35 mapped risk genes in GWAS Catalog. With these 141 significant risk genes, we detected functional clusters comprised of both known mapped GWAS risk genes of AD in GWAS Catalog and our identified TWAS risk genes by protein-protein interaction network analysis, as well as several enriched phenotypes related to AD.

CONCLUSION

We applied BGW-TWAS and aggregated Cauchy test methods to integrate both cis- and trans- eQTL data of brain and blood tissues with GWAS summary data, identifying 141 TWAS risk genes of AD dementia. These identified risk genes provide novel insights into the underlying biological mechanisms of AD dementia and potential gene targets for therapeutics development.

Detecting the effect of genetic diversity on brain composition in an Alzheimer's disease mouse model

Alzheimer's disease (AD) is broadly characterized by neurodegeneration, pathology accumulation, and cognitive decline. There is considerable variation in the progression of clinical symptoms and pathology in humans, highlighting the importance of genetic diversity in the study of AD. To address this, we analyze cell composition and amyloid-beta deposition of 6- and 14-month-old AD-BXD mouse brains. We utilize the analytical QUINT workflow- a suite of software designed to support atlas-based quantification, which we expand to deliver a highly effective method for registering and quantifying cell and pathology changes in diverse disease models. In applying the expanded QUINT workflow, we quantify near-global age-related increases in microglia, astrocytes, and amyloid-beta, and we identify strain-specific regional variation in neuron load. To understand how individual differences in cell composition affect the interpretation of bulk gene expression in AD, we combine hippocampal immunohistochemistry analyses with bulk RNA-sequencing data. This approach allows us to categorize genes whose expression changes in response to AD in a cell and/or pathology load-dependent manner. Ultimately, our study demonstrates the use of the QUINT workflow to standardize the quantification of immunohistochemistry data in diverse mice, - providing valuable insights into regional variation in cellular load and amyloid deposition in the AD-BXD model.

Supervised latent factor modeling isolates cell-type-specific transcriptomic modules that underlie Alzheimer's disease progression

Late onset Alzheimer's disease (AD) is a progressive neurodegenerative disease, with brain changes beginning years before symptoms surface. AD is characterized by neuronal loss, the classic feature of the disease that underlies brain atrophy. However, GWAS reports and recent single-nucleus RNA sequencing (snRNA-seq) efforts have highlighted that glial cells, particularly microglia, claim a central role in AD pathophysiology. Here, we tailor pattern-learning algorithms to explore distinct gene programs by integrating the entire transcriptome, yielding distributed AD-predictive modules within the brain's major cell-types. We show that these learned modules are biologically meaningful through the identification of new and relevant enriched signaling cascades. The predictive nature of our modules, especially in microglia, allows us to infer each subject's progression along a disease pseudo-trajectory, confirmed by post-mortem pathological brain tissue markers. Additionally, we quantify the interplay between pairs of cell-type modules in the AD brain, and localized known AD risk genes to enriched module gene programs. Our collective findings advocate for a transition from cell-type-specificity to gene modules specificity to unlock the potential of unique gene programs, recasting the roles of recently reported genome-wide AD risk loci.

Role of Epigenetic Modulation in Neurodegenerative Diseases: Implications of Phytochemical Interventions

Epigenetics defines changes in cell function without involving alterations in DNA sequence. Neuroepigenetics bridges neuroscience and epigenetics by regulating gene expression in the nervous system and its impact on brain function. With the increase in research in recent years, it was observed that alterations in the gene expression did not always originate from changes in the genetic sequence, which has led to understanding the role of epigenetics in neurodegenerative diseases (NDDs) including Alzheimer's disease (AD) and Parkinson's disease (PD). Epigenetic alterations contribute to the aberrant expression of genes involved in neuroinflammation, protein aggregation, and neuronal death. Natural phytochemicals have shown promise as potential therapeutic agents against NDDs because of their antioxidant, anti-inflammatory, and neuroprotective effects in cellular and animal models. For instance, resveratrol (grapes), curcumin (turmeric), and epigallocatechin gallate (EGCG; green tea) exhibit neuroprotective effects through their influence on DNA methylation patterns, histone acetylation, and non-coding RNA expression profiles. Phytochemicals also aid in slowing disease progression, preserving neuronal function, and enhancing cognitive and motor abilities. The present review focuses on various epigenetic modifications involved in the pathology of NDDs, including AD and PD, gene expression regulation related to epigenetic alterations, and the role of specific polyphenols in influencing epigenetic modifications in AD and PD.

Alzheimer's diseases in America, Europe, and Asian regions: a global genetic variation

Background

Alzheimer's disease (AD) is one of the multifaceted neurodegenerative diseases influenced by many genetic and epigenetic factors. Genetic factors are merely not responsible for developing AD in the whole population. The studies of genetic variants can provide significant insights into the molecular basis of Alzheimer's disease. Our research aimed to show how genetic variants interact with environmental influences in different parts of the world.

Methodology

We searched PubMed and Google Scholar for articles exploring the relationship between genetic variations and global regions such as America, Europe, and Asia. We aimed to identify common genetic variations susceptible to AD and have no significant heterogeneity. To achieve this, we analyzed 35 single-nucleotide polymorphisms (SNPs) from 17 genes (ABCA7, APOE, BIN1, CD2AP, CD33, CLU, CR1, EPHA1, TOMM40, MS4A6A, ARID5B, SORL1, APOC1, MTHFD1L, BDNF, TFAM, and PICALM) from different regions based on previous genomic studies of AD. It has been reported that rs3865444, CD33, is the most common polymorphism in the American and European populations. From TOMM40 and APOE rs2075650, rs429358, and rs6656401, CR1 is the common investigational polymorphism in the Asian population.

Conclusion

The results of all the research conducted on AD have consistently shown a correlation between genetic variations and the incidence of AD in the populations of each region. This review is expected to be of immense value in future genetic research and precision medicine on AD, as it provides a comprehensive understanding of the genetic factors contributing to the development of this debilitating disease.

Extracellular vesicles as nanotheranostic platforms for targeted neurological disorder interventions

Central Nervous System (CNS) disorders represent a profound public health challenge that affects millions of people around the world. Diseases such as Alzheimer's disease (AD), Parkinson's disease (PD), and traumatic brain injury (TBI) exemplify the complexities and diversities that complicate their early detection and the development of effective treatments. Amid these challenges, the emergence of nanotechnology and extracellular vesicles (EVs) signals a new dawn for treating and diagnosing CNS ailments. EVs are cellularly derived lipid bilayer nanosized particles that are pivotal in intercellular communication within the CNS and have the potential to revolutionize targeted therapeutic delivery and the identification of novel biomarkers. Integrating EVs with nanotechnology amplifies their diagnostic and therapeutic capabilities, opening new avenues for managing CNS diseases. This review focuses on examining the fascinating interplay between EVs and nanotechnology in CNS theranostics. Through highlighting the remarkable advancements and unique methodologies, we aim to offer valuable perspectives on how these approaches can bring about a revolutionary change in disease management. The objective is to harness the distinctive attributes of EVs and nanotechnology to forge personalized, efficient interventions for CNS disorders, thereby providing a beacon of hope for affected individuals. In short, the confluence of EVs and nanotechnology heralds a promising frontier for targeted and impactful treatments against CNS diseases, which continue to pose significant public health challenges. By focusing on personalized and powerful diagnostic and therapeutic methods, we might improve the quality of patients.

Prioritizing disease-related rare variants by integrating gene expression data

Rare variants, comprising a vast majority of human genetic variations, are likely to have more deleterious impact on human diseases compared to common variants. Here we present carrier statistic, a statistical framework to prioritize disease-related rare variants by integrating gene expression data. By quantifying the impact of rare variants on gene expression, carrier statistic can prioritize those rare variants that have large functional consequence in the diseased patients. Through simulation studies and analyzing real multi-omics dataset, we demonstrated that carrier statistic is applicable in studies with limited sample size (a few hundreds) and achieves substantially higher sensitivity than existing rare variants association methods. Application to Alzheimer's disease reveals 16 rare variants within 15 genes with extreme carrier statistics. We also found strong excess of rare variants among the top prioritized genes in diseased patients compared to that in healthy individuals. The carrier statistic method can be applied to various rare variant types and is adaptable to other omics data modalities, offering a powerful tool for investigating the molecular mechanisms underlying complex diseases.

The broken Alzheimer's disease genome

The complex pathobiology of late-onset Alzheimer's disease (AD) poses significant challenges to therapeutic and preventative interventions. Despite these difficulties, genomics and related disciplines are allowing fundamental mechanistic insights to emerge with clarity, particularly with the introduction of high-resolution sequencing technologies. After all, the disrupted processes at the interface between DNA and gene expression, which we call the broken AD genome, offer detailed quantitative evidence unrestrained by preconceived notions about the disease. In addition to highlighting biological pathways beyond the classical pathology hallmarks, these advances have revitalized drug discovery efforts and are driving improvements in clinical tools. We review genetic, epigenomic, and gene expression findings related to AD pathogenesis and explore how their integration enables a better understanding of the multicellular imbalances contributing to this heterogeneous condition. The frontiers opening on the back of these research milestones promise a future of AD care that is both more personalized and predictive.

Unraveling the genetic architecture of blood unfolded p-53 among non-demented elderlies: novel candidate genes for early Alzheimer's disease

BACKGROUND

Alzheimer's disease (AD) is a heritable neurodegenerative disease whose long asymptomatic phase makes the early diagnosis of it pivotal. Blood U-p53 has recently emerged as a superior predictive biomarker for AD in the early stages. We hypothesized that genetic variants associated with blood U-p53 could reveal novel loci and pathways involved in the early stages of AD.

RESULTS

We performed a blood U-p53 Genome-wide association study (GWAS) on 484 healthy and mild cognitively impaired subjects from the ADNI cohort using 612,843 Single nucleotide polymorphisms (SNPs). We performed a pathway analysis and prioritized candidate genes using an AD single-cell gene program. We fine-mapped the intergenic SNPs by leveraging a cell-type-specific enhancer-to-gene linking strategy using a brain single-cell multimodal dataset. We validated the candidate genes in an independent brain single-cell RNA-seq and the ADNI blood transcriptome datasets. The rs279686 between AASS and FEZF1 genes was the most significant SNP (p-value = 4.82 × 10-7). Suggestive pathways were related to the immune and nervous systems. Twenty-three candidate genes were prioritized at 27 suggestive loci. Fine-mapping of 5 intergenic loci yielded nine cell-specific candidate genes. Finally, 15 genes were validated in the independent single-cell RNA-seq dataset, and five were validated in the ADNI blood transcriptome dataset.

CONCLUSIONS

We underlined the importance of performing a GWAS on an early-stage biomarker of AD and leveraging functional omics datasets for pinpointing causal genes in AD. Our study prioritized nine genes (SORCS1, KIF5C, TMEFF2, TMEM63C, HLA-E, ATAT1, TUBB, ARID1B, and RUNX1) strongly implicated in the early stages of AD.

Exploring the genetic heterogeneity of Alzheimer's disease: Evidence for genetic subtypes

Background

Alzheimer's disease (AD) exhibits considerable phenotypic heterogeneity, suggesting the potential existence of subtypes. AD is under substantial genetic influence, thus identifying systematic variation in genetic risk may provide insights into disease origins.

Objective

We investigated genetic heterogeneity in AD risk through a multi-step analysis.

Methods

We performed principal component analysis (PCA) on AD-associated variants in the UK Biobank (AD cases=2,739, controls=5,478) to assess structured genetic heterogeneity. Subsequently, a biclustering algorithm searched for distinct disease-specific genetic signatures among subsets of cases. Replication tests were conducted using the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset (AD cases=500, controls=470). We categorized a separate set of ADNI individuals with mild cognitive impairment (MCI; n=399) into genetic subtypes and examined cognitive, amyloid, and tau trajectories.

Results

PCA revealed three distinct clusters ("constellations") driven primarily by different correlation patterns in a region of strong LD surrounding the MAPT locus. Constellations contained a mixture of cases and controls, reflecting disease-relevant but not disease-specific structure. We found two disease-specific biclusters among AD cases. Pathway analysis linked bicluster-associated variants to neuron morphogenesis and outgrowth. Disease-relevant and disease-specific structure replicated in ADNI, and bicluster 2 exhibited increased CSF p-tau and cognitive decline over time.

Conclusions

This study unveils a hierarchical structure of AD genetic risk. Disease-relevant constellations may represent haplotype structure that does not increase risk directly but may alter the relative importance of other genetic risk factors. Biclusters may represent distinct AD genetic subtypes. This structure is replicable and relates to differential pathological accumulation and cognitive decline over time.

Lessons from genetic studies in Alzheimer disease

Research on Alzheimer disease (AD) genetics has provided critical advances to the knowledge of AD pathophysiological mechanisms. The etiology of AD can be divided into monogenic (autosomal dominant inheritance) and complex (multifactorial determinism). In monogenic AD, recent advances mainly concern mutation-associated mechanisms, presymptomatic clinical studies, and the search for modifiers of ages of onset that are still ongoing. In complex AD, genetic factors can be further categorized into three classes: (i) the APOE-ɛ4 and ɛ2 common alleles that represent a category by themselves as they are both common and with a strong impact on AD risk; (ii) common variants with a modest effect, identified in genome-wide association studies (GWAS); and (iii) rare variants with a moderate-to-strong effect, identified in case-control sequencing studies. Regarding APOE, odds ratios, available in multiple ethnicities, can now be converted into penetrance curves, although such curves remain to be performed in diverse ethnicities. In addition, advances in the understanding of mechanisms have been recently reported and rare APOE variants add to the complexity. In the GWAS category, novel loci have been discovered thanks to larger studies, doubling the number of hits as compared to the previous reference meta-analysis. However, such modest risk factors cannot be used in the clinic, neither individually, nor in genetic risk scores. In the category of rare variants, two novel genes, ABCA1 and ATP8B4 now add to the three main ones, TREM2, SORL1, and ABCA7. The study of such rare variants suggests oligogenic inheritance in some families, as also suggested by digenic penetrance curves for SORL1 loss-of-function variants with APOE-ɛ4. Cumulate frequencies of definite (so-called) rare risk factors are 2.3% to 3.6% (depending on thresholds on odds ratios) in control databases and many more remain to be classified and identified, showing how important these risk factors may be as part of the complex determinism of AD. A better understanding of these rare risk factors and their combined effects on each other, with common variants, and with environmental factors, should allow for a prediction of AD risk and, eventually, preventive medicine. Taken together, most genetic determinants of AD, in monogenic and in complex forms, point toward the aggregation of Aβ as a pivotal triggering factor, such that targeting it may be efficient as prevention in at-risk individuals. The role of neuroinflammation, microglia, and Tau pathology modulation are important sources of research for disease modification.

Assessment of Mendelian and risk-factor genes in Alzheimer disease: A prospective nationwide clinical utility study and recommendations for genetic screening

PURPOSE

To assess the likely pathogenic/pathogenic (LP/P) variants rates in Mendelian dementia genes and the moderate-to-strong risk factors rates in patients with Alzheimer disease (AD).

METHODS

We included 700 patients in a prospective study and performed exome sequencing. A panel of 28 Mendelian and 6 risk-factor genes was interpreted and returned to patients. We built a framework for risk variant interpretation and risk gradation and assessed the detection rates among early-onset AD (EOAD, age of onset (AOO) ≤65 years, n = 608) depending on AOO and pedigree structure and late-onset AD (66 < AOO < 75, n = 92).

RESULTS

Twenty-one patients carried a LP/P variant in a Mendelian gene (all with EOAD, 3.4%), 20 of 21 affected APP, PSEN1, or PSEN2. LP/P variant detection rates in EOAD ranged from 1.7% to 11.6% based on AOO and pedigree structure. Risk factors were found in 69.5% of the remaining 679 patients, including 83 (12.2%) being heterozygotes for rare risk variants, in decreasing order of frequency, in TREM2, ABCA7, ATP8B4, SORL1, and ABCA1, including 5 heterozygotes for multiple rare risk variants, suggesting non-monogenic inheritance, even in some autosomal-dominant-like pedigrees.

CONCLUSION

We suggest that genetic screening should be proposed to all EOAD patients and should no longer be prioritized based on pedigree structure.

The ABC's of Alzheimer risk gene ABCA7

Alzheimer's disease (AD) is a growing problem worldwide. Since ABCA7's identification as a risk gene, it has been extensively researched for its role in the disease. We review its recently characterized structure and what the mechanistic insights teach us about its function. We furthermore provide an overview of identified ABCA7 mutations, their presence in different ancestries and protein domains and how they might cause AD. For ABCA7 PTC variants and a VNTR expansion, haploinsufficiency is proposed as the most likely mode-of-action, although splice events could further influence disease risk. Overall, the need to better understand expression of canonical ABCA7 and its isoforms in disease is indicated. Finally, ABCA7's potential functions in lipid metabolism, phagocytosis, amyloid deposition, and the interplay between these three, is described. To conclude, in this review, we provide a comprehensive overview and discussion about the current knowledge on ABCA7 in AD, and what research questions remain. HIGHLIGHTS: Alzheimer's risk-increasing variants in ABCA7 can be found in up to 7% of AD patients. We review the recently characterized protein structure of ABCA7. We present latest insights in genetics, expression patterns, and functions of ABCA7.

Association of whole-person eigen-polygenic risk scores with Alzheimer's disease

Late-Onset Alzheimer's Disease (LOAD) is a heterogeneous neurodegenerative disorder with complex etiology and high heritability. Its multifactorial risk profile and large portions of unexplained heritability suggest the involvement of yet unidentified genetic risk factors. Here we describe the "whole person" genetic risk landscape of polygenic risk scores for 2218 traits in 2044 elderly individuals and test if novel eigen-PRSs derived from clustered subnetworks of single-trait PRSs can improve the prediction of LOAD diagnosis, rates of cognitive decline, and canonical LOAD neuropathology. Network analyses revealed distinct clusters of PRSs with clinical and biological interpretability. Novel eigen-PRSs (ePRS) from these clusters significantly improved LOAD-related phenotypes prediction over current state-of-the-art LOAD PRS models. Notably, an ePRS representing clusters of traits related to cholesterol levels was able to improve variance explained in a model of the brain-wide beta-amyloid burden by 1.7% (likelihood ratio test P = 9.02 × 10-7). All associations of ePRS with LOAD phenotypes were eliminated by the removal of APOE-proximal loci. However, our association analysis identified modules characterized by PRSs of high cholesterol and LOAD. We believe this is due to the influence of the APOE region from both PRSs. We found significantly higher mean SNP effects for LOAD in the intersecting APOE region SNPs. Combining genetic risk factors for vascular traits and dementia could improve current single-trait PRS models of LOAD, enhancing the use of PRS in risk stratification. Our results are catalogued for the scientific community, to aid in generating new hypotheses based on our maps of clustered PRSs and associations with LOAD-related phenotypes.

Induced Pluripotent Stem Cells and Organoids in Advancing Neuropathology Research and Therapies

This review delves into the groundbreaking impact of induced pluripotent stem cells (iPSCs) and three-dimensional organoid models in propelling forward neuropathology research. With a focus on neurodegenerative diseases, neuromotor disorders, and related conditions, iPSCs provide a platform for personalized disease modeling, holding significant potential for regenerative therapy and drug discovery. The adaptability of iPSCs, along with associated methodologies, enables the generation of various types of neural cell differentiations and their integration into three-dimensional organoid models, effectively replicating complex tissue structures in vitro. Key advancements in organoid and iPSC generation protocols, alongside the careful selection of donor cell types, are emphasized as critical steps in harnessing these technologies to mitigate tumorigenic risks and other hurdles. Encouragingly, iPSCs show promising outcomes in regenerative therapies, as evidenced by their successful application in animal models.

Epigenetic modifications of DNA and RNA in Alzheimer's disease

Alzheimer's disease (AD) is a complex neurodegenerative disorder and the most common form of dementia. There are two main types of AD: familial and sporadic. Familial AD is linked to mutations in amyloid precursor protein (APP), presenilin-1 (PSEN1), and presenilin-2 (PSEN2). On the other hand, sporadic AD is the more common form of the disease and has genetic, epigenetic, and environmental components that influence disease onset and progression. Investigating the epigenetic mechanisms associated with AD is essential for increasing understanding of pathology and identifying biomarkers for diagnosis and treatment. Chemical covalent modifications on DNA and RNA can epigenetically regulate gene expression at transcriptional and post-transcriptional levels and play protective or pathological roles in AD and other neurodegenerative diseases.

Brain and Blood Transcriptome-Wide Association Studies Identify Five Novel Genes Associated with Alzheimer's Disease

INTRODUCTION

Transcriptome-wide Association Studies (TWAS) extend genome-wide association studies (GWAS) by integrating genetically-regulated gene expression models. We performed the most powerful AD-TWAS to date, using summary statistics from cis -eQTL meta-analyses and the largest clinically-adjudicated Alzheimer's Disease (AD) GWAS.

METHODS

We implemented the OTTERS TWAS pipeline, leveraging cis -eQTL data from cortical brain tissue (MetaBrain; N=2,683) and blood (eQTLGen; N=31,684) to predict gene expression, then applied these models to AD-GWAS data (Cases=21,982; Controls=44,944).

RESULTS

We identified and validated five novel gene associations in cortical brain tissue ( PRKAG1 , C3orf62 , LYSMD4 , ZNF439 , SLC11A2 ) and six genes proximal to known AD-related GWAS loci (Blood: MYBPC3 ; Brain: MTCH2 , CYB561 , MADD , PSMA5 , ANXA11 ). Further, using causal eQTL fine-mapping, we generated sparse models that retained the strength of the AD-TWAS association for MTCH2 , MADD , ZNF439 , CYB561 , and MYBPC3 .

DISCUSSION

Our comprehensive AD-TWAS discovered new gene associations and provided insights into the functional relevance of previously associated variants.

Cognitively healthy centenarians are genetically protected against Alzheimer's disease

BACKGROUND

Alzheimer's disease (AD) prevalence increases with age, yet a small fraction of the population reaches ages > 100 years without cognitive decline. We studied the genetic factors associated with such resilience against AD.

METHODS

Genome-wide association studies identified 86 single nucleotide polymorphisms (SNPs) associated with AD risk. We estimated SNP frequency in 2281 AD cases, 3165 age-matched controls, and 346 cognitively healthy centenarians. We calculated a polygenic risk score (PRS) for each individual and investigated the functional properties of SNPs enriched/depleted in centenarians.

RESULTS

Cognitively healthy centenarians were enriched with the protective alleles of the SNPs associated with AD risk. The protective effect concentrated on the alleles in/near ANKH, GRN, TMEM106B, SORT1, PLCG2, RIN3, and APOE genes. This translated to >5-fold lower PRS in centenarians compared to AD cases (P = 7.69 × 10-71), and 2-fold lower compared to age-matched controls (P = 5.83 × 10-17).

DISCUSSION

Maintaining cognitive health until extreme ages requires complex genetic protection against AD, which concentrates on the genes associated with the endolysosomal and immune systems.

HIGHLIGHTS

Cognitively healthy cent enarians are enriched with the protective alleles of genetic variants associated with Alzheimer's disease (AD). The protective effect is concentrated on variants involved in the immune and endolysosomal systems. Combining variants into a polygenic risk score (PRS) translated to > 5-fold lower PRS in centenarians compared to AD cases, and ≈ 2-fold lower compared to middle-aged healthy controls.

Branched-chain amino acids and the risks of dementia, Alzheimer's disease, and Parkinson's disease

Background

We aimed to examine the association between blood levels of Branched-chain amino acids (BCAAs) - specifically isoleucine, leucine, and valine - and the susceptibility to three neurodegenerative disorders: dementia, Alzheimer's disease (AD), and Parkinson's disease (PD).

Methods

Based on data from the UK Biobank, a Cox proportional hazard regression model and a dose-response relationship were used to analyze the association between BCAAs and the risks of dementia, AD, and PD. We also generated a healthy lifestyle score and a polygenic risk score. Besides, we conducted a sensitivity analysis to ensure the robustness of our findings.

Results

After adjusting for multiple covariates, blood concentrations of isoleucine, leucine, and valine were significantly associated with a reduced risk of dementia and AD. This association remained robust even in sensitivity analyses. Similarly, higher levels of isoleucine and leucine in the blood were found to be associated with an increased risk of PD, but this positive correlation could potentially be explained by the presence of covariates. Further analysis using a dose-response approach revealed that a blood leucine concentration of 2.14 mmol/L was associated with the lowest risk of dementia.

Conclusion

BCAAs have the potential to serve as a biomarker for dementia and AD. However, the specific mechanism through which BCAAs are linked to the development of dementia, AD, and PD remains unclear and necessitates additional investigation.

The concept of resilience to Alzheimer's Disease: current definitions and cellular and molecular mechanisms

Some individuals are able to maintain their cognitive abilities despite the presence of significant Alzheimer's Disease (AD) neuropathological changes. This discrepancy between cognition and pathology has been labeled as resilience and has evolved into a widely debated concept. External factors such as cognitive stimulation are associated with resilience to AD, but the exact cellular and molecular underpinnings are not completely understood. In this review, we discuss the current definitions used in the field, highlight the translational approaches used to investigate resilience to AD and summarize the underlying cellular and molecular substrates of resilience that have been derived from human and animal studies, which have received more and more attention in the last few years. From these studies the picture emerges that resilient individuals are different from AD patients in terms of specific pathological species and their cellular reaction to AD pathology, which possibly helps to maintain cognition up to a certain tipping point. Studying these rare resilient individuals can be of great importance as it could pave the way to novel therapeutic avenues for AD.

Cell type-specific functions of Alzheimer's disease endocytic risk genes

Endocytosis is a key cellular pathway required for the internalization of cellular nutrients, lipids and receptor-bound cargoes. It is also critical for the recycling of cellular components, cellular trafficking and membrane dynamics. The endocytic pathway has been consistently implicated in Alzheimer's disease (AD) through repeated genome-wide association studies and the existence of rare coding mutations in endocytic genes. BIN1 and PICALM are two of the most significant late-onset AD risk genes after APOE and are both key to clathrin-mediated endocytic biology. Pathological studies also demonstrate that endocytic dysfunction is an early characteristic of late-onset AD, being seen in the prodromal phase of the disease. Different cell types of the brain have specific requirements of the endocytic pathway. Neurons require efficient recycling of synaptic vesicles and microglia use the specialized form of endocytosis-phagocytosis-for their normal function. Therefore, disease-associated changes in endocytic genes will have varied impacts across different cell types, which remains to be fully explored. Given the genetic and pathological evidence for endocytic dysfunction in AD, understanding how such changes and the related cell type-specific vulnerabilities impact normal cellular function and contribute to disease is vital and could present novel therapeutic opportunities. This article is part of a discussion meeting issue 'Understanding the endo-lysosomal network in neurodegeneration'.

Apolipoprotein E Genetic Testing in a New Age of Alzheimer Disease Clinical Practice

The recent FDA approval of amyloid-lowering drugs is changing the landscape of Alzheimer disease (AD) clinical practice. Previously, apolipoprotein E (APOE) genetic testing was not recommended in the care of people with AD because of limited clinical utility. With the advent of amyloid-lowering drugs, APOE genotype will play an important role in guiding treatment recommendations. Recent clinical trials have reported strong associations between APOE genotype and the safety and possibly the efficacy of amyloid-lowering drugs. Therefore, a clinical workflow that includes biomarker and genetic testing should be implemented to provide patients with the opportunity to make informed decisions and instruct safety monitoring for clinicians. Pretest consent, education, and counseling will be an essential aspect of this process for patients and their family members to understand the implications of these tests and their results. Given that the approved amyloid-lowering drugs are indicated for patients with mild cognitive impairment or mild dementia with biomarker evidence of AD, biomarker testing should be performed before genetic testing and genetic testing should only be performed in patients interested in treatment with amyloid-lowering drugs. It is also important to consider other implications of genetic testing, including burden on and need for additional training for clinicians, the role of additional providers, and the potential challenges for patients and families.

Recent advances in Alzheimer disease genetics

PURPOSE OF REVIEW

Genetics studies provide important insights into Alzheimer disease (AD) etiology and mechanisms. Critical advances have been made recently, mainly thanks to the access to novel techniques and larger studies.

RECENT FINDINGS

In monogenic AD, progress has been made with a better understanding of the mechanisms associated with pathogenic variants and the input of clinical studies in presymptomatic individuals. In complex AD, increasing sample sizes in both DNA chip-based (genome-wide association studies, GWAS) and exome/genome sequencing case-control studies unveiled novel common and rare risk factors, while the understanding of their combined effect starts to suggest the existence of rare families with oligogenic inheritance of early-onset, nonmonogenic, AD.

SUMMARY

Most genetic risk factors with a known consequence designate the aggregation of the Aβ peptide as a core etiological factor in complex AD thus confirming that the research based on monogenic AD - where the amyloid cascade seems more straightforward - is relevant to complex AD as well. Novel mechanistic insights and risk factor studies unveiling novel factors and attempting to combine the effect of common and rare variants will offer promising perspectives for future AD prevention, at least regarding early-onset AD, and probably in case of later onset as well.

The endotoxin hypothesis of Alzheimer's disease

Lipopolysaccharide (LPS) constitutes much of the surface of Gram-negative bacteria, and if LPS enters the human body or brain can induce inflammation and act as an endotoxin. We outline the hypothesis here that LPS may contribute to the pathophysiology of Alzheimer's disease (AD) via peripheral infections or gut dysfunction elevating LPS levels in blood and brain, which promotes: amyloid pathology, tau pathology and microglial activation, contributing to the neurodegeneration of AD. The evidence supporting this hypothesis includes: i) blood and brain levels of LPS are elevated in AD patients, ii) AD risk factors increase LPS levels or response, iii) LPS induces Aβ expression, aggregation, inflammation and neurotoxicity, iv) LPS induces TAU phosphorylation, aggregation and spreading, v) LPS induces microglial priming, activation and neurotoxicity, and vi) blood LPS induces loss of synapses, neurons and memory in AD mouse models, and cognitive dysfunction in humans. However, to test the hypothesis, it is necessary to test whether reducing blood LPS reduces AD risk or progression. If the LPS endotoxin hypothesis is correct, then treatments might include: reducing infections, changing gut microbiome, reducing leaky gut, decreasing blood LPS, or blocking LPS response.

Involvement of transposable elements in Alzheimer's disease pathogenesis

Alzheimer's disease affects an average of 5 % of the population with a significant increase in prevalence with age, suggesting that the same mechanisms that underlie aging may influence this pathology. Investigation of these mechanisms is promising for effective methods of treatment and prevention of the disease. Possible participants in these mechanisms are transposons, which serve as drivers of epigenetic regulation, since they form species-specific distributions of non-coding RNA genes in genomes in evolution. Study of miRNA involvement in Alzheimer's disease pathogenesis is relevant, since the associations of protein-coding genes (APOE4, ABCA7, BIN1, CLU, CR1, PICALM, TREM2) with the disease revealed as a result of GWAS make it difficult to explain its complex pathogenesis. Specific expression changes of many genes were found in different brain parts of Alzheimer's patients, which may be due to global regulatory changes under the influence of transposons. Experimental and clinical studies have shown pathological activation of retroelements in Alzheimer's disease. Our analysis of scientific literature in accordance with MDTE DB revealed 28 miRNAs derived from transposons (17 from LINE, 5 from SINE, 4 from HERV, 2 from DNA transposons), the expression of which specifically changes in this disease (decreases in 17 and increases in 11 microRNA). Expression of 13 out of 28 miRNAs (miR-151a, -192, -211, -28, -31, -320c, -335, -340, -378a, -511, -576, -708, -885) also changes with aging and cancer development, which indicates the presence of possible common pathogenetic mechanisms. Most of these miRNAs originated from LINE retroelements, the pathological activation of which is associated with aging, carcinogenesis, and Alzheimer's disease, which supports the hypothesis that these three processes are based on the primary dysregulation of transposons that serve as drivers of epigenetic regulation of gene expression in ontogeny.

Genetic diversity promotes resilience in a mouse model of Alzheimer's disease

INTRODUCTION

Alzheimer's disease (AD) is a neurodegenerative disorder with multifactorial etiology, including genetic factors that play a significant role in disease risk and resilience. However, the role of genetic diversity in preclinical AD studies has received limited attention.

METHODS

We crossed five Collaborative Cross strains with 5xFAD C57BL/6J female mice to generate F1 mice with and without the 5xFAD transgene. Amyloid plaque pathology, microglial and astrocytic responses, neurofilament light chain levels, and gene expression were assessed at various ages.

RESULTS

Genetic diversity significantly impacts AD-related pathology. Hybrid strains showed resistance to amyloid plaque formation and neuronal damage. Transcriptome diversity was maintained across ages and sexes, with observable strain-specific variations in AD-related phenotypes. Comparative gene expression analysis indicated correlations between mouse strains and human AD.

DISCUSSION

Increasing genetic diversity promotes resilience to AD-related pathogenesis, relative to an inbred C57BL/6J background, reinforcing the importance of genetic diversity in uncovering resilience in the development of AD.

HIGHLIGHTS

Genetic diversity's impact on AD in mice was explored. Diverse F1 mouse strains were used for AD study, via the Collaborative Cross. Strain-specific variations in AD pathology, glia, and transcription were found. Strains resilient to plaque formation and plasma neurofilament light chain (NfL) increases were identified. Correlations with human AD transcriptomics were observed.

Role of the Exposome in Neurodegenerative Disease: Recent Insights and Future Directions

Neurodegenerative diseases are increasing in prevalence and place a significant burden on society. The causes are multifactorial and complex, and increasing evidence suggests a dynamic interplay between genes and the environment, emphasizing the importance of identifying and understanding the role of lifelong exposures, known as the exposome, on the nervous system. This review provides an overview of recent advances toward defining neurodegenerative disease exposomes, focusing on Parkinson's disease, amyotrophic lateral sclerosis, and Alzheimer's disease. We present the current state of the field based on emerging data, elaborate on key themes and potential mechanisms, and conclude with limitations and future directions. ANN NEUROL 2024;95:635-652.

Whole genome-wide sequence analysis of long-lived families (Long-Life Family Study) identifies MTUS2 gene associated with late-onset Alzheimer's disease

INTRODUCTION

Late-onset Alzheimer's disease (LOAD) has a strong genetic component. Participants in Long-Life Family Study (LLFS) exhibit delayed onset of dementia, offering a unique opportunity to investigate LOAD genetics.

METHODS

We conducted a whole genome sequence analysis of 3475 LLFS members. Genetic associations were examined in six independent studies (N = 14,260) with a wide range of LOAD risk. Association analysis in a sub-sample of the LLFS cohort (N = 1739) evaluated the association of LOAD variants with beta amyloid (Aβ) levels.

RESULTS

We identified several single nucleotide polymorphisms (SNPs) in tight linkage disequilibrium within the MTUS2 gene associated with LOAD (rs73154407, p = 7.6 × 10-9). Association of MTUS2 variants with LOAD was observed in the five independent studies and was significantly stronger within high levels of Aβ42/40 ratio compared to lower amyloid.

DISCUSSION

MTUS2 encodes a microtubule associated protein implicated in the development and function of the nervous system, making it a plausible candidate to investigate LOAD biology.

HIGHLIGHTS

Long-Life Family Study (LLFS) families may harbor late onset Alzheimer's dementia (LOAD) variants. LLFS whole genome sequence analysis identified MTUS2 gene variants associated with LOAD. The observed LLFS variants generalized to cohorts with wide range of LOAD risk. The association of MTUS2 with LOAD was stronger within high levels of beta amyloid. Our results provide evidence for MTUS2 gene as a novel LOAD candidate locus.

Protective effect of PDE4B subtype-specific inhibition in an App knock-in mouse model for Alzheimer's disease

Meta-analysis of genome-wide association study data has implicated PDE4B in the pathogenesis of Alzheimer's disease (AD), the leading cause of senile dementia. PDE4B encodes one of four subtypes of cyclic adenosine monophosphate (cAMP)-specific phosphodiesterase-4 (PDE4A-D). To interrogate the involvement of PDE4B in the manifestation of AD-related phenotypes, the effects of a hypomorphic mutation (Pde4bY358C) that decreases PDE4B's cAMP hydrolytic activity were evaluated in the AppNL-G-F knock-in mouse model of AD using the Barnes maze test of spatial memory, 14C-2-deoxyglucose autoradiography, thioflavin-S staining of β-amyloid (Aβ) plaques, and inflammatory marker assay and transcriptomic analysis (RNA sequencing) of cerebral cortical tissue. At 12 months of age, AppNL-G-F mice exhibited spatial memory and brain metabolism deficits, which were prevented by the hypomorphic PDE4B in AppNL-G-F/Pde4bY358C mice, without a decrease in Aβ plaque burden. RNA sequencing revealed that, among the 531 transcripts differentially expressed in AppNL-G-F versus wild-type mice, only 13 transcripts from four genes - Ide, Btaf1, Padi2, and C1qb - were differentially expressed in AppNL-G-F/Pde4bY358C versus AppNL-G-F mice, identifying their potential involvement in the protective effect of hypomorphic PDE4B. Our data demonstrate that spatial memory and cerebral glucose metabolism deficits exhibited by 12-month-old AppNL-G-F mice are prevented by targeted inhibition of PDE4B. To our knowledge, this is the first demonstration of a protective effect of PDE4B subtype-specific inhibition in a preclinical model of AD. It thus identifies PDE4B as a key regulator of disease manifestation in the AppNL-G-F model and a promising therapeutic target for AD.

Prioritizing disease-related rare variants by integrating gene expression data

Rare variants, comprising a vast majority of human genetic variations, are likely to have more deleterious impact on human diseases compared to common variants. Here we present carrier statistic, a statistical framework to prioritize disease-related rare variants by integrating gene expression data. By quantifying the impact of rare variants on gene expression, carrier statistic can prioritize those rare variants that have large functional consequence in the diseased patients. Through simulation studies and analyzing real multi-omics dataset, we demonstrated that carrier statistic is applicable in studies with limited sample size (a few hundreds) and achieves substantially higher sensitivity than existing rare variants association methods. Application to Alzheimer's disease reveals 16 rare variants within 15 genes with extreme carrier statistics. The carrier statistic method can be applied to various rare variant types and is adaptable to other omics data modalities, offering a powerful tool for investigating the molecular mechanisms underlying complex diseases.

Genetic overlap between Alzheimer's disease and immune-mediated diseases: an atlas of shared genetic determinants and biological convergence

The occurrence of immune disease comorbidities in Alzheimer's disease (AD) has been observed in both epidemiological and molecular studies, suggesting a neuroinflammatory basis in AD. However, their shared genetic components have not been systematically studied. Here, we composed an atlas of the shared genetic associations between 11 immune-mediated diseases and AD by analyzing genome-wide association studies (GWAS) summary statistics. Our results unveiled a significant genetic overlap between AD and 11 individual immune-mediated diseases despite negligible genetic correlations, suggesting a complex shared genetic architecture distributed across the genome. The shared loci between AD and immune-mediated diseases implicated several genes, including GRAMD1B, FUT2, ADAMTS4, HBEGF, WNT3, TSPAN14, DHODH, ABCB9, and TNIP1, all of which are protein-coding genes and thus potential drug targets. Top biological pathways enriched with these identified shared genes were related to the immune system and cell adhesion. In addition, in silico single-cell analyses showed enrichment of immune and brain cells, including neurons and microglia. In summary, our results suggest a genetic relationship between AD and the 11 immune-mediated diseases, pinpointing the existence of a shared however non-causal genetic basis. These identified protein-coding genes have the potential to serve as a novel path to therapeutic interventions for both AD and immune-mediated diseases and their comorbidities.

Andrographolide Improves ApoE4-Mediated Blood-Brain Barrier Injury by Alleviating Inflammation

The pathological and physiological studies of Alzheimer's disease (AD) have been in-depth, and apolipoprotein E4 (ApoE4) has been proven to be highly correlated with AD, and clinical and experimental data show that ApoE4 can cause blood-brain barrier (BBB) injury, and the change of BBB permeability is an important factor affecting the development of AD. Andrographolide (Andro), as the active component of the natural plant Andrographis paniculata, has been proven to have anti-inflammatory and antioxidant effects, which have potential neuroprotective effects. To verify the protective effect of Andro on BBB in a short term, our research group used atorvastatin (Atorva)-mediated zebrafish brain injury model and the ApoE4-mediated cell co-culture model of BBB injury to explore the protective effects and mechanisms of Andro on BBB injury. Studies have shown that Andro can inhibit the activation of CypA/NF-κB/MMP-9 signaling pathway and has achieved the effect of antagonizing the inhibition of ApoE4 on intercellular tight junction proteins (occludin, claudin-5, and ZO-1). At the same time, Andro can inhibit the secretion of cell adhesion molecules (VCAM-1 and ICAM-1) in cells, thereby delaying the occurrence and progression of neuroinflammation and playing a protective role in BBB. In conclusion, Andro is a potent natural product which can protect the blood-brain barrier.

Association between pre-dementia psychiatric diagnoses and all-cause dementia is independent from polygenic dementia risks in the UK Biobank

BACKGROUND

Psychiatric disorders have been associated with higher risk for future dementia. Understanding how pre-dementia psychiatric disorders (PDPD) relate to established dementia genetic risks has implications for dementia prevention.

METHODS

In this retrospective cohort study, we investigated the relationships between polygenic risk scores for Alzheimer's disease (AD PRS), PDPD, alcohol use disorder (AUD), and subsequent dementia in the UK Biobank (UKB) and tested whether the relationships are consistent with different causal models.

FINDINGS

Among 502,408 participants, 9352 had dementia. As expected, AD PRS was associated with greater risk for dementia (odds ratio (OR) 1.62, 95% confidence interval (CI), 1.59-1.65). A total of 94,237 participants had PDPD, of whom 2.6% (n = 2519) developed subsequent dementia, compared to 1.7% (n = 6833) of 407,871 participants without PDPD. Accordingly, PDPD were associated with 73% greater risk of incident dementia (OR 1.73, 1.65-1.83). Among dementia subtypes, the risk increase was 1.5-fold for AD (n = 3365) (OR 1.46, 1.34-1.59) and 2-fold for vascular dementia (VaD, n = 1823) (OR 2.08, 1.87-2.32). Our data indicated that PDPD were neither a dementia prodrome nor a mediator for AD PRS. Shared factors for both PDPD and dementia likely substantially account for the observed association, while a causal role of PDPD in dementia could not be excluded. AUD could be one of the shared causes for PDPD and dementia.

INTERPRETATION

Psychiatric diagnoses were associated with subsequent dementia in UKB participants, and the association is orthogonal to established dementia genetic risks. Investigating shared causes for psychiatric disorders and dementia would shed light on this dementia pathway.

FUNDING

US NIH (K08AG054727).

Dementia and mortality in older adults: A twin study

INTRODUCTION

Dementia predicts increased mortality. We used case-control and co-twin control models to investigate genetic and shared environmental influences on this association.

METHODS

Case-control design, including 987 twins with dementia and 2938 age- and sex-matched controls in the Swedish Twin Registry. Co-twin control design, including 90 monozygotic (MZ) and 288 dizygotic (DZ) twin pairs discordant for dementia. To test for genetic and environmental confounding, differences were examined in mortality risk between twins with dementia and their matched or co-twin controls.

RESULTS

Twins with dementia showed greater mortality risk than age- and sex-matched controls (HR = 2.02 [1.86, 2.18]). Mortality risk is significantly elevated but attenuated substantially in discordant twin pairs, for example, comparing MZ twins with dementia to their co-twin controls (HR = 1.48 [1.08, 2.04]).

DISCUSSION

Findings suggest that genetic factors partially confound the association between dementia and mortality and provide an alternative hypothesis to increased mortality due to dementia itself. Highlights We studied dementia and mortality in twin pairs discordant for dementia. People without dementia outlived people with dementia. Identical twins with dementia and their co-twin controls had similar survival time. Findings suggest genotype may explain the link between dementia and mortality.

Polygenic effects on the risk of Alzheimer's disease in the Japanese population

BACKGROUND

Polygenic effects have been proposed to account for some disease phenotypes; these effects are calculated as a polygenic risk score (PRS). This score is correlated with Alzheimer's disease (AD)-related phenotypes, such as biomarker abnormalities and brain atrophy, and is associated with conversion from mild cognitive impairment (MCI) to AD. However, the AD PRS has been examined mainly in Europeans, and owing to differences in genetic structure and lifestyle, it is unclear whether the same relationships between the PRS and AD-related phenotypes exist in non-European populations. In this study, we calculated and evaluated the AD PRS in Japanese individuals using genome-wide association study (GWAS) statistics from Europeans.

METHODS

In this study, we calculated the AD PRS in 504 Japanese participants (145 cognitively unimpaired (CU) participants, 220 participants with late mild cognitive impairment (MCI), and 139 patients with mild AD dementia) enrolled in the Japanese Alzheimer's Disease Neuroimaging Initiative (J-ADNI) project. In order to evaluate the clinical value of this score, we (1) determined the polygenic effects on AD in the J-ADNI and validated it using two independent cohorts (a Japanese neuropathology (NP) cohort (n = 565) and the North American ADNI (NA-ADNI) cohort (n = 617)), (2) examined the AD-related phenotypes associated with the PRS, and (3) tested whether the PRS helps predict the conversion of MCI to AD.

RESULTS

The PRS using 131 SNPs had an effect independent of APOE. The PRS differentiated between CU participants and AD patients with an area under the curve (AUC) of 0.755 when combined with the APOE variants. Similar AUC was obtained when PRS calculated by the NP and NA-ADNI cohorts was applied. In MCI patients, the PRS was associated with cerebrospinal fluid phosphorylated-tau levels (β estimate = 0.235, p value = 0.026). MCI with a high PRS showed a significantly increased conversion to AD in APOE ε4 noncarriers with a hazard rate of 2.22. In addition, we also developed a PRS model adjusted for LD and observed similar results.

CONCLUSIONS

We showed that the AD PRS is useful in the Japanese population, whose genetic structure is different from that of the European population. These findings suggest that the polygenicity of AD is partially common across ethnic differences.

LRRC25 expression during physiological aging and in mouse models of Alzheimer's disease and iPSC-derived neurons

The leucine-rich repeat-containing protein 25 (LRRC25) is relatively a novel protein with no information on its role in neuronal or brain function. A recent study suggested LRRC25 is a potential risk factor for Alzheimer's disease (AD). As a first step to understanding LRRC25's role in the brain and AD, we found LRRC25 is expressed in both cell membranes and cytoplasm in a punctuate appearance in astrocytes, microglia, and neurons in cell lines as well as mouse brain. We also found that LRRC25 expression is both age- and brain region-dependent and that 1-day-old (1D) pups expressed the least amount of LRRC25 protein compared to adult ages. In the APΔE9 mice, immunoblot quantified LRRC25 protein levels were increased by 166% (**p < 0.01) in the cortex (CX) and by 215% (***p < 0.001) in the hippocampus (HP) relative to wild-type (WT) controls. Both the brainstem (BS) and cerebellum (CB) showed no significant alterations. In the 3xTg mice, only CX showed an increase of LRRC25 protein by 91% (*p < 0.05) when compared to WT controls although the increased trend was noted in the other brain regions. In the AD patient brains also LRRC25 protein levels were increased by 153% (***p < 0.001) when compared to normal control (NC) subjects. Finally, LRRC25 expression in the iPSC-derived neurons quantified by immunofluorescence was increased by 181% (**p < 0.01) in AD-derived neurons when compared to NC-derived neurons. Thus increased LRRC25 protein in multiple models of AD suggests that LRRC25 may play a pathogenic role in either Aβ or tau pathology in AD. The mechanism for the increased levels of LRRC25 in AD is unknown at present, but a previous study showed that LRRC25 levels also increase during neonatal hypoxic-ischemia neuronal damage. Based on the evidence that autophagy is highly dysregulated in AD, the increased LRRC25 levels may be due to decreased autophagic degradation of LRRC25. Increased LRRC25 in turn may regulate the stability or activity of key enzymes involved in either Aβ or hyperphosphorylated tau generation and thus may contribute to increased plaques and neurofibrillary tangles.

2024 Heart Disease and Stroke Statistics: A Report of US and Global Data From the American Heart Association

BACKGROUND

The American Heart Association (AHA), in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, nutrition, sleep, and obesity) and health factors (cholesterol, blood pressure, glucose control, and metabolic syndrome) that contribute to cardiovascular health. The AHA Heart Disease and Stroke Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, brain health, complications of pregnancy, kidney disease, congenital heart disease, rhythm disorders, sudden cardiac arrest, subclinical atherosclerosis, coronary heart disease, cardiomyopathy, heart failure, valvular disease, venous thromboembolism, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The AHA, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States and globally to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2024 AHA Statistical Update is the product of a full year's worth of effort in 2023 by dedicated volunteer clinicians and scientists, committed government professionals, and AHA staff members. The AHA strives to further understand and help heal health problems inflicted by structural racism, a public health crisis that can significantly damage physical and mental health and perpetuate disparities in access to health care, education, income, housing, and several other factors vital to healthy lives. This year's edition includes additional global data, as well as data on the monitoring and benefits of cardiovascular health in the population, with an enhanced focus on health equity across several key domains.

RESULTS

Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.

CONCLUSIONS

The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

Comparative study of machine learning methods for modeling associations between risk factors and future dementia cases

A substantial portion of dementia risk can be attributed to modifiable risk factors that can be affected by lifestyle changes. Identifying the contributors to dementia risk could prove valuable. Recently, machine learning methods have been increasingly applied to healthcare data. Several studies have attempted to predict dementia progression by using such techniques. This study aimed to compare the performance of different machine-learning methods in modeling associations between known cognitive risk factors and future dementia cases. A subset of the AGES-Reykjavik Study dataset was analyzed using three machine-learning methods: logistic regression, random forest, and neural networks. Data were collected twice, approximately five years apart. The dataset included information from 1,491 older adults who underwent a cognitive screening process and were considered to have healthy cognition at baseline. Cognitive risk factors included in the models were based on demographics, MRI data, and other health-related data. At follow-up, participants were re-evaluated for dementia using the same cognitive screening process. Various performance metrics for all three machine learning algorithms were assessed. The study results indicate that a random forest algorithm performed better than neural networks and logistic regression in predicting the association between cognitive risk factors and dementia. Compared to more traditional statistical analyses, machine-learning methods have the potential to provide more accurate predictions about which individuals are more likely to develop dementia than others.

Trends in the application of "omics" to Alzheimer's disease: a bibliometric and visualized study

BACKGROUND

Alzheimer's disease (AD) is a progressive neurodegenerative disease with an insidious onset. The widespread application of omics techniques in AD has attracted considerable attention. We aimed to make a comprehensive analysis of published omics articles on AD in order to determine the research profile and application trends of omics techniques in AD.

METHODS

This study utilizes bibliometric and visual methods including a map collaboration map, co-citations, and keywords to identify knowledge structures, hot topics, and research trends based on 6,828 publications from the Web of Science Core Collection (WoSCC) database.

RESULTS

The results of this study showed that 5654 institutions from 91 countries published articles in this field. The USA, China, and the UK played a leading role in publishing numerous articles in relevant journals as well as prolific institutions and authors, respectively. This paper collects a large number of literatures on the application of AD omics technology from the WoSCC database and found the omics technology applied to AD is mainly based on genomics technology. The application of transcriptomics technology has shown an increasing trend in recent years, and the application of multi-omics technology will be the general trend in the future.

CONCLUSION

The development status, frontier hotspots, and general trends of omics application technologies are reviewed. This article will provide intelligence support to researchers and institutions in the field of Alzheimer's omics research and applications from a practical perspective.

Identification of common core ion channel genes in epilepsy and Alzheimer's disease

BACKGROUND

Although available literature indicates that the incidence of dementia in the epilepsy population and the risk of seizures in the Alzheimer's disease (AD) population are high, the specific genetic risk factors and the interaction mechanism are unclear, rendering rational genetic interpretation rather challenging.

AIMS

Our work aims to identify the common core ion channel genes in epilepsy and AD.

METHODS

In this study, we first integrated gene expression omnibus datasets (GSE48350 and GSE6834) on AD and epilepsy to identify differentially expressed genes (DEGs), performing Gene Ontology function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of DEGs. The related protein-protein interaction (PPI) network was constructed for DEGs, and the hub gene was evaluated.

RESULTS

A total of 2800 and 35 genes were identified in GSE48350 and GSE6834, and 12 DEGs were significantly differentially expressed between the datasets. KEGG pathway analysis showed that DEGs were primarily enriched in glutamatergic synapse and dopaminergic synapse pathways. SCN2A, GRIA1, and KCNJ9 were the hub genes with high connectivity.

CONCLUSIONS

The findings suggest that the three genes, SCN2A, GRIA1, and KCNJ9, may serve as potential targets for treating AD comorbid with epilepsy.

Machine Learning Models of Polygenic Risk for Enhanced Prediction of Alzheimer Disease Endophenotypes

Background and Objectives

Alzheimer disease (AD) has a polygenic architecture, for which genome-wide association studies (GWAS) have helped elucidate sequence variants (SVs) influencing susceptibility. Polygenic risk score (PRS) approaches show promise for generating summary measures of inherited risk for clinical AD based on the effects of APOE and other GWAS hits. However, existing PRS approaches, based on traditional regression models, explain only modest variation in AD dementia risk and AD-related endophenotypes. We hypothesized that machine learning (ML) models of polygenic risk (ML-PRS) could outperform standard regression-based PRS methods and therefore have the potential for greater clinical utility.

Methods

We analyzed combined data from the Mayo Clinic Study of Aging (n = 1,791) and the Alzheimer's Disease Neuroimaging Initiative (n = 864). An AD PRS was computed for each participant using the top common SVs obtained from a large AD dementia GWAS. In parallel, ML models were trained using those SV genotypes, with amyloid PET burden as the primary outcome. Secondary outcomes included amyloid PET positivity and clinical diagnosis (cognitively unimpaired vs impaired). We compared performance between ML-PRS and standard PRS across 100 training sessions with different data splits. In each session, data were split into 80% training and 20% testing, and then five-fold cross-validation was used within the training set to ensure the best model was produced for testing. We also applied permutation importance techniques to assess which genetic factors contributed most to outcome prediction.

Results

ML-PRS models outperformed the AD PRS (r2 = 0.28 vs r2 = 0.24 in test set) in explaining variation in amyloid PET burden. Among ML approaches, methods accounting for nonlinear genetic influences were superior to linear methods. ML-PRS models were also more accurate when predicting amyloid PET positivity (area under the curve [AUC] = 0.80 vs AUC = 0.63) and the presence of cognitive impairment (AUC = 0.75 vs AUC = 0.54) compared with the standard PRS.

Discussion

We found that ML-PRS approaches improved upon standard PRS for prediction of AD endophenotypes, partly related to improved accounting for nonlinear effects of genetic susceptibility alleles. Further adaptations of the ML-PRS framework could help to close the gap of remaining unexplained heritability for AD and therefore facilitate more accurate presymptomatic and early-stage risk stratification for clinical decision-making.

Longitudinal change in memory performance as a strong endophenotype for Alzheimer's disease

INTRODUCTION

Although large-scale genome-wide association studies (GWAS) have been conducted on AD, few have been conducted on continuous measures of memory performance and memory decline.

METHODS

We conducted a cross-ancestry GWAS on memory performance (in 27,633 participants) and memory decline (in 22,365 participants; 129,201 observations) by leveraging harmonized cognitive data from four aging cohorts.

RESULTS

We found high heritability for two ancestry backgrounds. Further, we found a novel ancestry locus for memory decline on chromosome 4 (rs6848524) and three loci in the non-Hispanic Black ancestry group for memory performance on chromosomes 2 (rs111471504), 7 (rs4142249), and 15 (rs74381744). In our gene-level analysis, we found novel genes for memory decline on chromosomes 1 (SLC25A44), 11 (BSX), and 15 (DPP8). Memory performance and memory decline shared genetic architecture with AD-related traits, neuropsychiatric traits, and autoimmune traits.

DISCUSSION

We discovered several novel loci, genes, and genetic correlations associated with late-life memory performance and decline.

HIGHLIGHTS

Late-life memory has high heritability that is similar across ancestries. We discovered four novel variants associated with late-life memory. We identified four novel genes associated with late-life memory. Late-life memory shares genetic architecture with psychiatric/autoimmune traits.

Knowledge domains and emerging trends of Genome-wide association studies in Alzheimer's disease: A bibliometric analysis and visualization study from 2002 to 2022

OBJECTIVES

Alzheimer's disease (AD) is a neurodegenerative disorder characterized by a progressive decline in cognitive and behavioral function. Studies have shown that genetic factors are one of the main causes of AD risk. genome-wide association study (GWAS), as a novel and effective tool for studying the genetic risk of diseases, has attracted attention from researchers in recent years and a large number of studies have been conducted. This study aims to summarize the literature on GWAS in AD by bibliometric methods, analyze the current status, research hotspots and future trends in this field.

METHODS

We retrieved articles on GWAS in AD published between 2002 and 2022 from Web of Science. CiteSpace and VOSviewer software were applied to analyze the articles for the number of articles published, countries/regions and institutions of publication, authors and cited authors, highly cited literature, and research hotspots.

RESULTS

We retrieved a total of 2,751 articles. The United States had the highest number of publications in this field, and Columbia University was the institution with the most published articles. The identification of AD-related susceptibility genes and their effects on AD is one of the current research hotspots. Numerous risk genes have been identified, among which APOE, CLU, CD2AP, CD33, EPHA1, PICALM, CR1, ABCA7 and TREM2 are the current genes of interest. In addition, risk prediction for AD and research on other related diseases are also popular research directions in this field.

CONCLUSION

This study conducted a comprehensive analysis of GWAS in AD and identified the current research hotspots and research trends. In addition, we also pointed out the shortcomings of current research and suggested future research directions. This study can provide researchers with information about the knowledge structure and emerging trends in the field of GWAS in AD and provide guidance for future research.

Multi-Omic Blood Biomarkers as Dynamic Risk Predictors in Late-Onset Alzheimer's Disease

Late-onset Alzheimer's disease is the leading cause of dementia worldwide, accounting for a growing burden of morbidity and mortality. Diagnosing Alzheimer's disease before symptoms are established is clinically challenging, but would provide therapeutic windows for disease-modifying interventions. Blood biomarkers, including genetics, proteins and metabolites, are emerging as powerful predictors of Alzheimer's disease at various timepoints within the disease course, including at the preclinical stage. In this review, we discuss recent advances in such blood biomarkers for determining disease risk. We highlight how leveraging polygenic risk scores, based on genome-wide association studies, can help stratify individuals along their risk profile. We summarize studies analyzing protein biomarkers, as well as report on recent proteomic- and metabolomic-based prediction models. Finally, we discuss how a combination of multi-omic blood biomarkers can potentially be used in memory clinics for diagnosis and to assess the dynamic risk an individual has for developing Alzheimer's disease dementia.

Hippocampus Glutathione S Reductase Potentially Confers Genetic Resilience to Cognitive Decline in the AD-BXD Mouse Population

Alzheimer's disease (AD) is a prevalent and costly age-related dementia. Heritable factors account for 58-79% of variation in late-onset AD, but substantial variation remains in age-of- onset, disease severity, and whether those with high-risk genotypes acquire AD. To emulate the diversity of human populations, we utilized the AD-BXD mouse panel. This genetically diverse resource combines AD genotypes with multiple BXD strains to discover new genetic drivers of AD resilience. Comparing AD-BXD carriers to noncarrier littermates, we computed a novel quantitative metric for resilience to cognitive decline in the AD-BXDs. Our quantitative AD resilience trait was heritable and genetic mapping identified a locus on chr8 associated with resilience to AD mutations that resulted in amyloid brain pathology. Using a hippocampus proteomics dataset, we nominated the mitochondrial glutathione S reductase protein (GR or GSHR) as a resilience factor, finding that the DBA/2J genotype was associated with substantially higher GR abundance. By mapping protein QTLs (pQTLs), we identified synaptic organization and mitochondrial proteins coregulated in trans with a cis-pQTL for GR. We found four coexpression modules correlated with the quantitative resilience score in aged 5XFAD mice using paracliques, which were related to cell structure, protein folding, and postsynaptic densities. Finally, we found significant positive associations between human GSR transcript abundance in the brain and better outcomes on AD-related cognitive and pathology traits in the Religious Orders Study/Memory and Aging project (ROSMAP). Taken together, these data support a framework for resilience in which neuronal antioxidant pathway activity provides for stability of synapses within the hippocampus.

Dynamic fusion of genomics and functional network connectivity in UK biobank reveals static and time-varying SNP manifolds

Many psychiatric and neurological disorders show significant heritability, indicating strong genetic influence. In parallel, dynamic functional network connectivity (dFNC) measures functional temporal coupling between brain networks in a time-varying manner and has proven to identify disease-related changes in the brain. However, it remains largely unclear how genetic risk contributes to brain dysconnectivity that further manifests into clinical symptoms. The current work aimed to address this gap by proposing a novel joint ICA (jICA)-based "dynamic fusion" framework to identify dynamically tuned SNP manifolds by linking static SNPs to dynamic functional information of the brain. The sliding window approach was utilized to estimate four dFNC states and compute subject-level state-specific dFNC features. Each state of dFNC features were then combined with 12946 SZ risk SNPs for jICA decomposition, resulting in four parallel fusions in 32861 European ancestry individuals within the UK Biobank cohort. The identified joint SNP-dFNC components were further validated for SZ relevance in an aggregated SZ cohort, and compared for across-state similarity to indicate level of dynamism. The results supported that dynamic fusion yielded "static" and "dynamic" components (i.e., high and low across-state similarity, respectively) for SNP and dFNC modalities. As expected, the SNP components presented a mixture of static and dynamic manifolds, with the latter largely driven by fusion with dFNC. We also showed that some of the dynamic SNP manifolds uniquely elicited by fusion with state-specific dFNC features complemented each other in terms of biological interpretation. This dynamic fusion framework thus allows expanding the SNP modality to manifolds in the time dimension, which provides a unique lens to elicit unique SNP correlates of dFNC otherwise unseen, promising additional insights on how genetic risk links to disease-related dysconnectivity.

Serum proteomics reveals APOE dependent and independent protein signatures in Alzheimer's disease

The current demand for early intervention, prevention, and treatment of late onset Alzheimer's disease (LOAD) warrants deeper understanding of the underlying molecular processes which could contribute to biomarker and drug target discovery. Utilizing high-throughput proteomic measurements in serum from a prospective population-based cohort of older adults (n = 5,294), we identified 303 unique proteins associated with incident LOAD (median follow-up 12.8 years). Over 40% of these proteins were associated with LOAD independently of APOE-ε4 carrier status. These proteins were implicated in neuronal processes and overlapped with protein signatures of LOAD in brain and cerebrospinal fluid. We found 17 proteins which LOAD-association was strongly dependent on APOE-ε4 carrier status. Most of them showed consistent associations with LOAD in cerebrospinal fluid and a third had brain-specific gene expression. Remarkably, four proteins in this group (TBCA, ARL2, S100A13 and IRF6) were downregulated by APOE-ε4 yet upregulated as a consequence of LOAD as determined in a bi-directional Mendelian randomization analysis, reflecting a potential response to the disease onset. Accordingly, the direct association of these proteins to LOAD was reversed upon APOE-ε4 genotype adjustment, a finding which we replicate in an external cohort (n = 719). Our findings provide an insight into the dysregulated pathways that may lead to the development and early detection of LOAD, including those both independent and dependent on APOE-ε4. Importantly, many of the LOAD-associated proteins we find in the circulation have been found to be expressed - and have a direct link with AD - in brain tissue. Thus, the proteins identified here, and their upstream modulating pathways, provide a new source of circulating biomarker and therapeutic target candidates for LOAD.