CHI3L2 Expression Levels Are Correlated with AIF1, PECAM1, and CALB1 in the Brains of Alzheimer's Disease Patients

A narrative review of the effects of dexamethasone on traumatic brain injury in clinical and animal studies: focusing on inflammation

Traumatic brain injury (TBI) is a type of brain injury resulting from a sudden physical force to the head. TBI can range from mild, such as a concussion, to severe, which might result in long-term complications or even death. The initial impact or primary injury to the brain is followed by neuroinflammation, excitotoxicity, and oxidative stress, which are the hallmarks of the secondary injury phase, that can further damage the brain tissue. Dexamethasone (DXM) has neuroprotective effects. It reduces neuroinflammation, a critical factor in secondary injury-associated neuronal damage. DXM can also suppress the microglia activation and infiltrated macrophages, which are responsible for producing pro-inflammatory cytokines that contribute to neuroinflammation. Considering the outcomes of this research, some of the effects of DXM on TBI include: (1) DXM-loaded hydrogels reduce apoptosis, neuroinflammation, and lesion volume and improves neuronal cell survival and motor performance, (2) DXM treatment elevates the levels of Ndufs2, Gria3, MAOB, and Ndufv2 in the hippocampus following TBI, (3) DXM decreases the quantity of circulating endothelial progenitor cells, (4) DXM reduces the expression of IL1, (5) DXM suppresses the infiltration of RhoA + cells into primary lesions of TBI and (6) DXM treatment led to an increase in fractional anisotropy values and a decrease in apparent diffusion coefficient values, indicating improved white matter integrity. According to the study, the findings show that DXM treatment has neuroprotective effects in TBI. This indicates that DXM is a promising therapeutic approach to treating TBI.

Combining donepezil and memantine via mannosylated PLGA nanoparticles for intranasal delivery: Characterization and preclinical studies

The current work is focused on developing mannose-coated PLGA nanoparticles for delivering Donepezil and Memantine in one dosage form. The formulated nanoparticles were prepared using a simple emulsification technique. The final coated NPs exhibited 179.4 nm size and - 33.1 mV zeta potential and spherical shape. The concentration of IN-administrated MEM and DPZ mannose coated NPs in brain was ~573 and 207 ng/mL respectively. This amount accounts for 3 times more in comparison to uncoated NPs administered via intranasal and peroral routes. The plasma concentration of coated NPs administered via the intranasal route was various times less in comparison to other groups. In the field of pharmacodynamics, the administration of coated NPs via the IN route has shown superior efficacy in comparison to other groups in various investigations involving neurobehavioral assessments, gene expression analyses and biochemical estimations. The findings indicate that the IN route may be a potential avenue for delivering therapeutic agents using nanoparticles to treat neurological illnesses. This approach shows promise as a viable alternative to traditional dose forms and administration methods.

Simultaneous Intranasal Codelivery of Donepezil and Memantine in a Nanocolloidal Carrier: Optimization, Pharmacokinetics, and Pharmacodynamics Studies

This work focuses on developing nanoemulsions using a low-energy emulsification method for the codelivery of donepezil and memantine in one dosage form intended to be administered via the intranasal route for enhanced brain delivery. The nanoemulsion formulation was prepared using a low emulsification technique and characterized using various microscopy and nasal ciliotoxicity studies. The safe nanoemulsion was intended for preclinical pharmacokinetics with brain distribution and pharmacodynamics in a scopolamine-induced murine model. The formulated nanoemulsion was 16 nm in size, with a zeta potential of -7.22 mV, and exhibited a spherical shape. The brain concentration of IN-administered NE for DPZ and MEM was ∼678 and 249 ng/mL after 15 min. This concentration is more than 2 times higher in amount when compared with NE administered via PO, free drug solution administered via IN and PO route both. However, the plasma concentration of IN-administered NE for DPZ and MEM was ∼3 and 28 ng/mL after 15 min. In pharmacodynamic studies, the efficacy of NE administered via the IN route was higher when compared with other groups in neurobehavioral, biochemical estimation, and gene expression studies. The results suggest that the IN route can be explored in the future for the delivery of actives via nanocolloidal carriers in the brain for neurological disorders and can serve as promising alternatives for conventional dosage forms and routes.

AIF1: Function and Connection with Inflammatory Diseases

Macrophages are a type of immune cell distributed throughout all tissues of an organism. Allograft inflammatory factor 1 (AIF1) is a calcium-binding protein linked to the activation of macrophages. AIF1 is a key intracellular signaling molecule that participates in phagocytosis, membrane ruffling and F-actin polymerization. Moreover, it has several cell type-specific functions. AIF1 plays important roles in the development of several diseases: kidney disease, rheumatoid arthritis, cancer, cardiovascular diseases, metabolic diseases and neurological disorders, and in transplants. In this review, we present a comprehensive review of the known structure, functions and role of AIF1 in inflammatory diseases.

A Novel Longitudinal Phenotype-Genotype Association Study Based on Deep Feature Extraction and Hypergraph Models for Alzheimer's Disease

Traditional image genetics primarily uses linear models to investigate the relationship between brain image data and genetic data for Alzheimer's disease (AD) and does not take into account the dynamic changes in brain phenotype and connectivity data across time between different brain areas. In this work, we proposed a novel method that combined Deep Subspace reconstruction with Hypergraph-Based Temporally-constrained Group Sparse Canonical Correlation Analysis (DS-HBTGSCCA) to discover the deep association between longitudinal phenotypes and genotypes. The proposed method made full use of dynamic high-order correlation between brain regions. In this method, the deep subspace reconstruction technique was applied to retrieve the nonlinear properties of the original data, and hypergraphs were used to mine the high-order correlation between two types of rebuilt data. The molecular biological analysis of the experimental findings demonstrated that our algorithm was capable of extracting more valuable time series correlation from the real data obtained by the AD neuroimaging program and finding AD biomarkers across multiple time points. Additionally, we used regression analysis to verify the close relationship between the extracted top brain areas and top genes and found the deep subspace reconstruction approach with a multi-layer neural network was helpful in enhancing clustering performance.

Sex, Age, and Regional Differences in CHRM1 and CHRM3 Genes Expression Levels in the Human Brain Biopsies: Potential Targets for Alzheimer's Disease-related Sleep Disturbances

BACKGROUND

Cholinergic hypofunction and sleep disturbance are hallmarks of Alzheimer's disease (AD), a progressive disorder leading to neuronal deterioration. Muscarinic acetylcholine receptors (M1-5 or mAChRs), expressed in hippocampus and cerebral cortex, play a pivotal role in the aberrant alterations of cognitive processing, memory, and learning, observed in AD. Recent evidence shows that two mAChRs, M1 and M3, encoded by CHRM1 and CHRM3 genes, respectively, are involved in sleep functions and, peculiarly, in rapid eye movement (REM) sleep.

METHODS

We used twenty microarray datasets extrapolated from post-mortem brain tissue of nondemented healthy controls (NDHC) and AD patients to examine the expression profile of CHRM1 and CHRM3 genes. Samples were from eight brain regions and stratified according to age and sex.

RESULTS

CHRM1 and CHRM3 expression levels were significantly reduced in AD compared with ageand sex-matched NDHC brains. A negative correlation with age emerged for both CHRM1 and CHRM3 in NDHC but not in AD brains. Notably, a marked positive correlation was also revealed between the neurogranin (NRGN) and both CHRM1 and CHRM3 genes. These associations were modulated by sex. Accordingly, in the temporal and occipital regions of NDHC subjects, males expressed higher levels of CHRM1 and CHRM3, respectively, than females. In AD patients, males expressed higher levels of CHRM1 and CHRM3 in the temporal and frontal regions, respectively, than females.

CONCLUSION

Thus, substantial differences, all strictly linked to the brain region analyzed, age, and sex, exist in CHRM1 and CHRM3 brain levels both in NDHC subjects and in AD patients.

Sex-dependent neuro-deconvolution analysis of Alzheimer's disease brain transcriptomes according to CHI3L1 expression levels

Glial activation and related neuroinflammatory processes play a key role in the aging and progression of Alzheimer's disease (AD). CHI3L1/ YKL40 is a widely investigated chitinase in neurodegenerative diseases and recent studies have shown its involvement in aging and AD. Nevertheless, the biological function of CHI3L1 in AD is still unknown. Here, we collected microarray datasets from the National Center for Biotechnology Information (NCBI) brain samples of not demented healthy controls (NDHC) who died from causes not attributable to neurodegenerative disorders (n = 460), and of deceased patients suffering from Alzheimer's disease (AD) (n = 697). The NDHC and AD patients were stratified according to CHI3L1 expression levels as a cut-off. We identified two groups both males and females, subsequently used for our statistical comparisons: the high CHI3L1 expression group (HCEG) and the low CHI3L1 expression group (LCEG). Comparing HCEG to LCEG, we attained four signatures according to the sex of patients, in order to identify the healthy and AD brain cellular architecture, performing a genomic deconvolution analysis. We used neurological signatures (NS) belonging to six neurological cells populations and nine signatures that included the main physiological neurological processes. We discovered that, in the brains of NDHC the high expression levels of CHI3L1 were associated with astrocyte activation profile, while in AD males and females we showed an inflammatory profile microglia-mediated. The low CHI3L1 brain expression levels in NDHC and AD patients highlighted a neuronal activation profile. Furthermore, using drugs opposing CHI3L1 transcriptomic signatures, we found a specific drug profile for AD males and females characterized by high levels of CHI3L1 composed of fostamatinib, rucaparib, cephaeline, prednisolone, and dinoprostone. Brain levels of CHI3L1 in AD patients represent a biological signature that allows distinguishing between males and females and their likely cellular brain architecture.

SARS-CoV-2 infection increases the gene expression profile for Alzheimer's disease risk

The coronavirus disease 2019 (COVID-19) pandemic has caused over 600,000,000 infections globally thus far. Up to 30% of individuals with mild to severe disease develop long COVID, exhibiting diverse neurologic symptoms including dementias. However, there is a paucity of knowledge of molecular brain markers and whether these can precipitate the onset of Alzheimer's disease (AD). Herein, we report the brain gene expression profiles of severe COVID-19 patients showing increased expression of innate immune response genes and genes implicated in AD pathogenesis. The use of a mouse-adapted strain of SARS-CoV-2 (MA10) in an aged mouse model shows evidence of viral neurotropism, prolonged viral infection, increased expression of tau aggregator FKBP51, interferon-inducible gene Ifi204, and complement genes C4 and C5AR1. Brain histopathology shows AD signatures including increased tau-phosphorylation, tau-oligomerization, and α-synuclein expression in aged MA10 infected mice. The results of gene expression profiling of SARS-CoV-2-infected and AD brains and studies in the MA10 aged mouse model taken together, for the first time provide evidence suggesting that SARS-CoV-2 infection alters expression of genes in the brain associated with the development of AD. Future studies of common molecular markers in SARS-CoV-2 infection and AD could be useful for developing novel therapies targeting AD.

Differential Gene Expression and DNA Methylation in the Risk of Depression in LOAD Patients

Depression is common among late-onset Alzheimer's Disease (LOAD) patients. Only a few studies investigated the genetic variability underlying the comorbidity of depression in LOAD. Moreover, the epigenetic and transcriptomic factors that may contribute to comorbid depression in LOAD have yet to be studied. Using transcriptomic and DNA-methylomic datasets from the ROSMAP cohorts, we investigated differential gene expression and DNA-methylation in LOAD patients with and without comorbid depression. Differential expression analysis did not reveal significant association between differences in gene expression and the risk of depression in LOAD. Upon sex-stratification, we identified 25 differential expressed genes (DEG) in males, of which CHI3L2 showed the strongest upregulation, and only 3 DEGs in females. Additionally, testing differences in DNA-methylation found significant hypomethylation of CpG (cg20442550) on chromosome 17 (log2FC = -0.500, p = 0.004). Sex-stratified differential DNA-methylation analysis did not identify any significant CpG probes. Integrating the transcriptomic and DNA-methylomic datasets did not discover relationships underlying the comorbidity of depression and LOAD. Overall, our study is the first multi-omics genome-wide exploration of the role of gene expression and epigenome alterations in the risk of comorbid depression in LOAD patients. Furthermore, we discovered sex-specific differences in gene expression underlying the risk of depression symptoms in LOAD.

A sex-stratified analysis of neuroimmune gene expression signatures in Alzheimer's disease brains

Alzheimer's disease (AD) is the most common form of progressively disabling dementia. The chitinases CHI3L1 and CHI3L2 have long been known as biomarkers for microglial and astrocytic activation in neurodegeneration. Here, we collected microarray datasets from the National Center for Biotechnology Information (NCBI) brain samples of non-demented controls (NDC) (n = 460), and of deceased patients with AD (n = 697). The AD patients were stratified according to sex. Comparing the high CHI3L1 and CHI3L2 expression group (75^th percentile), and low CHI3L1 and CHI3L2 expression group (25^th percentile), we obtained eight signatures according to the sex of patients and performed a genomic deconvolution analysis using neuroimmune signatures (NIS) belonging to twelve cell populations. Expression analysis revealed significantly higher CHI3L1 and CHI3L2 expression in AD compared with NDC, and positive correlations of these genes with GFAP and TMEM119. Furthermore, deconvolution analysis revealed that CHI3L1 and CHI3L2 high expression was associated with inflammatory signatures in both sexes. Neuronal activation profiles were significantly activated in AD patients with low CHI3L1 and CHI3L2 expression levels. Furthermore, gene ontology analysis of common genes regulated by the two chitinases unveiled immune response as a main biological process. Finally, microglia NIS significantly correlated with CHI3L2 expression levels and were more than 98% similar to microglia NIS determined by CHI3L1. According to our results, high levels of CHI3L1 and CHI3L2 in the brains of AD patients are associated with inflammatory transcriptomic signatures. The high correlation between CHI3L1 and CHI3L2 suggests strong co-regulation.

Development and validation of immune-based biomarkers and deep learning models for Alzheimer’s disease

Background: Alzheimer’s disease (AD) is the most common form of dementia in old age and poses a severe threat to the health and life of the elderly. However, traditional diagnostic methods and the ATN diagnostic framework have limitations in clinical practice. Developing novel biomarkers and diagnostic models is necessary to complement existing diagnostic procedures.

Methods: The AD expression profile dataset GSE63060 was downloaded from the NCBI GEO public database for preprocessing. AD-related differentially expressed genes were screened using a weighted co-expression network and differential expression analysis, and functional enrichment analysis was performed. Subsequently, we screened hub genes by random forest, analyzed the correlation between hub genes and immune cells using ssGSEA, and finally built an AD diagnostic model using an artificial neural network and validated it.

Results: Based on the random forest algorithm, we screened a total of seven hub genes from AD-related DEGs, based on which we confirmed that hub genes play an essential role in the immune microenvironment and successfully established a novel diagnostic model for AD using artificial neural networks, and validated its effectiveness in the publicly available datasets GSE63060 and GSE97760.

Conclusion: Our study establishes a reliable model for screening and diagnosing AD that provides a theoretical basis for adding diagnostic biomarkers for the AD gene.

Pan-Tissue Aging Clock Genes That Have Intimate Connections with the Immune System and Age-Related Disease

In our recent transcriptomic meta-analysis, we used random forest machine learning to accurately predict age in human blood, bone, brain, heart, and retina tissues given gene inputs. Although each tissue-specific model utilized a unique number of genes for age prediction, we found that the following six genes were prioritized in all five tissues: CHI3L2, CIDEC, FCGR3A, RPS4Y1, SLC11A1, and VTCN1. Since being selected for age prediction in multiple tissues is unique, we decided to explore these pan-tissue clock genes in greater detail. In the present study, we began by performing over-representation and network topology-based enrichment analyses in the Gene Ontology Biological Process database. These analyses revealed that the immunological terms "response to protozoan," "immune response," and "positive regulation of immune system process" were significantly enriched by these clock inputs. Expression analyses in mouse and human tissues identified that these inputs are frequently upregulated or downregulated with age. A detailed literature search showed that all six genes had noteworthy connections to age-related disease. For example, mice deficient in Cidec are protected against various metabolic defects, while suppressing VTCN1 inhibits age-related cancers in mouse models. Using a large multitissue transcriptomic dataset, we additionally generate a novel, minimalistic aging clock that can predict human age using just these six genes as inputs. Taken all together, these six genes are connected to diverse aspects of aging.

Enhancement of Fear Extinction Memory and Resistance to Age-Related Cognitive Decline in Butyrylcholinesterase Knockout Mice and (R)-Bambuterol Treated Mice

Simple Summary

Fear extinction is the driving mechanism to reduce the fear response, and it is the basis of exposure-based cognitive-behavioral therapy. Butyrylcholinesterase (BChE) seems to be involved in regulating cognitive function, and its relationship with fear extinction memory has not been reported. BChE knockout mice and wild-type mice with administration of (R)-bambuterol, a BChE inhibitor, were used in this study. In addition to immunohistochemistry and metabolite analysis using mass spectrometry imaging, the influence of age on the conditioned fear test, Morris water maze experiment, and open field test were carefully evaluated. Our results showed that BChE inhibition accelerates the fear extinction memory in mice and delays the cognitive decline in the early stages of aging.

Abstract

Butyrylcholinesterase (BChE) is detected in plaques preferentially in Alzheimer’s disease (AD) and may be associated with stress disorders. However, the physiological function of BChE in the central nervous system remains to be further investigated. BChE knockout (KO) mice and wild-type (WT) mice with orally or intranasal administration of (R)-bambuterol were used to explore the effect of BChE on behavior changes. (R)-bambuterol is a specific and reversible inhibitor of BChE. The behavior changes were evaluated and compared among 3–10 month old mice. Our finding showed that BChE KO and (R)-bambuterol administration enhanced episodic memory, including fear conditioning memory and fear extinction memory in fear conditioning and fear extinction test. BChE KO and (R)-bambuterol administered mice rescued age-related spatial memory and general activity in the water maze test and open field test. The brain metabolomics were imaged using a desorption electrospray ionization mass spectrometry imaging (DESI-MSI). The image of DESI-MS demonstrated that glutamine content increased in the brain of BChE KO mice. In conclusion, this study found that inhibition of BChE ameliorated episodic and spatial memories. This study also suggested that (R)-bambuterol as a BChE inhibitor has the potential application in the treatment of post-traumatic stress disorder (PTSD) and early cognitive decline.

Brain CHID1 Expression Correlates with NRGN and CALB1 in Healthy Subjects and AD Patients

Alzheimer’s disease is a progressive, devastating, and irreversible brain disorder that, day by day, destroys memory skills and social behavior. Despite this, the number of known genes suitable for discriminating between AD patients is insufficient. Among the genes potentially involved in the development of AD, there are the chitinase-like proteins (CLPs) CHI3L1, CHI3L2, and CHID1. The genes of the first two have been extensively investigated while, on the contrary, little information is available on CHID1. In this manuscript, we conducted transcriptome meta-analysis on an extensive sample of brains of healthy control subjects (n = 1849) (NDHC) and brains of AD patients (n = 1170) in order to demonstrate CHID1 involvement. Our analysis revealed an inverse correlation between the brain CHID1 expression levels and the age of NDHC subjects. Significant differences were highlighted comparing CHID1 expression of NDHC subjects and AD patients. Exclusive in AD patients, the CHID1 expression levels were correlated positively to calcium-binding adapter molecule 1 (IBA1) levels. Furthermore, both in NDHC and in AD patient’s brains, the CHID1 expression levels were directly correlated with calbindin 1 (CALB1) and neurogranin (NRGN). According to brain regions, correlation differences were shown between the expression levels of CHID1 in prefrontal, frontal, occipital, cerebellum, temporal, and limbic system. Sex-related differences were only highlighted in NDHC. CHID1 represents a new chitinase potentially involved in the principal processes underlying Alzheimer’s disease.

GNG13 Is a Potential Marker of the State of Health of Alzheimer's Disease Patients' Cerebellum

Brain regions such as the cerebellum (CB) have been neglected for a long time in the study of Alzheimer's disease (AD) pathogenesis. In reference to a new emerging hypothesis according to which there is an altered cerebellar synaptic processing in AD, we verified the possible role played by new biomarkers in the CB of AD patients compared with not-demented healthy control subjects (NDHS). Using a bioinformatics approach, we have collected several microarray datasets and obtained 626 cerebella sample biopsies belonging to subjects who did not die from causes related to neurological diseases and 199 cerebella belonging to AD. The analysis of logical relations between the transcriptome dataset highlighted guanine nucleotide-binding protein (G protein) gamma 13 (GNG13) as a potential new biomarker for Purkinje cells (PCs). We have correlated GNG13 expression levels with already widely existing bibliography of PC marker genes, such as Purkinje cell protein 2 (PCP2), Purkinje cell protein 4 (PCP4), and cerebellin 3 (CBLN3). We showed that expression levels of GNG13 and PCP2, PCP4, and CBLN3 were significantly correlated with each other in NDHS and in AD and significantly reduced in AD patients compared with NDHS subjects. In addition, we highlighted a negative correlation between the expression levels of PC biomarkers and age. From the outcome of our investigation, it is possible to conclude that the identification of GNG13 as a potentially biomarker in PCs represents also a state of health of CB, in association with the expression of PCP2, PCP4, and CBLN3.