Non-coding variants in MYH11, FZD3, and SORCS3 are associated with dementia in women

Genetic neurodevelopmental clustering and dyslexia

Dyslexia is a learning difficulty with neurodevelopmental origins, manifesting as reduced accuracy and speed in reading and spelling. It is substantially heritable and frequently co-occurs with other neurodevelopmental conditions, particularly attention deficit-hyperactivity disorder (ADHD). Here, we investigate the genetic structure underlying dyslexia and a range of psychiatric traits using results from genome-wide association studies of dyslexia, ADHD, autism, anorexia nervosa, anxiety, bipolar disorder, major depressive disorder, obsessive compulsive disorder, schizophrenia, and Tourette syndrome. Genomic Structural Equation Modelling (GenomicSEM) showed heightened support for a model consisting of five correlated latent genomic factors described as: F1) compulsive disorders (including obsessive-compulsive disorder, anorexia nervosa, Tourette syndrome), F2) psychotic disorders (including bipolar disorder, schizophrenia), F3) internalising disorders (including anxiety disorder, major depressive disorder), F4) neurodevelopmental traits (including autism, ADHD), and F5) attention and learning difficulties (including ADHD, dyslexia). ADHD loaded more strongly on the attention and learning difficulties latent factor (F5) than on the neurodevelopmental traits latent factor (F4). The attention and learning difficulties latent factor (F5) was positively correlated with internalising disorders (.40), neurodevelopmental traits (.25) and psychotic disorders (.17) latent factors, and negatively correlated with the compulsive disorders (-.16) latent factor. These factor correlations are mirrored in genetic correlations observed between the attention and learning difficulties latent factor and other cognitive, psychological and wellbeing traits. We further investigated genetic variants underlying both dyslexia and ADHD, which implicated 49 loci (40 not previously found in GWAS of the individual traits) mapping to 174 genes (121 not found in GWAS of individual traits) as potential pleiotropic variants. Our study confirms the increased genetic relation between dyslexia and ADHD versus other psychiatric traits and uncovers novel pleiotropic variants affecting both traits. In future, analyses including additional co-occurring traits such as dyscalculia and dyspraxia will allow a clearer definition of the attention and learning difficulties latent factor, yielding further insights into factor structure and pleiotropic effects.

Elucidation of the effects of 2,5-hexandione as a metabolite of n-hexane on cognitive impairment in leptin-knockout mice (C57BL/6-Lepem1Shwl/Korl)

Exposure to n-hexane and its metabolite 2,5-hexandione (HD) is a well-known cause of neurotoxicity, particularly in the peripheral nervous system. To date, few studies have focused on the neurotoxic effects of HD on cognitive impairment. Exposure to HD and diabetes mellitus can exacerbate neurotoxicity. There are links among HD, diabetes mellitus, and cognitive impairment; however, the specific mechanisms underlying them remain unclear. Therefore, we aimed to elucidate the neurotoxic effects of HD on cognitive impairment in ob/ob (C57BL/6-Lepem1Shwl/Korl) mice. We found that HD induced cognitive impairment by altering the expression of genes (FN1, AGT, ACTA2, MYH11, MKI67, MET, CTGF, and CD44), miRNAs (mmu-miR15a-5p, mmu-miR-17-5p, and mmu-miR-29a-3p), transcription factors (transcription factor AP-2 alpha [TFAP2A], serum response factor [Srf], and paired box gene 4 [PAX4]), and signaling pathways (ERK/CERB, PI3K/AKT, GSK-3β/p-tau/amyloid-β), as well as by causing neuroinflammation (TREM1/DAP12/NF-κB), oxidative stress, and apoptosis. The prevalent use of n-hexane in various industrial applications (for instance, shoe manufacturing, printing inks, paints, and varnishes) suggests that individuals with elevated body weight and glucose levels and those employed in high-risk workplaces have greater probability of cognitive impairment. Therefore, implementing screening strategies for HD-induced cognitive dysfunction is crucial.

Graphical abstract

Supplementary Information

The online version contains supplementary material available at 10.1007/s43188-024-00228-1.

A systematic review/meta-analysis of prevalence and incidence rates illustrates systemic underrepresentation of individuals racialized as Asian and/or Asian-American in ADRD research

We investigate Alzheimer's disease and related dementia (ADRD) prevalence, incidence rate, and risk factors in individuals racialized as Asian and/or Asian-American and assess sample representation. Prevalence, incidence rate, risk factors, and heterogeneity of samples were assessed. Random-effects meta-analysis was conducted, generating pooled estimates. Of 920 records across 14 databases, 45 studies were included. Individuals racialized as Asian and/or Asian-American were mainly from Eastern and Southern Asia, had higher education, and constituted a smaller sample relative to non-Hispanic white cohorts. The average prevalence was 10.9%, ranging from 0.4% to 46%. The average incidence rate was 20.03 (12.01-33.8) per 1000 person-years with a range of 75.19-13.59 (12.89-14.33). Risk factors included physiological, genetic, psychological, behavioral, and social factors. This review underscores the systemic underrepresentation of individuals racialized as Asian and/or Asian-American in ADRD research and the need for inclusive approaches accounting for culture, language, and immigration status. HIGHLIGHTS: There is considerable heterogeneity in the prevalence of ADRD among studies of Asian-Americans. There is limited data on group-specific risk factors for ADRD among Asian-Americans. The average prevalence of (ADRD) among Asian-Americans was found to be 7.4%, with a wide range from 0.5% to 46%.

Exploration of the influence of GOLGA8B on prostate cancer progression and the resistance of castration-resistant prostate cancer to cabazitaxel

Castration-resistant prostate cancer (CRPC) represents the final stage of prostate cancer (PCa). Cabazitaxel, a taxane chemotherapy drug, is used in treating CRPC. However, patients with CRPC eventually develop resistance to cabazitaxel, and the underlying mechanism remains unclear. Here, we aimed to investigate potential genetic alterations that may play a role in CRPC resistance to cabazitaxel. Using microarray data from the GSE158494 dataset, we identified ten critical genes (CXCL8, ITGB8, CLIP4, MAP1B, WIPI1, MMP13, CXCL1, C1S, GOLGA8B, and CXCL6) associated with CRPC cell resistance to cabazitaxel. The potential function of these key genes in PCa progression was analyzed using different databases, including Gene Expression Omnibus (GEO), The Cancer Genome Atlas (TCGA), and Chinese Prostate Cancer Genome and Epigenome Atlas (CPGEA). Our findings revealed altered expression of these genes in the development of PCa. Furthermore, CXCL1 and GOLGA8B were found to influence the disease-free survival (DFS) status of patients with PCa, with GOLGA8B affecting the overall prognosis in patients with PCa. Additionally, GOLGA8B expression was associated with the infiltration of various immune cells in PCa, and it was upregulated in clinical PCa and CRPC samples. Through CCK-8 assays, we established that GOLGA8B could influence the sensitivity of CRPC cells to cabazitaxel and docetaxel. In conclusion, we identified GOLGA8B as a crucial gene that influences PCa progression and contributes to CRPC resistance to cabazitaxel.

Dissecting the genetic overlap between severe mental disorders and markers of cellular aging: Identification of pleiotropic genes and druggable targets

Patients with severe mental disorders such as bipolar disorder (BD), schizophrenia (SCZ) and major depressive disorder (MDD) show a substantial reduction in life expectancy, increased incidence of comorbid medical conditions commonly observed with advanced age and alterations of aging hallmarks. While severe mental disorders are heritable, the extent to which genetic predisposition might contribute to accelerated cellular aging is not known. We used bivariate causal mixture models to quantify the trait-specific and shared architecture of mental disorders and 2 aging hallmarks (leukocyte telomere length [LTL] and mitochondrial DNA copy number), and the conjunctional false discovery rate method to detect shared genetic loci. We integrated gene expression data from brain regions from GTEx and used different tools to functionally annotate identified loci and investigate their druggability. Aging hallmarks showed low polygenicity compared with severe mental disorders. We observed a significant negative global genetic correlation between MDD and LTL (rg = -0.14, p = 6.5E-10), and no significant results for other severe mental disorders or for mtDNA-cn. However, conditional QQ plots and bivariate causal mixture models pointed to significant pleiotropy among all severe mental disorders and aging hallmarks. We identified genetic variants significantly shared between LTL and BD (n = 17), SCZ (n = 55) or MDD (n = 19), or mtDNA-cn and BD (n = 4), SCZ (n = 12) or MDD (n = 1), with mixed direction of effects. The exonic rs7909129 variant in the SORCS3 gene, encoding a member of the retromer complex involved in protein trafficking and intracellular/intercellular signaling, was associated with shorter LTL and increased predisposition to all severe mental disorders. Genetic variants underlying risk of SCZ or MDD and shorter LTL modulate expression of several druggable genes in different brain regions. Genistein, a phytoestrogen with anti-inflammatory and antioxidant effects, was an upstream regulator of 2 genes modulated by variants associated with risk of MDD and shorter LTL. While our results suggest that shared heritability might play a limited role in contributing to accelerated cellular aging in severe mental disorders, we identified shared genetic determinants and prioritized different druggable targets and compounds.

A Pilot Urinary Proteome Study Reveals Widespread Influences of Circadian Rhythm Disruption by Sleep Deprivation

It is widely accepted that circadian rhythm disruption caused short- or long-term adverse effects on health. Although many previous studies have focused on exploration of the molecular mechanisms, there is no rapid, convenient, and non-invasive method to reveal the influence on health after circadian rhythm disruption. Here, we performed a high-resolution mass spectrometry-based data-independent acquisition (DIA) quantitative urinary proteomic approach in order to explore whether urine could reveal stress changes to those brought about by circadian rhythm disruption after sleep deprivation. After sleep deprivation, the subjects showed a significant increase in both systolic and diastolic blood pressure compared with routine sleep. More than 2000 proteins were quantified and they contained specific proteins for various organs throughout the body. And a total of 177 significantly up-regulated proteins and 68 significantly down-regulated proteins were obtained after sleep deprivation. These differentially expressed proteins (DEPs) were associated with multiple organs and pathways, which reflected widespread influences of sleep deprivation. Besides, machine learning identified a panel of five DEPs (CD300A, SCAMP3, TXN2, EFEMP1, and MYH11) that can effectively discriminate circadian rhythm disruption. Taken together, our results validate the value of urinary proteome in predicting and diagnosing the changes by circadian rhythm disruption.

Brain high-throughput multi-omics data reveal molecular heterogeneity in Alzheimer's disease

Unbiased data-driven omic approaches are revealing the molecular heterogeneity of Alzheimer disease. Here, we used machine learning approaches to integrate high-throughput transcriptomic, proteomic, metabolomic, and lipidomic profiles with clinical and neuropathological data from multiple human AD cohorts. We discovered 4 unique multimodal molecular profiles, one of them showing signs of poor cognitive function, a faster pace of disease progression, shorter survival with the disease, severe neurodegeneration and astrogliosis, and reduced levels of metabolomic profiles. We found this molecular profile to be present in multiple affected cortical regions associated with higher Braak tau scores and significant dysregulation of synapse-related genes, endocytosis, phagosome, and mTOR signaling pathways altered in AD early and late stages. AD cross-omics data integration with transcriptomic data from an SNCA mouse model revealed an overlapping signature. Furthermore, we leveraged single-nuclei RNA-seq data to identify distinct cell-types that most likely mediate molecular profiles. Lastly, we identified that the multimodal clusters uncovered cerebrospinal fluid biomarkers poised to monitor AD progression and possibly cognition. Our cross-omics analyses provide novel critical molecular insights into AD.

Whole genome methylation sequencing in blood identifies extensive differential DNA methylation in late-onset dementia due to Alzheimer's disease

INTRODUCTION

DNA microarray-based studies report differentially methylated positions (DMPs) in blood between late-onset dementia due to Alzheimer's disease (AD) and cognitively unimpaired individuals, but interrogate < 4% of the genome.

METHODS

We used whole genome methylation sequencing (WGMS) to quantify DNA methylation levels at 25,409,826 CpG loci in 281 blood samples from 108 AD and 173 cognitively unimpaired individuals.

RESULTS

WGMS identified 28,038 DMPs throughout the human methylome, including 2707 differentially methylated genes (e.g., SORCS3, GABA, and PICALM) encoding proteins in biological pathways relevant to AD such as synaptic membrane, cation channel complex, and glutamatergic synapse. One hundred seventy-three differentially methylated blood-specific enhancers interact with the promoters of 95 genes that are differentially expressed in blood from persons with and without AD.

DISCUSSION

WGMS identifies differentially methylated CpGs in known and newly detected genes and enhancers in blood from persons with and without AD.

HIGHLIGHTS

Whole genome DNA methylation levels were quantified in blood from persons with and without Alzheimer's disease (AD). Twenty-eight thousand thirty-eight differentially methylated positions (DMPs) were identified. Two thousand seven hundred seven genes comprise DMPs. Forty-eight of 75 independent genetic risk loci for AD have DMPs. One thousand five hundred sixty-eight blood-specific enhancers comprise DMPs, 173 of which interact with the promoters of 95 genes that are differentially expressed in blood from persons with and without AD.

FZD3 regulates the viability, apoptosis, and extracellular matrix degradation of vaginal wall fibroblasts in pelvic organ prolapse via the Wnt signaling pathway

The occurrence of pelvic organ prolapse (POP) seriously affects women's quality of life. However, the pathogenesis of POP remains unclear. We aimed to clarify the role of Frizzled class receptor 3 (FZD3) in POP. FZD3 expression in the vaginal wall tissues was detected using immunohistochemistry, real-time polymerase chain reaction, and western blot analysis. Then, vaginal wall fibroblasts (VWFs) were isolated from patients with POP and non-POP, and were identified. Cell viability and apoptosis were evaluated using Cell Counting Kit-8 and flow cytometry, respectively. Extracellular matrix (ECM) degradation was assessed by western blot analysis. The results illustrated that FZD3 was downregulated in POP. VWFs from POP had lower cell viability, ECM degradation, and higher apoptosis. Knockdown of FZD3 inhibited cell viability, ECM degradation, and promoted apoptosis of VWFs, whereas overexpression of FZD3 had opposite results. Moreover, IWP-4 (Wingless-type [Wnt] pathway inhibitor) reversed the role of FZD3 overexpression on biological behaviors. Taken together, FZD3 facilitates VWFs viability, ECM degradation, and inhibits apoptosis via the Wnt pathway in POP. The findings provide a potential target for the treatment of POP.

Replication of previous autism-GWAS hits suggests the association between NAA1, SORCS3, and GSDME and autism in the Han Chinese population

Background

Autism is a severe neurodevelopmental disorder characterized by social interaction deficits, impairments in communication, and restricted and repetitive stereotyped behavior and activities. Family and twin studies suggested an essential role of genetic factors in the etiology of autism spectrum disorder (ASD). Also, other studies found SORCS3 and GSDME (DFNA5) might be involved in brain development and susceptible to ASD.

Methods

In this study, 17 genome-wide significant SNPs reported in previous ASD genome-wide association studies (GWAS) and 7 SNPs in strong linkage disequilibrium with known ASD GWAS hits were selected to investigate the association between these SNPs and autism in the Han Chinese population. Then, 10 tagSNPs in SORCS3 and 11 tagSNPs in GSDME were selected to analyze the association between these SNPs and autism. The selected 24 SNPs and tagSNPs were genotyped using the Agena MassARRAY SNP genotyping assay in 757 Han Chinese autism trios.

Results

Rs1484144 in NAA11 was significantly associated with autism; significance remained after the Bonferroni correction (P < 0.0022). Also, rs79879286, rs12154597, and rs12540919 near GSDME, as well as rs9787523 and rs3750261 in SORCS3, were nominally associated with autism.

Conclusion

Our study suggests that rs1484144 in NAA11 is a significant SNP for autism in the Han Chinese population, while SORCS3 and GSDME might be the susceptibility genes for autism in this population.

Novel Isolation Method Reveals Sex-Specific Composition and Neurotoxicity of Small Extracellular Vesicles in a Mouse Model of Alzheimer's Disease

We developed a new method to isolate small extracellular vesicles (sEVs) from male and female wild-type and 5xFAD mouse brains to investigate the sex-specific functions of sEVs in Alzheimer's disease (AD). A mass spectrometric analysis revealed that sEVs contained proteins critical for EV formation and Aβ. ExoView analysis showed that female mice contained more GFAP and Aβ-labeled sEVs, suggesting that a larger proportion of sEVs from the female brain is derived from astrocytes and/or more likely to bind to Aβ. Moreover, sEVs from female brains had more acid sphingomyelinase (ASM) and ceramide, an enzyme and its sphingolipid product important for EV formation and Aβ binding to EVs, respectively. We confirmed the function of ASM in EV formation and Aβ binding using co-labeling and proximity ligation assays, showing that ASM inhibitors prevented complex formation between Aβ and ceramide in primary cultured astrocytes. Finally, our study demonstrated that sEVs from female 5xFAD mice were more neurotoxic than those from males, as determined by impaired mitochondrial function (Seahorse assays) and LDH cytotoxicity assays. Our study suggests that sex-specific sEVs are functionally distinct markers for AD and that ASM is a potential target for AD therapy.

Group-shrinkage feature selection with a spatial network for mining DNA methylation data

Identifying disease-related biomarkers from high-dimensional DNA methylation data helps in reducing early screening costs and inferring pathogenesis mechanisms. Good discovery results have been achieved through spatial correlation methods of methylation sites, group-based regularization, and network constraints. However, these methods still have some key limitations as they cannot exclude isolated differential sites and only consider adjacent site ordering. Therefore, we propose a group-shrinkage feature selection algorithm to encourage the selection of clustered sites and discourage the selection of isolated differential sites. Specifically, a network-guided group-shrinkage strategy is developed to penalize weakly-correlated isolated methylation sites through a network structure constraint. The spatial network is constructed based on spatial correlation information of DNA methylation sites, where this information accounts for the uneven site distribution. The experimental simulations and applications demonstrated that the proposed method outperforms the advanced regularization methods, especially in rejecting isolated methylation sites; hence this study provides an efficient and clinical-valuable method for biomarker candidate discovery in DNA methylation data. Additionally, the proposed method exhibits enhanced reliability due to introducing biological prior knowledge into a regularization-based feature selection framework and could promote more research in the integration between biological prior knowledge and classical feature selection methods, thus facilitating their clinical application. Our source codes will be released at https://github.com/SJTUBME-QianLab/Group-shrinkage-Spatial-Network once this manuscript is accepted for publication.

Independent Associated SNPs at SORCS3 and Its Protein Interactors for Multiple Brain-Related Disorders and Traits

Sortilin-related vacuolar protein sorting 10 (VPS10) domain containing receptor 3 (SORCS3) is a neuron-specific transmembrane protein involved in the trafficking of proteins between intracellular vesicles and the plasma membrane. Genetic variation at SORCS3 is associated with multiple neuropsychiatric disorders and behavioural phenotypes. Here, we undertake a systematic search of published genome-wide association studies to identify and catalogue associations between SORCS3 and brain-related disorders and traits. We also generate a SORCS3 gene-set based on protein-protein interactions and investigate the contribution of this gene-set to the heritability of these phenotypes and its overlap with synaptic biology. Analysis of association signals at SORSC3 showed individual SNPs to be associated with multiple neuropsychiatric and neurodevelopmental brain-related disorders and traits that have an impact on the experience of feeling, emotion or mood or cognitive function, while multiple LD-independent SNPs were associated with the same phenotypes. Across these SNPs, alleles associated with the more favourable outcomes for each phenotype (e.g., decreased risk of neuropsychiatric illness) were associated with increased expression of the SORCS3 gene. The SORCS3 gene-set was enriched for heritability contributing to schizophrenia (SCZ), bipolar disorder (BPD), intelligence (IQ) and education attainment (EA). Eleven genes from the SORCS3 gene-set were associated with more than one of these phenotypes at the genome-wide level, with RBFOX1 associated with SCZ, IQ and EA. Functional annotation revealed that the SORCS3 gene-set is enriched for multiple ontologies related to the structure and function of synapses. Overall, we find many independent association signals at SORCS3 with brain-related disorders and traits, with the effect possibly mediated by reduced gene expression, resulting in a negative impact on synaptic function.

From attention-deficit hyperactivity disorder to sporadic Alzheimer's disease-Wnt/mTOR pathways hypothesis

Alzheimer's disease (AD) is the most common neurodegenerative disorder with the majority of patients classified as sporadic AD (sAD), in which etiopathogenesis remains unresolved. Though sAD is argued to be a polygenic disorder, apolipoprotein E (APOE) ε4, was found three decades ago to pose the strongest genetic risk for sAD. Currently, the only clinically approved disease-modifying drugs for AD are aducanumab (Aduhelm) and lecanemab (Leqembi). All other AD treatment options are purely symptomatic with modest benefits. Similarly, attention-deficit hyperactivity disorder (ADHD), is one of the most common neurodevelopmental mental disorders in children and adolescents, acknowledged to persist in adulthood in over 60% of the patients. Moreover, for ADHD whose etiopathogenesis is not completely understood, a large proportion of patients respond well to treatment (first-line psychostimulants, e.g., methylphenidate/MPH), however, no disease-modifying therapy exists. Interestingly, cognitive impairments, executive, and memory deficits seem to be common in ADHD, but also in early stages of mild cognitive impairment (MCI), and dementia, including sAD. Therefore, one of many hypotheses is that ADHD and sAD might have similar origins or that they intercalate with one another, as shown recently that ADHD may be considered a risk factor for sAD. Intriguingly, several overlaps have been shown between the two disorders, e.g., inflammatory activation, oxidative stress, glucose and insulin pathways, wingless-INT/mammalian target of rapamycin (Wnt/mTOR) signaling, and altered lipid metabolism. Indeed, Wnt/mTOR activities were found to be modified by MPH in several ADHD studies. Wnt/mTOR was also found to play a role in sAD and in animal models of the disorder. Moreover, MPH treatment in the MCI phase was shown to be successful for apathy including some improvement in cognition, according to a recent meta-analysis. In several AD animal models, ADHD-like behavioral phenotypes have been observed indicating a possible interconnection between ADHD and AD. In this concept paper, we will discuss the various evidence in human and animal models supporting the hypothesis in which ADHD might increase the risk for sAD, with common involvement of the Wnt/mTOR-pathway leading to lifespan alteration at the neuronal levels.

Forensic age estimation from human blood using age-related microRNAs and circular RNAs markers

Aging is a complicated process characterized by progressive and extensive changes in physiological homeostasis at the organismal, tissue, and cellular levels. In modern society, age estimation is essential in a large variety of legal rights and duties. Accumulating evidence suggests roles for microRNAs (miRNAs) and circular RNAs (circRNAs) in regulating numerous processes during aging. Here, we performed circRNA sequencing in two age groups and analyzed microarray data of 171 healthy subjects (17-104 years old) downloaded from Gene Expression Omnibus (GEO) and ArrayExpress databases with integrated bioinformatics methods. A total of 1,403 circular RNAs were differentially expressed between young and old groups, and 141 circular RNAs were expressed exclusively in elderly samples while 10 circular RNAs were expressed only in young subjects. Based on their expression pattern in these two groups, the circular RNAs were categorized into three classes: age-related expression between young and old, age-limited expression-young only, and age-limited expression-old only. Top five expressed circular RNAs among three classes and a total of 18 differentially expressed microRNAs screened from online databases were selected to validate using RT-qPCR tests. An independent set of 200 blood samples (20-80 years old) was used to develop age prediction models based on 15 age-related noncoding RNAs (11 microRNAs and 4 circular RNAs). Different machine learning algorithms for age prediction were applied, including regression tree, bagging, support vector regression (SVR), random forest regression (RFR), and XGBoost. Among them, random forest regression model performed best in both training set (mean absolute error = 3.68 years, r = 0.96) and testing set (MAE = 6.840 years, r = 0.77). Models using one single type of predictors, circular RNAs-only or microRNAs-only, result in bigger errors. Smaller prediction errors were shown in males than females when constructing models according to different-sex separately. Putative microRNA targets (430 genes) were enriched in the cellular senescence pathway and cell homeostasis and cell differentiation regulation, indirectly indicating that the microRNAs screened in our study were correlated with development and aging. This study demonstrates that the noncoding RNA aging clock has potential in predicting chronological age and will be an available biological marker in routine forensic investigation to predict the age of biological samples.

Finding memo: versatile interactions of the VPS10p-Domain receptors in Alzheimer’s disease

The family of VPS10p-Domain (D) receptors comprises five members named SorLA, Sortilin, SorCS1, SorCS2 and SorCS3. While their physiological roles remain incompletely resolved, they have been recognized for their signaling engagements and trafficking abilities, navigating a number of molecules between endosome, Golgi compartments, and the cell surface. Strikingly, recent studies connected all the VPS10p-D receptors to Alzheimer’s disease (AD) development. In addition, they have been also associated with diseases comorbid with AD such as diabetes mellitus and major depressive disorder. This systematic review elaborates on genetic, functional, and mechanistic insights into how dysfunction in VPS10p-D receptors may contribute to AD etiology, AD onset diversity, and AD comorbidities. Starting with their functions in controlling cellular trafficking of amyloid precursor protein and the metabolism of the amyloid beta peptide, we present and exemplify how these receptors, despite being structurally similar, regulate various and distinct cellular events involved in AD. This includes a plethora of signaling crosstalks that impact on neuronal survival, neuronal wiring, neuronal polarity, and synaptic plasticity. Signaling activities of the VPS10p-D receptors are especially linked, but not limited to, the regulation of neuronal fitness and apoptosis via their physical interaction with pro- and mature neurotrophins and their receptors. By compiling the functional versatility of VPS10p-D receptors and their interactions with AD-related pathways, we aim to further propel the AD research towards VPS10p-D receptor family, knowledge that may lead to new diagnostic markers and therapeutic strategies for AD patients.

A Fast and Robust Strategy to Remove Variant-Level Artifacts in Alzheimer Disease Sequencing Project Data

Background and Objectives

Exome sequencing (ES) and genome sequencing (GS) are expected to be critical to further elucidate the missing genetic heritability of Alzheimer disease (AD) risk by identifying rare coding and/or noncoding variants that contribute to AD pathogenesis. In the United States, the Alzheimer Disease Sequencing Project (ADSP) has taken a leading role in sequencing AD-related samples at scale, with the resultant data being made publicly available to researchers to generate new insights into the genetic etiology of AD. To achieve sufficient power, the ADSP has adapted a study design where subsets of larger AD cohorts are collected and sequenced across multiple centers, using a variety of sequencing platforms. This approach may lead to variable variant quality across sequencing centers and/or platforms. In this study, we sought to implement and evaluate filters that can be applied fast to robustly remove variant-level artifacts in the ADSP data.

Methods

We implemented a robust quality control procedure to handle ADSP data. We evaluated this procedure while performing exome-wide and genome-wide association analyses on AD risk using the latest ADSP whole ES (WES) and whole GS (WGS) data releases (NG00067.v5).

Results

We observed that many variants displayed large variation in allele frequencies across sequencing centers/platforms and contributed to spurious association signals with AD risk. We also observed that sequencing platform/center adjustment in association models could not fully account for these spurious signals. To address this issue, we designed and implemented variant filters that could capture and remove these center-specific/platform-specific artifactual variants.

Discussion

We derived a fast and robust approach to filter variants that represent sequencing center-related or platform-related artifacts underlying spurious associations with AD risk in ADSP WES and WGS data. This approach will be important to support future robust genetic association studies on ADSP data, as well as other studies with similar designs.

Genome-wide association study of brain arteriolosclerosis

Brain arteriolosclerosis (B-ASC) is characterized by pathologically altered brain parenchymal arterioles. B-ASC is associated with cognitive impairment and increased likelihood of clinical dementia. To date, no study has been conducted on genome-wide genetic risk of autopsy-proven B-ASC. We performed a genome-wide association study (GWAS) of the B-ASC phenotype using multiple independent aged neuropathologic cohorts. Included in the study were participants with B-ASC autopsy and genotype data available from the NACC, ROSMAP, ADNI, and ACT data sets. Initial Stage 1 GWAS (n = 3382) and Stage 2 mega-analysis (n = 4569) were performed using data from the two largest cohorts (NACC and ROSMAP). Replication of top variants and additional Stage 3 mega-analysis were performed incorporating two smaller cohorts (ADNI and ACT). Lead variants in the top two loci in the Stage 2 mega-analysis (rs7902929, p = 1.8 × 10 - 7 ; rs2603462, p = 4 × 10 - 7 ) were significant in the ADNI cohort (rs7902929, p = 0.012 ; rs2603462, p =0.012 ). The rs2603462 lead variant colocalized with ELOVL4 expression in the cerebellum (posterior probability = 90.1%). Suggestive associations were also found near SORCS1 and SORCS3. We thus identified putative loci associated with B-ASC risk, but additional replication is needed.

Preservation Analysis on Spatiotemporal Specific Co-expression Networks Suggests the Immunopathogenesis of Alzheimer's Disease

The occurrence and development of Alzheimer’s disease (AD) is a continuous clinical and pathophysiological process, molecular biological, and brain functional change often appear before clinical symptoms, but the detailed underlying mechanism is still unclear. The expression profiling of postmortem brain tissue from AD patients and controls provides evidence about AD etiopathogenesis. In the current study, we used published AD expression profiling data to construct spatiotemporal specific coexpression networks in AD and analyzed the network preservation features of each brain region in different disease stages to identify the most dramatically changed coexpression modules and obtained AD-related biological pathways, brain regions and circuits, cell types and key genes based on these modules. As result, we constructed 57 spatiotemporal specific networks (19 brain regions by three disease stages) in AD and observed universal expression changes in all 19 brain regions. The eight most dramatically changed coexpression modules were identified in seven brain regions. Genes in these modules are mostly involved in immune response-related pathways and non-neuron cells, and this supports the immune pathology of AD and suggests the role of blood brain barrier (BBB) injuries. Differentially expressed genes (DEGs) meta-analysis and protein–protein interaction (PPI) network analysis suggested potential key genes involved in AD development that might be therapeutic targets. In conclusion, our systematical network analysis on published AD expression profiling data suggests the immunopathogenesis of AD and identifies key brain regions and genes.