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BackgroundThe polygenic nature of Alzheimer's disease (AD) suggests that multiple variants jointly contribute to disease susceptibility. As an individual's genetic variants are constant throughout life, evaluating the combined effects of multiple disease-associated genetic risks enables reliable AD risk prediction. Because of the complexity of genomic data, current statistical analyses cannot comprehensively capture the polygenic risk of AD, resulting in unsatisfactory disease risk prediction. However, deep learning methods, which capture nonlinearity within high-dimensional genomic data, may enable more accurate disease risk prediction and improve our understanding of AD etiology. Accordingly, we developed deep learning neural network models for modeling AD polygenic risk.MethodsWe constructed neural network models to model AD polygenic risk and compared them with the widely used weighted polygenic risk score and lasso models. We conducted robust linear regression analysis to investigate the relationship between the AD polygenic risk derived from deep learning methods and AD endophenotypes (i.e., plasma biomarkers and individual cognitive performance). We stratified individuals by applying unsupervised clustering to the outputs from the hidden layers of the neural network model.ResultsThe deep learning models outperform other statistical models for modeling AD risk. Moreover, the polygenic risk derived from the deep learning models enables the identification of disease-associated biological pathways and the stratification of individuals according to distinct pathological mechanisms.ConclusionOur results suggest that deep learning methods are effective for modeling the genetic risks of AD and other diseases, classifying disease risks, and uncovering disease mechanisms.

Changes in the levels of circulating proteins are associated with Alzheimer's disease (AD), whereas their pathogenic roles in AD are unclear. Here, we identified soluble ST2 (sST2), a decoy receptor of interleukin-33-ST2 signaling, as a new disease-causing factor in AD. Increased circulating sST2 level is associated with more severe pathological changes in female individuals with AD. Genome-wide association analysis and CRISPR-Cas9 genome editing identified rs1921622 , a genetic variant in an enhancer element of IL1RL1, which downregulates gene and protein levels of sST2. Mendelian randomization analysis using genetic variants, including rs1921622 , demonstrated that decreased sST2 levels lower AD risk and related endophenotypes in females carrying the Apolipoprotein E (APOE)-ε4 genotype; the association is stronger in Chinese than in European-descent populations. Human and mouse transcriptome and immunohistochemical studies showed that rs1921622 /sST2 regulates amyloid-beta (Aβ) pathology through the modulation of microglial activation and Aβ clearance. These findings demonstrate how sST2 level is modulated by a genetic variation and plays a disease-causing role in females with AD.

Alzheimer's disease (AD) is a leading cause of mortality in the elderly. While the coding change of APOE-ε4 is a key risk factor for late-onset AD and has been believed to be the only risk factor in the APOE locus, it does not fully explain the risk effect conferred by the locus. Here, we report the identification of AD causal variants in PVRL2 and APOC1 regions in proximity to APOE and define common risk haplotypes independent of APOE-ε4 coding change. These risk haplotypes are associated with changes of AD-related endophenotypes including cognitive performance, and altered expression of APOE and its nearby genes in the human brain and blood. High-throughput genome-wide chromosome conformation capture analysis further supports the roles of these risk haplotypes in modulating chromatin states and gene expression in the brain. Our findings provide compelling evidence for additional risk factors in the APOE locus that contribute to AD pathogenesis.

Alzheimer's disease (AD) is a leading cause of mortality among the elderly. We performed a whole-genome sequencing study of AD in the Chinese population. In addition to the variants identified in or around the APOE locus (sentinel variant rs73052335, P = 1.44 × 10-14), two common variants, GCH1 (rs72713460, P = 4.36 × 10-5) and KCNJ15 (rs928771, P = 3.60 × 10-6), were identified and further verified for their possible risk effects for AD in three small non-Asian AD cohorts. Genotype-phenotype analysis showed that KCNJ15 variant rs928771 affects the onset age of AD, with earlier disease onset in minor allele carriers. In addition, altered expression level of the KCNJ15 transcript can be observed in the blood of AD subjects. Moreover, the risk variants of GCH1 and KCNJ15 are associated with changes in their transcript levels in specific tissues, as well as changes of plasma biomarkers levels in AD subjects. Importantly, network analysis of hippocampus and blood transcriptome datasets suggests that the risk variants in the APOE, GCH1, and KCNJ15 loci might exert their functions through their regulatory effects on immune-related pathways. Taking these data together, we identified common variants of GCH1 and KCNJ15 in the Chinese population that contribute to AD risk. These variants may exert their functional effects through the immune system.

INTRODUCTION: Blood protein biomarkers demonstrate potential for Alzheimer's disease (AD) diagnosis. Limited studies examine the molecular changes in AD blood cells. METHODS: Bulk RNA‐sequencing of blood cells was performed on AD patients of Chinese descent (n = 214 and 26 in the discovery and validation cohorts, respectively) with normal controls (n = 208 and 38 in the discovery and validation cohorts, respectively). Weighted gene co‐expression network analysis (WGCNA) and deconvolution analysis identified AD‐associated gene modules and blood cell types. Regression and unsupervised clustering analysis identified AD‐associated genes, gene modules, cell types, and established AD classification models. RESULTS: WGCNA on differentially expressed genes revealed 15 gene modules, with 6 accurately classifying AD (areas under the receiver operating characteristics curve [auROCs] > 0.90). These modules stratified AD patients into subgroups with distinct disease states. Cell‐type deconvolution analysis identified specific blood cell types potentially associated with AD pathogenesis. DISCUSSION: This study highlights the potential of blood transcriptome for AD diagnosis, patient stratification, and mechanistic studies. Highlights: We comprehensively analyze the blood transcriptomes of a well‐characterized Alzheimer's disease cohort to identify genes, gene modules, pathways, and specific blood cells associated with the disease.Blood transcriptome analysis accurately classifies and stratifies patients with Alzheimer's disease, with some gene modules achieving classification accuracy comparable to that of the plasma ATN biomarkers.Immune‐associated pathways and immune cells, such as neutrophils, have potential roles in the pathogenesis and progression of Alzheimer's disease. [ABSTRACT FROM AUTHOR]

Recent multi‐omics analyses paved the way for a comprehensive understanding of pathological processes. However, only few studies have explored Alzheimer's disease (AD) despite the possibility of biological subtypes within these patients. For this study, unsupervised classification of four datasets (genetics, miRNA transcriptomics, proteomics, and blood‐based biomarkers) using Multi‐Omics Factor Analysis+ (MOFA+), along with systems‐biological approaches following various downstream analyses are performed. New subgroups within 170 patients with cerebral amyloid pathology (Aβ+) are revealed and the features of them are identified based on the top‐rated targets constructing multi‐omics factors of both whole (M‐TPAD) and immune‐focused models (M‐IPAD). The authors explored the characteristics of subtypes and possible key‐drivers for AD pathogenesis. Further in‐depth studies showed that these subtypes are associated with longitudinal brain changes and autophagy pathways are main contributors. The significance of autophagy or clustering tendency is validated in peripheral blood mononuclear cells (PBMCs; n = 120 including 30 Aβ‐ and 90 Aβ+), induced pluripotent stem cell‐derived human brain organoids/microglia (n = 12 including 5 Aβ‐, 5 Aβ+, and CRISPR‐Cas9 apolipoprotein isogenic lines), and human brain transcriptome (n = 78). Collectively, this study provides a strategy for precision medicine therapy and drug development for AD using integrative multi‐omics analysis and network modelling. [ABSTRACT FROM AUTHOR]

Background: Alzheimer's disease (AD) is the most common cause of dementia in the elderly population. However, epidemiological studies on the demographics of AD in Hong Kong population are lacking.Objective: We investigated the demographics, comorbidities, mortality rates, and medication use of patients with AD in Hong Kong to understand how the disease has been managed locally.Methods: This was a collaborative study of The Hong Kong University of Science and Technology and the Hospital Authority Data Collaboration Lab. We analyzed the demographic data, clinical records, diagnoses, and medication records of patients with AD under the care of the Hospital Authority between January 1, 2007 and December 31, 2017.Results: We identified 23,467 patients diagnosed with AD. The median age at diagnosis was 84 years old, and 71% of patients were female. The most common comorbidity was hypertension (52.6%). 39.9% of patients received medications for dementia; of those, 68.4% had taken those medications for > 1 year. Compared to nonusers, long-term AD medication users had a significantly younger age of AD onset and were taking more lipid-regulating medication, diabetes medication, or antidepressants. Surprisingly, the use of antipsychotics in patients with AD was quite common; 50.7% of patients had received any type of antipsychotic during disease progression.Conclusion: This study provides detailed information on the demographics and medication use of patients with AD in Hong Kong. The data from this AD cohort will aid our future research aiming to identify potential AD risk factors and associations between AD and other diseases. [ABSTRACT FROM AUTHOR]

Background: Genetic studies reveal that single-nucleotide polymorphisms (SNPs) of SPI1 are associated with Alzheimer's disease (AD), while their effects in the Chinese population remain unclear.Objective: We aimed to examine the AD-association of SPI1 SNPs in the Chinese population and investigate the underlying mechanisms of these SNPs in modulating AD risk.Methods: We conducted a genetic analysis of three SPI1 SNPs (i.e., rs1057233, rs3740688, and rs78245530) in a Chinese cohort (n = 333 patients with AD, n = 721 normal controls). We also probed public European-descent AD cohorts and gene expression datasets to investigate the putative functions of those SNPs.Results: We showed that SPI1 SNP rs3740688 is significantly associated with AD in the Chinese population (odds ratio [OR] = 0.72 [0.58-0.89]) and identified AD-protective SPI1 haplotypes β (tagged by rs1057233 and rs3740688) and γ (tagged by rs3740688 and rs78245530). Specifically, haplotypes β and γ are associated with decreased SPI1 gene expression level in the blood and brain tissues, respectively. The regulatory roles of these haplotypes are potentially mediated by changes in miRNA binding and the epigenetic landscape. Our results suggest that the AD-protective SPI1 haplotypes regulate pathways involved in immune and neuronal functions.Conclusion: This study is the first to report a significant association of SPI1 with AD in the Chinese population. It also identifies SPI1 haplotypes that are associated with SPI1 gene expression and decreased AD risk. [ABSTRACT FROM AUTHOR]

Introduction: Blood proteins are emerging as candidate biomarkers for Alzheimer’s disease (AD). We systematically profiled the plasma proteome to identify novel AD blood biomarkers and develop a high-performance, blood-based test for AD. Methods: We quantified 1160 plasma proteins in a Hong Kong Chinese cohort by high-throughput proximity extension assay and validated the results in an independent cohort. In subgroup analyses, plasma biomarkers for amyloid, tau, phosphorylated tau, and neurodegeneration were used as endophenotypes of AD. Results: We identified 429 proteins that were dysregulated in AD plasma. We selected 19 “hub proteins” representative of the AD plasma protein profile, which formed the basis of a scoring system that accurately classified clinical AD (area under the curve = 0.9690–0.9816) and associated endophenotypes. Moreover, specific hub proteins exhibit disease stage-dependent dysregulation, which can delineate AD stages. Discussion: This study comprehensively profiled the AD plasma proteome and serves as a foundation for a high-performance, blood-based test for clinical AD screening and staging. [ABSTRACT FROM AUTHOR]

The high prevalence of Alzheimer's disease (AD) among the elderly population and its lack of effective treatments make this disease a critical threat to human health. Recent epidemiological and genetics studies have revealed the polygenic nature of the disease, which is possibly explainable by a polygenic score model that considers multiple genetic risks. Here, we systemically review the rationale and methods used to construct polygenic score models for studying AD. We also discuss the associations of polygenic risk scores (PRSs) with clinical outcomes, brain imaging findings, and biochemical biomarkers from both the brain and peripheral system. Finally, we discuss the possibility of incorporating polygenic score models into research and clinical practice along with potential challenges. [ABSTRACT FROM AUTHOR]

Background: Genetic factors are increasingly being recognized as important contributors to the pathogenesis of Alzheimer's disease (AD). While the expression of most AD risk genes is enriched in microglia, which leads to microglial dysfunction and amyloid‐beta (Aβ) accumulation, emerging studies suggest that changes in the brain micro‐environment—typically changes in the levels of soluble factors—also modulate microglial functions and disease‐related pathological changes. Therefore, understanding the genetic regulation and pathogenic roles of those soluble factors in AD will help clarify the pathophysiological mechanisms of the disease. Method: We examined the changes in the level of soluble ST2 (sST2), a decoy receptor of IL‐33/ST2 signaling, in the blood and brains of patients with AD, and performed a genome‐wide association study (GWAS) for sST2 to understand its genetic regulations. Result: We showed that elevated sST2 levels are associated with more severe neurodegeneration and Aβ pathological lesions in patients with AD. Our GWAS analysis identified a genetic variant in IL1RL1 (the gene encoding sST2) that is associated with decreased sST2 levels in the blood and brain in AD. Furthermore, we demonstrated that female APOE‐ε4 carriers harboring the genetic variant exhibit decreased sST2 level and reduced risk of AD as well as decreased Aβ accumulation through enhancing microglial activation and colocalization with Aβ. Conclusion: These findings demonstrate how sST2 level in the brain milieu is modulated by a genetic variation and plays a disease‐causing role in AD through microglial clearance of Aβ, and might thus be a novel target for AD therapy. [ABSTRACT FROM AUTHOR]

Background: Alzheimer's disease (AD) is a leading cause of mortality in the elderly. Genetics studies suggest that AD is polygenic in nature; thus, an individual's risk of AD can be predicted by polygenic risk score (PRS) models. Of these models, the deep learning models more accurately capture nonlinear interactions among different genetic risks and are more suitable for modeling disease polygenic risk. Method: We used the neural network‐based deep learning models to evaluate the polygenic risk of AD. Meanwhile, we examined the associations of resultant PRSs and plasma protein biomarkers for AD by regression analysis. We also identified the biological pathways that contribute to the polygenic risk using Gene Set Enrichment Analysis. Result: We found that the resultant PRSs of AD are associated with the levels of specific AD plasma protein biomarkers, including amyloid beta and p‐tau181, as well as changes in the activity of specific biological events, such as TNF‐α and cytokine‐related pathways. Conclusion: Our findings suggest that AD polygenic risk is associated with AD progression and modulates immune‐associated pathways. They also highlight the potential use of deep learning methods in investigating the underlying genetic mechanisms of AD. [ABSTRACT FROM AUTHOR]

Background: Blood proteins are emerging candidate biomarkers for Alzheimer's disease (AD). A comprehensive investigation of the AD blood proteome will help identify additional biomarkers to delineate the disease's pathways and define specific AD stages. Method: We quantified 1,160 plasma proteins in a Hong Kong Chinese cohort (n = 106 AD patients, n = 74 healthy controls) by high‐throughput proximity extension assay to identify AD‐associated plasma proteins. Result: Plasma proteins involved in diverse biological processes were found to be dysregulated in AD. A subset of plasma proteins was selected to represent the AD plasma protein profile, which formed the basis of a scoring system that can accurately classify AD and associated endophenotypes. In addition, we showed that certain plasma proteins and biological processes exhibit stage‐specific dysregulation in AD, thus adding biological annotations to AD stages. Conclusion: This study comprehensively profiled the AD plasma proteome and serves as a foundation for a high‐performance, blood‐based test for clinical AD screening and staging. [ABSTRACT FROM AUTHOR]

Background: Alzheimer's disease (AD) is a leading cause of mortality in the elderly. Genetics studies have identified variants associated with AD. Moreover, Polygenic score analysis can infer the risk of developing AD solely on the basis of genotype information. Method: Whole‐genome sequencing was performed in 2 AD cohorts recruited from mainland China (n = 2,340) and Hong Kong (n = 1,009). Genotype and phenotype data were input into a neural network model that output a polygenic score. Regression analysis was subsequently conducted to examine the associations between the resultant polygenic scores and AD plasma biomarkers. Result: The resultant polygenic scores were associated with AD pathogenesis and the levels of specific AD plasma biomarkers in the Chinese population. Conclusion: The results suggest that deep‐learning methods have utility for investigating the underlying mechanisms of AD and promote the possibility of developing a genotype‐based strategy for AD risk prediction. [ABSTRACT FROM AUTHOR]

During development, scaffold proteins serve as important platforms for orchestrating signaling complexes to transduce extracellular stimuli into intracellular responses that regulate dendritic spine morphology and function. Axin (“axis inhibitor”) is a key scaffold protein in canonical Wnt signaling that interacts with specific synaptic proteins. However, the cellular functions of these protein–protein interactions in dendritic spine morphology and synaptic regulation are unclear. Here, we report that Axin protein is enriched in synaptic fractions, colocalizes with the postsynaptic marker PSD-95 in cultured hippocampal neurons, and interacts with a signaling protein Ca2+/calmodulin-dependent protein kinase II (CaMKII) in synaptosomal fractions. Axin depletion by shRNA in cultured neurons or intact hippocampal CA1 regions significantly reduced dendritic spine density. Intriguingly, the defective dendritic spine morphogenesis in Axin-knockdown neurons could be restored by overexpression of the small Rho-GTPase Cdc42, whose activity is regulated by CaMKII. Moreover, pharmacological stabilization of Axin resulted in increased dendritic spine number and spontaneous neurotransmission, while Axin stabilization in hippocampal neurons reduced the elimination of dendritic spines. Taken together, our findings suggest that Axin promotes dendritic spine stabilization through Cdc42-dependent cytoskeletal reorganization. [ABSTRACT FROM AUTHOR]

Background: Although blood transcriptome has emerged as a powerful resource for studying human diseases, the changes in the blood transcriptome of Alzheimer's disease (AD) patients are poorly understood. Method: We conducted transcriptome profiling of 422 participants (208 normal controls and 214 patients with AD) from the Hong Kong Chinese population. WGCNA (weighted correlation network analysis) was performed to construct a co‐expression network to identify modules associated with AD and AD‐associated biomarkers. Result: Co‐expression modules exerting significant association with AD and AD plasma biomarkers (e.g., Aβ and NFL) were identified. Pathway enrichment analysis suggested their possible involvement in specific biological pathways. Motif analysis further revealed the potential mechanisms that driving the observed blood transcriptomic changes observed in AD. Conclusion: The co‐expression network analysis of the AD blood transcriptome changes may facilitate a better understanding of AD progression, as well as the identification of potential targets for disease intervention and monitoring. [ABSTRACT FROM AUTHOR]

Background: Alzheimer's disease (AD) is a leading cause of mortality in the elderly. Although genome‐wide association studies (GWASs) have identified dozens of genetic risk factors in the Caucasian population, their associations with AD in the Chinese population have not been thoroughly investigated. Method: A TaqMan‐based single‐nucleotide polymorphism genotyping assay was implemented to evaluate Caucasian GWAS risk variants in a Hong Kong Chinese AD cohort (n = 732). Logistic regression analysis was performed to examine the associations between these risk variants and AD, adjusting for age and gender. Result: Several Caucasian AD candidate loci including SORL1(rs11218343) and ABCA7(rs4147929) were associated with AD in the Hong Kong Chinese AD cohort. Conclusion: Known Caucasian AD GWAS candidates can contribute to AD risk in the Chinese population. This suggests that AD pathogenesis might share general mechanisms in both Asian and Caucasian populations. [ABSTRACT FROM AUTHOR]

Introduction: The SORL1 locus exhibits protective effects against Alzheimer's disease (AD) across ancestries, yet systematic studies in diverse populations are sparse., Methods: Logistic regression identified AD-associated SORL1 haplotypes in East Asian (N = 5249) and European (N = 8588) populations. Association analysis between SORL1 haplotypes and AD-associated traits or plasma biomarkers was conducted. The effects of non-synonymous mutations were assessed in cell-based systems., Results: Protective SORL1 variants/haplotypes were identified in the East Asian and European populations. Haplotype Hap_A showed a strong protective effect against AD in East Asians, linked to less severe AD phenotypes, higher SORL1 transcript levels, and plasma proteomic changes. A missense variant within Hap_A, rs2282647-C allele, was linked to a lower risk of AD and decreased expression of a truncated SORL1 protein isoform., Discussion: Our transethnic analysis revealed key SORL1 haplotypes that exert protective effects against AD, suggesting mechanisms of the protective role of SORL1 in AD., Highlights: We examined the AD-protective mechanisms of SORL1 in the general population across diverse ancestral backgrounds by jointly analyzing data from three East Asian cohorts (ie, mainland China, Hong Kong, and Japan) and a European cohort. Comparative analysis unveiled key ethnic-specific SORL1 genetic variants and haplotypes. Among these, the SORL1 minor haplotype, Hap_A, emerged as the primary AD-protective factor in East Asians. Hap_A exerts significant AD-protective effects in both APOE ε4 carriers and non-carriers. SORL1 haplotype Hap_A is associated with cognitive function, brain volume, and the activity of specific neuronal and immune-related pathways closely connected to AD risk. Protective variants within Hap_A are linked to increased SORL1 expression in human tissues. We identified an isoform-specific missense variant in Hap_A that modifies the function and levels of a truncated SORL1 protein isoform that is poorly investigated., (© 2024 The Author(s). Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

Introduction: Blood protein biomarkers demonstrate potential for Alzheimer's disease (AD) diagnosis. Limited studies examine the molecular changes in AD blood cells., Methods: Bulk RNA-sequencing of blood cells was performed on AD patients of Chinese descent (n = 214 and 26 in the discovery and validation cohorts, respectively) with normal controls (n = 208 and 38 in the discovery and validation cohorts, respectively). Weighted gene co-expression network analysis (WGCNA) and deconvolution analysis identified AD-associated gene modules and blood cell types. Regression and unsupervised clustering analysis identified AD-associated genes, gene modules, cell types, and established AD classification models., Results: WGCNA on differentially expressed genes revealed 15 gene modules, with 6 accurately classifying AD (areas under the receiver operating characteristics curve [auROCs] > 0.90). These modules stratified AD patients into subgroups with distinct disease states. Cell-type deconvolution analysis identified specific blood cell types potentially associated with AD pathogenesis., Discussion: This study highlights the potential of blood transcriptome for AD diagnosis, patient stratification, and mechanistic studies., Highlights: We comprehensively analyze the blood transcriptomes of a well-characterized Alzheimer's disease cohort to identify genes, gene modules, pathways, and specific blood cells associated with the disease. Blood transcriptome analysis accurately classifies and stratifies patients with Alzheimer's disease, with some gene modules achieving classification accuracy comparable to that of the plasma ATN biomarkers. Immune-associated pathways and immune cells, such as neutrophils, have potential roles in the pathogenesis and progression of Alzheimer's disease., (© 2024 The Authors. Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

Introduction: Blood proteins are emerging as candidate biomarkers for Alzheimer's disease (AD). We systematically profiled the plasma proteome to identify novel AD blood biomarkers and develop a high-performance, blood-based test for AD., Methods: We quantified 1160 plasma proteins in a Hong Kong Chinese cohort by high-throughput proximity extension assay and validated the results in an independent cohort. In subgroup analyses, plasma biomarkers for amyloid, tau, phosphorylated tau, and neurodegeneration were used as endophenotypes of AD., Results: We identified 429 proteins that were dysregulated in AD plasma. We selected 19 "hub proteins" representative of the AD plasma protein profile, which formed the basis of a scoring system that accurately classified clinical AD (area under the curve  = 0.9690-0.9816) and associated endophenotypes. Moreover, specific hub proteins exhibit disease stage-dependent dysregulation, which can delineate AD stages., Discussion: This study comprehensively profiled the AD plasma proteome and serves as a foundation for a high-performance, blood-based test for clinical AD screening and staging., (© 2021 The Authors. Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

Biochemical, pathogenic, and human genetic data confirm that GSAP (γ-secretase activating protein), a selective γ-secretase modulatory protein, plays important roles in Alzheimer's disease (AD) and Down's syndrome. However, the molecular mechanism(s) underlying GSAP-dependent pathogenesis remains largely elusive. Here, through unbiased proteomics and single-nuclei RNAseq, we identified that GSAP regulates multiple biological pathways, including protein phosphorylation, trafficking, lipid metabolism, and mitochondrial function. We demonstrated that GSAP physically interacts with the Fe65-APP complex to regulate APP trafficking/partitioning. GSAP is enriched in the mitochondria-associated membrane (MAM) and regulates lipid homeostasis through the amyloidogenic processing of APP. GSAP deletion generates a lipid environment unfavorable for AD pathogenesis, leading to improved mitochondrial function and the rescue of cognitive deficits in an AD mouse model. Finally, we identified a novel GSAP single-nucleotide polymorphism that regulates its brain transcript level and is associated with an increased AD risk. Together, our findings indicate that GSAP impairs mitochondrial function through its MAM localization and that lowering GSAP expression reduces pathological effects associated with AD., Competing Interests: Disclosures: Y.-M. Li is a co-inventor of the intellectual property (assay for γ-secretase activity and screening method for γ-secretase inhibitors) owned by MSKCC and licensed to Jiangsu Continental Medical Development. The authors have no further conflicts of interest to declare., (© 2021 Xu et al.)

Introduction: Dozens of Alzheimer's disease (AD)-associated loci have been identified in European-descent populations, but their effects have not been thoroughly investigated in the Hong Kong Chinese population., Methods: TaqMan array genotyping was performed for known AD-associated variants in a Hong Kong Chinese cohort. Regression analysis was conducted to study the associations of variants with AD-associated traits and biomarkers. Lasso regression was applied to establish a polygenic risk score (PRS) model for AD risk prediction., Results: SORL1 is associated with AD in the Hong Kong Chinese population. Meta-analysis corroborates the AD-protective effect of the SORL1 rs11218343 C allele. The PRS is developed and associated with AD risk, cognitive status, and AD-related endophenotypes. TREM2 H157Y might influence the amyloid beta 42/40 ratio and levels of immune-associated proteins in plasma., Discussion: SORL1 is associated with AD in the Hong Kong Chinese population. The PRS model can predict AD risk and cognitive status in this population., Competing Interests: All authors declare no conflicts of interests., (© 2020 The Authors. Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring published by Wiley Periodicals, Inc. on behalf of the Alzheimer's Association.)

The proper growth and arborization of dendrites in response to sensory experience are essential for neural connectivity and information processing in the brain. Although neuronal activity is important for sculpting dendrite morphology, the underlying molecular mechanisms are not well understood. Here, we report that cyclin-dependent kinase 5 (Cdk5)-mediated transcriptional regulation is a key mechanism that controls activity-dependent dendrite development in cultured rat neurons. During membrane depolarization, Cdk5 accumulates in the nucleus to regulate the expression of a subset of genes, including that of the neurotrophin brain-derived neurotrophic factor, for subsequent dendritic growth. Furthermore, Cdk5 function is mediated through the phosphorylation of methyl-CpG-binding protein 2, a key transcriptional repressor that is mutated in the mental disorder Rett syndrome. These findings collectively suggest that the nuclear import of Cdk5 is crucial for activity-dependent dendrite development by regulating neuronal gene transcription during neural development., Significance Statement: Neural activity directs dendrite development through the regulation of gene transcription. However, how molecular signals link extracellular stimuli to the transcriptional program in the nucleus remains unclear. Here, we demonstrate that neuronal activity stimulates the translocation of the kinase Cdk5 from the cytoplasmic compartment into the nucleus; furthermore, the nuclear localization of Cdk5 is required for dendrite development in cultured neurons. Genome-wide transcriptome analysis shows that Cdk5 deficiency specifically disrupts activity-dependent gene transcription of bdnf. The action of Cdk5 is mediated through the modulation of the transcriptional repressor methyl-CpG-binding protein 2. Therefore, this study elucidates the role of nuclear Cdk5 in the regulation of activity-dependent gene transcription and dendritic growth., (Copyright © 2015 the authors 0270-6474/15/3515127-08$15.00/0.)