Genome-wide meta-analysis, fine-mapping and integrative prioritization implicate new Alzheimer's disease risk genes

Genome-wide meta-analysis identifies ancestry-specific loci for Alzheimer's disease

INTRODUCTION

Alzheimer's disease (AD) is a devastating neurological disease with complex genetic etiology. Yet most known loci have only identified from the late-onset type AD in populations of European ancestry.

METHODS

We performed a two-stage genome-wide association study (GWAS) of AD totaling 6878 Chinese and 63,926 European individuals.

RESULTS

In addition to the apolipoprotein E (APOE) locus, our GWAS of two independent Chinese samples uncovered three novel AD susceptibility loci (KIAA2013, SLC52A3, and TCN2) and a novel ancestry-specific variant within EGFR (rs1815157). More replicated variants were observed in the Chinese (31%) than in the European samples (15%). In combining genome-wide associations and functional annotations, EGFR and TCN2 were prioritized as two of the most biologically significant genes. Phenome-wide Mendelian randomization suggests that high mean corpuscular hemoglobin concentration might protect against AD.

DISCUSSION

The current study reveals novel AD susceptibility loci, emphasizes the importance of diverse populations in AD genetic research, and advances our understanding of disease etiology.

HIGHLIGHTS

Loci KIAA2013, SLC52A3, and TCN2 were associated with Alzheimer's disease (AD) in Chinese populations. rs1815157 within the EGFR locus was associated with AD in Chinese populations. The genetic architecture of AD varied between Chinese and European populations. EGFR and TCN2 were prioritized as two of the most biologically significant genes. High mean corpuscular hemoglobin concentrations might have protective effects against AD.

Evaluation of polygenic scoring methods in five biobanks shows larger variation between biobanks than methods and finds benefits of ensemble learning

Methods of estimating polygenic scores (PGSs) from genome-wide association studies are increasingly utilized. However, independent method evaluation is lacking, and method comparisons are often limited. Here, we evaluate polygenic scores derived via seven methods in five biobank studies (totaling about 1.2 million participants) across 16 diseases and quantitative traits, building on a reference-standardized framework. We conducted meta-analyses to quantify the effects of method choice, hyperparameter tuning, method ensembling, and the target biobank on PGS performance. We found that no single method consistently outperformed all others. PGS effect sizes were more variable between biobanks than between methods within biobanks when methods were well tuned. Differences between methods were largest for the two investigated autoimmune diseases, seropositive rheumatoid arthritis and type 1 diabetes. For most methods, cross-validation was more reliable for tuning hyperparameters than automatic tuning (without the use of target data). For a given target phenotype, elastic net models combining PGS across methods (ensemble PGS) tuned in the UK Biobank provided consistent, high, and cross-biobank transferable performance, increasing PGS effect sizes (β coefficients) by a median of 5.0% relative to LDpred2 and MegaPRS (the two best-performing single methods when tuned with cross-validation). Our interactively browsable online-results and open-source workflow prspipe provide a rich resource and reference for the analysis of polygenic scoring methods across biobanks.

Eta-secretase-like processing of the amyloid precursor protein (APP) by the rhomboid protease RHBDL4

The amyloid precursor protein (APP) is a key protein in Alzheimer's disease synthesized in the endoplasmic reticulum (ER) and translocated to the plasma membrane where it undergoes proteolytic cleavages by several proteases. Conversely to other known proteases, we previously elucidated rhomboid protease RHBDL4 as a novel APP processing enzyme where several cleavages likely occur already in the ER. Interestingly, the pattern of RHBDL4-derived large APP C-terminal fragments resemble those generated by the η-secretase or MT5-MMP, which was described to generate so called Aη fragments. The similarity in large APP C-terminal fragments between both proteases raised the question whether RHBDL4 may contribute to η-secretase activity and Aη-like fragments. Here, we identified two cleavage sites of RHBDL4 in APP by mass spectrometry, which, intriguingly, lie in close proximity to the MT5-MMP cleavage sites. Indeed, we observed that RHBDL4 generates Aη-like fragments in vitro without contributions of α-, β-, or γ-secretases. Such Aη-like fragments are likely generated in the ER since RHBDL4-derived APP-C-terminal fragments do not reach the cell surface. Inherited, familial APP mutations appear to not affect this processing pathway. In RHBDL4 knockout mice, we observed increased cerebral full length APP in comparison to wild type (WT) in support of RHBDL4 being a physiologically relevant protease for APP. Furthermore, we found secreted Aη fragments in dissociated mixed cortical cultures from WT mice, however significantly less Aη fragments in RHBDL4 knockout cultures. Our data underscores that RHBDL4 contributes to η-secretease-like processing of APP and that RHBDL4 is a physiologically relevant protease for APP.

GRPa-PRS: A risk stratification method to identify genetically-regulated pathways in polygenic diseases

Background

Polygenic risk scores (PRS) are tools used to evaluate an individual's susceptibility to polygenic diseases based on their genetic profile. A considerable proportion of people carry a high genetic risk but evade the disease. On the other hand, some individuals with a low risk of eventually developing the disease. We hypothesized that unknown counterfactors might be involved in reversing the PRS prediction, which might provide new insights into the pathogenesis, prevention, and early intervention of diseases.

Methods

We built a novel computational framework to identify genetically-regulated pathways (GRPas) using PRS-based stratification for each cohort. We curated two AD cohorts with genotyping data; the discovery (disc) and the replication (rep) datasets include 2722 and 2854 individuals, respectively. First, we calculated the optimized PRS model based on the three recent AD GWAS summary statistics for each cohort. Then, we stratified the individuals by their PRS and clinical diagnosis into six biologically meaningful PRS strata, such as AD cases with low/high risk and cognitively normal (CN) with low/high risk. Lastly, we imputed individual genetically-regulated expression (GReX) and identified differential GReX and GRPas between risk strata using gene-set enrichment and variational analyses in two models, with and without APOE effects. An orthogonality test was further conducted to verify those GRPas are independent of PRS risk. To verify the generalizability of other polygenic diseases, we further applied a default model of GRPa-PRS for schizophrenia (SCZ).

Results

For each stratum, we conducted the same procedures in both the disc and rep datasets for comparison. In AD, we identified several well-known AD-related pathways, including amyloid-beta clearance, tau protein binding, and astrocyte response to oxidative stress. Additionally, we discovered resilience-related GRPs that are orthogonal to AD PRS, such as the calcium signaling pathway and divalent inorganic cation homeostasis. In SCZ, pathways related to mitochondrial function and muscle development were highlighted. Finally, our GRPa-PRS method identified more consistent differential pathways compared to another variant-based pathway PRS method.

Conclusions

We developed a framework, GRPa-PRS, to systematically explore the differential GReX and GRPas among individuals stratified by their estimated PRS. The GReX-level comparison among those strata unveiled new insights into the pathways associated with disease risk and resilience. Our framework is extendable to other polygenic complex diseases.

Association between glioma and neurodegenerative diseases risk: a two-sample bi-directional Mendelian randomization analysis

Background

Earlier observational studies have demonstrated a correlation between glioma and the risk of neurodegenerative diseases (NDs), but the causality and direction of their associations remain unclear. The objective of this study was to ascertain the causal link between glioma and NDs using Mendelian randomization (MR) methodology.

Methods

Genome-wide association study (GWAS) data were used in a two-sample bi-directional MR analysis. From the largest meta-analysis GWAS, encompassing 18,169 controls and 12,488 cases, summary statistics data on gliomas was extracted. Summarized statistics for NDs, including Alzheimer's disease (AD), multiple sclerosis (MS), amyotrophic lateral sclerosis (ALS) and Parkinson's disease (PD) were obtained from the GWAS of European ancestry. Inverse variance weighted (IVW) method was elected as the core MR approach with weighted median (WM) method and MR-Egger method as complementary methods. In addition, sensitivity analyses were performed. A Bonferroni correction was used to correct the results.

Results

Genetically predicted glioma had been related to decreased risk of AD. Specifically, for all glioma (IVW: OR = 0.93, 95% CI = 0.90-0.96, p = 4.88 × 10-6) and glioblastoma (GBM) (IVW: OR = 0.93, 95% CI = 0.91-0.95, p = 5.11 × 10-9). We also found that genetically predicted all glioma has a suggestive causative association with MS (IVW: OR = 0.90, 95% CI = 0.81-1.00, p = 0.045). There was no evidence of causal association between glioma and ALS or PD. According to the results of reverse MR analysis, no discernible causal connection of NDs was found on glioma. Sensitivity analyses validated the robustness of the above associations.

Conclusion

We report evidence in support of potential causal associations of different glioma subtypes with AD and MS. More studies are required to uncover the underlying mechanisms of these findings.

Single-nucleus multiomics reveals the disrupted regulatory programs in three brain regions of sporadic early-onset Alzheimer's disease

Sporadic early-onset Alzheimer's disease (sEOAD) represents a significant but less-studied subtype of Alzheimer's disease (AD). Here, we generated a single-nucleus multiome atlas derived from the postmortem prefrontal cortex, entorhinal cortex, and hippocampus of nine individuals with or without sEOAD. Comprehensive analyses were conducted to delineate cell type-specific transcriptomic changes and linked candidate cis- regulatory elements (cCREs) across brain regions. We prioritized seven conservative transcription factors in glial cells in multiple brain regions, including RFX4 in astrocytes and IKZF1 in microglia, which are implicated in regulating sEOAD-associated genes. Moreover, we identified the top 25 altered intercellular signaling between glial cells and neurons, highlighting their regulatory potential on gene expression in receiver cells. We reported 38 cCREs linked to sEOAD-associated genes overlapped with late-onset AD risk loci, and sEOAD cCREs enriched in neuropsychiatric disorder risk loci. This atlas helps dissect transcriptional and chromatin dynamics in sEOAD, providing a key resource for AD research.

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

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

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

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

Fast and flexible joint fine-mapping of multiple traits via the Sum of Single Effects model

We introduce mvSuSiE, a multi-trait fine-mapping method for identifying putative causal variants from genetic association data (individual-level or summary data). mvSuSiE learns patterns of shared genetic effects from data, and exploits these patterns to improve power to identify causal SNPs. Comparisons on simulated data show that mvSuSiE is competitive in speed, power and precision with existing multi-trait methods, and uniformly improves on single-trait fine-mapping (SuSiE) in each trait separately. We applied mvSuSiE to jointly fine-map 16 blood cell traits using data from the UK Biobank. By jointly analyzing the traits and modeling heterogeneous effect sharing patterns, we discovered a much larger number of causal SNPs (>3,000) compared with single-trait fine-mapping, and with narrower credible sets. mvSuSiE also more comprehensively characterized the ways in which the genetic variants affect one or more blood cell traits; 68% of causal SNPs showed significant effects in more than one blood cell type.

Emerging Perspectives on Prime Editor Delivery to the Brain

Prime editing shows potential as a precision genome editing technology, as well as the potential to advance the development of next-generation nanomedicine for addressing neurological disorders. However, turning in prime editors (PEs), which are macromolecular complexes composed of CRISPR/Cas9 nickase fused with a reverse transcriptase and a prime editing guide RNA (pegRNA), to the brain remains a considerable challenge due to physiological obstacles, including the blood-brain barrier (BBB). This review article offers an up-to-date overview and perspective on the latest technologies and strategies for the precision delivery of PEs to the brain and passage through blood barriers. Furthermore, it delves into the scientific significance and possible therapeutic applications of prime editing in conditions related to neurological diseases. It is targeted at clinicians and clinical researchers working on advancing precision nanomedicine for neuropathologies.

Causal associations of antioxidants with Alzheimer's disease and cognitive function: a Mendelian randomisation study

BACKGROUND

Circulating antioxidants are associated with a lower risk of Alzheimer's disease (AD) in observational studies, suggesting potential target areas for intervention. However, whether the associations are causal remains unclear. Here, we studied the causality between antioxidants and AD or cognitive function using two-sample Mendelian randomisation (MR).

METHODS

Single nucleotide polymorphisms strongly (p<5×10-8) associated with antioxidants (vitamin A, vitamin C, zinc, selenium, β-carotene and urate) and outcomes (AD, cognitive performance and reaction time) were obtained from the largest and most recent genome-wide association studies (GWAS). MR inverse variance weighting (IVW) and MR pleiotropy residual sum and outlier test (MR-PRESSO) were used for data analysis.

RESULTS

Higher genetically determined selenium level was associated with 5% higher risk of AD (OR 1.047, 95% CI 1.005 to 1.091, p=0.028) using IVW. Higher genetically determined urate level was associated with worse cognitive performance (β=-0.026, 95% CI -0.044 to -0.008, p=0.005) using MR-PRESSO. No association between the other antioxidants and AD, cognitive performance and reaction time was found. Similar results were found in the sensitivity analyses.

CONCLUSION

Our results suggest that lifelong exposure to higher selenium may be associated with a higher risk of AD, and higher urate levels could be associated with worse cognitive performance. Further analyses using larger GWAS of antioxidants are warranted to confirm these observations. Our results suggest that caution is needed in the interpretation of traditional observational evidence on the neuroprotective effects of antioxidants.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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

Systematic characterization of multi-omics landscape between gut microbial metabolites and GPCRome in Alzheimer's disease

Shifts in the magnitude and nature of gut microbial metabolites have been implicated in Alzheimer's disease (AD), but the host receptors that sense and respond to these metabolites are largely unknown. Here, we develop a systems biology framework that integrates machine learning and multi-omics to identify molecular relationships of gut microbial metabolites with non-olfactory G-protein-coupled receptors (termed the "GPCRome"). We evaluate 1.09 million metabolite-protein pairs connecting 408 human GPCRs and 335 gut microbial metabolites. Using genetics-derived Mendelian randomization and integrative analyses of human brain transcriptomic and proteomic profiles, we identify orphan GPCRs (i.e., GPR84) as potential drug targets in AD and that triacanthine experimentally activates GPR84. We demonstrate that phenethylamine and agmatine significantly reduce tau hyperphosphorylation (p-tau181 and p-tau205) in AD patient induced pluripotent stem cell-derived neurons. This study demonstrates a systems biology framework to uncover the GPCR targets of human gut microbiota in AD and other complex diseases if broadly applied.

Apo and Aβ46-bound γ-secretase structures provide insights into amyloid-β processing by the APH-1B isoform

Deposition of amyloid-β (Aβ) peptides in the brain is a hallmark of Alzheimer's disease. Aβs are generated through sequential proteolysis of the amyloid precursor protein by the γ-secretase complexes (GSECs). Aβ peptide length, modulated by the Presenilin (PSEN) and APH-1 subunits of GSEC, is critical for Alzheimer's pathogenesis. Despite high relevance, mechanistic understanding of the proteolysis of Aβ, and its modulation by APH-1, remain incomplete. Here, we report cryo-EM structures of human GSEC (PSEN1/APH-1B) reconstituted into lipid nanodiscs in apo form and in complex with the intermediate Aβ46 substrate without cross-linking. We find that three non-conserved and structurally divergent APH-1 regions establish contacts with PSEN1, and that substrate-binding induces concerted rearrangements in one of the identified PSEN1/APH-1 interfaces, providing structural basis for APH-1 allosteric-like effects. In addition, the GSEC-Aβ46 structure reveals an interaction between Aβ46 and loop 1PSEN1, and identifies three other H-bonding interactions that, according to functional validation, are required for substrate recognition and efficient sequential catalysis.

Cell-type specific inference from bulk RNA-sequencing data by integrating single cell reference profiles via EPIC-unmix

Cell type specific (CTS) analysis is essential to reveal biological insights obscured in bulk tissue data. However, single-cell (sc) or single-nuclei (sn) resolution data are still cost-prohibitive for large-scale samples. Thus, computational methods to perform deconvolution from bulk tissue data are highly valuable. We here present EPIC-unmix, a novel two-step empirical Bayesian method integrating reference sc/sn RNA-seq data and bulk RNA-seq data from target samples to enhance the accuracy of CTS inference. We demonstrate through comprehensive simulations across three tissues that EPIC-unmix achieved 4.6% - 109.8% higher accuracy compared to alternative methods. By applying EPIC-unmix to human bulk brain RNA-seq data from the ROSMAP and MSBB cohorts, we identified multiple genes differentially expressed between Alzheimer's disease (AD) cases versus controls in a CTS manner, including 57.4% novel genes not identified using similar sample size sc/snRNA-seq data, indicating the power of our in-silico approach. Among the 6-69% overlapping, 83%-100% are in consistent direction with those from sc/snRNA-seq data, supporting the reliability of our findings. EPIC-unmix inferred CTS expression profiles similarly empowers CTS eQTL analysis. Among the novel eQTLs, we highlight a microglia eQTL for AD risk gene AP3B2, obscured in bulk and missed by sc/snRNA-seq based eQTL analysis. The variant resides in a microglia-specific cCRE, forming chromatin loop with AP3B2 promoter region in microglia. Taken together, we believe EPIC-unmix will be a valuable tool to enable more powerful CTS analysis.

Causal effect of blood osteocalcin on the risk of Alzheimer's disease and the mediating role of energy metabolism

Growing evidence suggests an association between osteocalcin (OCN), a peptide derived from bone and involved in regulating glucose and lipid metabolism, and the risk of Alzheimer's disease (AD). However, the causality of these associations and the underlying mechanisms remain uncertain. We utilized a Mendelian randomization (MR) approach to investigate the causal effects of blood OCN levels on AD and to assess the potential involvement of glucose and lipid metabolism. Independent instrumental variables strongly associated (P < 5E-08) with blood OCN levels were obtained from three independent genome-wide association studies (GWAS) on the human blood proteome (N = 3301 to 35,892). Two distinct summary statistics datasets on AD from the International Genomics of Alzheimer's Project (IGAP, N = 63,926) and a recent study including familial-proxy AD patients (FPAD, N = 472,868) were used. Summary-level data for fasting glucose (FG), 2h-glucose post-challenge, fasting insulin, HbA1c, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, total cholesterol (TC), and triglycerides were incorporated to evaluate the potential role of glucose and lipid metabolism in mediating the impact of OCN on AD risk. Our findings consistently demonstrate a significantly negative correlation between genetically determined blood OCN levels and the risk of AD (IGAP: odds ratio [OR, 95%CI] = 0.83[0.72-0.96], P = 0.013; FPAD: OR = 0.81 [0.70-0.93], P = 0.002). Similar estimates with the same trend direction were obtained using other statistical approaches. Furthermore, employing multivariable MR analysis, we found that the causal relationship between OCN levels and AD was disappeared after adjustment of FG and TC (IGAP: OR = 0.97[0.80-1.17], P = 0.753; FPAD: OR = 0.98 [0.84-1.15], P = 0.831). There were no apparent instances of horizontal pleiotropy, and leave-one-out analysis showed good stability of the estimates. Our study provides evidence supporting a protective effect of blood OCN levels on AD, which is primarily mediated through regulating FG and TC levels. Further studies are warranted to elucidate the underlying physio-pathological mechanisms.

Microglia and amyloid plaque formation in Alzheimer's disease - Evidence, possible mechanisms, and future challenges

Alzheimer's disease (AD) is a neurodegenerative disease characterized by cognitive decline that severely affects patients and their families. Genetic and environmental risk factors, such as viral infections, synergize to accelerate the aging-associated neurodegeneration. Genetic risk factors for late-onset AD (LOAD), which accounts for most AD cases, are predominantly implicated in microglial and immune cell functions. As such, microglia play a major role in formation of amyloid beta (Aβ) plaques, the major pathological hallmark of AD. This review aims to provide an overview of the current knowledge regarding the role of microglia in Aβ plaque formation, as well as their impact on morphological and functional diversity of Aβ plaques. Based on this discussion, we seek to identify challenges and opportunities in this field with potential therapeutic implications.

Imbalance in Glucose Metabolism Regulates the Transition of Microglia from Homeostasis to Disease-Associated Microglia Stage 1

Microglia undergo two-stage activation in neurodegenerative diseases, known as disease-associated microglia (DAM). TREM2 mediates the DAM2 stage transition, but what regulates the first DAM1 stage transition is unknown. We report that glucose dyshomeostasis inhibits DAM1 activation and PKM2 plays a role. As in tumors, PKM2 was aberrantly elevated in both male and female human AD brains, but unlike in tumors, it is expressed as active tetramers, as well as among TREM2+ microglia surrounding plaques in 5XFAD male and female mice. snRNAseq analyses of microglia without Pkm2 in 5XFAD mice revealed significant increases in DAM1 markers in a distinct metabolic cluster, which is enriched in genes for glucose metabolism, DAM1, and AD risk. 5XFAD mice incidentally exhibited a significant reduction in amyloid pathology without microglial Pkm2 Surprisingly, microglia in 5XFAD without Pkm2 exhibited increases in glycolysis and spare respiratory capacity, which correlated with restoration of mitochondrial cristae alterations. In addition, in situ spatial metabolomics of plaque-bearing microglia revealed an increase in respiratory activity. These results together suggest that it is not only glycolytic but also respiratory inputs that are critical to the development of DAM signatures in 5XFAD mice.

SR-TWAS: Leveraging Multiple Reference Panels to Improve TWAS Power by Ensemble Machine Learning

Multiple reference panels of a given tissue or multiple tissues often exist, and multiple regression methods could be used for training gene expression imputation models for TWAS. To leverage expression imputation models (i.e., base models) trained with multiple reference panels, regression methods, and tissues, we develop a Stacked Regression based TWAS (SR-TWAS) tool which can obtain optimal linear combinations of base models for a given validation transcriptomic dataset. Both simulation and real studies showed that SR-TWAS improved power, due to increased effective training sample sizes and borrowed strength across multiple regression methods and tissues. Leveraging base models across multiple reference panels, tissues, and regression methods, our real application studies identified 6 independent significant risk genes for Alzheimer's disease (AD) dementia for supplementary motor area tissue and 9 independent significant risk genes for Parkinson's disease (PD) for substantia nigra tissue. Relevant biological interpretations were found for these significant risk genes.

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.

Response eQTLs, chromatin accessibility, and 3D chromatin structure in chondrocytes provide mechanistic insight into osteoarthritis risk

Osteoarthritis (OA) poses a significant healthcare burden with limited treatment options. While genome-wide association studies (GWAS) have identified over 100 OA-associated loci, translating these findings into therapeutic targets remains challenging. Integrating expression quantitative trait loci (eQTL), 3D chromatin structure, and other genomic approaches with OA GWAS data offers a promising approach to elucidate disease mechanisms; however, comprehensive eQTL maps in OA-relevant tissues and conditions remain scarce. We mapped gene expression, chromatin accessibility, and 3D chromatin structure in primary human articular chondrocytes in both resting and OA-mimicking conditions. We identified thousands of differentially expressed genes, including those associated with differences in sex and age. RNA-seq in chondrocytes from 101 donors across two conditions uncovered 3782 unique eGenes, including 420 that exhibited strong and significant condition-specific effects. Colocalization with OA GWAS signals revealed 13 putative OA risk genes, 10 of which have not been previously identified. Chromatin accessibility and 3D chromatin structure provided insights into the mechanisms and conditional specificity of these variants. Our findings shed light on OA pathogenesis and highlight potential targets for therapeutic development.

Highlights

∘ Comprehensive analysis of sex- and age-related global gene expression in human chondrocytes revealed differences that correlate with osteoarthritis ∘ First response eQTLs in chondrocytes treated with an OA-related stimulus ∘ Deeply sequenced Hi-C in resting and activated chondrocytes helps connect OA risk variants to their putative causal genes ∘ Colocalization analysis reveals 13 (including 10 novel) putative OA risk genes.

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

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

Beyond guilty by association at scale: searching for causal variants on the basis of genome-wide summary statistics

Understanding the causal genetic architecture of complex phenotypes is essential for future research into disease mechanisms and potential therapies. Here, we present a novel framework for genome-wide detection of sets of variants that carry non-redundant information on the phenotypes and are therefore more likely to be causal in a biological sense. Crucially, our framework requires only summary statistics obtained from standard genome-wide marginal association testing. The described approach, implemented in open-source software, is also computationally efficient, requiring less than 15 minutes on a single CPU to perform genome-wide analysis. Through extensive genome-wide simulation studies, we show that the method can substantially outperform usual two-stage marginal association testing and fine-mapping procedures in precision and recall. In applications to a meta-analysis of ten large-scale genetic studies of Alzheimer's disease (AD), we identified 82 loci associated with AD, including 37 additional loci missed by conventional GWAS pipeline. The identified putative causal variants achieve state-of-the-art agreement with massively parallel reporter assays and CRISPR-Cas9 experiments. Additionally, we applied the method to a retrospective analysis of 67 large-scale GWAS summary statistics since 2013 for a variety of phenotypes. Results reveal the method's capacity to robustly discover additional loci for polygenic traits and pinpoint potential causal variants underpinning each locus beyond conventional GWAS pipeline, contributing to a deeper understanding of complex genetic architectures in post-GWAS analyses.

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.

Spatiotemporal patterns of locus coeruleus integrity predict cortical tau and cognition

Autopsy studies indicated that the locus coeruleus (LC) accumulates hyperphosphorylated tau before allocortical regions in Alzheimer's disease. By combining in vivo longitudinal magnetic resonance imaging measures of LC integrity, tau positron emission tomography imaging and cognition with autopsy data and transcriptomic information, we examined whether LC changes precede allocortical tau deposition and whether specific genetic features underlie LC's selective vulnerability to tau. We found that LC integrity changes preceded medial temporal lobe tau accumulation, and together these processes were associated with lower cognitive performance. Common gene expression profiles between LC-medial temporal lobe-limbic regions map to biological functions in protein transport regulation. These findings advance our understanding of the spatiotemporal patterns of initial tau spreading from the LC and LC's selective vulnerability to Alzheimer's disease pathology. LC integrity measures can be a promising indicator for identifying the time window when individuals are at risk of disease progression and underscore the importance of interventions mitigating initial tau spread.

Genetic Complexities of Cerebral Small Vessel Disease, Blood Pressure, and Dementia

Importance

Vascular disease is a treatable contributor to dementia risk, but the role of specific markers remains unclear, making prevention strategies uncertain.

Objective

To investigate the causal association between white matter hyperintensity (WMH) burden, clinical stroke, blood pressure (BP), and dementia risk, while accounting for potential epidemiologic biases.

Design, Setting, and Participants

This study first examined the association of genetically determined WMH burden, stroke, and BP levels with Alzheimer disease (AD) in a 2-sample mendelian randomization (2SMR) framework. Second, using population-based studies (1979-2018) with prospective dementia surveillance, the genetic association of WMH, stroke, and BP with incident all-cause dementia was examined. Data analysis was performed from July 26, 2020, through July 24, 2022.

Exposures

Genetically determined WMH burden and BP levels, as well as genetic liability to stroke derived from genome-wide association studies (GWASs) in European ancestry populations.

Main Outcomes and Measures

The association of genetic instruments for WMH, stroke, and BP with dementia was studied using GWASs of AD (defined clinically and additionally meta-analyzed including both clinically diagnosed AD and AD defined based on parental history [AD-meta]) for 2SMR and incident all-cause dementia for longitudinal analyses.

Results

In 2SMR (summary statistics-based) analyses using AD GWASs with up to 75 024 AD cases (mean [SD] age at AD onset, 75.5 [4.4] years; 56.9% women), larger WMH burden showed evidence for a causal association with increased risk of AD (odds ratio [OR], 1.43; 95% CI, 1.10-1.86; P = .007, per unit increase in WMH risk alleles) and AD-meta (OR, 1.19; 95% CI, 1.06-1.34; P = .008), after accounting for pulse pressure for the former. Blood pressure traits showed evidence for a protective association with AD, with evidence for confounding by shared genetic instruments. In the longitudinal (individual-level data) analyses involving 10 699 incident all-cause dementia cases (mean [SD] age at dementia diagnosis, 74.4 [9.1] years; 55.4% women), no significant association was observed between larger WMH burden and incident all-cause dementia (hazard ratio [HR], 1.02; 95% CI, 1.00-1.04; P = .07). Although all exposures were associated with mortality, with the strongest association observed for systolic BP (HR, 1.04; 95% CI, 1.03-1.06; P = 1.9 × 10-14), there was no evidence for selective survival bias during follow-up using illness-death models. In secondary analyses using polygenic scores, the association of genetic liability to stroke, but not genetically determined WMH, with dementia outcomes was attenuated after adjusting for interim stroke.

Conclusions

These findings suggest that WMH is a primary vascular factor associated with dementia risk, emphasizing its significance in preventive strategies for dementia. Future studies are warranted to examine whether this finding can be generalized to non-European populations.

TREM1 disrupts myeloid bioenergetics and cognitive function in aging and Alzheimer disease mouse models

Human genetics implicate defective myeloid responses in the development of late-onset Alzheimer disease. A decline in peripheral and brain myeloid metabolism, triggering maladaptive immune responses, is a feature of aging. The role of TREM1, a pro-inflammatory factor, in neurodegenerative diseases is unclear. Here we show that Trem1 deficiency prevents age-dependent changes in myeloid metabolism, inflammation and hippocampal memory function in mice. Trem1 deficiency rescues age-associated declines in ribose 5-phosphate. In vitro, Trem1-deficient microglia are resistant to amyloid-β42 oligomer-induced bioenergetic changes, suggesting that amyloid-β42 oligomer stimulation disrupts homeostatic microglial metabolism and immune function via TREM1. In the 5XFAD mouse model, Trem1 haploinsufficiency prevents spatial memory loss, preserves homeostatic microglial morphology, and reduces neuritic dystrophy and changes in the disease-associated microglial transcriptomic signature. In aging APPSwe mice, Trem1 deficiency prevents hippocampal memory decline while restoring synaptic mitochondrial function and cerebral glucose uptake. In postmortem Alzheimer disease brain, TREM1 colocalizes with Iba1+ cells around amyloid plaques and its expression is associated with Alzheimer disease clinical and neuropathological severity. Our results suggest that TREM1 promotes cognitive decline in aging and in the context of amyloid pathology.

A cross-disease, pleiotropy-driven approach for therapeutic target prioritization and evaluation

Cross-disease genome-wide association studies (GWASs) unveil pleiotropic loci, mostly situated within the non-coding genome, each of which exerts pleiotropic effects across multiple diseases. However, the challenge "W-H-W" (namely, whether, how, and in which specific diseases pleiotropy can inform clinical therapeutics) calls for effective and integrative approaches and tools. We here introduce a pleiotropy-driven approach specifically designed for therapeutic target prioritization and evaluation from cross-disease GWAS summary data, with its validity demonstrated through applications to two systems of disorders (neuropsychiatric and inflammatory). We illustrate its improved performance in recovering clinical proof-of-concept therapeutic targets. Importantly, it identifies specific diseases where pleiotropy informs clinical therapeutics. Furthermore, we illustrate its versatility in accomplishing advanced tasks, including pathway crosstalk identification and downstream crosstalk-based analyses. To conclude, our integrated solution helps bridge the gap between pleiotropy studies and therapeutics discovery.

Comparative gene regulatory networks modulating APOE expression in microglia and astrocytes

Background

Single-cell technologies have unveiled various transcriptional states in different brain cell types. Transcription factors (TFs) regulate the expression of related gene sets, thereby controlling these diverse expression states. Apolipoprotein E ( APOE ), a pivotal risk-modifying gene in Alzheimer's disease (AD), is expressed in specific glial transcriptional states associated with AD. However, it is still unknown whether the upstream regulatory programs that modulate its expression are shared across brain cell types or specific to microglia and astrocytes.

Methods

We used pySCENIC to construct state-specific gene regulatory networks (GRNs) for resting and activated cell states within microglia and astrocytes based on single-nucleus RNA sequencing data from AD patients' cortices from the Knight ADRC-DIAN cohort. We then identified replicating TF using data from the ROSMAP cohort. We identified sets of genes co-regulated with APOE by clustering the GRN target genes and identifying genes differentially expressed after the virtual knockout of TFs regulating APOE . We performed enrichment analyses on these gene sets and evaluated their overlap with genes found in AD GWAS loci.

Results

We identified an average of 96 replicating regulators for each microglial and astrocyte cell state. Our analysis identified the CEBP, JUN, FOS, and FOXO TF families as key regulators of microglial APOE expression. The steroid/thyroid hormone receptor families, including the THR TF family, consistently regulated APOE across astrocyte states, while CEBP and JUN TF families were also involved in resting astrocytes. AD GWAS-associated genes ( PGRN , FCGR3A , CTSH , ABCA1 , MARCKS , CTSB , SQSTM1 , TSC22D4 , FCER1G , and HLA genes) are co-regulated with APOE. We also uncovered that APOE-regulating TFs were linked to circadian rhythm ( BHLHE40 , DBP , XBP1 , CREM , SREBF1 , FOXO3 , and NR2F1 ).

Conclusions

Our findings reveal a novel perspective on the transcriptional regulation of APOE in the human brain. We found a comprehensive and cell-type-specific regulatory landscape for APOE , revealing distinct and shared regulatory mechanisms across microglia and astrocytes, underscoring the complexity of APOE regulation. APOE -co-regulated genes might also affect AD risk. Furthermore, our study uncovers a potential link between circadian rhythm disruption and APOE regulation, shedding new light on the pathogenesis of 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.

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'.

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'.

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.

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.

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.

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.

The Alzheimer's disease risk gene BIN1 regulates activity-dependent gene expression in human-induced glutamatergic neurons

Bridging Integrator 1 (BIN1) is the second most important Alzheimer's disease (AD) risk gene, but its physiological roles in neurons and its contribution to brain pathology remain largely elusive. In this work, we show that BIN1 plays a critical role in the regulation of calcium homeostasis, electrical activity, and gene expression of glutamatergic neurons. Using single-cell RNA-sequencing on cerebral organoids generated from isogenic BIN1 wild type (WT), heterozygous (HET) and homozygous knockout (KO) human-induced pluripotent stem cells (hiPSCs), we show that BIN1 is mainly expressed by oligodendrocytes and glutamatergic neurons, like in the human brain. Both BIN1 HET and KO cerebral organoids show specific transcriptional alterations, mainly associated with ion transport and synapses in glutamatergic neurons. We then demonstrate that BIN1 cell-autonomously regulates gene expression in glutamatergic neurons by using a novel protocol to generate pure culture of hiPSC-derived induced neurons (hiNs). Using this system, we also show that BIN1 plays a key role in the regulation of neuronal calcium transients and electrical activity via its interaction with the L-type voltage-gated calcium channel Cav1.2. BIN1 KO hiNs show reduced activity-dependent internalization and higher Cav1.2 expression compared to WT hiNs. Pharmacological blocking of this channel with clinically relevant doses of nifedipine, a calcium channel blocker, partly rescues electrical and gene expression alterations in BIN1 KO glutamatergic neurons. Further, we show that transcriptional alterations in BIN1 KO hiNs that affect biological processes related to calcium homeostasis are also present in glutamatergic neurons of the human brain at late stages of AD pathology. Together, these findings suggest that BIN1-dependent alterations in neuronal properties could contribute to AD pathophysiology and that treatment with low doses of clinically approved calcium blockers should be considered as an option to slow disease-onset and progression.

Integrating multi-omics data to reveal the effect of genetic variant rs6430538 on Alzheimer's disease risk

Introduction

Growing evidence highlights a potential genetic overlap between Alzheimer's disease (AD) and Parkinson's disease (PD); however, the role of the PD risk variant rs6430538 in AD remains unclear.

Methods

In Stage 1, we investigated the risk associated with the rs6430538 C allele in seven large-scale AD genome-wide association study (GWAS) cohorts. In Stage 2, we performed expression quantitative trait loci (eQTL) analysis to calculate the cis-regulated effect of rs6430538 on TMEM163 in both AD and neuropathologically normal samples. Stage 3 involved evaluating the differential expression of TMEM163 in 4 brain tissues from AD cases and controls. Finally, in Stage 4, we conducted a transcriptome-wide association study (TWAS) to identify any association between TMEM163 expression and AD.

Results

The results showed that genetic variant rs6430538 C allele might increase the risk of AD. eQTL analysis revealed that rs6430538 up-regulated TMEM163 expression in AD brain tissue, but down-regulated its expression in normal samples. Interestingly, TMEM163 showed differential expression in entorhinal cortex (EC) and temporal cortex (TCX). Furthermore, the TWAS analysis indicated strong associations between TMEM163 and AD in various tissues.

Discussion

In summary, our findings suggest that rs6430538 may influence AD by regulating TMEM163 expression. These discoveries may open up new opportunities for therapeutic strategies targeting AD.

Neuropathogenesis-on-chips for neurodegenerative diseases

Developing diagnostics and treatments for neurodegenerative diseases (NDs) is challenging due to multifactorial pathogenesis that progresses gradually. Advanced in vitro systems that recapitulate patient-like pathophysiology are emerging as alternatives to conventional animal-based models. In this review, we explore the interconnected pathogenic features of different types of ND, discuss the general strategy to modelling NDs using a microfluidic chip, and introduce the organoid-on-a-chip as the next advanced relevant model. Lastly, we overview how these models are being applied in academic and industrial drug development. The integration of microfluidic chips, stem cells, and biotechnological devices promises to provide valuable insights for biomedical research and developing diagnostic and therapeutic solutions for NDs.

Deciphering the effect of phytosterols on Alzheimer's disease and Parkinson's disease: the mediating role of lipid profiles

BACKGROUND

Studies have suggested that blood circulating phytosterols, plant-derived sterols analogous to cholesterol, were associated with blood lipid levels and the risk of Alzheimer's disease (AD) and Parkinson's disease (PD). This Mendelian randomization (MR) study is performed to determine the causal effect of circulating phytosterols on AD and PD and evaluate the mediation effect of blood lipids.

METHODS

Leveraging genome-wide association studies summary-level data for phytosterols, blood lipids, AD, and PD, univariable and multivariable MR (MVMR) analyses were conducted. Four types of phytosterols (brassicasterol, campesterol, sitosterol, and stigmasterol), three blood lipids parameters (high-density lipoprotein cholesterol [HDL-C], non-HDL-C, and triglyceride), two datasets for AD and PD were used. Inverse-variance weighted method was applied as the primary analysis, and false discovery rate method was used for adjustment of multiple comparisons.

RESULTS

Using the largest AD dataset, genetically proxied higher levels of stigmasterol (OR = 0.593, 95%CI = 0.431-0.817, P = 0.004) and sitosterol (OR = 0.864, 95%CI = 0.791-0.943, P = 0.004) significantly correlated with a lower risk of AD. No significant associations were observed between all four types of phytosterols levels and PD. MVMR estimates showed that the above causal associations were missing after integrating the blood lipids as exposures. Sensitivity analyses confirmed the robustness of these associations, with no evidence of pleiotropy and heterogeneity.

CONCLUSION

The study supports a potential beneficial role of blood stigmasterol and sitosterol in reducing the risk of AD, but not PD, which is dependent on modulating blood lipids. These insights highlight circulating stigmasterol and sitosterol as possible biomarkers and therapeutic targets for AD.

Association evaluations of oral anticoagulants with dementia risk based on genomic and real-world data

BACKGROUND

Several observational studies have suggested that oral anticoagulants (OACs) might reduce the risk of dementia in the elderly, but the evidence is inconclusive. And the consistency of this relationship across different OAC classes and dementia subtypes is still uncertain.

METHODS

To comprehensively evaluate this association, we applied Mendelian randomization (MR) combined with pharmacovigilance analysis. MR was used to assess the associations between genetic proxies for three target genes of OACs (VKORC1, F2, and F10) and dementia, including Alzheimer's disease (AD) and vascular dementia (VaD). This genetic analysis was supplemented with real-world pharmacovigilance data, employing disproportionality analysis for more reliable causal inference.

RESULTS

Increased expression of the VKORC1 gene was strongly associated with increased risk of dementia, especially for AD (OR = 1.28, 95% CI = 1.14-1.43; p value < 0.001). Based on pharmacovigilance data, vitamin K antagonists (VKAs, inhibitors targeting VKORC1) exhibited a protective effect against dementia risk (ROR = 0.43, 95% CI = 0.28-0.67). Additional sensitivity analyses, including different MR models and cohorts, supported these results. Conversely, no strong causal associations of genetically proxied F2 and F10 target genes with dementia and its subtypes were found.

CONCLUSIONS

This study reveals that the inhibition of genetically proxied VKORC1 expression or VKAs exposure is associated with a reduced risk of Alzheimer's dementia. However, there is little evidence to support similar associations with direct oral anticoagulants (F2 inhibitors and F10 inhibitors). Further research is warranted to clinically validate our findings.

Leveraging electronic health records and knowledge networks for Alzheimer's disease prediction and sex-specific biological insights

Identification of Alzheimer's disease (AD) onset risk can facilitate interventions before irreversible disease progression. We demonstrate that electronic health records from the University of California, San Francisco, followed by knowledge networks (for example, SPOKE) allow for (1) prediction of AD onset and (2) prioritization of biological hypotheses, and (3) contextualization of sex dimorphism. We trained random forest models and predicted AD onset on a cohort of 749 individuals with AD and 250,545 controls with a mean area under the receiver operating characteristic of 0.72 (7 years prior) to 0.81 (1 day prior). We further harnessed matched cohort models to identify conditions with predictive power before AD onset. Knowledge networks highlight shared genes between multiple top predictors and AD (for example, APOE, ACTB, IL6 and INS). Genetic colocalization analysis supports AD association with hyperlipidemia at the APOE locus, as well as a stronger female AD association with osteoporosis at a locus near MS4A6A. We therefore show how clinical data can be utilized for early AD prediction and identification of personalized biological hypotheses.

Inflammation and Brain Structure in Alzheimer's Disease and Other Neurodegenerative Disorders: a Mendelian Randomization Study

Previous in vitro and post-mortem studies have reported the role of inflammation in neurodegenerative disorders. However, the association between inflammation and brain structure in vivo and the transcriptome-driven functional basis with relevance to neurodegenerative disorders remains elusive. The aim of the present study is to identify the association among inflammation, brain structure, and neurodegenerative disorders at genetic and transcriptomic levels. Genetic variants associated with inflammatory cytokines were selected from the latest and largest genome-wide association studies of European ancestry. Neurodegenerative disorders including Alzheimer's disease (AD), Parkinson's disease (PD), amyotrophic lateral sclerosis (ALS), and dementia with Lewy bodies (DLB) and brain structure imaging measures were selected as the outcomes. Two-sample Mendelian randomization analyses were conducted to identify the causal associations. Single-nucleus transcriptome data of the occipitotemporal cortex was further analyzed to identify the differential expressed genes in AD, which were tested for biological processes and protein interaction network. MR analysis indicated that genetically predicted TREM2 and sTREM2 were significantly associated with AD (TREM2: z-score = -9.088, p-value = 1.02 × 10-19; sTREM2: z-score = -7.495, p-value = 6.61 × 10-14). The present study found no evidence to support the causal associations between other inflammatory cytokines and the risks of AD, PD, ALS, or DLB. Genetically predicted TREM2 was significantly associated with the cortical thickness of inferior temporal (z-score = -4.238, p-value = 2.26 × 10-5) and pole temporal (z-score = -4.549, p-value = 5.40 × 10-6). In the occipitotemporal cortex samples, microglia were the main source of TREM2 gene and showed increasing expression of genes associated with inflammation and immunity. The present study has leveraged genetic and transcriptomic data to identify the association among TREM2, temporal lobe, and AD and the underlying cellular and molecular basis, thus providing a new perspective on the role of TREM2 in AD and insights into the complex associations among inflammation, brain structure, and neurodegenerative disorders, particularly AD.

Association of APOE gene with longitudinal changes of CSF amyloid beta and tau levels in Alzheimer's disease: racial differences

BACKGROUND

The Apolipoprotein E (APOE) ε4 allele is a risk factor for late-onset Alzheimer's disease (AD). However, no investigation has focused on racial differences in the longitudinal effect of APOE genotypes on CSF amyloid beta (Aβ42) and tau levels in AD.

METHODS

This study used data from the Alzheimer's Disease Neuroimaging Initiative (ADNI): 222 participants with AD, 264 with cognitive normal (CN), and 692 with mild cognitive impairment (MCI) at baseline and two years follow-up. We used a linear mixed model to investigate the effect of APOE-ε4-genotypes on longitudinal changes in the amyloid beta and tau levels.

RESULTS

Individuals with 1 or 2 APOE ε4 alleles revealed significantly higher t-Tau and p-Tau, but lower amyloid beta Aβ42 compared with individuals without APOE ε4 alleles. Significantly higher levels of log-t-Tau, log-p-Tau, and low levels of log-Aβ42 were observed in the subjects with older age, being female, and the two diagnostic groups (AD and MCI). The higher p-Tau and Aβ42 values are associated with poor Mini-Mental State Examination (MMSE) performance. Non-Hispanic Africa American (AA) and Hispanic participants were associated with decreased log-t-Tau levels (β =  - 0.154, p = 0.0112; β =  - 0.207, and p = 0.0016, respectively) as compared to those observed in Whites. Furthermore, Hispanic participants were associated with a decreased log-p-Tau level (β =  - 0.224, p = 0.0023) compared to those observed in Whites. There were no differences in Aβ42 level for non-Hispanic AA and Hispanic participants compared with White participants.

CONCLUSION

Our study, for the first time, showed that the APOE ε4 allele was associated with these biomarkers, however with differing degrees among racial groups.

CircRNAs in Alzheimer's disease: What are the prospects?

Circular RNAs (circRNAs) is a fascinating covalently closed circular non-coding RNA that is abundantly present in the transcriptome of eukaryotic cells. Its versatile nature allows it to participate in a multitude of pathological and physiological processes within the organism. One of its crucial functions is acting as a microRNA sponge, modulating protein transcription levels, and forming interactions with essential RNA-binding proteins. Remarkably, circRNAs demonstrates a specific enrichment in various vital areas of the brain, including the cortex, hippocampus, white matter, and photoreceptor neurons, particularly in aging organisms. This intriguing characteristic has led scientists to explore its potential as a significant biological marker of neurodegeneration, offering promising insights into neurodegenerative diseases like Alzheimer's disease (AD). In AD, there has been an interesting observation of elevated levels of circRNAs in both peripheral blood and synaptic terminals of affected individuals. This intriguing finding raises the possibility that circRNAs may have a central role in the initiation and progression of AD. Notably, different categories of circRNAs, including HDAC9, HOMER1, Cwc27, Tulp4, and PTK2, have been implicated in driving the pathological changes associated with AD through diverse mechanisms. For instance, these circRNAs have been demonstrated to contribute to the accumulation of beta-amyloid, which is a hallmark characteristic of AD. Additionally, these circRNAs contribute to the excessive phosphorylation of tau protein, a phenomenon associated with neurofibrillary tangles, further exacerbating the disease. Moreover, they are involved in aggravating neuroinflammation, which is known to play a critical role in AD's pathogenesis. Lastly, these circRNAs can cause mitochondrial dysfunction, disrupting cellular energy production and leading to cognitive impairment. As researchers delve deeper into the intricate workings of circRNAs, they hope to unlock its full potential as a diagnostic tool and therapeutic target for neurodegenerative disorders, paving the way for innovative treatments and better management of such devastating conditions.

Controlled Variable Selection from Summary Statistics Only? A Solution via GhostKnockoffs and Penalized Regression

Identifying which variables do influence a response while controlling false positives pervades statistics and data science. In this paper, we consider a scenario in which we only have access to summary statistics, such as the values of marginal empirical correlations between each dependent variable of potential interest and the response. This situation may arise due to privacy concerns, e.g., to avoid the release of sensitive genetic information. We extend GhostKnockoffs He et al. [2022] and introduce variable selection methods based on penalized regression achieving false discovery rate (FDR) control. We report empirical results in extensive simulation studies, demonstrating enhanced performance over previous work. We also apply our methods to genome-wide association studies of Alzheimer's disease, and evidence a significant improvement in power.

Priority index for critical Covid-19 identifies clinically actionable targets and drugs

While genome-wide studies have identified genomic loci in hosts associated with life-threatening Covid-19 (critical Covid-19), the challenge of resolving these loci hinders further identification of clinically actionable targets and drugs. Building upon our previous success, we here present a priority index solution designed to address this challenge, generating the target and drug resource that consists of two indexes: the target index and the drug index. The primary purpose of the target index is to identify clinically actionable targets by prioritising genes associated with Covid-19. We illustrate the validity of the target index by demonstrating its ability to identify pre-existing Covid-19 phase-III drug targets, with the majority of these targets being found at the leading prioritisation (leading targets). These leading targets have their evolutionary origins in Amniota ('four-leg vertebrates') and are predominantly involved in cytokine-cytokine receptor interactions and JAK-STAT signaling. The drug index highlights opportunities for repurposing clinically approved JAK-STAT inhibitors, either individually or in combination. This proposed strategic focus on the JAK-STAT pathway is supported by the active pursuit of therapeutic agents targeting this pathway in ongoing phase-II/III clinical trials for Covid-19.

Genome-Wide Association Studies of ARIA From the Aducanumab Phase 3 ENGAGE and EMERGE Studies

BACKGROUND AND OBJECTIVES

Amyloid-related imaging abnormalities (ARIA) were the most common adverse events reported in the phase 3 ENGAGE and EMERGE trials of aducanumab, an anti-amyloid monoclonal antibody. APOE ε4 carrier status has been shown to increase risk of ARIA in prior trials of aducanumab and other anti-amyloid therapies; however, the remainder of the human genome has not been evaluated for ARIA risk factors. Therefore, we sought to determine in a hypothesis-free manner whether genetic variants beyond APOE influence risk of ARIA in aducanumab-treated patients.

METHODS

We performed genome-wide association studies (GWAS) of ARIA in participants in the ENGAGE and EMERGE trials. Participants had mild cognitive impairment due to Alzheimer disease or mild Alzheimer disease dementia and were amyloid-positive on PET scans. All participants underwent regular MRI monitoring to detect and diagnose ARIA.

RESULTS

Of the 3,285 participants in the intent-to-treat population, this analysis included 1,691 with genotyping array data who received at least one dose of aducanumab with at least one post-baseline MRI. All participants in the study cohort were of European ancestry; 51% were female. The mean age was 70.3 years. 31% had ARIA-E, 19% had ARIA-H microhemorrhage, and 14% had ARIA-H superficial siderosis. We identified one genome-wide significant (p < 5.0 × 10-8) association at the chromosome 19 locus encompassing APOE. The APOE association with ARIA was stronger in ε4/ε4 homozygotes (OR = 4.28, 4.58, 7.84; p < 2.9 × 10-14 for ARIA-E, ARIA-H microhemorrhage, and ARIA-H superficial siderosis, respectively) than in ε3/ε4 heterozygotes (OR = 1.74, 1.46, 3.14; p ≤ 0.03). We found greater odds of radiographically severe ARIA (OR = 7.04-24.64, p ≤ 2.72 × 10-5) than radiographically mild ARIA (OR = 3.19-5.00, p ≤ 1.37 × 10-5) among ε4/ε4 homozygotes. APOE ε4 was also significantly associated with both symptomatic (ε4/ε4 OR = 3.64-9.52; p < 0.004) and asymptomatic (ε4/ε4 OR = 4.20-7.94, p < 1.7 × 10-11) cases, although among ARIA cases, APOE did not appear to modulate symptomatic status. No other genome-wide significant associations were found.

DISCUSSION

We identified a strong, genome-wide significant association between APOE and risk of ARIA. Future, larger studies may be better powered to detect associations beyond APOE. These findings indicate that APOE is the strongest genetic risk factor of ARIA incidence, with implications for patient management and risk-benefit treatment decisions.

TRIAL REGISTRATION INFORMATION

Both trials (ENGAGE [221AD301]: NCT02477800 and EMERGE [221AD302]: NCT02484547) were registered in June 2015 at clinicaltrials.gov and enrolled patients from August 2015 to July 2018.