Meta-analysis of 74,046 individuals identifies 11 new susceptibility loci for Alzheimer's disease

Dynamics of cognitive variability with age and its genetic underpinning in NIHR BioResource Genes and Cognition cohort participants

A leading explanation for translational failure in neurodegenerative disease is that new drugs are evaluated late in the disease course when clinical features have become irreversible. Here, to address this gap, we cognitively profiled 21,051 people aged 17-85 years as part of the Genes and Cognition cohort within the National Institute for Health and Care Research BioResource across England. We describe the cohort, present cognitive trajectories and show the potential utility. Surprisingly, when studied at scale, the APOE genotype had negligible impact on cognitive performance. Different cognitive domains had distinct genetic architectures, with one indicating brain region-specific activation of microglia and another with glycogen metabolism. Thus, the molecular and cellular mechanisms underpinning cognition are distinct from dementia risk loci, presenting different targets to slow down age-related cognitive decline. Participants can now be recalled stratified by genotype and cognitive phenotype for natural history and interventional studies of neurodegenerative and other disorders.

Human pluripotent stem cell (hPSC)-derived microglia for the study of brain disorders. A comprehensive review of existing protocols

Microglia, resident immune cells of the brain that originate from the yolk sac, play a critical role in maintaining brain homeostasis by monitoring and phagocytosing pathogens and cellular debris in the central nervous system (CNS). While they share characteristics with myeloid cells, they are distinct from macrophages. In response to injury, microglia release pro-inflammatory factors and contribute to brain homeostasis through activities such as synapse pruning and neurogenesis. To better understand their role in neurological disorders, the generation of in vitro models of human microglia has become essential. These models, derived from patient-specific induced pluripotent stem cells (iPSCs), provide a controlled environment to study the molecular and cellular mechanisms underlying microglia-mediated neuroinflammation and neurodegeneration. The incorporation or generation of microglia into three-dimensional (3D) organoid cultures provides a more physiologically relevant environment that offers further opportunities to study microglial dynamics and disease modeling. This review describes several protocols that have been recently developed for the generation of human-induced microglia. Importantly, it highlights the promise of these in vitro models in advancing our understanding of brain disorders and facilitating personalized drug screening.

SHIP inhibition mediates select TREM2-induced microglial functions

Microglia play a pivotal role in the pathology of Alzheimer's Disease (AD), with the Triggering Receptor Expressed on Myeloid cells 2 (TREM2) central to their neuroprotective functions. The R47H variant of TREM2 has emerged as a significant genetic risk factor for AD, leading to a loss-of-function phenotype in mouse AD models. This study elucidates the roles of TREM2 in human microglia-like HMC3 cells and the regulation of these functions by SH2-containing inositol-5'-phosphatase 1 (SHIP1). Using stable cell lines expressing wild-type TREM2, the R47H variant, and TREM2-deficient lines, we found that functional TREM2 is essential for the phagocytosis of Aβ, lysosomal capacity, and mitochondrial activity. Notably, the R47H variant displayed increased phagocytic activity towards apoptotic neurons. Introducing SHIP1, known to modulate TREM2 signaling in other cells, revealed its role as a negative regulator of these TREM2-mediated functions. Moreover, pharmacological inhibition of both SHIP1 and its isoform SHIP2 amplified Aβ phagocytosis and lysosomal capacity, independently of TREM2 or SHIP1 expression, suggesting a potential regulatory role for SHIP2 in these functions. The absence of TREM2, combined with the presence of both SHIP isoforms, suppressed mitochondrial activity. However, pan-SHIP1/2 inhibition enhanced mitochondrial function in these cells. In summary, our findings offer a deeper understanding of the relationship between TREM2 variants and SHIP1 in microglial functions, and emphasize the therapeutic potential of targeting the TREM2 and SHIP1 pathways in microglia for neurodegenerative diseases.

Physical frailty, genetic predisposition, and incident dementia: a large prospective cohort study

Physical frailty and genetic factors are both risk factors for increased dementia; nevertheless, the joint effect remains unclear. This study aimed to investigated the long-term relationship between physical frailty, genetic risk, and dementia incidence. A total of 274,194 participants from the UK Biobank were included. We applied Cox proportional hazards regression models to estimate the association between physical frailty and genetic and dementia risks. Among the participants (146,574 females [53.45%]; mean age, 57.24 years), 3,353 (1.22%) new-onset dementia events were recorded. Compared to non-frailty, the hazard ratio (HR) for dementia incidence in prefrailty and frailty was 1.396 (95% confidence interval [CI], 1.294-1.506, P < 0.001) and 2.304 (95% CI, 2.030-2.616, P < 0.001), respectively. Compared to non-frailty and low polygenic risk score (PRS), the HR for dementia risk was 3.908 (95% CI, 3.051-5.006, P < 0.001) for frailty and high PRS. Furthermore, among the participants, slow walking speed (HR, 1.817; 95% CI, 1.640-2.014, P < 0.001), low physical activity (HR, 1.719; 95% CI, 1.545-1.912, P < 0.001), exhaustion (HR, 1.670; 95% CI, 1.502-1.856, P < 0.001), low grip strength (HR, 1.606; 95% CI, 1.479-1.744, P < 0.001), and weight loss (HR, 1.464; 95% CI, 1.328-1.615, P < 0.001) were independently associated with dementia risk compared to non-frailty. Particularly, precise modulation for different dementia genetic risk populations can also be identified due to differences in dementia risk resulting from the constitutive pattern of frailty in different genetic risk populations. In conclusion, both physical frailty and high genetic risk are significantly associated with higher dementia risk. Early intervention to modify frailty is beneficial for achieving primary and precise prevention of dementia, especially in those at high genetic risk.

Biobank-wide association scan identifies risk factors for late-onset Alzheimer's disease and endophenotypes

Rich data from large biobanks, coupled with increasingly accessible association statistics from genome-wide association studies (GWAS), provide great opportunities to dissect the complex relationships among human traits and diseases. We introduce BADGERS, a powerful method to perform polygenic score-based biobank-wide association scans. Compared to traditional approaches, BADGERS uses GWAS summary statistics as input and does not require multiple traits to be measured in the same cohort. We applied BADGERS to two independent datasets for late-onset Alzheimer's disease (AD; n=61,212). Among 1738 traits in the UK biobank, we identified 48 significant associations for AD. Family history, high cholesterol, and numerous traits related to intelligence and education showed strong and independent associations with AD. Furthermore, we identified 41 significant associations for a variety of AD endophenotypes. While family history and high cholesterol were strongly associated with AD subgroups and pathologies, only intelligence and education-related traits predicted pre-clinical cognitive phenotypes. These results provide novel insights into the distinct biological processes underlying various risk factors for AD.

Alzheimer's disease risk allele of PICALM causes detrimental lipid droplets in microglia

Despite genome-wide association studies of late-onset Alzheimer's disease (LOAD) having identified many genetic risk loci1-6, the underlying disease mechanisms remain largely unknown. Determining causal disease variants and their LOAD-relevant cellular phenotypes has been a challenge. Leveraging our approach for identifying functional GWAS risk variants showing allele-specific open chromatin (ASoC)7, we systematically identified putative causal LOAD risk variants in human induced pluripotent stem cells (iPSC)-derived neurons, astrocytes, and microglia (MG) and linked PICALM risk allele to a previously unappreciated MG-specific role of PICALM in lipid droplet (LD) accumulation. ASoC mapping uncovered functional risk variants for 26 LOAD risk loci, mostly MG-specific. At the MG-specific PICALM locus, the LOAD risk allele of rs10792832 reduced transcription factor (PU.1) binding and PICALM expression, impairing the uptake of amyloid beta (Aβ) and myelin debris. Interestingly, MG with PICALM risk allele showed transcriptional enrichment of pathways for cholesterol synthesis and LD formation. Genetic and pharmacological perturbations of MG further established a causal link between the reduced PICALM expression, LD accumulation, and phagocytosis deficits. Our work elucidates the selective LOAD vulnerability in microglia for the PICALM locus through detrimental LD accumulation, providing a neurobiological basis that can be exploited for developing novel clinical interventions.

Genetic variants for head size share genes and pathways with cancer

The size of the human head is highly heritable, but genetic drivers of its variation within the general population remain unmapped. We perform a genome-wide association study on head size (N = 80,890) and identify 67 genetic loci, of which 50 are novel. Neuroimaging studies show that 17 variants affect specific brain areas, but most have widespread effects. Gene set enrichment is observed for various cancers and the p53, Wnt, and ErbB signaling pathways. Genes harboring lead variants are enriched for macrocephaly syndrome genes (37-fold) and high-fidelity cancer genes (9-fold), which is not seen for human height variants. Head size variants are also near genes preferentially expressed in intermediate progenitor cells, neural cells linked to evolutionary brain expansion. Our results indicate that genes regulating early brain and cranial growth incline to neoplasia later in life, irrespective of height. This warrants investigation of clinical implications of the link between head size and cancer.

Design and Rationale of a Two-Armed Randomized Controlled Trial on Yoga/Brisk Walking-Based Lifestyle Modification on Dementia Risk Reduction, and Influence of ApoE Genotypes on the Intervention

Background/Introduction

Though considered a late-onset disease, the 2020 report of the Lancet Commission emphasizes the necessity of conducting primary prevention trials with an approach of never too early in the life course for dementia prevention. Driven by the same notion, we hereby aim to compare the dementia risk reduction potential of two potential interventions, 48 weeks (12 months) of yoga and brisk walking, in middle-aged high-risk subjects.

Design

A randomized controlled trial.

Setting

Community in India.

Participants

In total, 323 at-risk dementia subjects will be recruited from community settings through health awareness camps and door-to-door surveys across Delhi, India. Participants will be randomized into yoga or brisk-walking groups (1:1). The yoga intervention group will receive 60 contact yoga sessions per 60-min/day at the community parks, followed by continued tele-supervised home practice, further followed by at-home self-practice, and will be tested at 3-time points (baseline, 24-week and 48-week, post-randomization) to test the efficacy of the intervention. The control group will be asked to do brisk walking daily for 45 minutes at their convenience, followed by weekly telephone follow-ups. Applying the intention-to-treat principle, the primary endpoint will be the change from baseline at the 12th month in the Cardiovascular Risk Factors, Aging, and Dementia (CAIDE) Scores. Secondary outcomes will include the composite scores derived from a comprehensive neuropsychology battery, comprising the Trail Making Test, Digit Span Test, N Back, Color Trail, Animal Fluency Test, COWA (Controlled Oral Word Association Test), and Digit Symbol Substitution. The primary outcome will be analyzed using mixed-effect models for repeated measures, adjusted for covariates as fixed effects. The study has been prospectively registered (CTRI/2023/02/049746) on February 15, 2023. The protocol was conceptualized in 2021 and approved by the Institutional Ethics Committee of SVYASA. Recruitment began in February 2023 and is underway with patient enrollment.

Conclusion

To our knowledge, this is the first controlled trial to investigate the longitudinal effects of a yoga-based intervention on dementia risk reduction using the CAIDE risk score. The findings of this trial will also provide insight into a better understanding of genotype-dependent responses to yoga intervention and open up avenues for understanding the implications of gene-intervention interactions for precision prevention using yoga.

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.

Alzheimer's disease rewires gene coexpression networks coupling different brain regions

Connectome studies have shown how Alzheimer's disease (AD) disrupts functional and structural connectivity among brain regions. But the molecular basis of such disruptions is less studied, with most genomic/transcriptomic studies performing within-brain-region analyses. To inspect how AD rewires the correlation structure among genes in different brain regions, we performed an Inter-brain-region Differential Correlation (Inter-DC) analysis of RNA-seq data from Mount Sinai Brain Bank on four brain regions (frontal pole, superior temporal gyrus, parahippocampal gyrus and inferior frontal gyrus, comprising 264 AD and 372 control human post-mortem samples). An Inter-DC network was assembled from all pairs of genes across two brain regions that gained (or lost) correlation strength in the AD group relative to controls at FDR 1%. The differentially correlated (DC) genes in this network complemented known differentially expressed genes in AD, and likely reflects cell-intrinsic changes since we adjusted for cell compositional effects. Each brain region used a distinctive set of DC genes when coupling with other regions, with parahippocampal gyrus showing the most rewiring, consistent with its known vulnerability to AD. The Inter-DC network revealed master dysregulation hubs in AD (at genes ZKSCAN1, SLC5A3, RCC1, IL17RB, PLK4, etc.), inter-region gene modules enriched for known AD pathways (synaptic signaling, endocytosis, etc.), and candidate signaling molecules that could mediate region-region communication. The Inter-DC network generated in this study is a valuable resource of gene pairs, pathways and signaling molecules whose inter-brain-region functional coupling is disrupted in AD, thereby offering a new perspective of AD etiology.

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.

MVMRmode: Introducing an R package for plurality valid estimators for multivariable Mendelian randomisation

BACKGROUND

Mendelian randomisation (MR) is the use of genetic variants as instrumental variables. Mode-based estimators (MBE) are one of the most popular types of estimators used in univariable-MR studies and is often used as a sensitivity analysis for pleiotropy. However, because there are no plurality valid regression estimators, modal estimators for multivariable-MR have been under-explored.

METHODS

We use the residual framework for multivariable-MR to introduce two multivariable modal estimators: multivariable-MBE, which uses IVW to create residuals fed into a traditional plurality valid estimator, and an estimator which instead has the residuals fed into the contamination mixture method (CM), multivariable-CM. We then use Monte-Carlo simulations to explore the performance of these estimators when compared to existing ones and re-analyse the data used by Grant and Burgess (2021) looking at the causal effect of intelligence, education, and household income on Alzheimer's disease as an applied example.

RESULTS

In our simulation, we found that multivariable-MBE was generally too variable to be much use. Multivariable-CM produced more precise estimates on the other hand. Multivariable-CM performed better than MR-Egger in almost all settings, and Weighted Median under balanced pleiotropy. However, it underperformed Weighted Median when there was a moderate amount of directional pleiotropy. Our re-analysis supported the conclusion of Grant and Burgess (2021), that intelligence had a protective effect on Alzheimer's disease, while education, and household income do not have a causal effect.

CONCLUSIONS

Here we introduced two, non-regression-based, plurality valid estimators for multivariable MR. Of these, "multivariable-CM" which uses IVW to create residuals fed into a contamination-mixture model, performed the best. This estimator uses a plurality of variants valid assumption, and appears to provide precise and unbiased estimates in the presence of balanced pleiotropy and small amounts of directional pleiotropy.

Annotation of nuclear lncRNAs based on chromatin interactions

The human genome is pervasively transcribed and produces a wide variety of long non-coding RNAs (lncRNAs), constituting the majority of transcripts across human cell types. Some specific nuclear lncRNAs have been shown to be important regulatory components acting locally. As RNA-chromatin interaction and Hi-C chromatin conformation data showed that chromatin interactions of nuclear lncRNAs are determined by the local chromatin 3D conformation, we used Hi-C data to identify potential target genes of lncRNAs. RNA-protein interaction data suggested that nuclear lncRNAs act as scaffolds to recruit regulatory proteins to target promoters and enhancers. Nuclear lncRNAs may therefore play a role in directing regulatory factors to locations spatially close to the lncRNA gene. We provide the analysis results through an interactive visualization web portal at https://fantom.gsc.riken.jp/zenbu/reports/#F6_3D_lncRNA.

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.

A comparative study of structural variant calling in WGS from Alzheimer's disease families

Detecting structural variants (SVs) in whole-genome sequencing poses significant challenges. We present a protocol for variant calling, merging, genotyping, sensitivity analysis, and laboratory validation for generating a high-quality SV call set in whole-genome sequencing from the Alzheimer's Disease Sequencing Project comprising 578 individuals from 111 families. Employing two complementary pipelines, Scalpel and Parliament, for SV/indel calling, we assessed sensitivity through sample replicates (N = 9) with in silico variant spike-ins. We developed a novel metric, D-score, to evaluate caller specificity for deletions. The accuracy of deletions was evaluated by Sanger sequencing. We generated a high-quality call set of 152,301 deletions of diverse sizes. Sanger sequencing validated 114 of 146 detected deletions (78.1%). Scalpel excelled in accuracy for deletions ≤100 bp, whereas Parliament was optimal for deletions >900 bp. Overall, 83.0% and 72.5% of calls by Scalpel and Parliament were validated, respectively, including all 11 deletions called by both Parliament and Scalpel between 101 and 900 bp. Our flexible protocol successfully generated a high-quality deletion call set and a truth set of Sanger sequencing-validated deletions with precise breakpoints spanning 1-17,000 bp.

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.

Targeting terminal pathway reduces brain complement activation, amyloid load and synapse loss, and improves cognition in a mouse model of dementia

Complement is dysregulated in the brain in Alzheimer's Disease and in mouse models of Alzheimer's disease. Each of the complement derived effectors, opsonins, anaphylatoxins and membrane attack complex (MAC), have been implicated as drivers of disease but their relative contributions remain unclarified. Here we have focussed on the MAC, a lytic and pro-inflammatory effector, in the AppNL-G-F mouse amyloidopathy model. To test the role of MAC, we back-crossed to generate AppNL-G-F mice deficient in C7, an essential MAC component. C7 deficiency ablated MAC formation, reduced synapse loss and amyloid load and improved cognition compared to complement-sufficient AppNL-G-F mice at 8-10 months age. Adding back C7 caused increased MAC formation in brain and an acute loss of synapses in C7-deficient AppNL-G-F mice. To explore whether C7 was a viable therapeutic target, a C7-blocking monoclonal antibody was administered systemically for one month in AppNL-G-F mice aged 8-9 months. Treatment reduced brain MAC and amyloid deposition, increased synapse density and improved cognitive performance compared to isotype control-treated AppNL-G-F mice. The findings implicate MAC as a driver of pathology and highlight the potential for complement inhibition at the level of MAC as a therapy in Alzheimer's disease.

Examination of the shared genetic architecture between multiple sclerosis and systemic lupus erythematosus facilitates discovery of novel lupus risk loci

Systemic Lupus Erythematosus (SLE) is an autoimmune disease with heterogeneous manifestations, including neurological and psychiatric symptoms. Genetic association studies in SLE have been hampered by insufficient sample size and limited power compared to many other diseases. Multiple Sclerosis (MS) is a chronic relapsing autoimmune disease of the central nervous system (CNS) that also manifests neurological and immunological features. Here, we identify a method of leveraging large-scale genome wide association studies (GWAS) in MS to identify novel genetic risk loci in SLE. Statistical genetic comparison methods including linkage disequilibrium score regression (LDSC) and cross-phenotype association analysis (CPASSOC) to identify genetic overlap in disease pathophysiology, traditional 2-sample and novel PPI-based mendelian randomization to identify causal associations and Bayesian colocalization were applied to association studies conducted in MS to facilitate discovery in the smaller, more limited datasets available for SLE. Pathway analysis using SNP-to-gene mapping identified biological networks composed of molecular pathways with causal implications for CNS disease in SLE specifically, as well as pathways likely causal of both pathologies, providing key insights for therapeutic selection.

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.

Diagnosis-Guided Deep Subspace Clustering Association Study for Pathogenetic Markers Identification of Alzheimer's Disease Based on Comparative Atlases

The roles of brain region activities and genotypic functions in the pathogenesis of Alzheimer's disease (AD) remain unclear. Meanwhile, current imaging genetics methods are difficult to identify potential pathogenetic markers by correlation analysis between brain network and genetic variation. To discover disease-related brain connectome from the specific brain structure and the fine-grained level, based on the Automated Anatomical Labeling (AAL) and human Brainnetome atlases, the functional brain network is first constructed for each subject. Specifically, the upper triangle elements of the functional connectivity matrix are extracted as connectivity features. The clustering coefficient and the average weighted node degree are developed to assess the significance of every brain area. Since the constructed brain network and genetic data are characterized by non-linearity, high-dimensionality, and few subjects, the deep subspace clustering algorithm is proposed to reconstruct the original data. Our multilayer neural network helps capture the non-linear manifolds, and subspace clustering learns pairwise affinities between samples. Moreover, most approaches in neuroimaging genetics are unsupervised learning, neglecting the diagnostic information related to diseases. We presented a label constraint with diagnostic status to instruct the imaging genetics correlation analysis. To this end, a diagnosis-guided deep subspace clustering association (DDSCA) method is developed to discover brain connectome and risk genetic factors by integrating genotypes with functional network phenotypes. Extensive experiments prove that DDSCA achieves superior performance to most association methods and effectively selects disease-relevant genetic markers and brain connectome at the coarse-grained and fine-grained levels.

Serotonergic dysfunction may mediate the relationship between alcohol consumption and Alzheimer's disease

The impact of Alzheimer's disease (AD) and its related dementias is rapidly expanding, and its mitigation remains an urgent social and technical challenge. To date there are no effective treatments or interventions for AD, but recent studies suggest that alcohol consumption is correlated with the risk of developing dementia. In this review, we synthesize data from preclinical, clinical, and epidemiological models to evaluate the combined role of alcohol consumption and serotonergic dysfunction in AD, underscoring the need for further research on this topic. We first discuss the limitations inherent to current data-collection methods, and how neuropsychiatric symptoms common among AD, alcohol use disorder, and serotonergic dysfunction may mask their co-occurrence. We additionally describe how excess alcohol consumption may accelerate the development of AD via direct effects on serotonergic function, and we explore the roles of neuroinflammation and proteostasis in mediating the relationship between serotonin, alcohol consumption, and AD. Lastly, we argue for a shift in current research to disentangle the pathogenic effects of alcohol on early-affected brainstem structures in AD.

Memory circuits in dementia: The engram, hippocampal neurogenesis and Alzheimer's disease

Here, we provide an in-depth consideration of our current understanding of engrams, spanning from molecular to network levels, and hippocampal neurogenesis, in health and Alzheimer's disease (AD). This review highlights novel findings in these emerging research fields and future research directions for novel therapeutic avenues for memory failure in dementia. Engrams, memory in AD, and hippocampal neurogenesis have each been extensively studied. The integration of these topics, however, has been relatively less deliberated, and is the focus of this review. We primarily focus on the dentate gyrus (DG) of the hippocampus, which is a key area of episodic memory formation. Episodic memory is significantly impaired in AD, and is also the site of adult hippocampal neurogenesis. Advancements in technology, especially opto- and chemogenetics, have made sophisticated manipulations of engram cells possible. Furthermore, innovative methods have emerged for monitoring neurons, even specific neuronal populations, in vivo while animals engage in tasks, such as calcium imaging. In vivo calcium imaging contributes to a more comprehensive understanding of engram cells. Critically, studies of the engram in the DG using these technologies have shown the important contribution of hippocampal neurogenesis for memory in both health and AD. Together, the discussion of these topics provides a holistic perspective that motivates questions for future research.

G-protein coupled receptors regulates Tauopathy in neurodegeneration

In Alzheimer's disease, the microtubule-associated protein, Tau misfolds to form aggregates and filaments in the intra- and extracellular region of neuronal cells. Microglial cells are the resident brain macrophage cells involved in constant surveillance and activated by the extracellular deposits. Purinergic receptors are involved in the chemotactic migration of microglial cells towards the site of inflammation. From our recent study, we have observed that the microglial P2Y12 receptor is involved in phagocytosis of full-length Tau species such as monomers, oligomers and aggregates by actin-driven chemotaxis. This study shows the interaction of repeat-domain of Tau (TauRD) with the microglial P2Y12 receptor and the corresponding residues for interaction have been analyzed by various in-silico approaches. In the cellular studies, TauRD was found to interact with microglial P2Y12R and induces its cellular expression confirmed by co-immunoprecipitation and western blot analysis. Furthermore, the P2Y12R-mediated TauRD internalization has demonstrated activation of microglia with an increase in the Iba1 level, and TauRD becomes accumulated at the peri-nuclear region for the degradation.

Escape from X-chromosome inactivation and sex differences in Alzheimer's disease

Sex differences exist in the onset and progression of Alzheimer's disease. Globally, women have a higher prevalence, while men with Alzheimer's disease experience earlier mortality and more pronounced cognitive decline than women. The cause of sex differences in Alzheimer's disease remains unclear. Accumulating evidence suggests the potential role of X-linked genetic factors in the sex difference of Alzheimer's disease (AD). During embryogenesis, a remarkable process known as X-chromosome inactivation (XCI) occurs in females, leading to one of the X chromosomes undergoing transcriptional inactivation, which balances the effects of two X chromosomes in females. Nevertheless, certain genes exceptionally escape from XCI, which provides a basis for dual expression dosage of specific genes in females. Based on recent research findings, we explore key escape genes and their potential therapeutic use associated with Alzheimer's disease. Also, we discuss their possible role in driving the sex differences in Alzheimer's disease. This will provide new perspectives for precision medicine and gender-specific treatment of AD.

Regulation of human microglial gene expression and function via RNAase-H active antisense oligonucleotides in vivo in Alzheimer's disease

BACKGROUND

Microglia play important roles in maintaining brain homeostasis and neurodegeneration. The discovery of genetic variants in genes predominately or exclusively expressed in myeloid cells, such as Apolipoprotein E (APOE) and triggering receptor expressed on myeloid cells 2 (TREM2), as the strongest risk factors for Alzheimer's disease (AD) highlights the importance of microglial biology in the brain. The sequence, structure and function of several microglial proteins are poorly conserved across species, which has hampered the development of strategies aiming to modulate the expression of specific microglial genes. One way to target APOE and TREM2 is to modulate their expression using antisense oligonucleotides (ASOs).

METHODS

In this study, we identified, produced, and tested novel, selective and potent ASOs for human APOE and TREM2. We used a combination of in vitro iPSC-microglia models, as well as microglial xenotransplanted mice to provide proof of activity in human microglial in vivo.

RESULTS

We proved their efficacy in human iPSC microglia in vitro, as well as their pharmacological activity in vivo in a xenografted microglia model. We demonstrate ASOs targeting human microglia can modify their transcriptional profile and their response to amyloid-β plaques in vivo in a model of AD.

CONCLUSIONS

This study is the first proof-of-concept that human microglial can be modulated using ASOs in a dose-dependent manner to manipulate microglia phenotypes and response to neurodegeneration in vivo.

Explaining the Variability of Alzheimer Disease Fluid Biomarker Concentrations in Memory Clinic Patients Without Dementia

BACKGROUND AND OBJECTIVES

Patients' comorbidities can affect Alzheimer disease (AD) blood biomarker concentrations. Because a limited number of factors have been explored to date, our aim was to assess the proportion of the variance in fluid biomarker levels explained by the clinical features of AD and by a large number of non-AD-related factors.

METHODS

MEMENTO enrolled 2,323 individuals with cognitive complaints or mild cognitive impairment in 26 French memory clinics. Baseline evaluation included clinical and neuropsychological assessments, brain MRI, amyloid-PET, CSF (optional), and blood sampling. Blood biomarker levels were determined using the Simoa-HDX analyzer. We performed linear regression analysis of the clinical features of AD (cognition, AD genetic risk score, and brain atrophy) to model biomarker concentrations. Next, we added covariates among routine biological tests, inflammatory markers, demographic and behavioral determinants, treatments, comorbidities, and preanalytical sample handling in final models using both stepwise selection processes and least absolute shrinkage and selection operator (LASSO).

RESULTS

In total, 2,257 participants were included in the analysis (median age 71.7, 61.8% women, 55.2% with high educational levels). For blood biomarkers, the proportion of variance explained by clinical features of AD was 13.7% for neurofilaments (NfL), 11.4% for p181-tau, 3.0% for Aβ-42/40, and 1.4% for total-tau. In final models accounting for non-AD-related factors, the variance was mainly explained by age, routine biological tests, inflammatory markers, and preanalytical sample handling. In CSF, the proportion of variance explained by clinical features of AD was 24.8% for NfL, 22.3% for Aβ-42/40, 19.8% for total-tau, and 17.2% for p181-tau. In contrast to blood biomarkers, the largest proportion of variance was explained by cognition after adjustment for covariates. The covariates that explained the largest proportion of variance were also the most frequently selected with LASSO. The performance of blood biomarkers for predicting A+ and T+ status (PET or CSF) remained unchanged after controlling for drivers of variance.

DISCUSSION

This comprehensive analysis demonstrated that the variance in AD blood biomarker concentrations was mainly explained by age, with minor contributions from cognition, brain atrophy, and genetics, conversely to CSF measures. These results challenge the use of blood biomarkers as isolated stand-alone biomarkers for AD.

Dissecting the shared genetic architecture between Alzheimer's disease and frailty: a cross-trait meta-analyses of genome-wide association studies

Introduction: Frailty is the most common medical condition affecting the aging population, and its prevalence increases in the population aged 65 or more. Frailty is commonly diagnosed using the frailty index (FI) or frailty phenotype (FP) assessments. Observational studies have indicated the association of frailty with Alzheimer's disease (AD). However, the shared genetic and biological mechanism of these comorbidity has not been studied. Methods: To assess the genetic relationship between AD and frailty, we examined it at single nucleotide polymorphism (SNP), gene, and pathway levels. Results: Overall, 16 genome-wide significant loci (15 unique loci) (p meta-analysis < 5 × 10-8) and 22 genes (21 unique genes) were identified between AD and frailty using cross-trait meta-analysis. The 8 shared loci implicated 11 genes: CLRN1-AS1, CRHR1, FERMT2, GRK4, LINC01929, LRFN2, MADD, RP11-368P15.1, RP11-166N6.2, RNA5SP459, and ZNF652 between AD and FI, and 8 shared loci between AD and FFS implicated 11 genes: AFF3, C1QTNF4, CLEC16A, FAM180B, FBXL19, GRK4, LINC01104, MAD1L1, RGS12, ZDHHC5, and ZNF521. The loci 4p16.3 (GRK4) was identified in both meta-analyses. The colocalization analysis supported the results of our meta-analysis in these loci. The gene-based analysis revealed 80 genes between AD and frailty, and 4 genes were initially identified in our meta-analyses: C1QTNF4, CRHR1, MAD1L1, and RGS12. The pathway analysis showed enrichment for lipoprotein particle plasma, amyloid fibril formation, protein kinase regulator, and tau protein binding. Conclusion: Overall, our results provide new insights into the genetics of AD and frailty, suggesting the existence of non-causal shared genetic mechanisms between these conditions.

Investigating the brain's neurochemical profile at midlife in relation to dementia risk factors

Changes in the brain's physiology in Alzheimer's disease are thought to occur early in the disease's trajectory. In this study our aim was to investigate the brain's neurochemical profile in a midlife cohort in relation to risk factors for future dementia using single voxel proton magnetic resonance spectroscopy. Participants in the multi-site PREVENT-Dementia study (age range 40-59 year old) underwent 3T magnetic resonance spectroscopy with the spectroscopy voxel placed in the posterior cingulate/precuneus region. Using LCModel, we quantified the absolute concentrations of myo-inositol, total N-acetylaspartate, total creatine, choline, glutathione and glutamate-glutamine for 406 participants (mean age 51.1; 65.3% female). Underlying partial volume effects were accounted for by applying a correction for the presence of cerebrospinal fluid in the magnetic resonance spectroscopy voxel. We investigated how metabolite concentrations related to apolipoprotein ɛ4 genotype, dementia family history, a risk score (Cardiovascular Risk Factors, Aging and Incidence of Dementia -CAIDE) for future dementia including non-modifiable and potentially-modifiable factors and dietary patterns (adherence to Mediterranean diet). Dementia family history was associated with decreased total N-acetylaspartate and no differences were found between apolipoprotein ɛ4 carriers and non-carriers. A higher Cardiovascular Risk Factors, Aging, and Incidence of Dementia score related to higher myo-inositol, choline, total creatine and glutamate-glutamine, an effect which was mainly driven by older age and a higher body mass index. Greater adherence to the Mediterranean diet was associated with lower choline, myo-inositol and total creatine; these effects did not survive correction for multiple comparisons. The observed associations suggest that at midlife the brain demonstrates subtle neurochemical changes in relation to both inherited and potentially modifiable risk factors for future dementia.

Epigenetic dysregulation in Alzheimer's disease peripheral immunity

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

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

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

Shared genetic aetiology of Alzheimer's disease and age-related macular degeneration by APOC1 and APOE genes

Background

Alzheimer's disease (AD) and age-related macular degeneration (AMD) share similar pathological features, suggesting common genetic aetiologies between the two. Investigating gene associations between AD and AMD may provide useful insights into the underlying pathogenesis and inform integrated prevention and treatment for both diseases.

Methods

A stratified quantile-quantile (QQ) plot was constructed to detect the pleiotropy among AD and AMD based on genome-wide association studies data from 17 008 patients with AD and 30 178 patients with AMD. A Bayesian conditional false discovery rate-based (cFDR) method was used to identify pleiotropic genes. UK Biobank was used to verify the pleiotropy analysis. Biological network and enrichment analysis were conducted to explain the biological reason for pleiotropy phenomena. A diagnostic test based on gene expression data was used to predict biomarkers for AD and AMD based on pleiotropic genes and their regulators.

Results

Significant pleiotropy was found between AD and AMD (significant leftward shift on QQ plots). APOC1 and APOE were identified as pleiotropic genes for AD-AMD (cFDR <0.01). Network analysis revealed that APOC1 and APOE occupied borderline positions on the gene co-expression networks. Both APOC1 and APOE genes were enriched on the herpes simplex virus 1 infection pathway. Further, machine learning-based diagnostic tests identified that APOC1, APOE (areas under the curve (AUCs) >0.65) and their upstream regulators, especially ZNF131, ADNP2 and HINFP, could be potential biomarkers for both AD and AMD (AUCs >0.8).

Conclusion

In this study, we confirmed the genetic pleiotropy between AD and AMD and identified APOC1 and APOE as pleiotropic genes. Further, the integration of multiomics data identified ZNF131, ADNP2 and HINFP as novel diagnostic biomarkers for AD and AMD.

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.

Immunological aspects of central neurodegeneration

The etiology of various neurodegenerative disorders that mainly affect the central nervous system including (but not limited to) Alzheimer's disease, Parkinson's disease and Huntington's disease has classically been attributed to neuronal defects that culminate with the loss of specific neuronal populations. However, accumulating evidence suggests that numerous immune effector cells and the products thereof (including cytokines and other soluble mediators) have a major impact on the pathogenesis and/or severity of these and other neurodegenerative syndromes. These observations not only add to our understanding of neurodegenerative conditions but also imply that (at least in some cases) therapeutic strategies targeting immune cells or their products may mediate clinically relevant neuroprotective effects. Here, we critically discuss immunological mechanisms of central neurodegeneration and propose potential strategies to correct neurodegeneration-associated immunological dysfunction with therapeutic purposes.

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.

Differential effects of SORL1 deficiency on the endo-lysosomal network in human neurons and microglia

The endosomal gene SORL1 is a strong Alzheimer's disease (AD) risk gene that harbours loss-of-function variants causative for developing AD. The SORL1 protein SORL1/SORLA is an endosomal receptor that interacts with the multi-protein sorting complex retromer to traffic various cargo through the endo-lysosomal network (ELN). Impairments in endo-lysosomal trafficking are an early cellular symptom in AD and a novel therapeutic target. However, the cell types of the central nervous system are diverse and use the ELN differently. If this pathway is to be effectively therapeutically targeted, understanding how key molecules in the ELN function in various cell types and how manipulating them affects cell-type specific responses relative to AD is essential. Here, we discuss an example where deficiency of SORL1 expression in a human model leads to stress on early endosomes and recycling endosomes in neurons, but preferentially leads to stress on lysosomes in microglia. The differences observed in these organelles could relate to the unique roles of these cells in the brain as neurons are professional secretory cells and microglia are professional phagocytic cells. Experiments to untangle these differences are fundamental to advancing the understanding of cell biology in AD and elucidating important pathways for therapeutic development. Human-induced pluripotent stem cell models are a valuable platform for such experiments. This article is part of a discussion meeting issue 'Understanding the endo-lysosomal network in neurodegeneration'.

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'.

Endo-lysosomal dysfunction in neurodegenerative diseases: opinion on current progress and future direction in the use of exosomes as biomarkers

Over the past two decades, increased research has highlighted the connection between endosomal trafficking defects and neurodegeneration. The endo-lysosomal network is an important, complex cellular system specialized in the transport of proteins, lipids, and other metabolites, essential for cell homeostasis. Disruption of this pathway is linked to a wide range of neurodegenerative diseases, including Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, Huntington's disease and frontotemporal dementia. Furthermore, there is strong evidence that defects in this pathway create opportunities for diagnostic and therapeutic intervention. In this Opinion piece, we concisely address the role of endo-lysosomal dysfunction in five neurodegenerative diseases and discuss how future research can investigate this intracellular pathway, including extracellular vesicles with a specific focus on exosomes for the identification of novel disease biomarkers. This article is part of a discussion meeting issue 'Understanding the endo-lysosomal network in neurodegeneration'.

Human brain glycoform coregulation network and glycan modification alterations in Alzheimer's disease

Despite the importance of protein glycosylation to brain health, current knowledge of glycosylated proteoforms or glycoforms in human brain and their alterations in Alzheimer's disease (AD) is limited. Here, we report a proteome-wide glycoform profiling study of human AD and control brains using intact glycopeptide-based quantitative glycoproteomics coupled with systems biology. Our study identified more than 10,000 human brain N-glycoforms from nearly 1200 glycoproteins and uncovered disease signatures of altered glycoforms and glycan modifications, including reduced sialylation and N-glycan branching and elongation as well as elevated mannosylation and N-glycan truncation in AD. Network analyses revealed a higher-order organization of brain glycoproteome into networks of coregulated glycoforms and glycans and discovered glycoform and glycan modules associated with AD clinical phenotype, amyloid-β accumulation, and tau pathology. Our findings provide valuable insights into disease pathogenesis and a rich resource of glycoform and glycan changes in AD and pave the way forward for developing glycosylation-based therapies and biomarkers for AD.

Regulation of inositol 5-phosphatase activity by the C2 domain of SHIP1 and SHIP2

SHIP1, an inositol 5-phosphatase, plays a central role in cellular signaling. As such, it has been implicated in many conditions. Exploiting SHIP1 as a drug target will require structural knowledge and the design of selective small molecules. We have determined apo, and magnesium and phosphate-bound structures of the phosphatase and C2 domains of SHIP1. The C2 domains of SHIP1 and the related SHIP2 modulate the activity of the phosphatase domain. To understand the mechanism, we performed activity assays, hydrogen-deuterium exchange mass spectrometry, and molecular dynamics on SHIP1 and SHIP2. Our findings demonstrate that the influence of the C2 domain is more pronounced for SHIP2 than SHIP1. We determined 91 structures of SHIP1 with fragments bound, with some near the interface between the two domains. We performed a mass spectrometry screen and determined four structures with covalent fragments. These structures could act as starting points for the development of potent, selective probes.

Unveiling Gene Interactions in Alzheimer's Disease by Integrating Genetic and Epigenetic Data with a Network-Based Approach

Alzheimer's Disease (AD) is a complex disease and the leading cause of dementia in older people. We aimed to uncover aspects of AD's pathogenesis that may contribute to drug repurposing efforts by integrating DNA methylation and genetic data. Implementing the network-based tool, a dense module search of genome-wide association studies (dmGWAS), we integrated a large-scale GWAS dataset with DNA methylation data to identify gene network modules associated with AD. Our analysis yielded 286 significant gene network modules. Notably, the foremost module included the BIN1 gene, showing the largest GWAS signal, and the GNAS gene, the most significantly hypermethylated. We conducted Web-based Cell-type-Specific Enrichment Analysis (WebCSEA) on genes within the top 10% of dmGWAS modules, highlighting monocyte as the most significant cell type (p < 5 × 10-12). Functional enrichment analysis revealed Gene Ontology Biological Process terms relevant to AD pathology (adjusted p < 0.05). Additionally, drug target enrichment identified five FDA-approved targets (p-value = 0.03) for further research. In summary, dmGWAS integration of genetic and epigenetic signals unveiled new gene interactions related to AD, offering promising avenues for future studies.

Polygenic burden and its association with baseline cognitive function and postoperative cognitive outcome in temporal lobe epilepsy

OBJECTIVE

Demographic and disease factors are associated with cognitive deficits and postoperative cognitive declines in adults with pharmacoresistant temporal lobe epilepsy (TLE), but the role of genetic factors in cognition in TLE is not well understood. Polygenic scores (PGS) for neurological and neuropsychiatric disorders and IQ have been associated with cognition in patient and healthy populations. In this exploratory study, we examined the relationship between PGS for Alzheimer's disease (AD), depression, and IQ and cognitive outcomes in adults with TLE.

METHODS

202 adults with pharmacoresistant TLE had genotyping and completed neuropsychological evaluations as part of a presurgical work-up. A subset (n = 116) underwent temporal lobe resection and returned for postoperative cognitive testing. Logistic regression was used to determine if PGS for AD, depression, and IQ predicted baseline domain-specific cognitive function and cognitive phenotypes as well as postoperative language and memory decline.

RESULTS

No significant findings survived correction for multiple comparisons. Prior to correction, higher PGS for AD and depression (i.e., increased genetic risk for the disorder), but lower PGS for IQ (i.e., decreased genetic likelihood of high IQ) appeared possibly associated with baseline cognitive impairment in TLE. In comparison, higher PGS for AD and IQ appeared as possible risk factors for cognitive decline following temporal lobectomy, while the possible relationship between PGS for depression and post-operative cognitive outcome was mixed.

SIGNIFICANCE

We did not observe any relationships of large effect between PGS and cognitive function or postsurgical outcome; however, results highlight several promising trends in the data that warrant future investigation in larger samples better powered to detect small genetic effects.

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

INTRODUCTION

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

METHODS

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

RESULTS

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

DISCUSSION

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

HIGHLIGHTS

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

Genetic associations with dementia-related proteinopathy: Application of item response theory

INTRODUCTION

Although dementia-related proteinopathy has a strong negative impact on public health, and is highly heritable, understanding of the related genetic architecture is incomplete.

METHODS

We applied multidimensional generalized partial credit modeling (GPCM) to test genetic associations with dementia-related proteinopathies. Data were analyzed to identify candidate single nucleotide variants for the following proteinopathies: Aβ, tau, α-synuclein, and TDP-43.

RESULTS

Final included data comprised 966 participants with neuropathologic and WGS data. Three continuous latent outcomes were constructed, corresponding to TDP-43-, Aβ/Tau-, and α-synuclein-related neuropathology endophenotype scores. This approach helped validate known genotype/phenotype associations: for example, TMEM106B and GRN were risk alleles for TDP-43 pathology; and GBA for α-synuclein/Lewy bodies. Novel suggestive proteinopathy-linked alleles were also discovered, including several (SDHAF1, TMEM68, and ARHGEF28) with colocalization analyses and/or high degrees of biologic credibility.

DISCUSSION

A novel methodology using GPCM enabled insights into gene candidates for driving misfolded proteinopathies.

HIGHLIGHTS

Latent factor scores for proteinopathies were estimated using a generalized partial credit model. The three latent continuous scores corresponded well with proteinopathy severity. Novel genes associated with proteinopathies were identified. Several genes had high degrees of biologic credibility for dementia risk factors.

Detecting time-varying genetic effects in Alzheimer's disease using a longitudinal genome-wide association studies model

INTRODUCTION

The development and progression of Alzheimer's disease (AD) is a complex process, during which genetic influences on phenotypes may also change. Incorporating longitudinal phenotypes in genome-wide association studies (GWAS) could unmask these genetic loci.

METHODS

We conducted a longitudinal GWAS using a varying coefficient test to identify age-dependent single nucleotide polymorphisms (SNPs) in AD. Data from 1877 Alzheimer's Neuroimaging Data Initiative participants, including impairment status and amyloid positron emission tomography (PET) scan standardized uptake value ratio (SUVR) scores, were analyzed using a retrospective varying coefficient mixed model association test (RVMMAT).

RESULTS

RVMMAT identified 244 SNPs with significant time-varying effects on AD impairment status, with 12 SNPs on chromosome 19 validated using National Alzheimer's Coordinating Center data. Age-stratified analyses showed these SNPs' effects peaked between 70 and 80 years. Additionally, 73 SNPs were linked to longitudinal amyloid accumulation changes. Pathway analyses implicated immune and neuroinflammation-related disruptions.

DISCUSSION

Our findings demonstrate that longitudinal GWAS models can uncover time-varying genetic signals in AD.

Highlights

Identify time-varying genetic effects using a longitudinal GWAS model in AD.Illustrate age-dependent genetic effects on both diagnoses and amyloid accumulation.Replicate time-varying effect of APOE in a second dataset.

T cell infiltration mediates neurodegeneration and cognitive decline in Alzheimer's disease

Alzheimer's disease (AD) is a prevalent neurodegenerative disorder with pathological features of β-amyloid (Aβ) and hyperphosphorylated tau protein accumulation in the brain, often accompanied by cognitive decline. So far, our understanding of the extent and role of adaptive immune responses in AD has been quite limited. T cells, as essential members of the adaptive immune system, exhibit quantitative and functional abnormalities in the brains of AD patients. Dysfunction of the blood-brain barrier (BBB) in AD is considered one of the factors leading to T cell infiltration. Moreover, the degree of neuronal loss in AD is correlated with the quantity of T cells. We first describe the differentiation and subset functions of peripheral T cells in AD patients and provide an overview of the key findings related to BBB dysfunction and how T cells infiltrate the brain parenchyma through the BBB. Furthermore, we emphasize the risk factors associated with AD, including Aβ, Tau protein, microglial cells, apolipoprotein E (ApoE), and neuroinflammation. We discuss their regulation of T cell activation and proliferation, as well as the connection between T cells, neurodegeneration, and cognitive decline. Understanding the innate immune response is crucial for providing comprehensive personalized therapeutic strategies for AD.

Cognitive Decline in Ageing and Disease: Risk factors, Genetics and Treatments

Aging is the primary risk factor for cognitive decline, impacting multiple cognitive domains and significantly elevating the risk of conditions such as mild cognitive impairment and dementia. In addition to aging, several diseases contribute to cognitive decline. Alzheimer's disease, a progressive neurodegenerative disorder, leads to the loss of neurons and synapses in the brain, resulting in a profound decline in cognitive abilities and functional capacity. Several studies provide compelling evidence that modifiable lifestyle factors play a crucial role in influencing cognitive health. Adopting healthier behaviors has been shown to significantly reduce the risk of cognitive decline. Genetic factors also play a crucial role in cognitive decline, with several genes being identified that influence the risk of developing conditions like Alzheimer's disease and other dementias. Long-term use of opioids and cocaine is also associated with cognitive decline, affecting functions such as memory and executive processes. Understanding the factors contributing to cognitive decline in aging and disease is essential for developing strategies to mitigate its impact. The drugs available to treat patients with cognitive decline due to advanced aging and drug abuse are also summarize.

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.

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.

Interpretation of 10 years of Alzheimer's disease genetic findings in the perspective of statistical heterogeneity

Common genetic variants and susceptibility loci associated with Alzheimer's disease (AD) have been discovered through large-scale genome-wide association studies (GWAS), GWAS by proxy (GWAX) and meta-analysis of GWAS and GWAX (GWAS+GWAX). However, due to the very low repeatability of AD susceptibility loci and the low heritability of AD, these AD genetic findings have been questioned. We summarize AD genetic findings from the past 10 years and provide a new interpretation of these findings in the context of statistical heterogeneity. We discovered that only 17% of AD risk loci demonstrated reproducibility with a genome-wide significance of P < 5.00E-08 across all AD GWAS and GWAS+GWAX datasets. We highlighted that the AD GWAS+GWAX with the largest sample size failed to identify the most significant signals, the maximum number of genome-wide significant genetic variants or maximum heritability. Additionally, we identified widespread statistical heterogeneity in AD GWAS+GWAX datasets, but not in AD GWAS datasets. We consider that statistical heterogeneity may have attenuated the statistical power in AD GWAS+GWAX and may contribute to explaining the low repeatability (17%) of genome-wide significant AD susceptibility loci and the decreased AD heritability (40-2%) as the sample size increased. Importantly, evidence supports the idea that a decrease in statistical heterogeneity facilitates the identification of genome-wide significant genetic loci and contributes to an increase in AD heritability. Collectively, current AD GWAX and GWAS+GWAX findings should be meticulously assessed and warrant additional investigation, and AD GWAS+GWAX should employ multiple meta-analysis methods, such as random-effects inverse variance-weighted meta-analysis, which is designed specifically for statistical heterogeneity.

Neuroinflammation of Microglial Regulation in Alzheimer's Disease: Therapeutic Approaches

Alzheimer's disease (AD) is a complex degenerative disease of the central nervous system that is clinically characterized by a progressive decline in memory and cognitive function. The pathogenesis of AD is intricate and not yet fully understood. Neuroinflammation, particularly microglial activation-mediated neuroinflammation, is believed to play a crucial role in increasing the risk, triggering the onset, and hastening the progression of AD. Modulating microglial activation and regulating microglial energy metabolic disorder are seen as promising strategies to intervene in AD. The application of anti-inflammatory drugs and the targeting of microglia for the prevention and treatment of AD has emerged as a new area of research interest. This article provides a comprehensive review of the role of neuroinflammation of microglial regulation in the development of AD, exploring the connection between microglial energy metabolic disorder, neuroinflammation, and AD development. Additionally, the advancements in anti-inflammatory and microglia-regulating therapies for AD are discussed.