A rare missense variant of CASP7 is associated with familial late-onset Alzheimer's disease

Whole-genome sequencing reveals the impact of lipid pathway and APOE genotype on brain amyloidosis

Amyloid-PET imaging tracks the accumulation of amyloid beta (Aβ) deposits in the brain. Amyloid plaques accumulation may begin 10 to 20 years before the individual experiences clinical symptoms associated with Alzheimer's diseases (ad). Recent large-scale genome-wide association studies reported common risk factors associated with brain amyloidosis, suggesting that this endophenotype is driven by genetic variants. However, these loci pinpoint to large genomic regions and the functional variants remain to be identified. To identify new risk factors associated with brain amyloid deposition, we performed whole-genome sequencing on a large cohort of European descent individuals with amyloid PET imaging data (n = 1,888). Gene-based analysis for coding variants was performed using SKAT-O for amyloid PET as a quantitative endophenotype that identified genome-wide significant association for APOE (P = 2.45 × 10-10), and 26 new candidate genes with suggestive significance association (P < 5. 0 × 10-03) including SCN7A (P = 7.31 × 10-05), SH3GL1 (P = 7.56 × 10-04), and MFSD12 (P = 8.51 × 10-04). Enrichment analysis highlighted the lipid binding pathways as associated with Aβ deposition in brain driven by PITPNM3 (P = 4.27 × 10-03), APOE (P = 2.45 × 10-10), AP2A2 (P = 1.06 × 10-03), and SH3GL1 (P = 7.56 × 10-04). Overall, our data strongly support a connection between lipid metabolism and the deposition of Aβ in the brain. Our study illuminates promising avenues for therapeutic interventions targeting lipid metabolism to address brain amyloidosis.

The impact of rare genetic variants on Alzheimer disease

Alzheimer disease (AD) is a progressive neurodegenerative disease with a strong genetic component. Although autosomal dominant mutations and common risk variants in AD risk have been extensively studied, the genetic underpinning of polygenic AD remains incompletely understood. Rare variants could elucidate part of the missing heritability in AD. Rare variant research gained momentum with the discovery of a rare variant in TREM2, along with loss-of-function variants in ABCA7 and SORL1, and has come into full bloom in recent years. Not only has the number of rare variant discoveries increased through large-scale whole-exome and genome sequencing studies, improved imputation in genome-wide association studies and increased focus on understudied populations, the number of studies mapping the functional effects of several of these rare variants has also significantly increased, leading to insights in the pathogenesis of AD and drug development. Here we provide a comprehensive overview of the known and novel rare variants implicated in AD risk, highlighting how they shine new light on AD pathophysiology and provide new inroads for drug development. We will review their impact on individual, familial and population levels, and discuss the potential and challenges of rare variants in genetic risk prediction.

Effects of Pesticide Exposure on Neuroinflammation and Microglial Gene Expression: Relevance to Mechanisms of Alzheimer's Disease Risk

Background

Alzheimer's disease (AD) is characterized by the presence of amyloid-β plaques, neurofibrillary tangles, and neuroinflammation. Previously, we reported serum levels of dichlorodiphenyldichloroethylene (DDE), the primary metabolite of the pesticide dichlorodiphenyltrichloroethane (DDT), were significantly higher in AD patients compared to age-matched controls and that DDT exposure worsened AD pathology in animal models.

Objective

Here, we investigated the effect of DDT on neuroinflammation in primary mouse microglia (PMG) and C57BL/6J mice.

Methods

Effects of DDT on inflammation and disease-associated microglia were determined in primary mouse microglia and C57BL/6J mice.

Results

PMG exposed to DDT (0.5-5.0 µM) elicited a ∼2-3-fold increase in Il-1b mRNA levels, with similar concentration-dependent upregulation in Il-6, Nos2, and Tnfa . These effects were blocked by the sodium channel antagonist tetrodotoxin, demonstrating the role of DDT-microglial sodium channel interactions in mediating this response. Additionally, NOS2 protein levels increased by ∼1.5-2-fold, while TNFa was elevated by 2-4-fold. C57BL/6J male and female mice exposed to DDT (30 mg/kg) demonstrated significantly increased mRNA levels of Nos2 , Il-1b , and Il-6 in the frontal cortex (1.5-2.3-fold), and Nos2 , Il-1b, and Tnfa (1.5-1.8-fold) in the hippocampus. Furthermore, microglial homeostatic genes, Cx3cr1 , P2ry12, and Tmem119 , were downregulated, while stage 1 disease-associated microglia genes were upregulated both in vitro and in vivo . Notably, Apoe and Trem2 were only upregulated in the frontal cortex and hippocampus of females.

Conclusion

These data indicate that DDT increases neuroinflammation, which may result from direct actions of DDT on microglia, providing a novel pathway by which DDT may contribute to AD risk.

Integrative Epigenomic Landscape of Alzheimer's Disease Brains Reveals Oligodendrocyte Molecular Perturbations Associated with Tau

Alzheimer's disease (AD) brains are characterized by neuropathologic and biochemical changes that are highly variable across individuals. Capturing epigenetic factors that associate with this variability can reveal novel biological insights into AD pathophysiology. We conducted an epigenome-wide association study of DNA methylation (DNAm) in 472 AD brains with neuropathologic measures (Braak stage, Thal phase, and cerebral amyloid angiopathy score) and brain biochemical levels of five proteins (APOE, amyloid-β (Aβ)40, Aβ42, tau, and p-tau) core to AD pathogenesis. Using a novel regional methylation (rCpGm) approach, we identified 5,478 significant associations, 99.7% of which were with brain tau biochemical measures. Of the tau-associated rCpGms, 93 had concordant associations in external datasets comprising 1,337 brain samples. Integrative transcriptome-methylome analyses uncovered 535 significant gene expression associations for these 93 rCpGms. Genes with concurrent transcriptome-methylome perturbations were enriched in oligodendrocyte marker genes, including known AD risk genes such as BIN1 , myelination genes MYRF, MBP and MAG previously implicated in AD, as well as novel genes like LDB3 . We further annotated the top oligodendrocyte genes in an additional 6 brain single cell and 2 bulk transcriptome datasets from AD and two other tauopathies, Pick's disease and progressive supranuclear palsy (PSP). Our findings support consistent rCpGm and gene expression associations with these tauopathies and tau-related phenotypes in both bulk brain tissue and oligodendrocyte clusters. In summary, we uncover the integrative epigenomic landscape of AD and demonstrate tau-related oligodendrocyte gene perturbations as a common potential pathomechanism across different tauopathies.

The identification of key genes and pathways in polycystic ovary syndrome by bioinformatics analysis of next-generation sequencing data

Background

Polycystic ovary syndrome (PCOS) is a reproductive endocrine disorder. The specific molecular mechanism of PCOS remains unclear. The aim of this study was to apply a bioinformatics approach to reveal related pathways or genes involved in the development of PCOS.

Methods

The next-generation sequencing (NGS) dataset GSE199225 was downloaded from the gene expression omnibus (GEO) database and NGS dataset analyzed is obtained from in vitro culture of PCOS patients’ muscle cells and muscle cells of healthy lean control women. Differentially expressed gene (DEG) analysis was performed using DESeq2. The g:Profiler was utilized to analyze the gene ontology (GO) and REACTOME pathways of the differentially expressed genes. A protein–protein interaction (PPI) network was constructed and module analysis was performed using HiPPIE and cytoscape. The miRNA-hub gene regulatory network and TF-hub gene regulatory network were constructed. The hub genes were validated by using receiver operating characteristic (ROC) curve analysis.

Results

We have identified 957 DEG in total, including 478 upregulated genes and 479 downregulated gene. GO terms and REACTOME pathways illustrated that DEG were significantly enriched in regulation of molecular function, developmental process, interferon signaling and platelet activation, signaling, and aggregation. The top 5 upregulated hub genes including HSPA5, PLK1, RIN3, DBN1, and CCDC85B and top 5 downregulated hub genes including DISC1, AR, MTUS2, LYN, and TCF4 might be associated with PCOS. The hub gens of HSPA5 and KMT2A, together with corresponding predicted miRNAs (e.g., hsa-mir-34b-5p and hsa-mir-378a-5p), and HSPA5 and TCF4 together with corresponding predicted TF (e.g., RCOR3 and TEAD4) were found to be significantly correlated with PCOS.

Conclusions

These study uses of bioinformatics analysis of NGS data to obtain hub genes and key signaling pathways related to PCOS and its associated complications. Also provides novel ideas for finding biomarkers and treatment methods for PCOS and its associated complications.

Identification of immune infiltration and PANoptosis-related molecular clusters and predictive model in Alzheimer's disease based on transcriptome analysis

This study aims to explore the expression profile of PANoptosis-related genes (PRGs) and immune infiltration in Alzheimer's disease (AD). Based on the Gene Expression Omnibus database, this study investigated the differentially expressed PRGs and immune cell infiltration in AD and explored related molecular clusters. Gene set variation analysis (GSVA) was used to analyze the expression of Gene Ontology and Kyoto Encyclopedia of Genes and Genomes in different clusters. Weighted gene co-expression network analysis was utilized to find co-expressed gene modules and core genes in the network. By analyzing the intersection genes in random forest, support vector machine, generalized linear model, and extreme gradient boosting (XGB), the XGB model was determined. Eventually, the first five genes (Signal Transducer and Activator of Transcription 3, Tumor Necrosis Factor (TNF) Receptor Superfamily Member 1B, Interleukin 4 Receptor, Chloride Intracellular Channel 1, TNF Receptor Superfamily Member 10B) in XGB model were selected as predictive genes. This research explored the relationship between PANoptosis and AD and established an XGB learning model to evaluate and screen key genes. At the same time, immune infiltration analysis showed that there were different immune infiltration expression profiles in AD.

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.

Novel loci for Alzheimer's disease identified by a genome-wide association study in Ashkenazi Jews

INTRODUCTION

Most Alzheimer's disease (AD) loci have been discovered in individuals with European ancestry (EA).

METHODS

We applied principal component analysis using Gaussian mixture models and an Ashkenazi Jewish (AJ) reference genome-wide association study (GWAS) data set to identify Ashkenazi Jews ascertained in GWAS (n = 42,682), whole genome sequencing (WGS, n = 16,815), and whole exome sequencing (WES, n = 20,504) data sets. The association of AD was tested genome wide (GW) in the GWAS and WGS data sets and exome wide (EW) in all three data sets (EW). Gene-based analyses were performed using aggregated rare variants.

RESULTS

In addition to apolipoprotein E (APOE), GW analyses (1355 cases and 1661 controls) revealed associations with TREM2 R47H (p = 9.66 × 10-9 ), rs541586606 near RAB3B (p = 5.01 × 10-8 ), and rs760573036 between SPOCK3 and ANXA10 (p = 6.32 × 10-8 ). In EW analyses (1504 cases and 2047 controls), study-wide significant association was observed with rs1003710 near SMAP2 (p = 1.91 × 10-7 ). A significant gene-based association was identified with GIPR (p = 7.34 × 10-7 ).

DISCUSSION

Our results highlight the efficacy of founder populations for AD genetic studies.

Genetics of Alzheimer's Disease in the African American Population

Black/African American (AA) individuals have a higher risk of Alzheimer's disease (AD) than White non-Hispanic persons of European ancestry (EUR) for reasons that may include economic disparities, cardiovascular health, quality of education, and biases in the methods used to diagnose AD. AD is also heritable, and some of the differences in risk may be due to genetics. Many AD-associated variants have been identified by candidate gene studies, genome-wide association studies (GWAS), and genome-sequencing studies. However, most of these studies have been performed using EUR cohorts. In this paper, we review the genetics of AD and AD-related traits in AA individuals. Importantly, studies of genetic risk factors in AA cohorts can elucidate the molecular mechanisms underlying AD risk in AA and other populations. In fact, such studies are essential to enable reliable precision medicine approaches in persons with considerable African ancestry. Furthermore, genetic studies of AA cohorts allow exploration of the ways the impact of genes can vary by ancestry, culture, and economic and environmental disparities. They have yielded important gains in our knowledge of AD genetics, and increasing AA individual representation within genetic studies should remain a priority for inclusive genetic study design.

Modifiable cardiovascular risk factors and genetics for targeted prevention of dementia

Dementia is a major global challenge for health and social care in the 21st century. A third of individuals >65 years of age die with dementia, and worldwide incidence numbers are projected to be higher than 150 million by 2050. Dementia is, however, not an inevitable consequence of old age; 40% of dementia may theoretically be preventable. Alzheimer's disease (AD) accounts for approximately two-thirds of dementia cases and the major pathological hallmark of AD is accumulation of amyloid-β. Nevertheless, the exact pathological mechanisms of AD remain unknown. Cardiovascular disease and dementia share several risk factors and dementia often coexists with cerebrovascular disease. In a public health perspective, prevention is crucial, and it is suggested that a 10% reduction in prevalence of cardiovascular risk factors could prevent more than nine million dementia cases worldwide by 2050. Yet this assumes causality between cardiovascular risk factors and dementia and adherence to the interventions over decades for a large number of individuals. Using genome-wide association studies, the entire genome can be scanned for disease/trait associated loci in a hypothesis-free manner, and the compiled genetic information is not only useful for pinpointing novel pathogenic pathways but also for risk assessments. This enables identification of individuals at high risk, who likely will benefit the most from a targeted intervention. Further optimization of the risk stratification can be done by adding cardiovascular risk factors. Additional studies are, however, highly needed to elucidate dementia pathogenesis and potential shared causal risk factors between cardiovascular disease and dementia.

Cerebrospinal Fluid Protein Biomarker Discovery in CLN3

Syndromic CLN3-Batten is a fatal, pediatric, neurodegenerative disease caused by variants in CLN3, which encodes the endolysosomal transmembrane CLN3 protein. No approved treatment for CLN3 is currently available. The protracted and asynchronous disease presentation complicates the evaluation of potential therapies using clinical disease progression parameters. Biomarkers as surrogates to measure the progression and effect of potential therapeutics are needed. We performed proteomic discovery studies using cerebrospinal fluid (CSF) samples from 28 CLN3-affected and 32 age-similar non-CLN3 individuals. Proximal extension assay (PEA) of 1467 proteins and untargeted data-dependent mass spectrometry [MS; MassIVE FTP server (ftp://MSV000090147@massive.ucsd.edu)] were used to generate orthogonal lists of protein marker candidates. At an adjusted p-value of <0.1 and threshold CLN3/non-CLN3 fold-change ratio of 1.5, PEA identified 54 and MS identified 233 candidate biomarkers. Some of these (NEFL, CHIT1) have been previously linked with other neurologic conditions. Others (CLPS, FAM217B, QRICH2, KRT16, ZNF333) appear to be novel. Both methods identified 25 candidate biomarkers, including CHIT1, NELL1, and ISLR2 which had absolute fold-change ratios >2. NELL1 and ISLR2 regulate axonal development in neurons and are intriguing new candidates for further investigation in CLN3. In addition to identifying candidate proteins for CLN3 research, this study provides a comparison of two large-scale proteomic discovery methods in CSF.

Characterisation of C101248: A novel selective THIK-1 channel inhibitor for the modulation of microglial NLRP3-inflammasome

Neuroinflammation, specifically the NLRP3 inflammasome cascade, is a common underlying pathological feature of many neurodegenerative diseases. Evidence suggests that NLRP3 activation involves changes in intracellular K+. Nuclear Enriched Transcript Sort Sequencing (NETSseq), which allows for deep sequencing of purified cell types from human post-mortem brain tissue, demonstrated a highly specific expression of the tandem pore domain halothane-inhibited K+ channel 1 (THIK-1) in microglia compared to other glial and neuronal cell types in the human brain. NETSseq also showed a significant increase of THIK-1 in microglia isolated from cortical regions of brains with Alzheimer's disease (AD) relative to control donors. Herein, we report the discovery and pharmacological characterisation of C101248, the first selective small-molecule inhibitor of THIK-1. C101248 showed a concentration-dependent inhibition of both mouse and human THIK-1 (IC50: ∼50 nM) and was inactive against K2P family members TREK-1 and TWIK-2, and Kv2.1. Whole-cell patch-clamp recordings of microglia from mouse hippocampal slices showed that C101248 potently blocked both tonic and ATP-evoked THIK-1 K+ currents. Notably, C101248 had no effect on other constitutively active resting conductance in slices from THIK-1-depleted mice. In isolated microglia, C101248 prevented NLRP3-dependent release of IL-1β, an effect not seen in THIK-1-depleted microglia. In conclusion, we demonstrated that inhibiting THIK-1 (a microglia specific gene that is upregulated in brains from donors with AD) using a novel selective modulator attenuates the NLRP3-dependent release of IL-1β from microglia, which suggests that this channel may be a potential therapeutic target for the modulation of neuroinflammation in AD.

An in-silico approach to studying a very rare neurodegenerative disease using a disease with higher prevalence with shared pathways and genes: Cerebral adrenoleukodystrophy and Alzheimer’s disease

Cerebral adrenoleukodystrophy (cALD) is a rare neurodegenerative disease characterized by inflammatory demyelination in the central nervous system. Another neurodegenerative disease with a high prevalence, Alzheimer’s disease (AD), shares many common features with cALD such as cognitive impairment and the alleviation of symptoms by erucic acid. We investigated cALD and AD in parallel to study the shared pathological pathways between a rare disease and a more common disease. The approach may expand the biological understandings and reveal novel therapeutic targets. Gene set enrichment analysis (GSEA) and weighted gene correlation network analysis (WGCNA) were conducted to identify both the resemblance in gene expression patterns and genes that are pathologically relevant in the two diseases. Within differentially expressed genes (DEGs), GSEA identified 266 common genes with similar up- or down-regulation patterns in cALD and AD. Among the interconnected genes in AD data, two gene sets containing 1,486 genes preserved in cALD data were selected by WGCNA that may significantly affect the development and progression of cALD. WGCNA results filtered by functional correlation via protein–protein interaction analysis overlapping with GSEA revealed four genes (annexin A5, beta-2-microglobulin, CD44 molecule, and fibroblast growth factor 2) that showed robust associations with the pathogeneses of cALD and AD, where they were highly involved in inflammation, apoptosis, and the mitogen-activated protein kinase pathway. This study provided an integrated strategy to provide new insights into a rare disease with scant publicly available data (cALD) using a more prevalent disorder with some pathological association (AD), which suggests novel druggable targets and drug candidates.

REPS1 as a Potential Biomarker in Alzheimer’s Disease and Vascular Dementia

Vascular dementia (VD) and Alzheimer’s disease (AD) are common types of dementia for which no curative therapies are known. In this study, we identified hub genes associated with AD and VD in order to explore new potential therapeutic targets. Genes differentially expressed in VD and AD in all three datasets (GSE122063, GSE132903, and GSE5281) were identified and used to construct a protein–protein interaction network. We identified 10 modules containing 427 module genes in AD and VD. Module genes showing an area under the diagnostic curve > 0.60 for AD or VD were used to construct a least absolute shrinkage and selection operator model and were entered into a support vector machine-recursive feature elimination algorithm, which identified REPS1 as a hub gene in AD and VD. Furthermore, REPS1 was associated with activation of pyruvate metabolism and inhibition of Ras signaling pathway. Module genes, together with differentially expressed microRNAs from the dataset GSE46579, were used to construct a regulatory network. REPS1 was predicted to bind to the microRNA hsa_miR_5701. Single-sample gene set enrichment analysis was used to explore immune cell infiltration, which suggested a negative correlation between REPS1 expression and infiltration by plasmacytoid dendritic cells in AD and VD. In conclusion, our results suggest core pathways involved in both AD and VD, and they identify REPS1 as a potential biomarker of both diseases. This protein may aid in early diagnosis, monitoring of treatment response, and even efforts to prevent these debilitating disorders.

Innate Immune Cell Death in Neuroinflammation and Alzheimer's Disease

Alzheimer's disease (AD) is a neurodegenerative disorder molecularly characterized by the formation of amyloid β (Aβ) plaques and type 2 microtubule-associated protein (Tau) abnormalities. Multiple studies have shown that many of the brain's immunological cells, specifically microglia and astrocytes, are involved in AD pathogenesis. Cells of the innate immune system play an essential role in eliminating pathogens but also regulate brain homeostasis and AD. When activated, innate immune cells can cause programmed cell death through multiple pathways, including pyroptosis, apoptosis, necroptosis, and PANoptosis. The cell death often results in the release of proinflammatory cytokines that propagate the innate immune response and can eliminate Aβ plaques and aggregated Tau proteins. However, chronic neuroinflammation, which can result from cell death, has been linked to neurodegenerative diseases and can worsen AD. Therefore, the innate immune response must be tightly balanced to appropriately clear these AD-related structural abnormalities without inducing chronic neuroinflammation. In this review, we discuss neuroinflammation, innate immune responses, inflammatory cell death pathways, and cytokine secretion as they relate to AD. Therapeutic strategies targeting these innate immune cell death mechanisms will be critical to consider for future preventive or palliative treatments for AD.

Transcriptional landscape of human microglia implicates age, sex, and APOE-related immunometabolic pathway perturbations

Microglia have fundamental roles in health and disease; however, effects of age, sex, and genetic factors on human microglia have not been fully explored. We applied bulk and single-cell approaches to comprehensively characterize human microglia transcriptomes and their associations with age, sex, and APOE. We identified a novel microglial signature, characterized its expression in bulk tissue and single-cell microglia transcriptomes. We discovered microglial co-expression network modules associated with age, sex, and APOE-ε4 that are enriched for lipid and carbohydrate metabolism genes. Integrated analyses of modules with single-cell transcriptomes revealed significant overlap between age-associated module genes and both pro-inflammatory and disease-associated microglial clusters. These modules and clusters harbor known neurodegenerative disease genes including APOE, PLCG2, and BIN1. Meta-analyses with published bulk and single-cell microglial datasets further supported our findings. Thus, these data represent a well-characterized human microglial transcriptome resource and highlight age, sex, and APOE-related microglial immunometabolism perturbations with potential relevance in neurodegeneration.

Multi-modality machine learning predicting Parkinson's disease

Personalized medicine promises individualized disease prediction and treatment. The convergence of machine learning (ML) and available multimodal data is key moving forward. We build upon previous work to deliver multimodal predictions of Parkinson's disease (PD) risk and systematically develop a model using GenoML, an automated ML package, to make improved multi-omic predictions of PD, validated in an external cohort. We investigated top features, constructed hypothesis-free disease-relevant networks, and investigated drug-gene interactions. We performed automated ML on multimodal data from the Parkinson's progression marker initiative (PPMI). After selecting the best performing algorithm, all PPMI data was used to tune the selected model. The model was validated in the Parkinson's Disease Biomarker Program (PDBP) dataset. Our initial model showed an area under the curve (AUC) of 89.72% for the diagnosis of PD. The tuned model was then tested for validation on external data (PDBP, AUC 85.03%). Optimizing thresholds for classification increased the diagnosis prediction accuracy and other metrics. Finally, networks were built to identify gene communities specific to PD. Combining data modalities outperforms the single biomarker paradigm. UPSIT and PRS contributed most to the predictive power of the model, but the accuracy of these are supplemented by many smaller effect transcripts and risk SNPs. Our model is best suited to identifying large groups of individuals to monitor within a health registry or biobank to prioritize for further testing. This approach allows complex predictive models to be reproducible and accessible to the community, with the package, code, and results publicly available.

Association of mitochondrial variants and haplogroups identified by whole exome sequencing with Alzheimer's disease

INTRODUCTION

Findings regarding the association between mitochondrial DNA (mtDNA) variants and Alzheimer's disease (AD) are inconsistent.

METHODS

We developed a pipeline for accurate assembly and variant calling in mitochondrial genomes embedded within whole exome sequences (WES) from 10,831 participants from the Alzheimer's Disease Sequencing Project (ADSP). Association of AD risk was evaluated with each mtDNA variant and variants located in 1158 nuclear genes related to mitochondrial function using the SCORE test. Gene-based tests were performed using SKAT-O.

RESULTS

Analysis of 4220 mtDNA variants revealed study-wide significant association of AD with a rare MT-ND4L variant (rs28709356 C>T; minor allele frequency = 0.002; P = 7.3 × 10-5 ) as well as with MT-ND4L in a gene-based test (P = 6.71 × 10-5 ). Significant association was also observed with a MT-related nuclear gene, TAMM41, in a gene-based test (P = 2.7 × 10-5 ). The expression of TAMM41 was lower in AD cases than controls (P = .00046) or mild cognitive impairment cases (P = .03).

DISCUSSION

Significant findings in MT-ND4L and TAMM41 provide evidence for a role of mitochondria in AD.

Large-scale sequencing studies expand the known genetic architecture of Alzheimer's disease

INTRODUCTION

Genes implicated by genome-wide association studies and family-based studies of Alzheimer's disease (AD) are largely discordant. We hypothesized that genes identified by sequencing studies like the Alzheimer's Disease Sequencing Project (ADSP) may bridge this gap and highlight shared biological mechanisms.

METHODS

We performed structured literature review of genes prioritized by ADSP studies, genes underlying familial dementias, and genes nominated by genome-wide association studies. Gene set enrichment analyses of each list identified enriched pathways.

RESULTS

The genes prioritized by the ADSP, familial dementia studies, and genome-wide association studies minimally overlapped. Each gene set identified dozens of enriched pathways, several of which were shared (e.g., regulation of amyloid beta clearance).

DISCUSSION

Alternative study designs provide unique insights into AD genetics. Shared pathways enriched by different genes highlight their relevance to AD pathogenesis, while the patterns of pathway enrichment unique to each gene set provide additional targets for functional studies.

Rare variants in the endocytic pathway are associated with Alzheimer's disease, its related phenotypes, and functional consequences

Late-onset Alzheimer's disease (LOAD) is the most common type of dementia causing irreversible brain damage to the elderly and presents a major public health challenge. Clinical research and genome-wide association studies have suggested a potential contribution of the endocytic pathway to AD, with an emphasis on common loci. However, the contribution of rare variants in this pathway to AD has not been thoroughly investigated. In this study, we focused on the effect of rare variants on AD by first applying a rare-variant gene-set burden analysis using genes in the endocytic pathway on over 3,000 individuals with European ancestry from three large whole-genome sequencing (WGS) studies. We identified significant associations of rare-variant burden within the endocytic pathway with AD, which were successfully replicated in independent datasets. We further demonstrated that this endocytic rare-variant enrichment is associated with neurofibrillary tangles (NFTs) and age-related phenotypes, increasing the risk of obtaining severer brain damage, earlier age-at-onset, and earlier age-of-death. Next, by aggregating rare variants within each gene, we sought to identify single endocytic genes associated with AD and NFTs. Careful examination using NFTs revealed one significantly associated gene, ANKRD13D. To identify functional associations, we integrated bulk RNA-Seq data from over 600 brain tissues and found two endocytic expression genes (eGenes), HLA-A and SLC26A7, that displayed significant influences on their gene expressions. Differential expressions between AD patients and controls of these three identified genes were further examined by incorporating scRNA-Seq data from 48 post-mortem brain samples and demonstrated distinct expression patterns across cell types. Taken together, our results demonstrated strong rare-variant effect in the endocytic pathway on AD risk and progression and functional effect of gene expression alteration in both bulk and single-cell resolution, which may bring more insight and serve as valuable resources for future AD genetic studies, clinical research, and therapeutic targeting.

Tau Protein Interaction Partners and Their Roles in Alzheimer's Disease and Other Tauopathies

Tau protein plays a critical role in the assembly, stabilization, and modulation of microtubules, which are important for the normal function of neurons and the brain. In diseased conditions, several pathological modifications of tau protein manifest. These changes lead to tau protein aggregation and the formation of paired helical filaments (PHF) and neurofibrillary tangles (NFT), which are common hallmarks of Alzheimer's disease and other tauopathies. The accumulation of PHFs and NFTs results in impairment of physiological functions, apoptosis, and neuronal loss, which is reflected as cognitive impairment, and in the late stages of the disease, leads to death. The causes of this pathological transformation of tau protein haven't been fully understood yet. In both physiological and pathological conditions, tau interacts with several proteins which maintain their proper function or can participate in their pathological modifications. Interaction partners of tau protein and associated molecular pathways can either initiate and drive the tau pathology or can act neuroprotective, by reducing pathological tau proteins or inflammation. In this review, we focus on the tau as a multifunctional protein and its known interacting partners active in regulations of different processes and the roles of these proteins in Alzheimer's disease and tauopathies.

Characterization of Human Genes Modulated by Porphyromonas gingivalis Highlights the Ribosome, Hypothalamus, and Cholinergic Neurons

Porphyromonas gingivalis, a bacterium associated with periodontal disease, is a suspected cause of Alzheimer's disease. This bacterium is reliant on gingipain proteases, which cleave host proteins after arginine and lysine residues. To characterize gingipain susceptibility, we performed enrichment analyses of arginine and lysine proportion proteome-wide. Genes differentially expressed in brain samples with detected P. gingivalis reads were also examined. Genes from these analyses were tested for functional enrichment and specific neuroanatomical expression patterns. Proteins in the SRP-dependent cotranslational protein targeting to membrane pathway were enriched for these residues and previously associated with periodontal and Alzheimer's disease. These ribosomal genes are up-regulated in prefrontal cortex samples with detected P. gingivalis sequences. Other differentially expressed genes have been previously associated with dementia (ITM2B, MAPT, ZNF267, and DHX37). For an anatomical perspective, we characterized the expression of the P. gingivalis associated genes in the mouse and human brain. This analysis highlighted the hypothalamus, cholinergic neurons, and the basal forebrain. Our results suggest markers of neural P. gingivalis infection and link the cholinergic and gingipain hypotheses of Alzheimer's disease.

A Machine Learning Method to Identify Genetic Variants Potentially Associated With Alzheimer's Disease

There is hope that genomic information will assist prediction, treatment, and understanding of Alzheimer's disease (AD). Here, using exome data from ∼10,000 individuals, we explore machine learning neural network (NN) methods to estimate the impact of SNPs (i.e., genetic variants) on AD risk. We develop an NN-based method (netSNP) that identifies hundreds of novel potentially protective or at-risk AD-associated SNPs (along with an effect measure); the majority with frequency under 0.01. For case individuals, the number of "protective" (or "at-risk") netSNP-identified SNPs in their genome correlates positively (or inversely) with their age of AD diagnosis and inversely (or positively) with autopsy neuropathology. The effect measure increases correlations. Simulations suggest our results are not due to genetic linkage, overfitting, or bias introduced by netSNP. These findings suggest that netSNP can identify SNPs associated with AD pathophysiology that may assist with the diagnosis and mechanistic understanding of the disease.

How understudied populations have contributed to our understanding of Alzheimer's disease genetics

The majority of genome-wide association studies have been conducted using samples with a broadly European genetic background. As a field, we acknowledge this limitation and the need to increase the diversity of populations studied. A major challenge when designing and conducting such studies is to assimilate large samples sizes so that we attain enough statistical power to detect variants associated with disease, particularly when trying to identify variants with low and rare minor allele frequencies. In this review, we aimed to illustrate the benefits to genetic characterization of Alzheimer's disease, in researching currently understudied populations. This is important for both fair representation of world populations and the translatability of findings. To that end, we conducted a literature search to understand the contributions of studies, on different populations, to Alzheimer's disease genetics. Using both PubMed and Alzforum Mutation Database, we systematically quantified the number of studies reporting variants in known disease-causing genes, in a worldwide manner, and discuss the contributions of research in understudied populations to the identification of novel genetic factors in this disease. Additionally, we compared the effects of genome-wide significant single nucleotide polymorphisms across populations by focusing on loci that show different association profiles between populations (a key example being APOE). Reports of variants in APP, PSEN1 and PSEN2 can initially determine whether patients from a country have been studied for Alzheimer's disease genetics. Most genome-wide significant associations in non-Hispanic white genome-wide association studies do not reach genome-wide significance in such studies of other populations, with some suggesting an opposite effect direction; this is likely due to much smaller sample sizes attained. There are, however, genome-wide significant associations first identified in understudied populations which have yet to be replicated. Familial studies in understudied populations have identified rare, high effect variants, which have been replicated in other populations. This work functions to both highlight how understudied populations have furthered our understanding of Alzheimer's disease genetics, and to help us gauge our progress in understanding the genetic architecture of this disease in all populations.

Set-Based Rare Variant Expression Quantitative Trait Loci in Blood and Brain from Alzheimer Disease Study Participants

Because studies of rare variant effects on gene expression have limited power, we investigated set-based methods to identify rare expression quantitative trait loci (eQTL) related to Alzheimer disease (AD). Gene-level and pathway-level cis rare-eQTL mapping was performed genome-wide using gene expression data derived from blood donated by 713 Alzheimer's Disease Neuroimaging Initiative participants and from brain tissues donated by 475 Religious Orders Study/Memory and Aging Project participants. The association of gene or pathway expression with a set of all cis potentially regulatory low-frequency and rare variants within 1 Mb of genes was evaluated using SKAT-O. A total of 65 genes expressed in the brain were significant targets for rare expression single nucleotide polymorphisms (eSNPs) among which 17% (11/65) included established AD genes HLA-DRB1 and HLA-DRB5. In the blood, 307 genes were significant targets for rare eSNPs. In the blood and the brain, GNMT, LDHC, RBPMS2, DUS2, and HP were targets for significant eSNPs. Pathway enrichment analysis revealed significant pathways in the brain (n = 9) and blood (n = 16). Pathways for apoptosis signaling, cholecystokinin receptor (CCKR) signaling, and inflammation mediated by chemokine and cytokine signaling were common to both tissues. Significant rare eQTLs in inflammation pathways included five genes in the blood (ALOX5AP, CXCR2, FPR2, GRB2, IFNAR1) that were previously linked to AD. This study identified several significant gene- and pathway-level rare eQTLs, which further confirmed the importance of the immune system and inflammation in AD and highlighted the advantages of using a set-based eQTL approach for evaluating the effect of low-frequency and rare variants on gene expression.

Enhancing and Complementary Mechanisms of Synergistic Action of Acori Tatarinowii Rhizoma and Codonopsis Radix for Alzheimer's Disease Based on Systems Pharmacology

Materials and Methods

In this study, a systems pharmacology-based strategy was used to elucidate the synergistic mechanism of Acori Tatarinowii Rhizoma and Codonopsis Radix for the treatment of AD. This novel systems pharmacology model consisted of component information, pharmacokinetic analysis, and pharmacological data. Additionally, the related pathways were compressed using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database, and the organ distributions were determined in the BioGPS bank.

Results

Sixty-eight active ingredients with suitable pharmacokinetic profiles and biological activities were selected through ADME screening in silico. Based on 62 AD-related targets, such as APP, CHRM1, and PTGS1, systematic analysis showed that these two herbs were mainly involved in the PI3K-Akt signaling pathway, MAPK signaling pathway, neuroactive ligand-receptor interaction, and fluid shear stress and atherosclerosis, indicating that they had a synergistic effect on AD. However, ATR acted on the KDR gene, while CR acted on IGF1R, MET, IL1B, and CHUK, showing that they also had complementary effects on AD. The ingredient contribution score involved 29 ingredients contributing 90.14% of the total contribution score of this formula for AD treatment, which emphasized that the effective therapeutic effects of these herbs for AD were derived from both ATR and CR, not a single herb. Organ distribution showed that the targets of the active ingredients were mainly located in the whole blood, the brain, and the muscle, which are associated with AD.

Conclusions

In sum, our findings suggest that the systems pharmacology methods successfully revealed the synergistic and complementary mechanisms of ATR and CR for the treatment of AD.

Executive Summary of the 2019 International Conference of Korean Dementia Association: Exploring the Novel Concept of Alzheimer's Disease and Other Dementia: a Report from the Academic Committee of the Korean Dementia Association

Because of repeated failures of clinical trials, the concept of Alzheimer's disease (AD) has been changing rapidly in recent years. As suggested by the National Institute on Aging and the Alzheimer's Association Research Framework, the diagnosis and classification of AD is now based on biomarkers rather than on symptoms, allowing more accurate identification of proper candidates for clinical trials by pathogenesis and disease stage. Recent development in neuroimaging has provided a way to reveal the complex dynamics of amyloid and tau in the brain in vivo, and studies of blood biomarkers are taking another leap forward in diagnosis and treatment of AD. In the field of basic and translational research, the development of animal models and a deeper understanding of the role of neuroinflammation are taking a step closer to clarifying the pathogenesis of AD. Development of big data and the Internet of Things is also incorporating dementia care and research into other aspects. Large-scale genetic research has identified genetic abnormalities that can provide a foundation for precision medicine along with the aforementioned digital technologies. Through the first international conference of the Korean Dementia Association, experts from all over the world gathered to exchange opinions with association members on these topics. The Academic Committee of the Korean Dementia Association briefly summarizes the contents of the lectures to convey the depth of the conference and discussions. This will be an important milestone in understanding the latest trends in AD's pathogenesis, diagnostic and therapeutic research and in establishing a future direction.

Proteomic and biological profiling of extracellular vesicles from Alzheimer's disease human brain tissues

Introduction

Extracellular vesicles (EVs) from human Alzheimer's disease (AD) biospecimens contain amyloid beta (Aβ) peptide and tau. While AD EVs are known to affect brain disease pathobiology, their biochemical and molecular characterizations remain ill defined.

Methods

EVs were isolated from the cortical gray matter of 20 AD and 18 control brains. Tau and Aβ levels were measured by immunoassay. Differentially expressed EV proteins were assessed by quantitative proteomics and machine learning.

Results

Levels of pS396 tau and Aβ1–42 were significantly elevated in AD EVs. High levels of neuron‐ and glia‐specific factors are detected in control and AD EVs, respectively. Machine learning identified ANXA5, VGF, GPM6A, and ACTZ in AD EV compared to controls. They distinguished AD EVs from controls in the test sets with 88% accuracy.

Discussion

In addition to Aβ and tau, ANXA5, VGF, GPM6A, and ACTZ are new signature proteins in AD EVs.

Analysis of Whole-Exome Sequencing Data for Alzheimer Disease Stratified by APOE Genotype

IMPORTANCE

Previous genome-wide association studies of common variants identified associations for Alzheimer disease (AD) loci evident only among individuals with particular APOE alleles.

OBJECTIVE

To identify APOE genotype-dependent associations with infrequent and rare variants using whole-exome sequencing.

DESIGN, SETTING, AND PARTICIPANTS

The discovery stage included 10 441 non-Hispanic white participants in the Alzheimer Disease Sequencing Project. Replication was sought in 2 independent, whole-exome sequencing data sets (1766 patients with AD, 2906 without AD [controls]) and a chip-based genotype imputation data set (8728 patients with AD, 9808 controls). Bioinformatics and functional analyses were conducted using clinical, cognitive, neuropathologic, whole-exome sequencing, and gene expression data obtained from a longitudinal cohort sample including 402 patients with AD and 647 controls. Data were analyzed between March 2017 and September 2018.

MAIN OUTCOMES AND MEASURES

Score, Firth, and sequence kernel association tests were used to test the association of AD risk with individual variants and genes in subgroups of APOE ε4 carriers and noncarriers. Results with P ≤ 1 × 10-5 were further evaluated in the replication data sets and combined by meta-analysis.

RESULTS

Among 3145 patients with AD and 4213 controls lacking ε4 (mean [SD] age, 83.4 [7.6] years; 4363 [59.3.%] women), novel genome-wide significant associations were obtained in the discovery sample with rs536940594 in AC099552 (odds ratio [OR], 88.0; 95% CI, 9.08-852.0; P = 2.22 × 10-7) and rs138412600 in GPAA1 (OR, 1.78; 95% CI, 1.44-2.2; meta-P = 7.81 × 10-8). GPAA1 was also associated with expression in the brain of GPAA1 (β = -0.08; P = .03) and its repressive transcription factor, FOXG1 (β = 0.13; P = .003), and global cognition function (β = -0.53; P = .009). Significant gene-wide associations (threshold P ≤ 6.35 × 10-7) were observed for OR8G5 (P = 4.67 × 10-7), IGHV3-7 (P = 9.75 × 10-16), and SLC24A3 (P = 2.67 × 10-12) in 2377 patients with AD and 706 controls with ε4 (mean [SD] age, 75.2 [9.6] years; 1668 [54.1%] women).

CONCLUSIONS AND RELEVANCE

The study identified multiple possible novel associations for AD with individual and aggregated rare variants in groups of individuals with and without APOE ε4 alleles that reinforce known and suggest additional pathways leading to AD.

miRNAs Identify Shared Pathways in Alzheimer's and Parkinson's Diseases

Despite the identification of several dozens of common genetic variants associated with Alzheimer's disease (AD) and Parkinson's disease (PD), most of the genetic risk remains uncharacterised. Therefore, it is important to understand the role of regulatory elements, such as miRNAs. Dysregulated miRNAs are implicated in AD and PD, with potential value in dissecting the shared pathophysiology between the two disorders. miRNAs relevant to both neurodegenerative diseases are related to axonal guidance, apoptosis, and inflammation, therefore, AD and PD likely arise from similar underlying biological pathway defects. Furthermore, pathways regulated by APP, L1CAM, and genes of the caspase family may represent promising therapeutic miRNA targets in AD and PD since they are targeted by dysregulated miRNAs in both disorders.

Association of Rare Coding Mutations With Alzheimer Disease and Other Dementias Among Adults of European Ancestry

Importance

Some of the unexplained heritability of Alzheimer disease (AD) may be due to rare variants whose effects are not captured in genome-wide association studies because very large samples are needed to observe statistically significant associations.

Objective

To identify genetic variants associated with AD risk using a nonstatistical approach.

Design, Setting, and Participants

Genetic association study in which rare variants were identified by whole-exome sequencing in unrelated individuals of European ancestry from the Alzheimer's Disease Sequencing Project (ADSP). Data were analyzed between March 2017 and September 2018.

Main Outcomes and Measures

Minor alleles genome-wide and in 95 genes previously associated with AD, AD-related traits, or other dementias were tabulated and filtered for predicted functional impact and occurrence in participants with AD but not controls. Support for several findings was sought in a whole-exome sequencing data set comprising 19 affected relative pairs from Utah high-risk pedigrees and whole-genome sequencing data sets from the ADSP and Alzheimer's Disease Neuroimaging Initiative.

Results

Among 5617 participants with AD (3202 [57.0%] women; mean [SD] age, 76.4 [9.3] years) and 4594 controls (2719 [59.0%] women; mean [SD] age, 86.5 [4.5] years), a total of 24 variants with moderate or high functional impact from 19 genes were observed in 10 or more participants with AD but not in controls. These variants included a missense mutation (rs149307620 [p.A284T], n = 10) in NOTCH3, a gene in which coding mutations are associated with cerebral autosomal-dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL), that was also identified in 1 participant with AD and 1 participant with mild cognitive impairment in the whole genome sequencing data sets. Four participants with AD carried the TREM2 rs104894002 (p.Q33X) high-impact mutation that, in homozygous form, causes Nasu-Hakola disease, a rare disorder characterized by early-onset dementia and multifocal bone cysts, suggesting an intermediate inheritance model for the mutation. Compared with controls, participants with AD had a significantly higher burden of deleterious rare coding variants in dementia-associated genes (2314 vs 3354 cumulative variants, respectively; P = .006).

Conclusions and Relevance

Different mutations in the same gene or variable dose of a mutation may be associated with result in distinct dementias. These findings suggest that minor differences in the structure or amount of protein may be associated with in different clinical outcomes. Understanding these genotype-phenotype associations may provide further insight into the pathogenic nature of the mutations, as well as offer clues for developing new therapeutic targets.