The effect of neutral alpha glucosidase on semen parameters.

INTRODUCTION: To investigate the relationship between the activity of neutral α-glucosidase in seminal plasma and semen quality. To explore the effect of secretory capability of the epididymis on male fertility. METHODS: A retrospective analysis of 542 men treated in the Center for Reproductive Medicine and Infertility from February to December 2022, the semen parameters and neutral α-glucosidase were tested and compared among different groups. These 542 men included normozoospermia, oligospermia, asthenospermia and teratozoospermia. RESULTS: There was statistical difference in neutral alpha glucosidase (NAG) level among different groups with different sperm concentration, motility and morphology (P＜0.001). The NAG activity in seminal plasma was positively correlated with ejaculate volume and sperm concentration, meanwhile a very weak positive correlation was found between NAG level and sperm motility, sperm morphology, respectively. CONCLUSIONS: Our results indicated that the secretion of NAG affected the volume, concentration, motility and morphology of sperm to a certain extent. Given that NAG is a specific and marker enzyme in epididymis, where is the site of sperm maturation, we can conclude that there is a close relationship between NAG and sperm quality. Therefore, seminal plasma NAG has a definite clinical value in helping diagnosis of male infertility.

Using blood transcriptome analysis for Alzheimer's disease diagnosis and patient stratification.

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.

Deep learning-based polygenic risk analysis for Alzheimer's disease prediction.

BACKGROUND: The 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. METHODS: We 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. RESULTS: The 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. CONCLUSION: Our 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.

Polygenic diseases, such as Alzheimer's disease (AD), are those caused by the interplay between multiple genetic risk factors. Statistical models can be used to predict disease risk based on a person's genetic profile. However, there are limitations to existing methods, while emerging methods such as deep learning may improve risk prediction. Deep learning involves computer-based software learning from patterns in data to perform a certain task, e.g. predict disease risk. Here, we test whether deep learning models can help to predict AD risk. Our models not only outperformed existing methods in modeling AD risk, they also allow us to estimate an individual's risk of AD and determine the biological processes that may be involved in AD. With further testing and optimization, deep learning may be a useful tool to help accurately predict risk of AD and other diseases.

Multi-Omics-Based Autophagy-Related Untypical Subtypes in Patients with Cerebral Amyloid Pathology.

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 (Aß+) 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 Aß- and 90 Aß+), induced pluripotent stem cell-derived human brain organoids/microglia (n = 12 including 5 Aß-, 5 Aß+, 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.

Demographics and Medication Use of Patients with Late-Onset Alzheimer's Disease in Hong Kong.

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.

Association of SPI1 Haplotypes with Altered SPI1 Gene Expression and Alzheimer's Disease Risk.

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 ß (tagged by rs1057233 and rs3740688) and γ (tagged by rs3740688 and rs78245530). Specifically, haplotypes ß 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.

Brain-wide Cas9-mediated cleavage of a gene causing familial Alzheimer's disease alleviates amyloid-related pathologies in mice.

The pathology of familial Alzheimer's disease, which is caused by dominant mutations in the gene that encodes amyloid-beta precursor protein (APP) and in those that encode presenilin 1 and presenilin 2, is characterized by extracellular amyloid plaques and intracellular neurofibrillary tangles in multiple brain regions. Here we show that the brain-wide selective disruption of a mutated APP allele in transgenic mouse models carrying the human APP Swedish mutation alleviates amyloid-beta-associated pathologies for at least six months after a single intrahippocampal administration of an adeno-associated virus that encodes both Cas9 and a single-guide RNA that targets the mutation. We also show that the deposition of amyloid-beta, as well as microgliosis, neurite dystrophy and the impairment of cognitive performance, can all be ameliorated when the CRISPR-Cas9 construct is delivered intravenously via a modified adeno-associated virus that can cross the blood-brain barrier. Brain-wide disease-modifying genome editing could represent a viable strategy for the treatment of familial Alzheimer's disease and other monogenic diseases that affect multiple brain regions.

Large-scale plasma proteomic profiling identifies a high-performance biomarker panel for Alzheimer's disease screening and staging.

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.

An IL1RL1 genetic variant lowers soluble ST2 levels and the risk effects of APOE-ε4 in female patients with Alzheimer's disease.

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 (Aß) pathology through the modulation of microglial activation and Aß clearance. These findings demonstrate how sST2 level is modulated by a genetic variation and plays a disease-causing role in females with AD.

GSAP regulates lipid homeostasis and mitochondrial function associated with Alzheimer's disease.

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.

Polygenic Score Models for Alzheimer's Disease: From Research to Clinical Applications.

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.

APOE signaling in neurodegenerative diseases: an integrative approach targeting APOE coding and noncoding variants for disease intervention.

APOE (apolipoprotein E) is a key regulator of lipid metabolism and a leading genetic risk factor for Alzheimer's disease. While APOE participates in multiple biological pathways, its roles in diseases are largely due to the mutant protein encoded by APOE-ε4. However, emerging evidence suggests that some noncoding Alzheimer's disease risk variants residing in APOE and its nearby regions exert APOE-ε4-independent risks and modify APOE gene expression. Moreover, intervention strategies targeting APOE are being explored. In this review, we summarize the literature on the genetic risks and roles of APOE in biological systems. Moreover, we propose an integrative approach to evaluate disease risk and tailor interventions to aid research on APOE-associated diseases.

Genetic and polygenic risk score analysis for Alzheimer's disease in the Chinese population.

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.

Changes of Protein Phosphorylation Are Associated with Synaptic Functions during the Early Stage of Alzheimer's Disease.

Alzheimer's disease is an irreversible neurodegenerative disorder for which we have limited knowledge of the mechanisms underlying its pathogenesis, especially the molecular events that trigger the deterioration of neuronal functions in the early stage. Protein phosphorylation and dephosphorylation are highly dynamic and reversible post-translational modifications that control protein signaling and hence neuronal functions, aberrations of which are implicated in various neurodegenerative diseases including Alzheimer's disease. We conducted a quantitative phosphoproteomic analysis in the brains of APP/PS1 mice, an Aß-deposition transgenic mouse model, at 3 months old, the stage at which amyloid pathology just initiates. Compared to the wild-type mouse brains, we found that changes in serine phosphorylation were predominant in the APP/PS1 mouse brains, and that the occurrence of proline-directed phosphorylation was most common among the overrepresented phosphopeptides. Further analysis of the 167 phosphoproteins that were significantly up- or downregulated in APP/PS1 mouse brains revealed the enrichment of these proteins in synapse-related pathways. In particular, Western blot analysis validated the increased phosphorylation of chromogranin B, a protein enriched in large dense-core vesicles, in APP/PS1 mouse brains. These findings collectively suggest that changes in the phosphoprotein network may be associated with the deregulation of synaptic functions during the pathogenesis of Alzheimer's disease.

Non-coding variability at the APOE locus contributes to the Alzheimer's risk.

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.

Magnetic properties and structure of tetranuclear lanthanide complexes based on 8-hydroxylquinoline Schiff base derivative and ß-diketone coligand.

Five tetranuclear lanthanide complexes [Gd4(dbm)4(L)6(µ3-OH)2]·5CH3CN (1), [Tb4(dbm)4(L)6(µ3-OH)2]·2CH3CH2OH·4CH3CN (2), [Dy4(dbm)4(L)6(µ3-OH)2]·4CH3CN·2H2O (3), [Ho4(dbm)4(L)6(µ3-OH)2]·CH3CH2OH·4CH3CN·2H2O (4) and [Er4(dbm)4(L)6(µ3-OH)2] (5) are obtained from the reaction of 5-(4-pyridinecarboxaldehyde)amino-8-hydroxylquinoline (HL) and Ln(dbm)3·2H2O (dbm = 1,3-diphenyl-1,3-propanedione). Complexes 1-5 are isomorphous and crystallize in the monoclinic space group P21/c. The metal ions in 1-5 adopt an approximately square-antiprismatic coordination environment. Magnetic studies indicate that complex 1 features a magnetocaloric effect (MCE) with the magnetic entropy change of -ΔSm(T) = 16.35 J kg-1 K-1 at 3 K for ΔH = 7 T. Additionally, complex 3 displays single molecule magnet (SMM) behavior, exhibiting an effective energy barrier of the relaxation of magnetization Ueff/kB = 89.38 K and pre-exponential factor τ0 = 3.32 × 10-8 s.

Identification of genetic risk factors in the Chinese population implicates a role of immune system in Alzheimer's disease 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.

A Dy4 single-molecule magnet and its Gd(iii), Tb(iii), Ho(iii), and Er(iii) analogues encapsulated by an 8-hydroxyquinoline Schiff base derivative and ß-diketonate coligand.

Five new tetranuclear complexes based on an 8-hydroxyquinoline Schiff base derivative and the ß-diketone coligand, [Ln4(acac)4L6(µ3-OH)2]·CH3CN·0.5CH2Cl2 (Ln = Gd (1), Tb (2), Dy (3), Ho (4) and Er (5); HL = 5-(benzylidene)amino-8-hydroxyquinoline; acac = acetylacetonate) have been synthesized, and structurally and magnetically characterized. Complexes 1-5 have similar tetranuclear structures. Each LnIII ion is eight coordinated and its coordination polyhedra can be described as being in a distorted square-antiprismatic geometry. The magnetic studies reveal that 1 features the magnetocaloric effect (MCE) with the magnetic entropy change of -ΔSm(T) = 25.08 J kg-1 K-1 at 2 K for ΔH = 7 T, and 3 displays the slow magnetic relaxation behavior of Single Molecule Magnets (SMMs) with the anisotropic barrier of 86.20 K and the pre-exponential factor τ0 = 2.99 × 10-8 s.

Modulation of the relaxation dynamics of linear-shaped tetranuclear rare-earth clusters through utilizing different solvents.

Nine new tetranuclear centrosymmetric linear complexes, [RE4(dbm)8L2(DMF)2]·nCH2Cl2·mC2H3N (RE = Y (1), Tb (2), Dy (3), Ho (4), Er (5), Lu (6)) and [RE4(dbm)8L2(C2H5OH)2]·nCH3CN (RE = Tb (7), Dy (8), Ho (9)) (HL = 2-[(2-(hydroxyimino)propanehydrazide)methyl]-8-hydroxyquinoline and dbm = 1,3-diphenyl-1,3-propanedione) have been synthesized. Complexes 1-9 are tetranuclear complexes. Magnetic studies reveal that both DyIII-based complexes (3 and 8) exhibit single-molecule magnet (SMM) behavior under a zero dc field. Furthermore, complex 3 presents one relaxation process under a zero dc field, while application of an external dc field (1500 Oe) induces multi-relaxation signals of the ac magnetic susceptibility.