Temporal Cortex Microarray Analysis Revealed Impaired Ribosomal Biogenesis and Hyperactivity of the Glutamatergic System: An Early Signature of Asymptomatic Alzheimer's Disease

A Map of Transcriptomic Signatures of Different Brain Areas in Alzheimer's Disease

Alzheimer's disease (AD) is a neurodegenerative disorder that progressively involves brain regions with an often-predictable pattern. Damage to the brain appears to spread and worsen with time, but the molecular mechanisms underlying the region-specific distribution of AD pathology at different stages of the disease are still under-investigated. In this study, a whole-transcriptome analysis was carried out on brain samples from the hippocampus (HI), temporal and parietal cortices (TC and PC, respectively), cingulate cortex (CG), and substantia nigra (SN) of six subjects with a definite AD diagnosis and three healthy age-matched controls in duplicate. The transcriptomic results showed a greater number of differentially expressed genes (DEGs) in the TC (1571) and CG (1210) and a smaller number of DEGs in the HI (206), PC (109), and SN (60). Furthermore, the GSEA showed a difference between the group of brain areas affected early (HI and TC) and the group of areas that were subsequently involved (PC, CG, and SN). Notably, in the HI and TC, there was a significant downregulation of shared DEGs primarily involved in synaptic transmission, while in the PC, CG, and SN, there was a significant downregulation of genes primarily involved in protein folding and trafficking. The course of AD could follow a definite time- and severity-related pattern that arises from protein misfolding, as observed in the PC, CG, and SN, and leads to synaptic impairment, as observed in the HI and TC. Therefore, a map of the molecular and biological processes involved in AD pathogenesis may be traced. This could aid in the discovery of novel biological targets in order to develop effective and well-timed therapeutic approaches.

Multi-omics analyses highlight molecular differences between clinical and neuropathological diagnoses in Alzheimer's disease

Both clinical diagnosis and neuropathological diagnosis are commonly used in literature to categorize individuals as Alzheimer's disease (AD) or non-AD in omics analyses. Whether these diagnostic strategies result in distinct profiles of molecular abnormalities is poorly understood. Here, we analysed one of the most commonly used AD omics datasets in the literature from the Religious Orders Study and Memory and Aging Project (ROSMAP) cohort and compared the two diagnosis strategies using brain transcriptome and metabolome by grouping individuals as non-AD and AD according to clinical or neuropathological diagnosis separately. Differentially expressed genes, associated pathways related with AD hallmarks and AD-related genes showed that the categorization based on neuropathological diagnosis more accurately reflects the disease state at the molecular level than the categorization based on clinical diagnosis. We further identified consensus biomarker candidates between the two diagnosis strategies such as 5-hydroxylysine, sphingomyelin and 1-myristoyl-2-palmitoyl-GPC as metabolite biomarkers and sphingolipid metabolism as a pathway biomarker, which could be robust AD biomarkers since they are independent of diagnosis strategies. We also used consensus AD and consensus non-AD individuals between the two diagnostic strategies to train a machine-learning based model, which we used to classify the individuals who were cognitively normal but diagnosed as AD based on neuropathological diagnosis (asymptomatic AD individuals). The majority of these individuals were classified as consensus AD patients for both omics data types. Our study provides a detailed characterization of both diagnostic strategies in terms of the association of the corresponding multi-omics profiles with AD.

Electroacupuncture Enhances the Functional Connectivity of Limbic System to Neocortex in the 5xFAD Mouse Model of Alzheimer's Disease

Our previous study revealed that acupuncture may exhibit therapeutic effects on Alzheimer's disease (AD) through the activation of metabolism in memory-related brain regions. However, the underlying functional mechanism remains poorly understood and warrants further investigation. In this study, we used resting-state functional magnetic resonance imaging (rsfMRI) to explore the potential effect of electroacupuncture (EA) on the 5xFAD mouse model of AD. We found that the EA group exhibited significant improvements in the number of platforms crossed and the time spent in the target quadrant when compared with the Model group (p < 0.05). The functional connectivity (FC) of left hippocampus (Hip) was enhanced significantly among 12 regions of interest (ROIs) in the EA group (p < 0.05). Based on the left Hip as the seed point, the rsfMRI analysis of the entire brain revealed increased FC between the limbic system and the neocortex in the 5xFAD mice after EA treatment. Additionally, the expression of amyloid-β(Aβ) protein and deposition in the Hip showed a downward trend in the EA group compared to the Model group (p < 0.05). In conclusion, our findings indicate that EA treatment can improve the learning and memory abilities and inhibit the expression of Aβ protein and deposition of 5xFAD mice. This improvement may be attributed to the enhancement of the resting-state functional activity and connectivity within the limbic-neocortical neural circuit, which are crucial for cognition, motor function, as well as spatial learning and memory abilities in AD mice.

Longitudinal APOE4- and amyloid-dependent changes in the blood transcriptome in cognitively intact older adults

BACKGROUND

Gene expression is dysregulated in Alzheimer's disease (AD) patients, both in peripheral blood and post mortem brain. We investigated peripheral whole-blood gene (co)expression to determine molecular changes prior to symptom onset.

METHODS

RNA was extracted and sequenced for 65 cognitively healthy F-PACK participants (65 (56-80) years, 34 APOE4 non-carriers, 31 APOE4 carriers), at baseline and follow-up (interval: 5.0 (3.4-8.6) years). Participants received amyloid PET at both time points and amyloid rate of change derived. Accumulators were defined with rate of change ≥ 2.19 Centiloids. We performed differential gene expression and weighted gene co-expression network analysis to identify differentially expressed genes and networks of co-expressed genes, respectively, with respect to traits of interest (APOE4 status, amyloid accumulation (binary/continuous)), and amyloid positivity status, followed by Gene Ontology annotation.

RESULTS

There were 166 significant differentially expressed genes at follow-up compared to baseline in APOE4 carriers only, whereas 12 significant differentially expressed genes were found only in APOE4 non-carriers, over time. Among the significant genes in APOE4 carriers, several had strong evidence for a pathogenic role in AD based on direct association scores generated from the DISQOVER platform: NGRN, IGF2, GMPR, CLDN5, SMIM24. Top enrichment terms showed upregulated mitochondrial and metabolic pathways, and an exacerbated upregulation of ribosomal pathways in APOE4 carriers compared to non-carriers. Similarly, there were 33 unique significant differentially expressed genes at follow-up compared to baseline in individuals classified as amyloid negative at baseline and positive at follow-up or amyloid positive at both time points and 32 unique significant differentially expressed genes over time in individuals amyloid negative at both time points. Among the significant genes in the first group, the top five with the highest direct association scores were as follows: RPL17-C18orf32, HSP90AA1, MBP, SIRPB1, and GRINA. Top enrichment terms included upregulated metabolism and focal adhesion pathways. Baseline and follow-up gene co-expression networks were separately built. Seventeen baseline co-expression modules were derived, with one significantly negatively associated with amyloid accumulator status (r² =  - 0.25, p = 0.046). This was enriched for proteasomal protein catabolic process and myeloid cell development. Thirty-two follow-up modules were derived, with two significantly associated with APOE4 status: one downregulated (r² =  - 0.27, p = 0.035) and one upregulated (r² = 0.26, p = 0.039) module. Top enrichment processes for the downregulated module included proteasomal protein catabolic process and myeloid cell homeostasis. Top enrichment processes for the upregulated module included cytoplasmic translation and rRNA processing.

CONCLUSIONS

We show that there are longitudinal gene expression changes that implicate a disrupted immune system, protein removal, and metabolism in cognitively intact individuals who carry APOE4 or who accumulate in cortical amyloid. This provides insight into the pathophysiology of AD, whilst providing novel targets for drug and therapeutic development.

Predicting Key Genes and Therapeutic Molecular Modelling to Explain the Association between Porphyromonas gingivalis (P. gingivalis) and Alzheimer’s Disease (AD)

The association between Porphyromonas gingivalis (P. gingivalis) and Alzheimer’s disease (AD) remains unclear. The major aim of this study was to elucidate the role of genes and molecular targets in P. gingivalis-associated AD. Two Gene Expression Omnibus (GEO) datasets, GSE5281 for AD (n = 84 Alzheimer’s, n = 74 control) and GSE9723 (n = 4 P. gingivalis, n = 4 control), were downloaded from the GEO database. Differentially expressed genes (DEGs) were obtained, and genes common to both diseases were drawn. Additionally, Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) analysis was performed from the top 100 genes (50 upregulated and 50 downregulated genes). We then proceeded with CMap analysis to screen for possible small drug molecules targeting these genes. Subsequently, we performed molecular dynamics simulations. A total of 10 common genes (CALD1, HES1, ID3, PLK2, PPP2R2D, RASGRF1, SUN1, VPS33B, WTH3DI/RAB6A, and ZFP36L1) were identified with a p-value < 0.05. The PPI network of the top 100 genes showed UCHL1, SST, CHGB, CALY, and INA to be common in the MCC, DMNC, and MNC domains. Out of the 10 common genes identified, only 1 was mapped in CMap. We found three candidate small drug molecules to be a fit for PLK2, namely PubChem ID: 24971422, 11364421, and 49792852. We then performed molecular docking of PLK2 with PubChem ID: 24971422, 11364421, and 49792852. The best target, 11364421, was used to conduct the molecular dynamics simulations. The results of this study unravel novel genes to P. gingivalis-associated AD that warrant further validation.