Genetic diagnosis and prognosis of Alzheimer's disease: challenges and opportunities

Gene therapy: an alternative to treat Alzheimer's disease

Alzheimer's disease (AD), a neuro-degenerative disease that primarily affects the elderly, is a worldwide phenomenon. Loss of memory, cognitive decline, behavioural changes, and many other signs are used to classify it. Various hypotheses that may contribute to Alzheimer's disease have been found during decades of survey, including tau theory, the amyloid theory, the cholinergic hypothesis, and the oxidative stress hypothesis. According to some theories, the two leading causes of AD are the accumulation of amyloid beta plaque and development of NFTs in the brain. The hippocampus and cerebral cortex are the primary sites where amyloid beta plaques gather in the body. NFT formation in the brain impairs the brain's neurons' potential of signalling. According to the age at which it manifests in a person, there are two subtypes of AD: 'LOAD (Late Onset Alzheimer's Disease)' and 'EOAD (Early Onset Alzheimer's Disease)'. Long-term research into AD treatment has resulted in the introduction of some medications that provided symptomatic relief to patients but did not alter the disease's pathophysiology, like cholinesterase inhibitors, inhibitors of tau aggregation, and monoclonal antibodies to Aβ aggregation. Even though the medications did not halt the progression of AD, researchers did not discontinue their work, which lead to the introduction of gene therapy - a recently created cutting-edge method of delivering genes to target sites where they can express the intended functionalities. Viral or non-viral vectors could be used to deliver the gene, each with advantages and limitations of their own. Gene therapy is proven to be a potential disease-modifying treatment for AD. This article discusses about gene therapy, its merits and demerits and the various ways of gene delivery. Additionally, it focuses on AD as the target for treatment through gene therapy, the pathophysiology of AD, and the multiple targets for gene therapy in the treatment of AD.

The Role of RIN3 Gene in Alzheimer's Disease Pathogenesis: a Comprehensive Review

Alzheimer's disease (AD) is a globally prevalent form of dementia that impacts diverse populations and is characterized by progressive neurodegeneration and impairments in executive memory. Although the exact mechanisms underlying AD pathogenesis remain unclear, it is commonly accepted that the aggregation of misfolded proteins, such as amyloid plaques and neurofibrillary tau tangles, plays a critical role. Additionally, AD is a multifactorial condition influenced by various genetic factors and can manifest as either early-onset AD (EOAD) or late-onset AD (LOAD), each associated with specific gene variants. One gene of particular interest in both EOAD and LOAD is RIN3, a guanine nucleotide exchange factor. This gene plays a multifaceted role in AD pathogenesis. Firstly, upregulation of RIN3 can result in endosomal enlargement and dysfunction, thereby facilitating the accumulation of beta-amyloid (Aβ) peptides in the brain. Secondly, RIN3 has been shown to impact the PICLAM pathway, affecting transcytosis across the blood-brain barrier. Lastly, RIN3 has implications for immune-mediated responses, notably through its influence on the PTK2B gene. This review aims to provide a concise overview of AD and delve into the role of the RIN3 gene in its pathogenesis.

Sensitivity of substrate translocation in chaperone-mediated autophagy to Alzheimer's disease progression

Alzheimer's disease (AD) is a progressive brain disorder marked by abnormal protein accumulation and resulting proteotoxicity. This study examines Chaperone-Mediated Autophagy (CMA), particularly substrate translocation into lysosomes, in AD. The study observes: (1) Increased substrate translocation activity into lysosomes, vital for CMA, aligns with AD progression, highlighted by gene upregulation and more efficient substrate delivery. (2) This CMA phase strongly correlates with AD's clinical symptoms; more proteotoxicity links to worse dementia, underscoring the need for active degradation. (3) Proteins like GFAP and LAMP2A, when upregulated, almost certainly indicate AD risk, marking this process as a significant AD biomarker. Based on these observations, this study proposes the following hypothesis: As AD progresses, the aggregation of pathogenic proteins increases, the process of substrate entry into lysosomes via CMA becomes active. The genes associated with this process exhibit heightened sensitivity to AD. This conclusion stems from an analysis of over 10,000 genes and 363 patients using two AI methodologies. These methodologies were instrumental in identifying genes highly sensitive to AD and in mapping the molecular networks that respond to the disease, thereby highlighting the significance of this critical phase of CMA.

Amyloid, Crohn's disease, and Alzheimer's disease - are they linked?

Crohn's disease (CD) is a chronic inflammatory disease that most frequently affects part of the distal ileum, but it may affect any part of the gastrointestinal tract. CD may also be related to systemic inflammation and extraintestinal manifestations. Alzheimer's disease (AD) is the most common neurodegenerative disease, gradually worsening behavioral and cognitive functions. Despite the meaningful progress, both diseases are still incurable and have a not fully explained, heterogeneous pathomechanism that includes immunological, microbiological, genetic, and environmental factors. Recently, emerging evidence indicates that chronic inflammatory condition corresponds to an increased risk of neurodegenerative diseases, and intestinal inflammation, including CD, increases the risk of AD. Even though it is now known that CD increases the risk of AD, the exact pathways connecting these two seemingly unrelated diseases remain still unclear. One of the key postulates is the gut-brain axis. There is increasing evidence that the gut microbiota with its proteins, DNA, and metabolites influence several processes related to the etiology of AD, including β-amyloid abnormality, Tau phosphorylation, and neuroinflammation. Considering the role of microbiota in both CD and AD pathology, in this review, we want to shed light on bacterial amyloids and their potential to influence cerebral amyloid aggregation and neuroinflammation and provide an overview of the current literature on amyloids as a potential linker between AD and CD.

Predicting early Alzheimer's with blood biomarkers and clinical features

Alzheimer's disease (AD) is an incurable neurodegenerative disorder that leads to dementia. This study employs explainable machine learning models to detect dementia cases using blood gene expression, single nucleotide polymorphisms (SNPs), and clinical data from Alzheimer's Disease Neuroimaging Initiative (ADNI). Analyzing 623 ADNI participants, we found that the Support Vector Machine classifier with Mutual Information (MI) feature selection, trained on all three data modalities, achieved exceptional performance (accuracy = 0.95, AUC = 0.94). When using gene expression and SNP data separately, we achieved very good performance (AUC = 0.65, AUC = 0.63, respectively). Using SHapley Additive exPlanations (SHAP), we identified significant features, potentially serving as AD biomarkers. Notably, genetic-based biomarkers linked to axon myelination and synaptic vesicle membrane formation could aid early AD detection. In summary, this genetic-based biomarker approach, integrating machine learning and SHAP, shows promise for precise AD diagnosis, biomarker discovery, and offers novel insights for understanding and treating the disease. This approach addresses the challenges of accurate AD diagnosis, which is crucial given the complexities associated with the disease and the need for non-invasive diagnostic methods.

The associations of herpes simplex virus and varicella zoster virus infection with dementia: a nationwide retrospective cohort study

BACKGROUND

In this study, the risk of dementia in patients with a history of herpes simplex virus (HSV) or varicella zoster virus (VZV) infection was evaluated.

METHODS

This nationwide cohort study used data from the Korean National Health Insurance Service collected between 2006 and 2017. A total of 752,205 subjects ≥ 45 years of age not diagnosed with dementia until 2006 were included. A multivariate Cox regression model, adjusted for age, sex, and other comorbidities, was used to assess the hazard ratio (HR) for dementia based on VZV or HSV infection. The interaction effects of both viral infections were analysed. Viral infections are classified into four categories: eye, central nervous system (CNS), simple, and complicated. The hazard ratio (HR) of viral infection was analysed based on the type of dementia.

RESULTS

In multivariable analysis, both HSV and VZV infection were associated with an increased risk of dementia (HR = 1.38, 95% confidence interval, CI:1.33-1.43) and (HR = 1.41, 95% CI:1.37-1.46), respectively. Patients who experienced both HSV and VZV infections were also at an increased risk of dementia (HR = 1.57, 95% CI:1.50-1.63). The co-infection group showed the shortest time from viral infection to dementia diagnosis (4.09 ± 3.02 years). In the subgroup analysis, all types of HSV and VZV infections were associated with an increased risk of dementia compared to the non-infection group. The eye, CNS, and complicated VZV infections were associated with a significantly higher risk than simple VZV infections. There were no significant differences between the subtypes of HSV infection. Furthermore, HSV, VSV, and co-infection were associated with an increased risk of all dementia types, including Alzheimer's disease (AD) and vascular dementia (VD).

CONCLUSIONS

Individual HSV and VZV infections were associated with an increased risk of all types of dementia, including AD and VD. Patients co-infected with HSV and VZV, VZV infection in the eye, CNS, or complicated type were more vulnerable to the development of dementia.

Association of birthweight and risk of incident dementia: a prospective cohort study

Given the epidemiological studies investigating the relationship between birthweight and dementia are limited. Our study aimed to explore the association between birthweight and the risk of dementia, cognitive function, and brain structure. We included 275,648 participants from the UK Biobank, categorizing birthweight into quartiles (Q1 ≤ 2.95 kg; Q2 > 2.95 kg, ≤ 3.32 kg; Q3 > 3.32 kg, ≤ 3.66 kg; Q4 > 3.66 kg), with Q3 as the reference. Cox regression models and restricted cubic splines estimated the relationship between birthweight and the risk of all causes of dementia (ACD), Alzheimer's disease (AD), and vascular dementia (VD). Multivariable linear regression models assessed the relationship between birthweight, cognitive function, and MRI biomarkers. Over a median follow-up of 13.0 years, 3103 incident dementia cases were recorded. In the fully adjusted model, compared to Q3 (> 3.32 kg, ≤ 3.66 kg), lower birthweight in Q1 (≤ 2.95 kg) was significantly associated with increased risk of ACD (HR = 1.18, 95%CI 1.06-1.30, P = 0.001) and VD (HR = 1.32, 95%CI 1.07-1.62, P = 0.010), but no significant association with AD was found. Continuous birthweight showed a U-shaped nonlinear association with dementia. Lower birthweight was associated with worse performance in cognitive tasks, including reaction time, fluid intelligence, numeric, and prospective memory. Additionally, certain brain structure indices were identified, including brain atrophy and reductions in area, thickness, and volume of regional subcortical areas. Our study emphasizes the association between lower birthweight and increased dementia risk, correlating cognitive function and MRI biomarkers of brain structure, suggesting that in utero or early-life exposures might impact cognitive health in adulthood.

Proton Pump Inhibitors and Cognitive Health: Review on Unraveling the Dementia Connection and Co-morbid Risks

Dementia, an international health issue distinguished by the impairment of daily functioning due to cognitive decline, currently affects more than 55 million people worldwide, with the majority residing in low-income and middle-income countries. Globally, dementia entails significant economic burdens in 2019, amounting to a cost of 1.3 trillion US dollars. Informal caregivers devote considerable hours to providing care for those affected. Dementia imposes a greater caregiving and disability-adjusted life-year burden on women. A recent study has established a correlation between prolonged Proton Pump Inhibitor (PPI) usage and dementia, in addition to other neurodegenerative conditions. PPIs are frequently prescribed to treat peptic ulcers and GERD (gastroesophageal reflux disease) by decreasing stomach acid secretion. They alleviate acid-related symptoms through the inhibition of acid-secreting H+, K+ ATPase. In a number of observational studies, cognitive decline and dementia in the elderly have been linked to the use of PPIs. The precise mechanism underlying this relationship is unknown. These drugs might also alter the pH of brain cells, resulting in the accumulation of amyloid-beta (Aβ) peptides and the development of Alzheimer's disease (AD). Despite the compelling evidence supporting the association of PPIs with dementia, the results of studies remain inconsistent. The absence of a correlation between PPI use and cognitive decline in some studies emphasizes the need for additional research. Chronic PPI use can conceal underlying conditions, including cancer, celiac disease, vitamin B12 deficiency, and renal injury, highlighting dementia risk and the need for further investigations on cognitive health.

Correlative factors of poor prognosis and abnormal cellular immune function in patients with Alzheimer's disease

BACKGROUND

Alzheimer's disease (AD) is a serious disease causing human dementia and social problems. The quality of life and prognosis of AD patients have attracted much attention. The role of chronic immune inflammation in the pathogenesis of AD is becoming more and more important.

AIM

To study the relationship among cognitive dysfunction, abnormal cellular immune function, neuroimaging results and poor prognostic factors in patients.

METHODS

A retrospective analysis of 62 hospitalized patients clinical diagnosed with AD who were admitted to our hospital from November 2015 to November 2020. Collect cognitive dysfunction performance characteristics, laboratory test data and neuroimaging data from medical records within 24 h of admission, including Mini Mental State Examination Scale score, drawing clock test, blood T lymphocyte subsets, and neutrophils and lymphocyte ratio (NLR), disturbance of consciousness, extrapyramidal symptoms, electroencephalogram (EEG) and head nucleus magnetic spectroscopy (MRS) and other data. Multivariate logistic regression analysis was used to determine independent prognostic factors. the modified Rankin scale (mRS) was used to determine whether the prognosis was good. The correlation between drug treatment and prognostic mRS score was tested by the rank sum test.

RESULTS

Univariate analysis showed that abnormal cellular immune function, extrapyramidal symptoms, obvious disturbance of consciousness, abnormal EEG, increased NLR, abnormal MRS, and complicated pneumonia were related to the poor prognosis of AD patients. Multivariate logistic regression analysis showed that the decrease in the proportion of T lymphocytes in the blood after abnormal cellular immune function (odd ratio: 2.078, 95% confidence interval: 1.156-3.986, P < 0.05) was an independent risk factor for predicting the poor prognosis of AD. The number of days of donepezil treatment to improve cognitive function was negatively correlated with mRS score (r = 0.578, P < 0.05).

CONCLUSION

The decrease in the proportion of T lymphocytes may have predictive value for the poor prognosis of AD. It is recommended that the proportion of T lymphocytes < 55% is used as the cut-off threshold for predicting the poor prognosis of AD. The early and continuous drug treatment is associated with a good prognosis.

Dementia risk and thalamic nuclei volumetry in healthy midlife adults: the PREVENT Dementia study

A reduction in the volume of the thalamus and its nuclei has been reported in Alzheimer's disease, mild cognitive impairment and asymptomatic individuals with risk factors for early-onset Alzheimer's disease. Some studies have reported thalamic atrophy to occur prior to hippocampal atrophy, suggesting thalamic pathology may be an early sign of cognitive decline. We aimed to investigate volumetric differences in thalamic nuclei in middle-aged, cognitively unimpaired people with respect to dementia family history and apolipoprotein ε4 allele carriership and the relationship with cognition. Seven hundred participants aged 40-59 years were recruited into the PREVENT Dementia study. Individuals were stratified according to dementia risk (approximately half with and without parental dementia history). The subnuclei of the thalamus of 645 participants were segmented on T1-weighted 3 T MRI scans using FreeSurfer 7.1.0. Thalamic nuclei were grouped into six regions: (i) anterior, (ii) lateral, (iii) ventral, (iv) intralaminar, (v) medial and (vi) posterior. Cognitive performance was evaluated using the computerized assessment of the information-processing battery. Robust linear regression was used to analyse differences in thalamic nuclei volumes and their association with cognitive performance, with age, sex, total intracranial volume and years of education as covariates and false discovery rate correction for multiple comparisons. We did not find significant volumetric differences in the thalamus or its subregions, which survived false discovery rate correction, with respect to first-degree family history of dementia or apolipoprotein ε4 allele status. Greater age was associated with smaller volumes of thalamic subregions, except for the medial thalamus, but only in those without a dementia family history. A larger volume of the mediodorsal medial nucleus (Pfalse discovery rate = 0.019) was associated with a faster processing speed in those without a dementia family history. Larger volumes of the thalamus (P = 0.016) and posterior thalamus (Pfalse discovery rate = 0.022) were associated with significantly worse performance in the immediate recall test in apolipoprotein ε4 allele carriers. We did not find significant volumetric differences in thalamic subregions in relation to dementia risk but did identify an interaction between dementia family history and age. Larger medial thalamic nuclei may exert a protective effect on cognitive performance in individuals without a dementia family history but have little effect on those with a dementia family history. Larger volumes of posterior thalamic nuclei were associated with worse recall in apolipoprotein ε4 carriers. Our results could represent initial dysregulation in the disease process; further study is needed with functional imaging and longitudinal analysis.

Bioinformatics to analyze the differentially expressed genes in different degrees of Alzheimer's disease and their roles in progress of the disease

Employing bioinformatics approaches, this investigation pinpointed pivotal differentially expressed genes (DEGs) across the spectrum of Alzheimer's disease (AD), from incipient to severe stages, using the GSE28146 dataset from the GEO repository. Analytical methods included DEG identification via the limma package in R, coupled with GO and KEGG pathway analyses through clusterProfiler, to discern biological processes and pathway involvements. Key findings spotlighted the roles of proteasome subunits PSMB4, PSMB8, PSMC4, and PSMD6 in the early stage, ribosomal proteins RPS3 and RPL11 during moderate AD, and mitochondrial components COX5B, COX6B2, and COX7A2 in severe AD, underscoring their importance in the disease's pathogenesis. Conclusively, these results not only delineate the dynamic genetic shifts accompanying AD progression but also propose critical biomarkers for potential therapeutic targeting, offering a consolidated basis for future AD research and treatment development. This offered a novel idea for analyzing the pathogenesis and development of AD and investigation of targeted drugs.

Translational bioinformatics and data science for biomarker discovery in mental health: an analytical review

Translational bioinformatics and data science play a crucial role in biomarker discovery as it enables translational research and helps to bridge the gap between the bench research and the bedside clinical applications. Thanks to newer and faster molecular profiling technologies and reducing costs, there are many opportunities for researchers to explore the molecular and physiological mechanisms of diseases. Biomarker discovery enables researchers to better characterize patients, enables early detection and intervention/prevention and predicts treatment responses. Due to increasing prevalence and rising treatment costs, mental health (MH) disorders have become an important venue for biomarker discovery with the goal of improved patient diagnostics, treatment and care. Exploration of underlying biological mechanisms is the key to the understanding of pathogenesis and pathophysiology of MH disorders. In an effort to better understand the underlying mechanisms of MH disorders, we reviewed the major accomplishments in the MH space from a bioinformatics and data science perspective, summarized existing knowledge derived from molecular and cellular data and described challenges and areas of opportunities in this space.

The Biochemistry Behind Cognitive Decline: Biomarkers of Alzheimer's Disease

Alzheimer's disease (AD) is the most prevalent type of dementia. Pathologically, the disease is marked by neurofibrillary tangles (NFT), which are aberrant accumulations of the tau protein that develop inside neurons, and extracellular plaque deposits of the amyloid β peptide (Aβ). These pathological lesions are present in the brain before the beginning of clinical manifestations. However, despite advancements in the comprehension of AD pathophysiology, timely and accurate clinical diagnosis remains challenging. Therefore, developing biomarkers capable of detecting AD during the preclinical phase holds enormous promise for precise diagnosis since detecting the disease early is crucial because it enables interventions when treatments may be more effective. This article intends to provide a comprehensive review of AD biomarkers, discussing their significance, classification, and recent developments in the field.

Association between Mineral Intake and Cognition Evaluated by Montreal Cognitive Assessment (MoCA): A Cross-Sectional Study

BACKGROUND

Mineral intake may protect against cognitive impairment (CI) and all-cause dementia, which affects a large number of adults worldwide. The aim of this study was to investigate the association between mineral intake and Montreal Cognitive Assessment (MoCA), which is a sensitive and specific test.

METHODS

In total, 201 adults were included in a cross-sectional study. They completed a three-day dietary record to estimate their average daily intake of minerals. Contributions to dietary reference intakes (DRIs) were also calculated. The participants were divided into tertiles according to their mineral intake. CI classifications were determined via the MoCA (score < 26). Apolipoprotein E (APOE) genotyping was carried out, and the patients' anthropometric measurements and physical activity, health and personal data were collected.

RESULTS

The prevalence of CI in this selective sample was 54.2% (34.3% females and 19.9% males). In women, being in the third tertiles of iron and manganese intake was associated with lower odds of having CI (OR [95% CI]: 0.32 [0.11 ± 0.93]; 0.33 [0.12 ± 0.93], p < 0.05). No significant differences were observed for any of the nutrients studied in men.

CONCLUSIONS

These findings suggest that a low mineral intake, especially low iron and manganese intake in women, is associated with a worse cognition as assessed by MoCA.

c-Diadem: a constrained dual-input deep learning model to identify novel biomarkers in Alzheimer's disease

BACKGROUND

Alzheimer's disease (AD) is an incurable, debilitating neurodegenerative disorder. Current biomarkers for AD diagnosis require expensive neuroimaging or invasive cerebrospinal fluid sampling, thus precluding early detection. Blood-based biomarker discovery in Alzheimer's can facilitate less-invasive, routine diagnostic tests to aid early intervention. Therefore, we propose "c-Diadem" (constrained dual-input Alzheimer's disease model), a novel deep learning classifier which incorporates KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway constraints on the input genotyping data to predict disease, i.e., mild cognitive impairment (MCI)/AD or cognitively normal (CN). SHAP (SHapley Additive exPlanations) was used to explain the model and identify novel, potential blood-based genetic markers of MCI/AD.

METHODS

We developed a novel constrained deep learning neural network which utilizes SNPs (single nucleotide polymorphisms) and microarray data from ADNI (Alzheimer's Disease Neuroimaging Initiative) to predict the disease status of participants, i.e., CN or with disease (MCI/AD), and identify potential blood-based biomarkers for diagnosis and intervention. The dataset contains samples from 626 participants, of which 212 are CN (average age 74.6 ± 5.4 years) and 414 patients have MCI/AD (average age 72.7 ± 7.6 years). KEGG pathway information was used to generate constraints applied to the input tensors, thus enhancing the interpretability of the model. SHAP scores were used to identify genes which could potentially serve as biomarkers for diagnosis and targets for drug development.

RESULTS

Our model's performance, with accuracy of 69% and AUC of 70% in the test dataset, is superior to previous models. The SHAP scores show that SNPs in PRKCZ, PLCB1 and ITPR2 as well as expression of HLA-DQB1, EIF1AY, HLA-DQA1, and ZFP57 have more impact on model predictions.

CONCLUSIONS

In addition to predicting MCI/AD, our model has been interrogated for potential genetic biomarkers using SHAP. From our analysis, we have identified blood-based genetic markers related to Ca2+ ion release in affected regions of the brain, as well as depression. The findings from our study provides insights into disease mechanisms, and can facilitate innovation in less-invasive, cost-effective diagnostics. To the best of our knowledge, our model is the first to use pathway constraints in a multimodal neural network to identify potential genetic markers for AD.

SERS-Based Optical Nanobiosensors for the Detection of Alzheimer's Disease

Alzheimer's disease (AD) is a leading cause of dementia, impacting millions worldwide. However, its complex neuropathologic features and heterogeneous pathophysiology present significant challenges for diagnosis and treatment. To address the urgent need for early AD diagnosis, this review focuses on surface-enhanced Raman scattering (SERS)-based biosensors, leveraging the excellent optical properties of nanomaterials to enhance detection performance. These highly sensitive and noninvasive biosensors offer opportunities for biomarker-driven clinical diagnostics and precision medicine. The review highlights various types of SERS-based biosensors targeting AD biomarkers, discussing their potential applications and contributions to AD diagnosis. Specific details about nanomaterials and targeted AD biomarkers are provided. Furthermore, the future research directions and challenges for improving AD marker detection using SERS sensors are outlined.

Immunological characterization and diagnostic models of RNA N6-methyladenosine regulators in Alzheimer's disease

Alzheimer's disease (AD) is the most prevalent form of dementia, and it displays both clinical and molecular variability. RNA N6-methyladenosine (m6A) regulators are involved in a wide range of essential cellular processes. In this study, we aimed to identify molecular signatures associated with m6A in Alzheimer's disease and use those signatures to develop a predictive model. We examined the expression patterns of m6A regulators and immune features in Alzheimer's disease using the GSE33000 dataset. We examined the immune cell infiltration and molecular groups based on m6A-related genes in 310 Alzheimer's disease samples. The WGCNA algorithm was utilized to determine differently expressed genes within each cluster. After evaluating the strengths and weaknesses of the random forest model, the support vector machine model, the generalized linear model, and eXtreme Gradient Boosting, the best machine model was selected. Methods such as nomograms, calibration curves, judgment curve analysis, and the use of independent data sets were used to verify the accuracy of the predictions made. Alzheimer's disease and non-disease Alzheimer's groups were compared to identify dysregulated m6A-related genes and activated immune responses. In Alzheimer's disease, two molecular clusters linked to m6A were identified. Immune infiltration analysis indicated substantial variation in protection between groups. Cluster 1 included processes like the Toll-like receptor signaling cascade, positive regulation of chromatin binding, and numerous malignancies; cluster 2 included processes like the cell cycle, mRNA transport, and ubiquitin-mediated proteolysis. With a lower residual and root mean square error and a larger area under the curve (AUC = 0.951), the Random forest machine model showed the greatest discriminative performance. The resulting random forest model was based on five genes, and it performed well (AUC = 0.894) on external validation datasets. Accuracy in predicting Alzheimer's disease subgroups was also shown by analyses of nomograms, calibration curves, and decision curves. In this research, we methodically outlined the tangled web of connections between m6A and AD and created a promising prediction model for gauging the correlation between m6A subtype risk and AD pathology.

Comparative Study of Safety and Efficacy of Angiotensin-Receptor Blockers and Anti Amyloid-ß Monoclonal Antibodies for the Treatment of Alzheimer's Disease: A Systematic Review

Amyloid-ß (Aß) plaques and Neurofibrillary tangles are hallmarks of Alzheimer's disease (AD) pathology. Recent advances to find a cure for AD have led to the exploration of Anti-Aß monoclonal antibodies and angiotensin-receptor blockers (ARBs). The antibodies can decrease plaque formation or remove already formed plaques. ARBs increase angiotensin II (AT2) levels and decrease the effect of AT2 on the AT1 receptor (AT1R). This systematic analysis reviews evidence of monoclonal antibodies (Aducanumab, Lecanemab, Donanemab, and Solanezumab) and ARBs in managing AD. An in-depth methodical search was conducted across PubMed, Science Direct, and Mendeley. PRISMA 2020 guidelines were followed for this study. Randomized control trials for antibodies and ARBs and one retrospective cohort study were included. The comparison was made among studies that shared similar measured outcomes. Antibodies were found to be more effective than ARBs, with Aducanumab and Lecanemab being the most effective. ARBs, on the other hand, were found to be the safer choice. Further trials of longer duration and larger sample sizes are needed to explore both groups' long-term safety and efficacy.

m 6A methylation in cellular senescence of age-associated diseases

Cellular senescence is a state of irreversible cellular growth arrest that occurs in response to various stresses. In addition to exiting the cell cycle, senescent cells undergo many phenotypic alterations, including metabolic reprogramming, chromatin rearrangement, and senescence-associated secretory phenotype (SASP) development. Furthermore, senescent cells can affect most physiological and pathological processes, such as physiological development; tissue homeostasis; tumour regression; and age-associated disease progression, including diabetes, atherosclerosis, Alzheimer's disease, and hypertension. Although corresponding anti-senescence therapies are actively being explored for the treatment of age-associated diseases, the specific regulatory mechanisms of senescence remain unclear. N 6-methyladenosine (m 6A), a chemical modification commonly distributed in eukaryotic RNA, plays an important role in biological processes such as translation, shearing, and RNA transcription. Numerous studies have shown that m 6A plays an important regulatory role in cellular senescence and aging-related disease. In this review, we systematically summarize the role of m 6A modifications in cellular senescence with regard to oxidative stress, DNA damage, telomere alterations, and SASP development. Additionally, diabetes, atherosclerosis, and Alzheimer's disease regulation via m 6A-mediated cellular senescence is discussed. We further discuss the challenges and prospects of m 6A in cellular senescence and age-associated diseases with the aim of providing rational strategies for the treatment of these age-associated diseases.

Combined analysis of single-cell and bulk RNA sequencing reveals the expression patterns of circadian rhythm disruption in the immune microenvironment of Alzheimer's disease

Background

Circadian rhythm disruption (CRD) represents a critical contributor to the pathogenesis of Alzheimer's disease (AD). Nonetheless, how CRD functions within the AD immune microenvironment remains to be illustrated.

Methods

Circadian rhythm score (CRscore) was utilized to quantify the microenvironment status of circadian disruption in a single-cell RNA sequencing dataset derived from AD. Bulk transcriptome datasets from public repository were employed to validate the effectiveness and robustness of CRscore. A machine learning-based integrative model was applied for constructing a characteristic CRD signature, and RT-PCR analysis was employed to validate their expression levels.

Results

We depicted the heterogeneity in B cells, CD4⁺ T cells, and CD8⁺ T cells based on the CRscore. Furthermore, we discovered that CRD might be strongly linked to the immunological and biological features of AD, as well as the pseudotime trajectories of major immune cell subtypes. Additionally, cell-cell interactions revealed that CRD was critical in the alternation of ligand-receptor pairs. Bulk sequencing analysis indicated that the CRscore was found to be a reliable predictive biomarker in AD patients. The characteristic CRD signature, which included 9 circadian-related genes (CRGs), was an independent risk factor that accurately predicted the onset of AD. Meanwhile, abnormal expression of several characteristic CRGs, including GLRX, MEF2C, PSMA5, NR4A1, SEC61G, RGS1, and CEBPB, was detected in neurons treated with Aβ1-42 oligomer.

Conclusion

Our study revealed CRD-based cell subtypes in the AD microenvironment at single-cell level and proposed a robust and promising CRD signature for AD diagnosis. A deeper knowledge of these mechanisms may provide novel possibilities for incorporating "circadian rhythm-based anti-dementia therapies" into the treatment protocols of individualized medicine.

Protective effect of glutamic-oxaloacetic transaminase on hippocampal neurons in Alzheimer's disease using model mice

Alzheimer's disease (AD), a neurodegenerative disease affecting the elderly, frequently causes cognitive impairment and memory decline, and there are currently no effective therapeutic drugs available. Glutamate excitotoxicity is one of the pathogeneses of AD, and there is evidence that glutamic-oxaloacetic transaminase (GOT) can significantly reduce glutamate concentrations in the hippocampi of mice, but its role in APP/PS1 transgenic mice is unknown. We investigated the improvement of neurological function and related protein expression following subcutaneous injection of GOT in mice with AD. We performed immunohistochemical staining on the brain tissue of 3-, 6-, and 12-month-old mice and found that the content of the β-amyloid protein Aβ1-42 in the 6 months old GOT treatment group was significantly reduced. Meanwhile, the APP-GOT group outperformed the APP group in the water maze and spatial object recognition experiments. The number of neurons in the hippocampal CA1 area of the APP-GOT group increased when compared to the APP group according to Nissl staining. Electron microscopic examination of the hippocampal CA1 area demonstrated that the number of synapses in the APP-GOT group was more than that in the APP group, and the mitochondrial structure was relatively complete. Finally, the protein content of the hippocampus was detected. In comparison to the APP group, SIRT1 content increased in the APP-GOT group whereas Aβ1-42 content decreased, and Ex527 could reverse this trend. These results suggest that GOT can significantly improve the cognitive function of mice in the early stage of AD, and the underlying mechanism may be through decreasing Aβ1-42 and increasing SIRT1 expressions.

Testing times for dementia: a community survey identifying contemporary barriers to risk reduction and screening

BACKGROUND

Advances in pharmacological and non-pharmacological dementia interventions may mean future dementia prevention incorporates a combination of targeted screening and lifestyle modifications. Elucidating potential barriers which may prevent community engagement with dementia prevention initiatives is important to maximise the accessibility and feasibility of these initiatives across the lifespan.

METHODS

Six hundred seven adults aged over 18 years completed a 54-item, multiple-choice survey exploring contemporary attitudes towards, and barriers to, dementia risk reduction and screening relative to other common health conditions. Participants were sourced from Australia's largest, paid, data analytics service (ORIMA).

RESULTS

Finances (p = .009), poor motivation (p = .043), and time (p ≤ .0001) emerged as significant perceived barriers to dementia risk reduction behaviours. Lack of time was more likely to be reported by younger, relative to older, participants (p ≤ .0001), while females were more likely than males to report financial (p = .019) and motivational (p = .043) factors. Binary logistic regression revealed willingness to undertake dementia testing modalities was significantly influenced by gender (genetic testing, p = .012; saliva, p = .038, modifiable risk factors p = .003), age (cognitive testing, p ≤ .0001; blood, p = .010), and socio-economic group (retinal imaging, p = .042; modifiable risk-factor screening, p = .019). Over 65% of respondents felt adequately informed about risk reduction for at least one non-dementia health condition, compared to 30.5% for dementia.

CONCLUSIONS

This study found perceived barriers to dementia risk reduction behaviours, and the willingness to engage in various dementia testing modalities, was significantly associated with socio-demographic factors across the lifespan. These findings provide valuable insight regarding the accessibility and feasibility of potential methods for identifying those most at risk of developing dementia, as well as the need to better promote and support wide-scale engagement in dementia risk reduction behaviours across the lifespan.

(S)-N-Benzyl-1-phenyl-3,4-dihydroisoqunoline-2(1H)-carboxamide Derivatives, Multi-Target Inhibitors of Monoamine Oxidase and Cholinesterase: Design, Synthesis, and Biological Activity

A series of (S)-1-phenyl-3,4-dihydroisoquinoline-2(1H)-carboxamide derivatives was synthesized and evaluated for inhibitory activity against monoamine oxidase (MAO)-A and-B, acetylcholine esterase (AChE), and butyrylcholine esterase (BChE). Four compounds (2i, 2p, 2t, and 2v) showed good inhibitory activity against both MAO-A and MAO-B, and two compounds (2d and 2j) showed selective inhibitory activity against MAO-A, with IC₅₀ values of 1.38 and 2.48 µM, respectively. None of the compounds showed inhibitory activity against AChE; however, 12 compounds showed inhibitory activity against BChE. None of the active compounds showed cytotoxicity against L929cells. Molecular docking revealed several important interactions between the active analogs and amino acid residues of the protein receptors. This research paves the way for further study aimed at designing MAO and ChE inhibitors for the treatment of depression and neurodegenerative disorders.

Genomics in Treatment Development

The Human Genome Project mapped the 3 billion base pairs in the human genome, which ushered in a new generation of genomically focused treatment development. While this has been very successful in other areas, neuroscience has been largely devoid of such developments. This is in large part because there are very few neurological or mental health conditions that are related to single-gene variants. While developments in pharmacogenomics have been somewhat successful, the use of genetic information in practice has to do with drug metabolism and adverse reactions. Studies of drug metabolism related to genetic variations are an important part of drug development. However, outside of cancer biology, the actual translation of genomic information into novel therapies has been limited. Epigenetics, which relates in part to the effects of the environment on DNA, is a promising newer area of relevance to CNS disorders. The environment can induce chemical modifications of DNA (e.g., cytosine methylation), which can be induced by the environment and may represent either shorter- or longer-term changes. Given the importance of environmental influences on CNS disorders, epigenetics may identify important treatment targets in the future.

Hypothetical Strategies of Gene and Environmental Influence on Life Expectancy: A Brief Review

Almost all diseases have a genetic basis. However, several disorders stem from a combination of genes and environmental conditions. In the present study, databases including PubMed, Scopus and Google scholar were searched and reviewed and those relevant studies that investigated the association between environmental and genetic factors with the incidence of diseases were extracted and used. At the final step, it is concluded that in many cases, disorders have a multifactorial etiology. Having a gene related to a specific disorder is not the only reason for contracting the disease. Both genes and environmental factors play a role in human disease etiology. Everything outside of DNA, may affect health and even in many people with a positive family history of a specific disorder, environmental factors can facilitate or prevent the occurrence of the disease. Therefore, living a healthy lifestyle is important in reducing exposure to diseases, and long-life expectancy.

Identification of the molecular subgroups in Alzheimer's disease by transcriptomic data

Background

Alzheimer's disease (AD) is a heterogeneous pathological disease with genetic background accompanied by aging. This inconsistency is present among molecular subtypes, which has led to diagnostic ambiguity and failure in drug development. We precisely distinguished patients of AD at the transcriptome level.

Methods

We collected 1,240 AD brain tissue samples collected from the GEO dataset. Consensus clustering was used to identify molecular subtypes, and the clinical characteristics were focused on. To reveal transcriptome differences among subgroups, we certificated specific upregulated genes and annotated the biological function. According to RANK METRIC SCORE in GSEA, TOP10 was defined as the hub gene. In addition, the systematic correlation between the hub gene and “A/T/N” was analyzed. Finally, we used external data sets to verify the diagnostic value of hub genes.

Results

We identified three molecular subtypes of AD from 743 AD samples, among which subtypes I and III had high-risk factors, and subtype II had protective factors. All three subgroups had higher neuritis plaque density, and subgroups I and III had higher clinical dementia scores and neurofibrillary tangles than subgroup II. Our results confirmed a positive association between neurofibrillary tangles and dementia, but not neuritis plaques. Subgroup I genes clustered in viral infection, hypoxia injury, and angiogenesis. Subgroup II showed heterogeneity in synaptic pathology, and we found several essential beneficial synaptic proteins. Due to presenilin one amplification, Subgroup III was a risk subgroup suspected of familial AD, involving abnormal neurogenic signals, glial cell differentiation, and proliferation. Among the three subgroups, the highest combined diagnostic value of the hub genes were 0.95, 0.92, and 0.83, respectively, indicating that the hub genes had sound typing and diagnostic ability.

Conclusion

The transcriptome classification of AD cases played out the pathological heterogeneity of different subgroups. It throws daylight on the personalized diagnosis and treatment of AD.

Establishment and Analysis of a Combined Diagnostic Model of Alzheimer's Disease With Random Forest and Artificial Neural Network

Alzheimer's disease (AD) is a neurodegenerative condition that causes cognitive decline over time. Because existing diagnostic approaches for AD are limited, improving upon previously established diagnostic models based on genetic biomarkers is necessary. Firstly, four AD gene expression datasets were collected from the Gene Expression Omnibus (GEO) database. Two datasets were used to establish diagnostic models, and the other two datasets were used to verify the model effect. We merged GSE5281 with GSE44771 as the training dataset and found 120 DEGs. Then, we used random forest (RF) to screen 6 key genes (KLF15, MAFF, ITPKB, SST, DDIT4, and NRXN3) as being critical for separating AD and normal samples. The weights of these key genes were measured, and a diagnostic model was created using an artificial neural network (ANN). The area under the curve (AUC) of the model is 0.953, while the accuracy is 0.914. In the final step, two validation datasets were utilized to assess AUC performance. In GSE109887, our model had an AUC of 0.854, and in GSE132903, it had an AUC of 0.810. To summarize, we successfully identified key gene biomarkers and developed a new AD diagnostic model.

Many faces and functions of GSKIP: a temporospatial regulation view

Glycogen synthase kinase 3 (GSK3)-β (GSK3β) interaction protein (GSKIP) is one of the smallest A-kinase anchoring proteins that possesses a binding site for GSK3β. Recently, our group identified the protein kinase A (PKA)-GSKIP-GSK3β-X axis; knowledge of this axis may help us decipher the many roles of GSKIP and perhaps help explain the evolutionary reason behind the interaction between GSK3β and PKA. In this review, we highlight the critical and multifaceted role of GSKIP in facilitating PKA kinase activity and its function as a scaffolding protein in signaling pathways. We also highlight how these pivotal PKA and GSK3 kinases can control context-specific functions and interact with multiple target proteins, such as β-catenin, Drp1, Tau, and other proteins. GSKIP is a key regulator of multiple mechanisms because of not only its location at certain subcellular compartments but also its serial changes during the developmental process. Moreover, the involvement of critical upstream regulatory signaling pathways in GSKIP signaling in various cancers, such as miRNA (microRNA) and lncRNA (long noncoding RNA), may help in the identification of therapeutic targets in the era of precision medicine and personalized therapy. Finally, we emphasize on the model of the early stage of pathogenesis of Alzheimer Disease (AD). Although the model requires validation, it can serve as a basis for diagnostic biomarkers development and drug discovery for early-stage AD.

Biomarker Candidates for Alzheimer’s Disease Unraveled through In Silico Differential Gene Expression Analysis

Alzheimer’s disease (AD) is neurodegeneration that accounts for 60–70% of dementia cases. Symptoms begin with mild memory difficulties and evolve towards cognitive impairment. The underlying risk factors remain primarily unclear for this heterogeneous disorder. Bioinformatics is a relevant research tool that allows for identifying several pathways related to AD. Open-access databases of RNA microarrays from the peripheral blood and brain of AD patients were analyzed after background correction and data normalization; the Limma package was used for differential expression analysis (DEA) through statistical R programming language. Data were corrected with the Benjamini and Hochberg approach, and genes with p-values equal to or less than 0.05 were considered to be significant. The direction of the change in gene expression was determined by its variation in the log2-fold change between healthy controls and patients. We performed the functional enrichment analysis of GO using goana and topGO-Limma. The functional enrichment analysis of DEGs showed upregulated (UR) pathways: behavior, nervous systems process, postsynapses, enzyme binding; downregulated (DR) were cellular component organization, RNA metabolic process, and signal transduction. Lastly, the intersection of DEGs in the three databases showed eight shared genes between brain and blood, with potential use as AD biomarkers for blood tests.

Contributive Role of Hyperglycemia and Hypoglycemia Towards the Development of Alzheimer's Disease

Alzheimer's disease (AD) is one of the causes of dementia that results from several infections/biological conditions leading to either cell disruption or loss of neuronal communication. Studies have documented the accumulation of two proteins, beta-amyloid (Aβ), which accumulates on the exteriors of neurons, and tau (Tau), which assembles at the interiors of brain cells and is chiefly liable for the progression of the disease. Several molecular and cellular pathways account for the accumulation of amyloid-β and the formation of neurofibrillary tangles, which are phosphorylated variants of Tau protein. Moreover, research has revealed a potential connection between AD and diabetes. It has also been demonstrated that both hypoglycemia and hyperglycemia have a significant role in the development of AD. In addition, SUMO (small ubiquitin-like modifier protein) plays a crucial role in the pathogenesis of AD. SUMOylation is the process by which modification of amyloid precursor protein (APP) and Tau takes place. Furthermore, Drosophila melanogaster has proven to be an efficient model organism in studies to establish the relationship between AD and variations in blood glucose levels. In addition, the review successfully identifies the common pathway that links the effects of fluctuations in glucose levels on AD pathogenesis and advancements.

Re-analysis of genomic data: An overview of the mechanisms and complexities of clinical adoption

Re-analyzing genomic information from a patient suspected of having an underlying genetic condition can improve the diagnostic yield of sequencing tests, potentially providing significant benefits to the patient and to the health care system. Although a significant number of studies have shown the clinical potential of re-analysis, less work has been performed to characterize the mechanisms responsible for driving the increases in diagnostic yield. Complexities surrounding re-analysis have also emerged. The terminology itself represents a challenge because "re-analysis" can refer to a range of different concepts. Other challenges include the increased workload that re-analysis demands of curators, adequate reimbursement pathways for clinical and diagnostic services, and the development of systems to handle large volumes of data. Re-analysis also raises ethical implications for patients and families, most notably when re-classification of a variant alters diagnosis, treatment, and prognosis. This review highlights the possibilities and complexities associated with the re-analysis of existing clinical genomic data. We propose a terminology that builds on the foundation presented in a recent statement from the American College of Medical Genetics and Genomics and describes each re-analysis process. We identify mechanisms for increasing diagnostic yield and provide perspectives on the range of challenges that must be addressed by health care systems and individual patients.

Increase of ALCAM and VCAM-1 in the plasma predicts the Alzheimer's disease

Cell adhesion molecules (CAM) are crucial in several pathological inflammation processes in Alzheimer's disease (AD). However, their potential for clinical diagnostics remains unknown. The present investigation evaluated the clinical significance of ALCAM, VCAM-1, NCAM, and ICAM-1 levels in the plasma of participants with cognitive impairment (44 patients with mild cognitive impairment, 71 patients with Alzheimer's dementia, and 18 patients with other dementia) and 28 controls with normal cognitive ability. We also detected plasma levels of multiple inflammatory factors (IFN-gamma, IL-18, IL-1beta, IL-13, IL-8, IL-7, CCL11, MCP-1, TSLP, IL-10, BDNF, IL-17, IL-5, TREM-1) using Multiplex liquid chip and plasma levels of Abeta1-42 and Abeta1-40 using liquid-phase flow cytometry (FCM). Our findings demonstrated a correlation of ALCAM and VCAM-1 with age, the severity of cognitive decline, and MTA, but no significant difference between groups for NCAM and ICAM-1. ALCAM and VCAM-1 both demonstrated a positive correlation with the degree of atrophy in the medial temporal lobe structure. Further analysis revealed no significant correlation in plasma between VCAM-1, ALCAM and Abeta1-40, Abeta1-42. Nevertheless, there was a significant correlation between VCAM-1, ALCAM and many inflammatory factors. Furthermore, the predictive value of ALCAM and VCAM-1 for AD was assessed using a multi-parameter regression model. ALCAM and VCAM-1 in combination with ApoE4, education, age, and MMSE could predict AD with high precision (AUC=0.891; AIC=146.9) without imaging diagnosis. ALCAM and VCAM-1 combination improved the predictive accuracy significantly. In a nutshell, these findings revealed ALCAM and VCAM-1 as reliable indicators of Alzheimer's disease.

IL-6, IL-8 and IL-10 polymorphisms may impact predisposition of Alzheimer's disease: a meta-analysis

Gene polymorphisms in interleukin-6 (IL-6), interleukin-8 (IL-8), and interleukin-10 (IL-10) may affect the predisposition of Alzheimer's disease (AD), but the results of the so far published studies remain controversial. The authors conducted this meta-analysis to assess relationships between IL-6/IL-8/IL-10 polymorphisms and predisposition of AD by pooling the findings of so far published studies. A comprehensive search of Pubmed, Embase, Web of Science, and CNKI was endorsed by the authors to identify the already published studies. Forty-five studies were found to be eligible for meta-analyses. The pooled meta-analyses results showed that genotypic frequencies of IL-6 - 174 G/C, IL-6 - 572 G/C and IL-10 - 1082 A/G polymorphisms among patients with AD and controls differed significantly. Moreover, genotypic frequencies of IL-6 - 174 G/C, IL-6 - 572 G/C, and IL-8 - 251 A/T polymorphisms among patients with AD and controls in Asians also differed significantly. But no such genotypic frequencies' differences were observed for IL-10 - 819 C/T and 592 C/A polymorphisms. This meta-analysis suggests that IL-6 - 174 G/C, IL-6 - 572 G/C, and IL-10 - 1082 A/G polymorphisms may affect the predisposition of AD in overall population. Moreover, IL-6 - 174 G/C, IL-6 - 572 G/C, and IL-8 - 251 A/T polymorphisms may affect the predisposition of AD in Asians.

Diagnostic accuracy of blood biomarkers for Alzheimer's disease and amnestic mild cognitive impairment: A meta-analysis

OBJECTIVE

To examine the diagnostic accuracy of blood-based biomarkers for detecting Alzheimer's disease (AD) and amnestic mild cognitive impairment (aMCI).

METHODS

Seven electronic databases were comprehensively searched for studies evaluating the diagnostic accuracy of blood-based biomarkers for detecting AD or aMCI up to July 31, 2020. The pooled sensitivity, specificity, and the diagnostic odds ratio (DOR) were calculated using a hierarchical summary receiver operating characteristic model.

RESULTS

A total of 17 studies (n = 2,083) were included. In differentiating patients with AD from the controls, the DOR was 32.2 for the plasma Aβ42 (sensitivity = 88 %, specificity = 81 %), 29.1 for the plasma Aβ oligomer (sensitivity = 80 %, specificity = 88 %), and 52.1 for the plasma tau (sensitivity = 90 %, specificity = 87 %). For differentiating aMCI from the controls, the DOR was 60.4 for the plasma Aβ42 (sensitivity = 86 %, specificity = 90 %) and 49.1 for the plasma tau (sensitivity = 79 %, specificity = 94 %). The use of ultra-high sensitive technology explained the heterogeneity in the diagnostic performance of blood-based biomarkers (P =  .01).

CONCLUSIONS

We suggest that blood-based biomarkers are minimally invasive and cost-effective tools for detecting AD; however, the evidence for detecting aMCI was still limited.

MicroRNA-132-3p alleviates neuron apoptosis and impairments of learning and memory abilities in Alzheimer's disease by downregulation of HNRNPU stabilized BACE1

Alzheimer's disease (AD) is a progressive neuro-degenerative disease characterized by dementia. MicroRNAs (miRNAs) are involved in many diseases, including AD. MiR-132-3p has been identified to be downregulated in AD. In this study, we explored the effects of miR-132-3p on neuron apoptosis and impairments of learning and memory abilities. Aβ1-42-stimulated SH-SY5Y cells were used as in vitro models of AD. An AD-like homocysteine (Hcy) rat model was established to evaluate the effects of miR-132-3p on AD pathogenesis in vivo. RIP, RNA pull down and luciferase reporter assays were conducted to investigate the relationship between miR-132-3p and its downstream target genes. The viability and apoptosis of SH-SY5Y cells were measured by CCK-8 and TUNEL assays. The rat spatial learning and memory abilities were accessed using Morris water maze test. Results indicated that miR-132-3p was downregulated in SH-SY5Y cells after Aβ1-42 treatment and promoted cell apoptosis. Mechanistically, miR-132-3p targeted heterogeneous nuclear ribonucleoprotein U (HNRNPU). HNRNPU acted as an RNA binding protein (RBP) to regulate the mRNA stability of β-site amyloid precursor protein cleaving enzyme 1 (BACE1). Overexpression of HNRNPU or BACE1 reversed the effects of miR-132-3p overexpression on the viability and apoptosis of Aβ1-42-treated SH-SY5Y cells. In vivo experiments revealed the downregulation of miR-132-3p in the hippocampus of Hcy-treated rats. MiR-132-3p suppressed levels of apoptotic genes in hippocampus and reduced impairments of learning and memory abilities in Hcy-treated rats. In conclusion, miR-132-3p reduces apoptosis of SH-SY5Y cells and alleviates impairments of learning and memory abilities in AD rats by modulating the HNRNPU/BACE1 axis.

Association between chronic periodontitis and the risk of Alzheimer's disease: combination of text mining and GEO dataset

BACKGROUND

Although chronic periodontitis has previously been reported to be linked with Alzheimer's disease (AD), the pathogenesis between the two is unclear. The purpose of this study is to analyze and screen the relevant and promising molecular markers between chronic periodontitis and Alzheimer's disease (AD).

METHODS

In this paper, we analyzed three AD expression datasets and extracted differentially expressed genes (DEGs), then intersected them with chronic periodontitis genes obtained from text mining, and finally obtained integrated DEGs. We followed that by enriching the matching the matching cell signal cascade through DAVID analysis. Moreover, the MCODE of Cytoscape software was employed to uncover the protein-protein interaction (PPI) network and the matching hub gene. Finally, we verified our data using a different independent AD cohort.

RESULTS

The chronic periodontitis gene set acquired from text abstracting was intersected with the previously obtained three AD groups, and 12 common genes were obtained. Functional enrichment assessment uncovered 12 cross-genes, which were mainly linked to cell morphogenesis involved in neuron differentiation, leading edge membrane, and receptor ligand activity. After PPI network creation, the ten hub genes linked to AD were retrieved, consisting of SPP1, THY1, CD44, ITGB1, HSPB3, CREB1, SST, UCHL1, CCL5 and BMP7. Finally, the function terms in the new independent dataset were used to verify the previous dataset, and we found 22 GO terms and one pathway, "ECM-receptor interaction pathways", in the overlapping functional terms.

CONCLUSIONS

The establishment of the above-mentioned candidate key genes, as well as the enriched signaling cascades, provides promising molecular markers for chronic periodontitis-related AD, which may help the diagnosis and treatment of AD patients in the future.

A 3-Gene-Based Diagnostic Signature in Alzheimer's Disease

BACKGROUND

Alzheimer's disease (AD) is a chronic neurodegenerative disease. In this study, potential diagnostic biomarkers were identified for AD.

METHODS

All AD samples and healthy samples were collected from 2 datasets in the GEO database, in which differentially expressed genes (DEGs) were analyzed by using the limma package of R language. GO and KEGG pathway enrichment was conducted basing on the DEGs via the clusterProfiler package of R. And, the PPI network construction and gene prediction were performed using the STRING database and Cytoscape. Then, a logistic regression model was constructed to predict the sample type.

RESULTS

Bioinformatic analysis of GEO datasets revealed 2,063 and 108 DEGs in GSE5281 and GSE4226 datasets, separately, and 15 overlapping DEGs were found. GO and KEGG enrichment analysis revealed terms associated with neurodevelopment. Then, we built a logistic regression model based on the hub genes from the PPI network and optimized the model to 3 genes (ALDOA, ENC1, and NFKBIA). The values of area under the curve of the training set GSE5281 and testing set GSE4226 were 0.9647 and 0.7857, respectively, which implied the efficacy of this model.

CONCLUSION

The comprehensive bioinformatic analysis of gene expression in AD patients and the effective logistic regression model built in our study may provide promising research value for diagnostic methods of AD.

Nanodelivery of oxiracetam enhances memory, functional recovery and induces neuroprotection following concussive head injury

Military personnel are the most susceptible to concussive head injury (CHI) caused by explosion, blast or missile or blunt head trauma. Mild to moderate CHI could induce lifetime functional and cognitive disturbances causing significant decrease in quality of life. Severe CHI leads to instant death and lifetime paralysis. Thus, further exploration of novel therapeutic agents or new features of known pharmacological agents are needed to enhance quality of life of CHI victims. Previous reports from our laboratory showed that mild CHI induced by weight drop technique causing an impact of 0.224N results in profound progressive functional deficit, memory impairment and brain pathology from 5h after trauma that continued over several weeks of injury. In this investigation we report that TiO2 nanowired delivery of oxiracetam (50mg/kg, i.p.) daily for 5 days after CHI resulted in significant improvement of functional deficit on the 8th day. This was observed using Rota Rod treadmill, memory improvement assessed by the time spent in finding hidden platform under water. The motor function improvement is seen in oxiracetam treated CHI group by placing forepaw on an inclined mesh walking and foot print analysis for stride length and distance between hind feet. TiO2-nanowired oxiracetam also induced marked improvements in the cerebral blood flow, reduction in the BBB breakdown and edema formation as well as neuroprotection of neuronal, glial and myelin damages caused by CHI at light and electron microscopy on the 7th day after 5 days TiO2 oxiracetam treatment. Adverse biochemical events such as upregulation of CSF nitrite and nitrate, IL-6, TNF-a and p-Tau are also reduced significantly in oxiracetam treated CHI group. On the other hand post treatment of 100mg/kg dose of normal oxiracetam in identical conditions after CHI is needed to show slight but significant neuroprotection together with mild recovery of memory function and functional deficits on the 8th day. These observations are the first to point out that nanowired delivery of oxiracetam has superior neuroprotective ability in CHI. These results indicate a promising clinical future of TiO2 oxiracetam in treating CHI patients for better quality of life and neurorehabilitation, not reported earlier.

Novel Variants in the CLCN1, RYR2, and DCTN1 Found in Elderly Japanese Dementia Patients: A Case Series

Dementia has an enormous impact on medical and financial resources in aging societies like Japan. Diagnosis of dementia can be made by physical and mental examinations, imaging tests, and findings of high abnormal proteins in cerebrospinal fluids. In addition, genetic tests can be performed in neurodegenerative diseases such as Alzheimer’s disease (AD), frontotemporal dementia (FTD), and Parkinson’s disease (PD). In this case series, we presented three cases of dementia with unknown causes who carry novel variants in the genes associated with neurodegenerative diseases. Three patients (Patients 1, 2, and 6) were found by screening 18 dementia patients using a gene panel including 63 genes. The age of onset for Patient 1 was 74 years old, and his father had PD and mother had AD. The age of onset for Patient 2 was 75 years old, and her mother had AD. The age of onset for Patient 6 was 83 years old, and her father, two sisters, and daughter had dementia. The Mini-Mental State Examination produced results of 20, 15, and 22, respectively. The suspected diagnosis by neurological examinations and imaging studies for Patients 1 and 2 was AD, and for Patient 6 was FTD. Patient 1 was treated with donepezil; Patient 2 was treated with donepezil and memantine; and Patient 6 was treated with donepezil, galantamine, and rivastigmine. The three rare variants identified were: CLCN1, encoding a chloride channel, c.2848G>A:p.Glu950Lys (Patient 1); RYR2, encoding a calcium releasing ryanodine receptor, c.13175A>G:p.Lys4392Arg (Patient 2); and DCTN1, encoding a subunit of dynactin, c. 3209G>A:p.Arg1070Gln (Patient 6). The detected variants were interpreted according to the American College of Medical Genetics (ACMG) guidelines. The minor allele frequency for each variant was 0.025%, 0.023%, and 0.0004% in East Asians, respectively. The DCTN1 variant found in Patient 6 might be associated with FTD. Although none of them were previously reported in dementia patients, all variants were classified as variants of unknown significance (VUS). Our report suggests that results of genetic tests in elderly patients with dementia need to be carefully interpreted. Further data accumulation of genotype–phenotype relationships and development of appropriate functional models are warranted.

Inhibitor Kappa B Kinase β, Modulated by DJ-1/p-VHL, Reduces Phosphorylated Tau (p-Tau) Accumulation via Autophagy in Alzheimer's Disease Model

It has been demonstrated Inhibitor Kappa B Kinase β (IKKβ) facilitates autophagy, which in turn mediates p-Tau protein clearance. However, the specific regulatory mechanism in Alzheimer's disease (AD) remains unclear. Firstly, AD model was generated by the intracerebroventricular (ICV) injection of the Β-amyloid 1-42 (Aβ_1-42) peptide. Subsequently, mice were injected with shRNA adenoviral transduction particles designed to target DJ-1 or Aβ_1-42 or Aβ_1-42 + shNC or Aβ_1-42 + shRNA against DJ-1. shRNA against DJ-1 were injected into hippocampus of mice (8 × 10⁴ viral particles for each mice) for seven consecutive days. Immunohistochemistry was performed to detect the accumulation of Aβ in the hippocampus of mice, and Hematoxylin-Eosin (HE) staining assay was carried to detect pathological changes in the hippocampus of mice. Further, sh-IKKβ, shDJ-1, pcDNA-IKKβ and pcDNA-DJ-1 plasmids were transfected into HT-22 cells, MTT assay, TUNEL staining and Hoechst staining were performed to detect cell viability and apoptosis, respectively. Western blotting was carried to measure the relative expression of proteins. Findings indicated that Aβ_1-42 inhibited autophagy and up-regulated p-Tau protein expression; Overexpression of IKKβ and DJ-1 all rescued the autophagy inhibited by Aβ_1-42 and down-regulated p-Tau protein expression induced by Aβ_1-42; DJ-1 up-regulated IKKβ via p-VHL, further promoted autophagy and reduced the expression of p-Tau protein; DJ-1 knockdown inhibited autophagy and up-regulated p-Tau protein expression, resulting in delayed behavior in mice. In conclusion, IKKβ, modulated by DJ-1/p-VHL, reduces p-Tau accumulation via autophagy in AD's disease model. This study may provide theoretical basis for the treatment of AD.

Environment and Gene Association With Obesity and Their Impact on Neurodegenerative and Neurodevelopmental Diseases

Obesity is a multifactorial disease in which environmental conditions and several genes play an important role in the development of this disease. Obesity is associated with neurodegenerative diseases (Alzheimer, Parkinson, and Huntington diseases) and with neurodevelopmental diseases (autism disorder, schizophrenia, and fragile X syndrome). Some of the environmental conditions that lead to obesity are physical activity, alcohol consumption, socioeconomic status, parent feeding behavior, and diet. Interestingly, some of these environmental conditions are shared with neurodegenerative and neurodevelopmental diseases. Obesity impairs neurodevelopment abilities as memory and fine-motor skills. Moreover, maternal obesity affects the cognitive function and mental health of the offspring. The common biological mechanisms involved in obesity and neurodegenerative/neurodevelopmental diseases are insulin resistance, pro-inflammatory cytokines, and oxidative damage, among others, leading to impaired brain development or cell death. Obesogenic environmental conditions are not the only factors that influence neurodegenerative and neurodevelopmental diseases. In fact, several genes implicated in the leptin–melanocortin pathway (LEP, LEPR, POMC, BDNF, MC4R, PCSK1, SIM1, BDNF, TrkB, etc.) are associated with obesity and neurodegenerative and neurodevelopmental diseases. Moreover, in the last decades, the discovery of new genes associated with obesity (FTO, NRXN3, NPC1, NEGR1, MTCH2, GNPDA2, among others) and with neurodegenerative or neurodevelopmental diseases (APOE, CD38, SIRT1, TNFα, PAI-1, TREM2, SYT4, FMR1, TET3, among others) had opened new pathways to comprehend the common mechanisms involved in these diseases. In conclusion, the obesogenic environmental conditions, the genes, and the interaction gene–environment would lead to a better understanding of the etiology of these diseases.

A novel variant c.3706C>T p.(Avg 1236Cys) in the ABCA7 gene in a Saudi patient with susceptibility to Alzheimer's disease 9

Alzheimer's disease (AD) is the most common cause of dementia with around 50 million people suffering from this disease worldwide. Mutations in the ATP-binding cassette sub-family A member 7 (ABCA7) have been reported to cause susceptibility to AD 9 (OMIM #608907). In this study, we report a novel variant in ABCA7 in a Saudi patient with susceptibility to AD 9 and a strong family history of neurodegenerative disorders, which may be explained by the same variant. We studied a single 57-year-old female patient with typical symptoms of AD supported by MRI findings from a Saudi family with a positive history of a similar disease in multiple individuals. The case study was conducted in King Abdulaziz Medical City in Jeddah, Saudi Arabia. Whole-exome sequencing identified the novel heterozygous variant c.3706C>T p.(Avg 1236Cys) in the ABCA7 gene, which leads to an amino acid exchange. Furthermore, bioinformatics in silico programs predict a pathogenic effect for this variant. To the best of our knowledge, the variant has not been described in the literature so far as evidenced by a thorough literature review using multiple databases such as Ovid, Medline, EMBASE, ProQuest, Science Direct, Google Scholar, and PubMed. In this article, we reported a middle-aged Saudi woman with a novel variant in ABCA7 who had clinical features of both AD and Parkinson's disease. Given the reported function of this gene, it is most likely that it is etiological and pathological because of the presenting complex neurological disease due to decreased clearance of β-amyloid and α-Synuclein. We illustrate the importance of this interesting gene that could be implicated in several neurodegenerative disorders.

Inhibition of NF-κB might enhance the protective role of roflupram on SH-SY5Y cells under amyloid β stimulation via PI3K/AKT/mTOR signaling pathway

Alzheimer disease (AD) is a progressive neurodegenerative disease and mostly endanger the health of people older than 65 years. Accumulation of beta amyloid protein (Aβ) is the main characteristic of AD. Roflupram (ROF) could improve the behavior of AD in a mouse model. In this study, we first detected the increased concentration of molecules related to inflammatory response in serum sample of patients with AD. Next, a cell model of nuclear factor kappa B (NF-κB) inhibition and NF-κB overexpression was established in SH-SY5Y cells, Aβ was used to simulate the toxicity to cells. ROF treatment decreased expression of apoptosis-related molecules via inhibition of PI3K/AKT/mTOR signaling pathway, decreased expression of pro-inflammatory factors, and increased expression of key enzymes in the tricarboxylic acid (TCA) cycle was observed in SH-SY5Y cells after ROF treatment. Inhibition of NF-κB could enlarge these trends whereas overexpression of NF-κB could reduce these trends.

Correlation Between SIRT2 3'UTR Gene Polymorphism and the Susceptibility to Alzheimer's Disease

The purpose of this study is to investigate the correlation between single-nucleotide polymorphism (SNP) at the 3' end of the untranslated region (UTR) of Sirtuin 2 (SIRT2) gene and the risk of developing Alzheimer's disease (AD), and to explore its underlying mechanisms. In total, 260 patients with AD and 260 healthy controls were recruited in this study. The genotype of rs2015 and rs2241703 loci of the SIRT2 gene was analyzed by Sanger sequencing for all participants. Quantitative real-time Polymerase chain reaction (qRT-PCR) was used to analyze microRNAs (miRNAs) and SIRT2 mRNA levels. Western blotting was used to analyze the expression level of SIRT2 protein. The dual luciferase reporter gene assay and cell transfection were performed to examine the role of miRNAs in regulating SIRT2 expression. Carriers of the SIRT2 gene rs2015 locus A allele were 0.69 times less likely to develop AD than the carriers of the C allele (95% confidence interval (CI): 0.59-0.80, p < 0.01). The carriers of the SIRT2 gene rs2241703 locus A allele were 1.43 times more likely to develop AD than the carriers of the G allele (95% CI: 1.23-1.61, p < 0.01). The rs2015 locus single-nucleotide polymorphism (SNP) affected the binding efficiency between miR-376a-5p and miR-8061 and the 3'UTR of the SIRT2 gene, and miR-376a-5p and miR-8061 bound to SIRT2 rs2015 A allele to down-regulate the expression of the SIRT2 protein. The rs2241703 SNP affected the binding efficiency between miR-486-3p and the 3'UTR of SIRT2 gene, and miR-486-3p bound to SIRT2 rs2241703 A allele to down-regulate SIRT2 protein expression. The SIRT2 gene rs2015 and rs2241703 loci SNPs are associated with the risk of AD. The rs2015 locus SNP affects regulation of miR-376a-5p and miR-8061 in SIRT2 expression and the rs2241703 locus SNP affects regulation of miR-486-3p in SIRT2, but further studies are needed to verify this mechanism.

Specific Signatures of Serum miRNAs as Potential Biomarkers to Discriminate Clinically Similar Neurodegenerative and Vascular-Related Diseases

Neurodegenerative diseases (NDs) are age-dependent; among them, Alzheimer's disease (AD) and Parkinson's disease (PD) are the most frequent. Similarly, cerebrovascular damage can induce the development of vascular-related disorders that share common features with AD and PD, respectively, named vascular dementia (VD) and vascular parkinsonism (VP). To date, ND diagnosis is mainly clinical; therefore, since these disorders show similar symptoms, their correct discrimination may be difficult. We detected 23 ND-associated microRNAs (miRNAs) by literature mining and investigated their serum expression in a cohort of 139 patients including AD, PD, VD, and VP patients and healthy controls. TaqMan RT-PCR data showed that miR-23a upregulation was associated with an ongoing neurodegenerative process, similar to miR-22* and miR-29a, while let-7d, miR-15b, miR-24, miR-142-3p, miR-181c, and miR-222 showed an altered expression in Parkinson-like phenotypes, as well as miR-34b, miR-125b, and miR-130b in Alzheimer-like disorders. By computing logistic regression models and ROC curves, we identified signatures of neuro-miRNAs specific for each disease, showing good diagnostic performance. Interestingly, we found that miR-23a, miR-29a, miR-34b, and miR-125b exhibited a different distribution between exosomes and vesicle-free serum, suggesting a heterogeneity of secretion for these miRNAs. Our results suggest that miRNA signatures could discriminate in a non-invasive manner neurodegenerative disorders, thus improving clinical diagnoses.

A Chemometric Approach Toward Predicting the Relative Aggregation Propensity: Aβ(1-42)

A number of algorithms have been developed to predict the aggregation propensity of peptides and proteins, but virtually none have the ability to provide sequence-specific information on what physicochemical properties are most important in altering aggregation propensity. In this study, a chemometric approach using reduced amino acid properties is used to examine the aggregation behavior of a highly amyloidogenic peptide, Aβ(1-42). Specific residues are identified as being critical to the aggregation process. At each of these positions, the important physicochemical properties are identified that would either accelerate or inhibit fibril formation.

Voxel-wise analysis of 18F-fluorodeoxyglucose metabolism in correlation with variations in the presentation of Alzheimer’s disease: a clinician’s guide

BACKGROUND Diagnostic imaging can be applied in the management of Alzheimer’s disease as it provides structural and functional information to exclude possible secondary causes and offers additional information, especially in atypical cases of Alzheimer’s disease. The utility of positron emission tomography/computed tomography (PET/CT) can help in the noninvasive diagnosis of Alzheimer’s disease by voxel-wise quantification of cerebral 18F-fluorodeoxyglucose (FDG) metabolism.  METHODS This prospective study was conducted among 10 subjects with Alzheimer’s disease and 10 healthy control subjects who underwent neuropsychological testing and 18F-FDG PET/CT scans. Images of the brain were postprocessed using voxel-wise analysis and segmented into 20 regions of interest. The standardized uptake value (SUV)max/SUVmean/standard deviation of SUVmean results were analyzed accordingly and correlated with the subjects’ Montreal cognitive assessment (MoCA) results that were adjusted for age and education level.  RESULTS Hypometabolism at the right parietal lobe significantly correlated with increasing age and lower MoCA scores. Global hypometabolism was observed in subjects who had advanced Alzheimer’s disease but preserved primary somatosensory cortices (S1) region metabolism. Predominance of frontal lobe hypometabolism was a feature of subjects with Alzheimer’s disease having associated depressive symptoms.  CONCLUSIONS 18F-FDG PET/CT voxel-wise analysis can be used for quantitative assessment and can assist clinicians in the diagnosis of Alzheimer’s disease and other variations of the disease spectrum.

Integrated identification of key genes and pathways in Alzheimer's disease via comprehensive bioinformatical analyses

Background

Alzheimer's disease (AD) is known to be caused by multiple factors, meanwhile the pathogenic mechanism and development of AD associate closely with genetic factors. Existing understanding of the molecular mechanisms underlying AD remains incomplete.

Methods

Gene expression data (GSE48350) derived from post-modern brain was extracted from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were derived from hippocampus and entorhinal cortex regions between AD patients and healthy controls and detected via Morpheus. Functional enrichment analyses, including Gene Ontology (GO) and pathway analyses of DEGs, were performed via Cytoscape and followed by the construction of protein-protein interaction (PPI) network. Hub proteins were screened using the criteria: nodes degree≥10 (for hippocampus tissues) and ≥ 8 (for entorhinal cortex tissues). Molecular Complex Detection (MCODE) was used to filtrate the important clusters. University of California Santa Cruz (UCSC) and the database of RNA-binding protein specificities (RBPDB) were employed to identify the RNA-binding proteins of the long non-coding RNA (lncRNA).

Results

251 & 74 genes were identified as DEGs, which consisted of 56 & 16 up-regulated genes and 195 & 58 down-regulated genes in hippocampus and entorhinal cortex, respectively. Biological analyses demonstrated that the biological processes and pathways related to memory, transmembrane transport, synaptic transmission, neuron survival, drug metabolism, ion homeostasis and signal transduction were enriched in these genes. 11 genes were identified as hub genes in hippocampus and entorhinal cortex, and 3 hub genes were identified as the novel candidates involved in the pathology of AD. Furthermore, 3 lncRNAs were filtrated, whose binding proteins were closely associated with AD.

Conclusions

Through GO enrichment analyses, pathway analyses and PPI analyses, we showed a comprehensive interpretation of the pathogenesis of AD at a systematic biology level, and 3 novel candidate genes and 3 lncRNAs were identified as novel and potential candidates participating in the pathology of AD. The results of this study could supply integrated insights for understanding the pathogenic mechanism underlying AD and potential novel therapeutic targets.