Association between adding salt in food and dementia in European descent: A mendelian randomization study.

BACKGROUND: High salt intake has been proposed as a risk factor for dementia. However, causal relationship between salt intake and dementia remains uncertain. PURPOSE: The aim of this study was to employ a mendelian randomization (MR) design to investigate the causal impact of salt intake on the risk of dementia. METHODS: Genome-wide association study (GWAS) data of exposures and outcomes (any dementia, cognitive performance, different types of dementia, Alzheimer's disease [AD], and Parkinson's disease) were obtained from the IEU database. MR estimates were generated though inverse-variance weighted model. MR-Egger, weighted median, and MR-Pleiotropy Residual Sum and Outlier (MR-PRESSO) method also used in our study. Sensitivity analyses included Cochran's Q test, MR-Egger intercept, MR-PRESSO global test and outlier test, leave-one-out analysis, and funnel plot assessment. RESULTS: Our MR analysis provided evidence of a causal association between high salt added to food and dementia (odds ratio [OR] = 1.73, 95% confidence interval [CI]: 1.21-2.49, and p = .003), dementia in AD (OR = 2.10, 95% CI: 1.15-3.83, and p = .015), and undefined dementia (OR = 2.61, 95% CI: 1.26-5.39, and p = .009). Higher salt added was also associated with increased risk of AD (OR = 1.80, 95% CI: 1.12-2.87, and p = .014) and lower cognitive performance (ß = -.133, 95% CI: -.229 to -.038, and p = .006). CONCLUSION: This study provides evidence suggesting that high salt intake is causally associated with an increased risk of developing dementia, including AD and undefined dementia, highlighting the potential importance of reducing salt consumption as a preventive measure.

Metabolic phenotyping reveals an emerging role of ammonia abnormality in Alzheimer's disease.

The metabolic implications in Alzheimer's disease (AD) remain poorly understood. Here, we conducted a metabolomics study on a moderately aging Chinese Han cohort (n = 1397; mean age 66 years). Conjugated bile acids, branch-chain amino acids (BCAAs), and glutamate-related features exhibited strong correlations with cognitive impairment, clinical stage, and brain amyloid-ß deposition (n = 421). These features demonstrated synergistic performances across clinical stages and subpopulations and enhanced the differentiation of AD stages beyond demographics and Apolipoprotein E ε4 allele (APOE-ε4). We validated their performances in eight data sets (total n = 7685) obtained from Alzheimer's Disease Neuroimaging Initiative (ADNI) and Religious Orders Study and Memory and Aging Project (ROSMAP). Importantly, identified features are linked to blood ammonia homeostasis. We further confirmed the elevated ammonia level through AD development (n = 1060). Our findings highlight AD as a metabolic disease and emphasize the metabolite-mediated ammonia disturbance in AD and its potential as a signature and therapeutic target for AD.

Polygenic Risk Score Reveals Genetic Heterogeneity of Alzheimer's Disease between the Chinese and European Populations.

BACKGROUND: The polygenic risk score (PRS) aggregates the effects of numerous genetic variants associated with a condition across the human genome and may help to predict late-onset Alzheimer's disease (LOAD). Most of the current PRS studies on Alzheimer's disease (AD) have been conducted in Caucasian ancestry populations, while it is less studied in Chinese. OBJECTIVE: To establish and examine the validity of Chinese PRS, and explore its racial heterogeneity. DESIGN: We constructed a PRS using both discovery (N = 2012) and independent validation samples (N = 1008) from Chinese population. The associations between PRS and age at onset of LOAD or cerebrospinal fluid (CSF) biomarkers were assessed. We also replicated the PRS in an independent replication cohort with CSF data and constructed an alternative PRS using European weights. SETTING: Multi-center genetics study. PARTICIPANTS: A total of 3020 subjects were included in the study. MEASUREMENTS: PRS was calculated using genome-wide association studies data and evaluated the performance alone (PRSnoAPOE) and with other predictors (full model: LOAD ~ PRSnoAPOE + APOE+ sex + age) by measuring the area under the receiver operating curve (AUC). RESULTS: PRS of the full model achieved the highest AUC of 84.0% (95% CI = 81.4-86.5) with pT< 0.5, compared with the model containing APOE alone (61.0%). The AUC of PRS with pT<5e-8 was 77.8% in the PRSnoAPOE model, 81.5% in the full model, and only ranged from 67.5% to 75.1% in the PRS with the European weights model. A higher PRS was significantly associated with an earlier age at onset (P <0.001). The PRS also performed well in the replication cohort of the full model (AUC=83.1%, 95% CI = 74.3-92.0). The CSF biomarkers of Aß42 and the ratio of Aß42/Aß40 were significantly inversely associated with the PRS, while p-Tau181 showed a positive association. CONCLUSIONS: This finding suggests that PRS reveal genetic heterogeneity and higher prediction accuracy of the PRS for AD can be achieved using a base dataset and validation within the same ethnicity. The effective PRS model has the clinical potential to predict individuals at risk of developing LOAD at a given age and with abnormal levels of CSF biomarkers in the Chinese population.

Mendelian Randomization Analysis Reveals Causal Factors behind Alzheimer's Disease Risk: Evidence, Opportunities, and Challenges.

Alzheimer's disease and its comorbidities pose a heavy disease burden globally, and its treatment remains a major challenge. Identifying the protective and risk factors for Alzheimer's disease, as well as its possible underlying molecular processes, can facilitate the development of interventions that can slow its progression. Observational studies and randomized controlled trials have provided some evidence regarding potential risk factors for Alzheimer's disease; however, the results of these studies vary. Mendelian randomization is a novel epidemiological methodology primarily used to infer causal relationships between exposures and outcomes. Many Mendelian randomization studies have identified potential causal relationships between Alzheimer's disease and certain diseases, lifestyle habits, and biological exposures, thus providing valuable data for further mechanistic studies and the development and implementation of clinical prevention strategies. However, the results and data from Mendelian randomization studies must be interpreted based on comprehensive evidence. Moreover, the existing Mendelian randomization studies on the epidemiology of Alzheimer's disease have some limitations that are worth exploring. Therefore, the aim of this review was to summarize the available evidence on the potential protective and risk factors for Alzheimer's disease by assessing published Mendelian randomization studies on Alzheimer's disease, and to provide new perspectives on the etiology of Alzheimer's disease.

Genetic influence on within-person longitudinal change in anthropometric traits in the UK Biobank.

The causes of temporal fluctuations in adult traits are poorly understood. Here, we investigate the genetic determinants of within-person trait variability of 8 repeatedly measured anthropometric traits in 50,117 individuals from the UK Biobank. We found that within-person (non-directional) variability had a SNP-based heritability of 2-5% for height, sitting height, body mass index (BMI) and weight (P ≤ 2.4 × 10-3). We also analysed longitudinal trait change and show a loss of both average height and weight beyond about 70 years of age. A variant tracking the Alzheimer's risk APOE- E 4 allele (rs429358) was significantly associated with weight loss ( ß = -0.047 kg per yr, s.e. 0.007, P = 2.2 × 10-11), and using 2-sample Mendelian Randomisation we detected a relationship consistent with causality between decreased lumbar spine bone mineral density and height loss (bxy = 0.011, s.e. 0.003, P = 3.5 × 10-4). Finally, population-level variance quantitative trait loci (vQTL) were consistent with within-person variability for several traits, indicating an overlap between trait variability assessed at the population or individual level. Our findings help elucidate the genetic influence on trait-change within an individual and highlight disease risks associated with these changes.

Long-read sequencing for 29 immune cell subsets reveals disease-linked isoforms.

Alternative splicing events are a major causal mechanism for complex traits, but they have been understudied due to the limitation of short-read sequencing. Here, we generate a full-length isoform annotation of human immune cells from an individual by long-read sequencing for 29 cell subsets. This contains a number of unannotated transcripts and isoforms such as a read-through transcript of TOMM40-APOE in the Alzheimer's disease locus. We profile characteristics of isoforms and show that repetitive elements significantly explain the diversity of unannotated isoforms, providing insight into the human genome evolution. In addition, some of the isoforms are expressed in a cell-type specific manner, whose alternative 3'-UTRs usage contributes to their specificity. Further, we identify disease-associated isoforms by isoform switch analysis and by integration of several quantitative trait loci analyses with genome-wide association study data. Our findings will promote the elucidation of the mechanism of complex diseases via alternative splicing.

Bidirectional two-sample Mendelian randomization analyses support causal relationships between structural and diffusion imaging-derived phenotypes and the risk of major neurodegenerative diseases.

Previous observational investigations suggest that structural and diffusion imaging-derived phenotypes (IDPs) are associated with major neurodegenerative diseases; however, whether these associations are causal remains largely uncertain. Herein we conducted bidirectional two-sample Mendelian randomization analyses to infer the causal relationships between structural and diffusion IDPs and major neurodegenerative diseases using common genetic variants-single nucleotide polymorphism (SNPs) as instrumental variables. Summary statistics of genome-wide association study (GWAS) for structural and diffusion IDPs were obtained from 33,224 individuals in the UK Biobank cohort. Summary statistics of GWAS for seven major neurodegenerative diseases were obtained from the largest GWAS for each disease to date. The forward MR analyses identified significant or suggestively statistical causal effects of genetically predicted three structural IDPs on Alzheimer's disease (AD), frontotemporal dementia (FTD), and multiple sclerosis. For example, the reduction in the surface area of the left superior temporal gyrus was associated with a higher risk of AD. The reverse MR analyses identified significantly or suggestively statistical causal effects of genetically predicted AD, Lewy body dementia (LBD), and FTD on nine structural and diffusion IDPs. For example, LBD was associated with increased mean diffusivity in the right superior longitudinal fasciculus and AD was associated with decreased gray matter volume in the right ventral striatum. Our findings might contribute to shedding light on the prediction and therapeutic intervention for the major neurodegenerative diseases at the neuroimaging level.

The amyloid precursor protein and its derived fragments concomitantly contribute to the alterations of mitochondrial transport machinery in Alzheimer's disease.

Mitochondria dysfunctions and mitophagy failure have been associated with several Alzheimer's disease (AD) related molecular actors including amyloid beta (Aß) and recently the amyloid precursor protein-C terminal fragments (APP-CTFs). The efficacy of the mitophagy process in neurons relies on regulated mitochondrial transport along axons involving a complex molecular machinery. The contribution of the amyloid precursor protein (APP) and its derived fragments to the mitochondrial transport machinery alterations in AD have not been investigated before. We report herein a change of the expression of mitochondrial transport proteins (SNPH and Miro1), motor adapters (TRANK1 and TRAK2), and components of the dynein and kinesin motors (i.e., IC1,2 and Kif5 (A, B, C) isoforms) by endogenous APP and by overexpression of APP carrying the familial Swedish mutation (APPswe). We show that APP-CTFs and Aß concomitantly regulate the expression of a set of transport proteins as demonstrated in APPswe cells treated with ß- and γ-secretase inhibitors and in cells Knock-down for presenilin 1 and 2. We further report the impact of APP-CTFs on the expression of transport proteins in AAV-injected C99 mice brains. Our data also indicate that both Aß oligomers (Aßo) and APP-CTFs impair the colocalization of mitochondria and transport proteins. This has been demonstrated in differentiated SH-SY5Y naive cells treated with Aßo and in differentiated SH-SY5Y and murine primary neurons expressing APPswe and treated with the γ-secretase inhibitor. Importantly, we uncover that the expression of a set of transport proteins is modulated in a disease-dependent manner in 3xTgAD mice and in human sporadic AD brains. This study highlights molecular mechanisms underlying mitochondrial transport defects in AD that likely contribute to mitophagy failure and disease progression.

Single-nucleus analysis reveals microenvironment-specific neuron and glial cell enrichment in Alzheimer's disease.

BACKGROUND: Alzheimer's disease (AD) is a complicated neurodegenerative disease. Neuron-glial cell interactions are an important but not fully understood process in the progression of AD. We used bioinformatic methods to analyze single-nucleus RNA sequencing (snRNA-seq) data to investigate the cellular and molecular biological processes of AD. METHOD: snRNA-seq data were downloaded from Gene Expression Omnibus (GEO) datasets and reprocessed to identify 240,804 single nuclei from healthy controls and patients with AD. The cellular composition of AD was further explored using Uniform Manifold Approximation and Projection (UMAP). Enrichment analysis for the functions of the DEGs was conducted and cell development trajectory analyses were used to reveal underlying cell fate decisions. iTALK was performed to identify ligand-receptor pairs among various cell types in the pathological ecological microenvironment of AD. RESULTS: Six cell types and multiple subclusters were identified based on the snRNA-seq data. A subcluster of neuron and glial cells co-expressing lncRNA-SNHG14, myocardin-related transcription factor A (MRTFA), and MRTFB was found to be more abundant in the AD group. This subcluster was enriched in mitogen-activated protein kinase (MAPK)-, immune-, and apoptosis-related pathways. Through molecular docking, we found that lncRNA-SNHG14 may bind MRTFA and MRTFB, resulting in an interaction between neurons and glial cells. CONCLUSIONS: The findings of this study describe a regulatory relationship between lncRNA-SNHG14, MRTFA, and MRTFB in the six main cell types of AD. This relationship may contribute to microenvironment remodeling in AD and provide a theoretical basis for a more in-depth analysis of AD.

Learning semi-supervised enrichment of longitudinal imaging-genetic data for improved prediction of cognitive decline.

BACKGROUND: Alzheimer's Disease (AD) is a progressive memory disorder that causes irreversible cognitive decline. Given that there is currently no cure, it is critical to detect AD in its early stage during the disease progression. Recently, many statistical learning methods have been presented to identify cognitive decline with temporal data, but few of these methods integrate heterogeneous phenotype and genetic information together to improve the accuracy of prediction. In addition, many of these models are often unable to handle incomplete temporal data; this often manifests itself in the removal of records to ensure consistency in the number of records across participants. RESULTS: To address these issues, in this work we propose a novel approach to integrate the genetic data and the longitudinal phenotype data to learn a fixed-length "enriched" biomarker representation derived from the temporal heterogeneous neuroimaging records. Armed with this enriched representation, as a fixed-length vector per participant, conventional machine learning models can be used to predict clinical outcomes associated with AD. CONCLUSION: The proposed method shows improved prediction performance when applied to data derived from Alzheimer's Disease Neruoimaging Initiative cohort. In addition, our approach can be easily interpreted to allow for the identification and validation of biomarkers associated with cognitive decline.

3-Hydroxyanthranilic Acid Delays Paralysis in Caenorhabditis elegans Models of Amyloid-Beta and Polyglutamine Proteotoxicity.

Age is the primary risk factor for neurodegenerative diseases such as Alzheimer's and Huntington's disease. Alzheimer's disease is the most common form of dementia and a leading cause of death in the elderly population of the United States. No effective treatments for these diseases currently exist. Identifying effective treatments for Alzheimer's, Huntington's, and other neurodegenerative diseases is a major current focus of national scientific resources, and there is a critical need for novel therapeutic strategies. Here, we investigate the potential for targeting the kynurenine pathway metabolite 3-hydroxyanthranilic acid (3HAA) using Caenorhabditis elegans expressing amyloid-beta or a polyglutamine peptide in body wall muscle, modeling the proteotoxicity in Alzheimer's and Huntington's disease, respectively. We show that knocking down the enzyme that degrades 3HAA, 3HAA dioxygenase (HAAO), delays the age-associated paralysis in both models. This effect on paralysis was independent of the protein aggregation in the polyglutamine model. We also show that the mechanism of protection against proteotoxicity from HAAO knockdown is mimicked by 3HAA supplementation, supporting elevated 3HAA as the mediating event linking HAAO knockdown to delayed paralysis. This work demonstrates the potential for 3HAA as a targeted therapeutic in neurodegenerative disease, though the mechanism is yet to be explored.

Transcriptomic Analysis of Lipid Metabolism Genes in Alzheimer's Disease: Highlighting Pathological Outcomes and Compartmentalized Immune Status.

The dysregulation of lipid metabolism has been strongly associated with Alzheimer's disease (AD) and has intricate connections with various aspects of disease progression, such as amyloidogenesis, bioenergetic deficit, oxidative stress, neuroinflammation, and myelin degeneration. Here, a comprehensive bioinformatic assessment was conducted on lipid metabolism genes in the brains and peripheral blood of AD-derived transcriptome datasets, characterizing the correlation between differentially expressed genes (DEGs) of lipid metabolism and disease pathologies, as well as immune cell preferences. Through the application of weighted gene co-expression network analysis (WGCNA), modules eigengenes related to lipid metabolism were pinpointed, and the examination of their molecular functions within biological processes, molecular pathways, and their associations with pathological phenotypes and molecular networks has been characterized. Analysis of biological networks indicates notable discrepancies in the expression patterns of the DEGs between neuronal and immune cells, as well as variations in cell type enrichments within both brain tissue and peripheral blood. Additionally, drugs targeting the DEGs from central and peripheral and a diagnostic model for hub genes from the blood were retrieved and assessed, some of which were shown to be useful for therapeutic and diagnostic. These results revealed the distinctive pattern of transcriptionally abnormal lipid metabolism in central, peripheral, and immune cell activation, providing valuable insight into lipid metabolism for diagnosing and guiding more effective treatment for AD.

Experimental colitis in young Tg2576 mice accelerates the onset of an Alzheimer's-like clinical phenotype.

Systemic inflammation and neuroinflammation affect the natural course of the sporadic form of Alzheimer's disease (AD), as supported by epidemiological and preclinical data, and several epidemiological studies indicate a higher prevalence of AD in patients with inflammatory bowel disease. In this study, we explored whether colitis induced by dextran sulfate sodium (DSS) in young, presymptomatic/preplaque mice worsens and/or anticipates age-dependent cognitive impairment in Tg2576, a widely used mouse model of AD. We demonstrated that DSS colitis induced in young Tg2576 mice anticipates the onset age of learning and memory deficit in the Morris water maze test. To explore potential mechanisms behind the acceleration of cognitive decline in Tg2576 mice by DSS colitis, we focused on gut microbiota, systemic inflammation and neuroinflammation markers. We observed a Firmicutes/Bacteroidetes ratio change in Tg2576 DSS animals comparable to that of elderly Tg2576 mice, suggesting accelerated microbiota aging in Tg2576 DSS mice, a change not observed in C57BL6 DSS mice. We also observed substantial differences between Tg2576 and WT mice in several inflammation and neuroinflammation-related parameters as early as 3 months of age, well before plaque deposition, a picture which evolved rapidly (between 3 and 5.5 months of age) in contrast to Tg2576 and WT littermates not treated with DSS. In detail, following induction of DSS colitis, WT and Tg2576 mice exhibited contrasting features in the expression level of inflammation-evoked astrocyte-associated genes in the hippocampus. No changes in microglial features occurred in the hippocampus between the experimental groups, whereas a reduced glial fibrillary acidic protein immunoreactivity was observed in Tg2576 vs. WT mice. This finding may reflect an atrophic, "loss-of-function" profile, further exacerbated by DSS where a decreased of GFAP mRNA expression level was detected. In conclusion, we suggest that as-yet unidentified peripheral mediators evoked by DSS colitis and involving the gut-brain axis emphasize an astrocyte "loss-of-function" profile present in young Tg2576 mice, leading to impaired synaptic morphological and functional integrity as a very early sign of AD.

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

Importance: Vascular disease is a treatable contributor to dementia risk, but the role of specific markers remains unclear, making prevention strategies uncertain. Objective: To investigate the causal association between white matter hyperintensity (WMH) burden, clinical stroke, blood pressure (BP), and dementia risk, while accounting for potential epidemiologic biases. Design, Setting, and Participants: This study first examined the association of genetically determined WMH burden, stroke, and BP levels with Alzheimer disease (AD) in a 2-sample mendelian randomization (2SMR) framework. Second, using population-based studies (1979-2018) with prospective dementia surveillance, the genetic association of WMH, stroke, and BP with incident all-cause dementia was examined. Data analysis was performed from July 26, 2020, through July 24, 2022. Exposures: Genetically determined WMH burden and BP levels, as well as genetic liability to stroke derived from genome-wide association studies (GWASs) in European ancestry populations. Main Outcomes and Measures: The association of genetic instruments for WMH, stroke, and BP with dementia was studied using GWASs of AD (defined clinically and additionally meta-analyzed including both clinically diagnosed AD and AD defined based on parental history [AD-meta]) for 2SMR and incident all-cause dementia for longitudinal analyses. Results: In 2SMR (summary statistics-based) analyses using AD GWASs with up to 75 024 AD cases (mean [SD] age at AD onset, 75.5 [4.4] years; 56.9% women), larger WMH burden showed evidence for a causal association with increased risk of AD (odds ratio [OR], 1.43; 95% CI, 1.10-1.86; P = .007, per unit increase in WMH risk alleles) and AD-meta (OR, 1.19; 95% CI, 1.06-1.34; P = .008), after accounting for pulse pressure for the former. Blood pressure traits showed evidence for a protective association with AD, with evidence for confounding by shared genetic instruments. In the longitudinal (individual-level data) analyses involving 10 699 incident all-cause dementia cases (mean [SD] age at dementia diagnosis, 74.4 [9.1] years; 55.4% women), no significant association was observed between larger WMH burden and incident all-cause dementia (hazard ratio [HR], 1.02; 95% CI, 1.00-1.04; P = .07). Although all exposures were associated with mortality, with the strongest association observed for systolic BP (HR, 1.04; 95% CI, 1.03-1.06; P = 1.9 × 10-14), there was no evidence for selective survival bias during follow-up using illness-death models. In secondary analyses using polygenic scores, the association of genetic liability to stroke, but not genetically determined WMH, with dementia outcomes was attenuated after adjusting for interim stroke. Conclusions: These findings suggest that WMH is a primary vascular factor associated with dementia risk, emphasizing its significance in preventive strategies for dementia. Future studies are warranted to examine whether this finding can be generalized to non-European populations.

High-resolution hybrid micro-CT imaging pipeline for mouse brain region segmentation and volumetric morphometry.

BACKGROUND: Brain region segmentation and morphometry in humanized apolipoprotein E (APOE) mouse models with a human NOS2 background (HN) contribute to Alzheimer's disease (AD) research by demonstrating how various risk factors affect the brain. Photon-counting detector (PCD) micro-CT provides faster scan times than MRI, with superior contrast and spatial resolution to energy-integrating detector (EID) micro-CT. This paper presents a pipeline for mouse brain imaging, segmentation, and morphometry from PCD micro-CT. METHODS: We used brains of 26 mice from 3 genotypes (APOE22HN, APOE33HN, APOE44HN). The pipeline included PCD and EID micro-CT scanning, hybrid (PCD and EID) iterative reconstruction, and brain region segmentation using the Small Animal Multivariate Brain Analysis (SAMBA) tool. We applied SAMBA to transfer brain region labels from our new PCD CT atlas to individual PCD brains via diffeomorphic registration. Region-based and voxel-based analyses were used for comparisons by genotype and sex. RESULTS: Together, PCD and EID scanning take ~5 hours to produce images with a voxel size of 22 µm, which is faster than MRI protocols for mouse brain morphometry with voxel size above 40 µm. Hybrid iterative reconstruction generates PCD images with minimal artifacts and higher spatial resolution and contrast than EID images. Our PCD atlas is qualitatively and quantitatively similar to the prior MRI atlas and successfully transfers labels to PCD brains in SAMBA. Male and female mice had significant volume differences in 26 regions, including parts of the entorhinal cortex and cingulate cortex. APOE22HN brains were larger than APOE44HN brains in clusters from the hippocampus, a region where atrophy is associated with AD. CONCLUSIONS: This work establishes a pipeline for mouse brain analysis using PCD CT, from staining to imaging and labeling brain images. Our results validate the effectiveness of the approach, setting a foundation for research on AD mouse models while reducing scanning durations.

Brain cell-type shifts in Alzheimer's disease, autism, and schizophrenia interrogated using methylomics and genetics.

Few neuropsychiatric disorders have replicable biomarkers, prompting high-resolution and large-scale molecular studies. However, we still lack consensus on a more foundational question: whether quantitative shifts in cell types-the functional unit of life-contribute to neuropsychiatric disorders. Leveraging advances in human brain single-cell methylomics, we deconvolve seven major cell types using bulk DNA methylation profiling across 1270 postmortem brains, including from individuals diagnosed with Alzheimer's disease, schizophrenia, and autism. We observe and replicate cell-type compositional shifts for Alzheimer's disease (endothelial cell loss), autism (increased microglia), and schizophrenia (decreased oligodendrocytes), and find age- and sex-related changes. Multiple layers of evidence indicate that endothelial cell loss contributes to Alzheimer's disease, with comparable effect size to APOE genotype among older people. Genome-wide association identified five genetic loci related to cell-type composition, involving plausible genes for the neurovascular unit (P2RX5 and TRPV3) and excitatory neurons (DPY30 and MEMO1). These results implicate specific cell-type shifts in the pathophysiology of neuropsychiatric disorders.

Meta-analysis and transcriptomic analysis reveal that NKRF and ZBTB17 regulate the NF-κB signaling pathway, contributing to the shared molecular mechanisms of Alzheimer's disease and atherosclerosis.

INTRODUCTION: Alzheimer's disease (AD) and atherosclerosis (AS) are widespread diseases predominantly observed in the elderly population. Despite their prevalence, the underlying molecular interconnections between these two conditions are not well understood. METHODS: Utilizing meta-analysis, bioinformatics methodologies, and the GEO database, we systematically analyzed transcriptome data to pinpoint key genes concurrently differentially expressed in AD and AS. Our experimental validations in mouse models highlighted the prominence of two genes, NKRF (NF-κB-repressing factor) and ZBTB17 (MYC-interacting zinc-finger protein 1). RESULTS: These genes appear to influence the progression of both AD and AS by modulating the NF-κB signaling pathway, as confirmed through subsequent in vitro and in vivo studies. CONCLUSIONS: This research uncovers a novel shared molecular pathway between AD and AS, underscoring the significant roles of NKRF and ZBTB17 in the pathogenesis of these disorders.

Transcriptomic analysis reveals sex-specific patterns in the hippocampus in Alzheimer's disease.

Background: The hippocampus, vital for memory and learning, is among the first brain regions affected in Alzheimer's Disease (AD) and exhibits adult neurogenesis. Women face twice the risk of developing AD compare to men, making it crucial to understand sex differences in hippocampal function for comprehending AD susceptibility. Methods: We conducted a comprehensive analysis of bulk mRNA postmortem samples from the whole hippocampus (GSE48350, GSE5281) and its CA1 and CA3 subfields (GSE29378). Our aim was to perform a comparative molecular signatures analysis, investigating sex-specific differences and similarities in the hippocampus and its subfields in AD. This involved comparing the gene expression profiles among: (a) male controls (M-controls) vs. female controls (F-controls), (b) females with AD (F-AD) vs. F-controls, (c) males with AD (M-AD) vs. M-controls, and (d) M-AD vs. F-AD. Furthermore, we identified AD susceptibility genes interacting with key targets of menopause hormone replacement drugs, specifically the ESR1 and ESR2 genes, along with GPER1. Results: The hippocampal analysis revealed contrasting patterns between M-AD vs. M-controls and F-AD vs. F-controls, as well as M-controls vs. F-controls. Notably, BACE1, a key enzyme linked to amyloid-beta production in AD pathology, was found to be upregulated in M-controls compared to F-controls in both CA1 and CA3 hippocampal subfields. In M-AD vs. M-controls, the GABAergic synapse was downregulated, and the Estrogen signaling pathway was upregulated in both subfields, unlike in F-AD vs. F-controls. Analysis of the whole hippocampus also revealed upregulation of the GABAergic synapse in F-AD vs. F-controls. While direct comparison of M-AD vs. F-AD, revealed a small upregulation of the ESR1 gene in the CA1 subfield of males. Conversely, F-AD vs. F-controls exhibited downregulation of the Dopaminergic synapse in both subfields, while the Calcium signaling pathway showed mixed regulation, being upregulated in CA1 but downregulated in CA3, unlike in M-AD vs. M-controls. The upregulated Estrogen signaling pathway in M-AD, suggests a compensatory response to neurodegenerative specifically in males with AD. Our results also identified potential susceptibility genes interacting with ESR1 and ESR2, including MAPK1, IGF1, AKT1, TP53 and CD44. Conclusion: These findings underscore the importance of sex-specific disease mechanisms in AD pathogenesis. Region-specific analysis offers a more detailed examination of localized changes in the hippocampus, enabling to capture sex-specific molecular patterns in AD susceptibility and progression.

Biomarkers of Alzheimer's Disease Associated with Programmed Cell Death Reveal Four Repurposed Drugs.

Alzheimer's disease (AD) is a neurodegenerative disorder and the most common cause of dementia. Programmed cell death (PCD) is mainly characterized by unique morphological features and energy-dependent biochemical processes. The predominant pathway leading to cell death in AD has not been thoroughly analyzed, although there is evidence of neuron loss in AD and numerous pathways of PCD have been associated with this process. A better understanding of the systems biology underlying the relationship between AD and PCD could lead to the development of new therapeutic approaches. To this end, publicly available transcriptome data were examined using bioinformatic methods such as differential gene expression and weighted gene coexpression network analysis (WGCNA) to find PCD-related AD biomarkers. The diagnostic significance of these biomarkers was evaluated using a logistic regression-based predictive model. Using these biomarkers, a multifactorial regulatory network was developed. Last, a drug repositioning study was conducted to propose new drugs for the treatment of AD targeting PCD. The development of 3PM (predictive, preventive, and personalized) drugs for the treatment of AD would be enabled by additional research on the effects of these drugs on this disease.

Reduction of spermine synthase enhances autophagy to suppress Tau accumulation.

Precise polyamine metabolism regulation is vital for cells and organisms. Mutations in spermine synthase (SMS) cause Snyder-Robinson intellectual disability syndrome (SRS), characterized by significant spermidine accumulation and autophagy blockage in the nervous system. Emerging evidence connects polyamine metabolism with other autophagy-related diseases, such as Tauopathy, however, the functional intersection between polyamine metabolism and autophagy in the context of these diseases remains unclear. Here, we altered SMS expression level to investigate the regulation of autophagy by modulated polyamine metabolism in Tauopathy in Drosophila and human cellular models. Interestingly, while complete loss of Drosophila spermine synthase (dSms) impairs lysosomal function and blocks autophagic flux recapitulating SRS disease phenotype, partial loss of dSms enhanced autophagic flux, reduced Tau protein accumulation, and led to extended lifespan and improved climbing performance in Tauopathy flies. Measurement of polyamine levels detected a mild elevation of spermidine in flies with partial loss of dSms. Similarly, in human neuronal or glial cells, partial loss of SMS by siRNA-mediated knockdown upregulated autophagic flux and reduced Tau protein accumulation. Importantly, proteomics analysis of postmortem brain tissue from Alzheimer's disease (AD) patients showed a significant albeit modest elevation of SMS level. Taken together, our study uncovers a functional correlation between polyamine metabolism and autophagy in AD: SMS reduction upregulates autophagy, suppresses Tau accumulation, and ameliorates neurodegeneration and cell death. These findings provide a new potential therapeutic target for AD.