Distinctive RNA expression profiles in blood associated with Alzheimer disease after accounting for white matter hyperintensities

Meta-Analysis of Transcriptomic Studies of Blood and Six Brain Regions Identifies a Consensus of 15 Cross-Tissue Mechanisms in Alzheimer's Disease and Suggests an Origin of Cross-Study Heterogeneity

The comprehensive genome-wide nature of transcriptome studies in Alzheimer's disease (AD) should provide a reliable description of disease molecular states. However, the genes and molecular systems nominated by transcriptomic studies do not always overlap. Even when results do align, it is not clear if those observations represent true consensus across many studies. A couple of sources of variation have been proposed to explain this variability, including tissue-of-origin and cohort type, but its basis remains uncertain. To address this variability and extract reliable results, we utilized all publicly available blood or brain transcriptomic datasets of AD, comprised of 24 brain studies with 4007 samples from six different brain regions, and eight blood studies with 1566 samples. We identified a consensus of AD-associated genes across brain regions and AD-associated gene-sets across blood and brain, generalizable machine learning and linear scoring classifiers, and significant contributors to biological diversity in AD datasets. While AD-associated genes did not significantly overlap between blood and brain, our findings highlighted 15 dysregulated processes shared across blood and brain in AD. The top five most significantly dysregulated processes were DNA replication, metabolism of proteins, protein localization, cell cycle, and programmed cell death. Conversely, addressing the discord across studies, we found that large-scale gene co-regulation patterns can account for a significant fraction of variability in AD datasets. Overall, this study ranked and characterized a compilation of genes and molecular systems consistently identified across a large assembly of AD transcriptome studies in blood and brain, providing potential candidate biomarkers and therapeutic targets.

Exosomal MicroRNAs modulate the cognitive function in fasudil treated APPswe/PSEN1dE9 transgenic (APP/PS1) mice model of Alzheimer's disease

Alzheimer's disease (AD) is characterized by cognitive decline stemming from the accumulation of beta-amyloid (Aβ) plaques and the propagation of tau pathology through synapses. Exosomes, crucial mediators in neuronal development, maintenance, and intercellular communication, have gained attention in AD research. Yet, the molecular mechanisms involving exosomal miRNAs in AD remain elusive. In this study, we treated APPswe/PSEN1dE9 transgenic (APP/PS1) mice, a model for AD, with either vehicle (ADNS) or fasudil (ADF), while C57BL/6 (control) mice received vehicle (WT). Cognitive function was evaluated using the Y-maze test, and AD pathology was confirmed through immunostaining and western blot analysis of Aβ plaques and phosphorylated tau. Exosomal RNAs were extracted, sequenced, and analyzed from each mouse group. Our findings revealed that fasudil treatment improved cognitive function in AD mice, as evidenced by increased spontaneous alternation in the Y-maze test and reduced Aβ plaque load and phosphorylated tau protein expression in the hippocampus. Analysis of exosomal miRNAs identified three miRNAs (mmu-let-7i-5p, mmu-miR-19a-3p, mmu-miR-451a) common to both ADNS vs ADF and WT vs ADNS groups. Utilizing miRTarBase software, we predicted and analyzed target genes associated with these miRNAs. Gene ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of miRNA target genes indicated that mmu-miR-19a-3p and mmu-miR-451a are implicated in signal transduction, immune response, cellular communication, and nervous system pathways. Specifically, mmu-miR-19a-3p targeted genes involved in the sphingolipid signaling pathway, such as Pten and Tnf, while mmu-miR-451a targeted Nsmaf, Gnai3, and Akt3. Moreover, mmu-miR-451a targeted Myc in signaling pathways regulating the pluripotency of stem cells. In conclusion, fasudil treatment enhanced cognitive function by modulating exosomal MicroRNAs, particularly mmu-miR-451a and mmu-miR-19a-3p. These miRNAs hold promise as potential biomarkers and therapeutic targets for novel AD treatments.

Identification of Immune-Related Biomarkers of Schizophrenia in the Central Nervous System Using Bioinformatic Methods and Machine Learning Algorithms

Schizophrenia is a disastrous mental disorder. Identification of diagnostic biomarkers and therapeutic targets is of significant importance. In this study, five datasets of schizophrenia post-mortem prefrontal cortex samples were downloaded from the GEO database and then merged and de-batched for the analyses of differentially expressed genes (DEGs) and weighted gene co-expression network analysis (WGCNA). The WGCNA analysis showed the six schizophrenia-related modules containing 12,888 genes. The functional enrichment analyses indicated that the DEGs were highly involved in immune-related processes and functions. The immune cell infiltration analysis with the CIBERSORT algorithm revealed 12 types of immune cells that were significantly different between schizophrenia subjects and controls. Additionally, by intersecting DEGs, WGCNA module genes, and an immune gene set obtained from online databases, 151 schizophrenia-associated immune-related genes were obtained. Moreover, machine learning algorithms including LASSO and Random Forest were employed to further screen out 17 signature genes, including GRIN1, P2RX7, CYBB, PTPN4, UBR4, LTF, THBS1, PLXNB3, PLXNB1, PI15, RNF213, CXCL11, IL7, ARHGAP10, TTR, TYROBP, and EIF4A2. Then, SVM-RFE was added, and together with LASSO and Random Forest, a hub gene (EIF4A2) out of the 17 signature genes was revealed. Lastly, in a schizophrenia rat model, the EIF4A2 expression levels were reduced in the model rat brains in a brain-regional dependent manner, but can be reversed by risperidone. In conclusion, by using various bioinformatic and biological methods, this study found 17 immune-related signature genes and a hub gene of schizophrenia that might be potential diagnostic biomarkers and therapeutic targets of schizophrenia.

Dysregulated AEBP1 and COLEC12 Genes in Late-Onset Alzheimer's Disease: Insights from Brain Cortex and Peripheral Blood Analysis

Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by memory and cognitive impairment, often accompanied by alterations in mood, confusion, and, ultimately, a state of acute mental disturbance. The cerebral cortex is considered a promising area for investigating the underlying causes of AD by analyzing transcriptional patterns, which could be complemented by investigating blood samples obtained from patients. We analyzed the RNA expression profiles of three distinct areas of the brain cortex, including the frontal cortex (FC), temporal cortex (TC), and entorhinal cortex (EC) in patients with AD. Functional enrichment analysis was performed on the differentially expressed genes (DEGs) across the three regions. The two genes with the most significant expression changes in the EC region were selected for assessing mRNA expression levels in the peripheral blood of late-onset AD patients using quantitative PCR (qPCR). We identified eight shared DEGs in these regions, including AEBP1 and COLEC12, which exhibited prominent changes in expression. Functional enrichment analysis uncovered a significant association of these DEGs with the transforming growth factor-β (TGF-β) signaling pathway and processes related to angiogenesis. Importantly, we established a robust connection between the up-regulation of AEBP1 and COLEC12 in both the brain and peripheral blood. Furthermore, we have demonstrated the potential of AEBP1 and COLEC12 genes as effective diagnostic tools for distinguishing between late-onset AD patients and healthy controls. This study unveils the intricate interplay between AEBP1 and COLEC12 in AD and underscores their potential as markers for disease detection and monitoring.

Gene expression patterns of CRYM and SIGLEC10 in Alzheimer's disease: potential early diagnostic indicators

BACKGROUND

Alzheimer's disease (AD) is a neurological condition that may lead to dementia as well as a slow and steady decline in cognitive ability. Finding early signs that may be used in the diagnosis of AD is still a difficult aim to achieve in the field of medical practice.

METHODS AND RESULTS

The purpose of this research was to investigate to determine any differences in the gene expression patterns of crystallin mu (CRYM) and sialic acid-binding immunoglobulin-like lectin 10 (SIGLEC10) in whole blood samples obtained from fifty individuals who were diagnosed with AD and fifty individuals as a control group. When compared with controls, it was discovered that the expression of the CRYM gene was substantially decreased in AD patients, but the expression of the SIGLEC10 gene was significantly higher. A positive correlation between CRYM and SIGLEC10 was noticed solely in patients with AD. Furthermore, assessing the diagnostic value of these genes, CRYM and SIGLEC10 transcript levels displayed an area under the curve (AUC) of 0.74 and 0.81, respectively.

CONCLUSIONS

These results suggest that alterations in CRYM and SIGLEC10 expression may be implicated in AD pathology and that these genes expression levels can potentially serve as biomarkers for early detection and diagnosis of AD. Nevertheless, further validation of these findings requires the inclusion of more extensive and heterogeneous cohorts. The findings derived from this study possess the capability to offer a significant contribution towards the progression of innovative diagnostic and therapeutic strategies for AD.

Identification of Novel Biomarkers for Alzheimer's Disease and Related Dementias Using Unbiased Plasma Proteomics

Alzheimer's disease (AD) and related dementias (ADRD) is a complex disease with multiple pathophysiological drivers that determine clinical symptomology and disease progression. These diseases develop insidiously over time, through many pathways and disease mechanisms and continue to have a huge societal impact for affected individuals and their families. While emerging blood-based biomarkers, such as plasma p-tau181 and p-tau217, accurately detect Alzheimer neuropthology and are associated with faster cognitive decline, the full extension of plasma proteomic changes in ADRD remains unknown. Earlier detection and better classification of the different subtypes may provide opportunities for earlier, more targeted interventions, and perhaps a higher likelihood of successful therapeutic development. In this study, we aim to leverage unbiased mass spectrometry proteomics to identify novel, blood-based biomarkers associated with cognitive decline. 1,786 plasma samples from 1,005 patients were collected over 12 years from partcipants in the Massachusetts Alzheimer's Disease Research Center Longitudinal Cohort Study. Patient metadata includes demographics, final diagnoses, and clinical dementia rating (CDR) scores taken concurrently. The Proteograph™ Product Suite (Seer, Inc.) and liquid-chromatography mass-spectrometry (LC-MS) analysis were used to process the plasma samples in this cohort and generate unbiased proteomics data. Data-independent acquisition (DIA) mass spectrometry results yielded 36,259 peptides and 4,007 protein groups. Linear mixed effects models revealed 138 differentially abundant proteins between AD and healthy controls. Machine learning classification models for AD diagnosis identified potential candidate biomarkers including MBP, BGLAP, and APoD. Cox regression models were created to determine the association of proteins with disease progression and suggest CLNS1A, CRISPLD2, and GOLPH3 as targets of further investigation as potential biomarkers. The Proteograph workflow provided deep, unbiased coverage of the plasma proteome at a speed that enabled a cohort study of almost 1,800 samples, which is the largest, deep, unbiased proteomics study of ADRD conducted to date.

Plasma cell-free RNA profiling of Vietnamese Alzheimer's patients reveals a linkage with chronic inflammation and apoptosis: a pilot study

Introduction

Circulating cell-free RNA (cfRNA) is a potential hallmark for early diagnosis of Alzheimer's Disease (AD) as it construes the genetic expression level, giving insights into the pathological progress from the outset. Profiles of cfRNA in Caucasian AD patients have been investigated thoroughly, yet there was no report exploring cfRNAs in the ASEAN groups. This study examined the gap, expecting to support the development of point-of-care AD diagnosis.

Methods

cfRNA profiles were characterized from 20 Vietnamese plasma samples (10 probable AD and 10 age-matched controls). RNA reads were subjected to differential expression (DE) analysis. Weighted gene correlation network analysis (WGCNA) was performed to identify gene modules that were significantly co-expressed. These modules' expression profiles were then correlated with AD status to identify relevant modules. Genes with the highest intramodular connectivity (module membership) were selected as hub genes. Transcript counts of differentially expressed genes were correlated with key AD measures-MMSE and MTA scores-to identify potential biomarkers.

Results

136 genes were identified as significant AD hallmarks (p < 0.05), with 52 downregulated and 84 upregulated in the AD cohort. 45.6% of these genes are highly expressed in the hippocampus, cerebellum, and cerebral cortex. Notably, all markers related to chronic inflammation were upregulated, and there was a significant shift in all apoptotic markers. Three co-expressed modules were found to be significantly correlated with Alzheimer's status (p < 0.05; R2> 0.5). Functional enrichment analysis on these modules reveals an association with focal adhesion, nucleocytoplasmic transport, and metal ion response leading to apoptosis, suggesting the potential participation of these pathways in AD pathology. 47 significant hub genes were found to be differentially expressed genes with the highest connectivity. Six significant hub genes (CREB1, YTHDC1, IL1RL1, PHACTR2, ANKRD36B, RNF213) were found to be significantly correlated with MTA and MMSE scores. Other significant transcripts (XRN1, UBB, CHP1, THBS1, S100A9) were found to be involved in inflammation and neuronal death. Overall, we have identified candidate transcripts in plasma cf-RNA that are differentially expressed and are implicated in inflammation and apoptosis, which can jumpstart further investigations into applying cf-RNA as an AD biomarker in Vietnam and ASEAN countries.

Serum proteomics reveals APOE dependent and independent protein signatures in Alzheimer's disease

The current demand for early intervention, prevention, and treatment of late onset Alzheimer's disease (LOAD) warrants deeper understanding of the underlying molecular processes which could contribute to biomarker and drug target discovery. Utilizing high-throughput proteomic measurements in serum from a prospective population-based cohort of older adults (n=5,294), we identified 303 unique proteins associated with incident LOAD (median follow-up 12.8 years). Over 40% of these proteins were associated with LOAD independently of APOE-ε4 carrier status. These proteins were implicated in neuronal processes and overlapped with protein signatures of LOAD in brain and cerebrospinal fluid. We found 17 proteins which LOAD-association was strongly dependent on APOE-ε4 carrier status. Most of them showed consistent associations with LOAD in cerebrospinal fluid and a third had brain-specific gene expression. Remarkably, four proteins in this group (TBCA, ARL2, S100A13 and IRF6) were downregulated by APOE-ε4 yet upregulated as a consequence of LOAD as determined in a bi-directional Mendelian randomization analysis, reflecting a potential response to the disease onset. Accordingly, the direct association of these proteins to LOAD was reversed upon APOE-ε4 genotype adjustment, a finding which we replicate in an external cohort (n=719). Our findings provide an insight into the dysregulated pathways that may lead to the development and early detection of LOAD, including those both independent and dependent on APOE-ε4. Importantly, many of the LOAD-associated proteins we find in the circulation have been found to be expressed - and have a direct link with AD - in brain tissue. Thus, the proteins identified here, and their upstream modulating pathways, provide a new source of circulating biomarker and therapeutic target candidates for LOAD.

Identification of TGF-β-related genes in cardiac hypertrophy and heart failure based on single cell RNA sequencing

BACKGROUND

Heart failure (HF) remains a huge medical burden worldwide. Pathological cardiac hypertrophy is one of the most significant phenotypes of HF. Several studies have reported that the TGF-β pathway plays a double-sided role in HF. Therefore, TGF-β-related genes (TRGs) may be potential therapeutic targets for cardiac hypertrophy and HF. However, the roles of TRGs in HF at the single-cell level remain unclear.

METHOD

In this study, to analyze the expression pattern of TRGs during the progress of cardiac hypertrophy and HF, we used three public single-cell RNA sequencing datasets for HF (GSE161470, GSE145154, and GSE161153), one HF transcriptome data (GSE57338), and one hypertrophic cardiomyopathy transcriptome data (GSE141910). Weighted gene co-expression network analysis (WGCNA), functional enrichment analysis and machine learning algorithms were used to filter hub genes. Transverse aortic constriction mice model, CCK-8, wound healing assay, quantitative real-time PCR and western blotting were used to validate bioinformatics results.

RESULTS

We observed that cardiac fibroblasts (CFs) and endothelial cells showed high TGF-β activity during the progress of HF. Three modules (royalblue, brown4, and darkturquoize) were identified to be significantly associated with TRGs in HF. Six hub genes (TANC2, ADAMTS2, DYNLL1, MRC2, EGR1, and OTUD1) showed anomaly trend in cardiac hypertrophy. We further validated the regulation of the TGF-β-MYC-ADAMTS2 axis on CFs activation in vitro.

CONCLUSIONS

This study identified six hub genes (TANC2, ADAMTS2, DYNLL1, MRC2, EGR1, and OTUD1) by integrating scRNA and transcriptome data. These six hub genes might be therapeutic targets for cardiac hypertrophy and HF.

Biomarkers of gut barrier dysfunction in obstructive sleep apnea: A systematic review and meta-analysis

We conducted this systematic review and meta-analysis to evaluate the impact of obstructive sleep apnea (OSA) on gut barrier dysfunction as represented by the following biomarkers: zonulin, lipopolysaccharide, lipopolysaccharide binding protein, intestinal fatty acid binding protein, and lactic acid. A comprehensive search of the literature was conducted in Ovid MEDLINE, Embase, Scopus, Cochrane Central Register of Controlled Trials, and ClinicalTrials.gov without language restrictions from inception to October 2022. The analysis of all outcomes was performed using a random-effects model. We included eight studies (seven cross sectional and one case control) in the final quantitative synthesis with a total of 897 patients. We concluded that OSA was associated with higher levels of gut barrier dysfunction biomarkers [Hedges' g = 0.73 (95%CI 0.37-1.09, p < 0.01). Biomarker levels were positively correlated with the apnea-hypopnea index [r = 0.48 (95%CI 0.35-0.6, p < 0.01)] and oxygen desaturation index [r = 0.30 (95%CI 0.17-0.42, p < 0.01)], and negatively correlated with the nadir oxygen desaturation values [r = -0.45 (95%CI - 0.55 - - 0.32, p < 0.01). Our systematic review and meta-analysis suggests that OSA is associated with gut barrier dysfunction. Furthermore, OSA severity appears to be correlated with higher biomarkers of gut barrier dysfunction. PROSPERO REGISTRATION NUMBER: CRD42022333078.

A family-based study of genetic and epigenetic effects across multiple neurocognitive, motor, social-cognitive and social-behavioral functions

Many psychiatric and neurodevelopmental disorders are known to be heritable, but studies trying to elucidate the genetic architecture of such traits often lag behind studies of somatic traits and diseases. The reasons as to why relatively few genome-wide significant associations have been reported for such traits have to do with the sample sizes needed for the detection of small effects, the difficulty in defining and characterizing the phenotypes, partially due to overlaps in affected underlying domains (which is especially true for cognitive phenotypes), and the complex genetic architectures of the phenotypes, which are not wholly captured in traditional case-control GWAS designs. We aimed to tackle the last two issues by performing GWASs of eight quantitative neurocognitive, motor, social-cognitive and social-behavioral traits, which may be considered endophenotypes for a variety of psychiatric and neurodevelopmental conditions, and for which we employed models capturing both general genetic association and parent-of-origin effects, in a family-based sample comprising 402 children and their parents (mostly family trios). We identified 48 genome-wide significant associations across several traits, of which 3 also survived our strict study-wide quality criteria. We additionally performed a functional annotation of implicated genes, as most of the 48 associations were with variants within protein-coding genes. In total, our study highlighted associations with five genes (TGM3, CACNB4, ANKS1B, CSMD1 and SYNE1) associated with measures of working memory, processing speed and social behavior. Our results thus identify novel associations, including previously unreported parent-of-origin associations with relevant genes, and our top results illustrate new potential gene → endophenotype → disorder pathways.

Finding memo: versatile interactions of the VPS10p-Domain receptors in Alzheimer’s disease

The family of VPS10p-Domain (D) receptors comprises five members named SorLA, Sortilin, SorCS1, SorCS2 and SorCS3. While their physiological roles remain incompletely resolved, they have been recognized for their signaling engagements and trafficking abilities, navigating a number of molecules between endosome, Golgi compartments, and the cell surface. Strikingly, recent studies connected all the VPS10p-D receptors to Alzheimer’s disease (AD) development. In addition, they have been also associated with diseases comorbid with AD such as diabetes mellitus and major depressive disorder. This systematic review elaborates on genetic, functional, and mechanistic insights into how dysfunction in VPS10p-D receptors may contribute to AD etiology, AD onset diversity, and AD comorbidities. Starting with their functions in controlling cellular trafficking of amyloid precursor protein and the metabolism of the amyloid beta peptide, we present and exemplify how these receptors, despite being structurally similar, regulate various and distinct cellular events involved in AD. This includes a plethora of signaling crosstalks that impact on neuronal survival, neuronal wiring, neuronal polarity, and synaptic plasticity. Signaling activities of the VPS10p-D receptors are especially linked, but not limited to, the regulation of neuronal fitness and apoptosis via their physical interaction with pro- and mature neurotrophins and their receptors. By compiling the functional versatility of VPS10p-D receptors and their interactions with AD-related pathways, we aim to further propel the AD research towards VPS10p-D receptor family, knowledge that may lead to new diagnostic markers and therapeutic strategies for AD patients.

Screening of Crucial Differentially-Methylated/Expressed Genes for Alzheimer's Disease

Background: We aimed to make an integrated analysis of published transcriptome and DNA methylation dataset to ascertain the key differentially methylated and differentially expressed genes for Alzherimer's disease (AD). Methods: Two gene expression microarrays and 1 gene methylation microarray were downloaded for identification of differentially expressed genes and differentially methylated genes. Then, we used various biological information databases to annotate the functions of the differentially-methylated/expressed genes, and screen out key genes and important signaling pathways. Finally, we validate the differentially-methylated/expressed genes in the additional online datasets and in blood from AD patients.Results: A total of 8 hub hypomethylated-high expression genes were obtained, including Rac family small GTPase 2, FGR proto-oncogene, Src family tyrosine kinase, LYN proto-oncogene, Src family tyrosine kinase, protein kinase C delta, myosin IF, integrin subunit alpha 5, semaphorin 4D, and growth arrest specific protein 7. Some enriched signaling pathways of hypomethylated-high expression genes were identified, including regulation of actin cytoskeleton, chemokine signaling pathway, Fc gamma R-mediated phagocytosis, and axon guidance. Conclusion: Differentially-methylated/expressed genes are likely to be associated with AD.

Rare variants in the endocytic pathway are associated with Alzheimer's disease, its related phenotypes, and functional consequences

Late-onset Alzheimer's disease (LOAD) is the most common type of dementia causing irreversible brain damage to the elderly and presents a major public health challenge. Clinical research and genome-wide association studies have suggested a potential contribution of the endocytic pathway to AD, with an emphasis on common loci. However, the contribution of rare variants in this pathway to AD has not been thoroughly investigated. In this study, we focused on the effect of rare variants on AD by first applying a rare-variant gene-set burden analysis using genes in the endocytic pathway on over 3,000 individuals with European ancestry from three large whole-genome sequencing (WGS) studies. We identified significant associations of rare-variant burden within the endocytic pathway with AD, which were successfully replicated in independent datasets. We further demonstrated that this endocytic rare-variant enrichment is associated with neurofibrillary tangles (NFTs) and age-related phenotypes, increasing the risk of obtaining severer brain damage, earlier age-at-onset, and earlier age-of-death. Next, by aggregating rare variants within each gene, we sought to identify single endocytic genes associated with AD and NFTs. Careful examination using NFTs revealed one significantly associated gene, ANKRD13D. To identify functional associations, we integrated bulk RNA-Seq data from over 600 brain tissues and found two endocytic expression genes (eGenes), HLA-A and SLC26A7, that displayed significant influences on their gene expressions. Differential expressions between AD patients and controls of these three identified genes were further examined by incorporating scRNA-Seq data from 48 post-mortem brain samples and demonstrated distinct expression patterns across cell types. Taken together, our results demonstrated strong rare-variant effect in the endocytic pathway on AD risk and progression and functional effect of gene expression alteration in both bulk and single-cell resolution, which may bring more insight and serve as valuable resources for future AD genetic studies, clinical research, and therapeutic targeting.

Inflammatory gene expression profiling in peripheral blood from patients with Alzheimer's disease reveals key pathways and hub genes with potential diagnostic utility: a preliminary study

BACKGROUND

Alzheimer's disease (AD) is an age-related neurodegenerative disease caused by central nervous system disorders. Late-onset Alzheimer disease (LOAD) is the most common neurodegenerative disorder worldwide. Differences at the expression level of certain genes, resulting from either genetic variations or environmental interactions, might be one of the mechanisms underlying differential risks for developing AD. Peripheral blood genome transcriptional profiling may provide a powerful and minimally invasive tool for the identification of novel targets beyond Aβ and tau for AD research.

METHODS

This preliminary study explores molecular pathogenesis of LOAD-related inflammation through next generation sequencing, to assess RNA expression profiles in peripheral blood from five patients with LOAD and 10 healthy controls.

RESULTS

The analysis of RNA expression profiles revealed 94 genes up-regulated and 147 down-regulated. Gene function analysis, including Gene Ontology (GO) and KOBAS-Kyoto Encyclopedia of DEGs and Genomes (KEGG) pathways indicated upregulation of interferon family (INF) signaling, while the down-regulated genes were mainly associated with the cell cycle process. KEGG metabolic pathways mapping showed gene expression alterations in the signaling pathways of JAK/STAT, chemokines, MAP kinases and Alzheimer disease. The results of this preliminary study provided not only a comprehensive picture of gene expression, but also the key processes associated with pathology for the regulation of neuroinflammation, to improve the current mechanisms to treat LOAD.

RNF213 p.R4810K (c.14429G > A) Variant Determines Anatomical Variations of the Circle of Willis in Cerebrovascular Disease

Introduction

Dysregulation of the RING finger protein 213 (RNF213) gene impairs vascular formation in experimental animal models. In addition, vascular abnormalities in the circle of Willis are associated with cerebrovascular disease. Here, we evaluated the relationship between the East Asian founder variant RNF213 p.R4810K and consequent anatomical variations in the circle of Willis in cerebrovascular disease.

Patients and Methods

The present study is an observational cross-sectional study. It included patients with acute anterior circulation non-cardioembolic stroke admitted to our institution within 7 days of symptom onset or last-known-well from 2011 to 2019, and those who participated in the National Cerebral and Cardiovascular Center Biobank. We compared anatomical variations of the vessels constituting the circle of Willis between RNF213 p.R4810K (c.14429G > A) variant carriers and non-carriers using magnetic resonance angiography and assessed the association between the variants and the presence of the vessels constituting the circle of Willis. Patients with moyamoya disease were excluded.

Results

Four hundred eighty-one patients [146 women (30%); median age 70 years; median baseline National Institutes of Health Stroke Scale score 5] were analyzed. The RNF213 p.R4810K variant carriers (n = 25) were more likely to have both posterior communicating arteries (PComAs) than the variant non-carriers (n = 456) (56% vs. 13%, P < 0.01). Furthermore, variant carriers were less likely to have an anterior communicating artery (AComA) than non-carriers (68% vs. 84%, P = 0.04). In a multivariate logistic regression analysis, the association of RNF213 p.R4810K variant carriers with the presence of both PComAs and the absence of AComA remained significant.

Conclusion

Our findings suggest that the RNF213 p.R4810K variant is an important factor in determining anatomical variations in the circle of Willis.

Detecting adaptive introgression in human evolution using convolutional neural networks

Studies in a variety of species have shown evidence for positively selected variants introduced into a population via introgression from another, distantly related population—a process known as adaptive introgression. However, there are few explicit frameworks for jointly modelling introgression and positive selection, in order to detect these variants using genomic sequence data. Here, we develop an approach based on convolutional neural networks (CNNs). CNNs do not require the specification of an analytical model of allele frequency dynamics and have outperformed alternative methods for classification and parameter estimation tasks in various areas of population genetics. Thus, they are potentially well suited to the identification of adaptive introgression. Using simulations, we trained CNNs on genotype matrices derived from genomes sampled from the donor population, the recipient population and a related non-introgressed population, in order to distinguish regions of the genome evolving under adaptive introgression from those evolving neutrally or experiencing selective sweeps. Our CNN architecture exhibits 95% accuracy on simulated data, even when the genomes are unphased, and accuracy decreases only moderately in the presence of heterosis. As a proof of concept, we applied our trained CNNs to human genomic datasets—both phased and unphased—to detect candidates for adaptive introgression that shaped our evolutionary history.

Non-coding variants in MYH11, FZD3, and SORCS3 are associated with dementia in women

INTRODUCTION

Recent studies suggest that both sex-specific genetic risk factors and those shared between dementia and stroke are involved in dementia pathogenesis.

METHODS

We performed both single-variant and gene-based genome-wide association studies of >11,000 whole genome sequences from the Women's Health Initiative cohort to discover loci associated with dementia, with adjustment for age, ethnicity, stroke, and venous thromboembolism status. Evidence for prior evidence of association and differential gene expression in dementia-related tissues and samples was gathered for each locus.

RESULTS

Our multiethnic studies identified significant associations between variants within APOE, MYH11, FZD3, SORCS3, and GOLGA8B and risk of dementia. Ten genes implicated by these loci, including MYH11, FZD3, SORCS3, and GOLGA8B, were differentially expressed in the context of Alzheimer's disease.

DISCUSSION

Our association of MYH11, FZD3, SORCS3, and GOLGA8B with dementia is supported by independent functional studies in human subjects, model systems, and associations with shared risk factors for stroke and dementia.

Evaluation of Peripheral Immune Dysregulation in Alzheimer's Disease and Vascular Dementia

Immune dysregulation has been observed in the brain and blood of patients with Alzheimer's disease (AD). However, a convenient assay to evaluate peripheral immune dysregulation in AD has not been developed, partly due to the inconsistent observations from different studies. We hypothesized that peripheral immune dysregulation may only exist in a subpopulation of AD patients; therefore it may be valuable to identify this subpopulation with a convenient assay. Along this line, we selected 14 candidate genes based on our analysis of microarray data on peripheral blood of AD and other diseases. We used RT-qPCR to examine the expression of these 14 genes in a cohort of 288 subjects, including 74 patients with AD, 64 patients with mild cognitive impairment (MCI), 51 patients with vascular dementia (VaD), and 99 elderly controls with no cognitive dysfunction/impairment. Seven of these 14 genes displayed significant difference in group comparison. Switching from group comparison to individualized evaluation revealed more in-depth information. First, there existed a wide dynamic range for the expression of these immune genes in peripheral blood even within the control group. Second, for the vast majority of the patients (AD, VaD, and MCI patients), the expression of these genes fell within the dynamic range of the control group. Third, a small portion of outliers were observed in the patient groups, more so in the VaD group than that in the AD or MCI groups. This is our first attempt to conduct personalized evaluation of peripheral immune dysregulation in AD and VaD. These findings may be applicable to the identification of peripheral immune dysregulation in AD and VaD patients which may lead to tailored treatment toward those patients.

Immune and Inflammatory Pathways Implicated by Whole Blood Transcriptomic Analysis in a Diverse Ancestry Alzheimer's Disease Cohort

BACKGROUND

Significant work has identified genetic variants conferring risk and protection for Alzheimer's disease (AD), but functional effects of these variants is lacking, particularly in under-represented ancestral populations. Expression studies performed in easily accessible tissue, such as whole blood, can recapitulate some transcriptional changes occurring in brain and help to identify mechanisms underlying neurodegenerative processes.

OBJECTIVE

We aimed to identify transcriptional differences between AD cases and controls in a cohort of diverse ancestry.

METHODS

We analyzed the protein coding transcriptome using RNA sequencing from peripheral blood collected from 234 African American (AA) (115 AD, 119 controls) and 240 non-Hispanic Whites (NHW) (121 AD, 119 controls). To identify case-control differentially expressed genes and pathways, we performed stratified, joint, and interaction analyses using linear regression models within and across ancestral groups followed by pathway and gene set enrichment analyses.

RESULTS

Overall, we identified 418 (291 upregulated, 127 downregulated) and 488 genes (352 upregulated, 136 downregulated) differentially expressed in the AA and NHW datasets, respectively, with only 16 genes commonly differentially expressed in both ancestral groups. Joint analyses provided greater power to detect case-control differences and identified 1,102 differentially expressed genes between cases and controls (812 upregulated, 290 downregulated). Interaction analysis identified only 27 genes with different effects in AA compared to NHW. Pathway and gene-set enrichment analyses revealed differences in immune response-related pathways that were enriched across the analyses despite different underlying gene sets.

CONCLUSION

These results support the hypothesis of converging underlying pathophysiological processes in AD across ancestral groups.

Predicting Clinical Dementia Rating Using Blood RNA Levels

The Clinical Dementia Rating (CDR) is commonly used to assess cognitive decline in Alzheimer's disease patients and is included in the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset. We divided 741 ADNI participants with blood microarray data into three groups based on their most recent CDR assessment: cognitive normal (CDR = 0), mild cognitive impairment (CDR = 0.5), and probable Alzheimer's disease (CDR ≥ 1.0). We then used machine learning to predict cognitive status using only blood RNA levels. Only one probe for chloride intracellular channel 1 (CLIC1) was significant after correction. However, by combining individually nonsignificant probes with p-values less than 0.1, we averaged 87.87% (s = 1.02) predictive accuracy for classifying the three groups, compared to a 55.46% baseline for this study due to unequal group sizes. The best model had an overall precision of 0.902, recall of 0.895, and a receiver operating characteristic (ROC) curve area of 0.904. Although we identified one significant probe in CLIC1, CLIC1 levels alone were not sufficient to predict dementia status and cannot be used alone in a clinical setting. Additional analyses combining individually suggestive, but nonsignificant, blood RNA levels were significantly predictive and may improve diagnostic accuracy for Alzheimer's disease. Therefore, we propose that patient features that do not individually predict cognitive status might still contribute to overall cognitive decline through interactions that can be elucidated through machine learning.

Indole Compound NC009-1 Augments APOE and TRKA in Alzheimer's Disease Cell and Mouse Models for Neuroprotection and Cognitive Improvement

Alzheimer's disease (AD), associated with abnormal accumulation of amyloid-β (Aβ), is the most common cause of dementia among older people. A few studies have identified substantial AD biomarkers in blood but their results were inconsistent. Here we screened gene expression alterations on Aβ-GFP SH-SY5Y neuronal model for AD, and evaluated the findings on peripheral leukocytes from 78 patients with AD and 56 healthy controls. The therapeutic responses of identified biomarker candidates were further examined in Aβ-GFP SH-SY5Y neuronal and APP/PS1/Tau triple transgenic (3×Tg-AD) mouse models. Downregulation of apolipoprotein E (APOE) and tropomyosin receptor kinase A (TRKA) were detected in Aβ-GFP SH-SY5Y cells and validated by peripheral leukocytes from AD patients. Treatment with an in-house indole compound NC009-1 upregulated the expression of APOE and TRKA accompanied with improvement of neurite outgrowth in Aβ-GFP SH-SY5Y cells. NC009-1 further rescued the downregulated APOE and TRKA and reduced Aβ and tau levels in hippocampus and cortex, and ameliorated cognitive deficits in streptozocin-induced hyperglycemic 3×Tg-AD mice. These results suggest the role of APOE and TRKA as potential peripheral biomarkers in AD, and offer a new drug development target of AD treatment. Further studies of a large series of AD patients will be warranted to verify the findings and confirm the correlation between these markers and therapeutic efficacy.

RNF213 suppresses carcinogenesis in glioblastoma by affecting MAPK/JNK signaling pathway

PURPOSE

Glioblastoma is the most common malignant brain tumor in central nervous system. Due to absence of the mechanism underlying glioblastoma, the clinical outcome is poor. RNF213 is a ring finger protein and mutation in RNF213 gene is detected in cancers. But the role of RNF213 in glioblastoma is unknown.

METHODS

RNF213 expression was detected by qPCR, western blotting, IHC technology. RNF213 was overexpressed in plasmid pcDNA3.1. Assays including CCK-8, plate colony formation, wound healing, transwell and FITC/PI dye were used to detect cell behaviors.

RESULTS

RNF213 was shown to express much lower in tumor tissues and in tumor cell lines compared to control. The patients with higher RNF213 expression displayed longer survival time. When RNF213 was overexpressed in U87MG cells, cell proliferation and colony formation were inhibited significantly. The ability of cell migration and invasion was also suppressed. FAC analysis demonstrated that cell apoptosis was increased after RNF213 overexpression. But cell cycle distribution was not affected by RNF213. Then the expression level of MEKK1, JNK, c-Jun, and cdc42 was decreased after RNF213 overexpression, but increased reversely when RNF213 was knocked down by RNAi technology.

CONCLUSIONS

RNF213 suppresses carcinogenesis and affects MAPK/JNK signaling pathway in glioblastoma. This study suggests that RNF213 might be a promising target for therapy of glioblastoma.

Dysregulated Fc gamma receptor-mediated phagocytosis pathway in Alzheimer's disease: network-based gene expression analysis

Transcriptomics has become an important tool for identification of biological pathways dysregulated in Alzheimer's disease (AD). We performed a network-based gene expression analysis of blood-based microarray gene expression profiles using 2 independent cohorts, Alzheimer's Disease Neuroimaging Initiative (ADNI; N = 661) and AddNeuroMed (N = 674). Weighted gene coexpression network analysis identified 17 modules from ADNI and 13 from AddNeuroMed. Four of the modules derived in ADNI were significantly related to AD; 5 modules in AddNeuroMed were significant. Gene-set enrichment analysis of the AD-related modules identified and replicated 3 biological pathways including the Fc gamma receptor-mediated phagocytosis pathway. Module-based association analysis showed the AD-related module, which has the 3 pathways, to be associated with cognitive function and neuroimaging biomarkers. Gene-based association analysis identified PRKCD in the Fc gamma receptor-mediated phagocytosis pathway as being significantly associated with cognitive function and cerebrospinal fluid biomarkers. The identification of the Fc gamma receptor-mediated phagocytosis pathway implicates the peripheral innate immune system in the pathophysiology of AD. PRKCD is known to be related to neurodegeneration induced by amyloid-β.

A serum protein signature of APOE genotypes in centenarians

The discovery of treatments to prevent or delay dementia and Alzheimer's disease is a priority. The gene APOE is associated with cognitive change and late-onset Alzheimer's disease, and epidemiological studies have provided strong evidence that the e2 allele of APOE has a neuroprotective effect, it is associated with increased longevity and an extended healthy lifespan in centenarians. In this study, we correlated APOE genotype data of 222 participants of the New England Centenarian Study, including 75 centenarians, 82 centenarian offspring, and 65 controls, comprising 55 carriers of APOE e2 , with aptamer-based serum proteomics (SomaLogic technology) of 4,785 human proteins corresponding to 4,137 genes. We discovered a signature of 16 proteins that associated with different APOE genotypes and replicated the signature in three independent studies. We also show that the protein signature tracks with gene expression profiles in brains of late-onset Alzheimer's disease versus healthy controls. Finally, we show that seven of these proteins correlate with cognitive function patterns in longitudinally collected data. This analysis in particular suggests that Baculoviral IAP repeat containing two (BIRC2) is a novel biomarker of neuroprotection that associates with the neuroprotective allele of APOE. Therefore, targeting APOE e2 molecularly may preserve cognitive function.

Predicting novel genomic regions linked to genetic disorders using GWAS and chromosome conformation data - a case study of schizophrenia

Genome-wide association studies identified numerous loci harbouring single nucleotide polymorphisms (SNPs) associated with various human diseases, although the causal role of many of them remains unknown. In this paper, we postulate that co-location and shared biological function of novel genes with genes known to associate with a specific phenotype make them potential candidates linked to the same phenotype (“guilt-by-proxy”). We propose a novel network-based approach for predicting candidate genes/genomic regions utilising the knowledge of the 3D architecture of the human genome and GWAS data. As a case study we used a well-studied polygenic disorder ‒ schizophrenia ‒ for which we compiled a comprehensive dataset of SNPs. Our approach revealed 634 novel regions covering ~398 Mb of the human genome and harbouring ~9000 genes. Using various network measures and enrichment analysis, we identified subsets of genes and investigated the plausibility of these genes/regions having an association with schizophrenia using literature search and bioinformatics resources. We identified several genes/regions with previously reported associations with schizophrenia, thus providing proof-of-concept, as well as novel candidates with no prior known associations. This approach has the potential to identify novel genes/genomic regions linked to other polygenic disorders and provide means of aggregating genes/SNPs for further investigation.

Alzheimer's disease-associated (hydroxy)methylomic changes in the brain and blood

BACKGROUND

Late-onset Alzheimer's disease (AD) is a complex multifactorial affliction, the pathogenesis of which is thought to involve gene-environment interactions that might be captured in the epigenome. The present study investigated epigenome-wide patterns of DNA methylation (5-methylcytosine, 5mC) and hydroxymethylation (5-hydroxymethylcytosine, 5hmC), as well as the abundance of unmodified cytosine (UC), in relation to AD.

RESULTS

We identified epigenetic differences in AD patients (n = 45) as compared to age-matched controls (n = 35) in the middle temporal gyrus, pertaining to genomic regions close to or overlapping with genes such as OXT (- 3.76% 5mC, pŠidák = 1.07E-06), CHRNB1 (+ 1.46% 5hmC, pŠidák = 4.01E-04), RHBDF2 (- 3.45% UC, pŠidák = 4.85E-06), and C3 (- 1.20% UC, pŠidák = 1.57E-03). In parallel, in an independent cohort, we compared the blood methylome of converters to AD dementia (n = 54) and non-converters (n = 42), at a preclinical stage. DNA methylation in the same region of the OXT promoter as found in the brain was found to be associated with subsequent conversion to AD dementia in the blood of elderly, non-demented individuals (+ 3.43% 5mC, pŠidák = 7.14E-04).

CONCLUSIONS

The implication of genome-wide significant differential methylation of OXT, encoding oxytocin, in two independent cohorts indicates it is a promising target for future studies on early biomarkers and novel therapeutic strategies in AD.

Quantitative proteomics of synaptosome S-nitrosylation in Alzheimer's disease

Increasing evidence suggests that both synaptic loss and neuroinflammation constitute early pathologic hallmarks of Alzheimer's disease. A downstream event during inflammatory activation of microglia and astrocytes is the induction of nitric oxide synthase type 2, resulting in an increased release of nitric oxide and the post-translational S-nitrosylation of protein cysteine residues. Both early events, inflammation and synaptic dysfunction, could be connected if this excess nitrosylation occurs on synaptic proteins. In the long term, such changes could provide new insight into patho-mechanisms as well as biomarker candidates from the early stages of disease progression. This study investigated S-nitrosylation in synaptosomal proteins isolated from APP/PS1 model mice in comparison to wild type and NOS2^-/- mice, as well as human control, mild cognitive impairment and Alzheimer's disease brain tissues. Proteomics data were obtained using an established protocol utilizing an isobaric mass tag method, followed by nanocapillary high performance liquid chromatography tandem mass spectrometry. Statistical analysis identified the S-nitrosylation sites most likely derived from an increase in nitric oxide (NO) in dependence of presence of AD pathology, age and the key enzyme NOS2. The resulting list of candidate proteins is discussed considering function, previous findings in the context of neurodegeneration, and the potential for further validation studies.

Artificial Intelligence and the detection of pediatric concussion using epigenomic analysis

Concussion, also referred to as mild traumatic brain injury (mTBI) is the most common type of traumatic brain injury. Currently concussion is an area ofintensescientific interest to better understand the biological mechanisms and for biomarker development. We evaluated whole genome-wide blood DNA cytosine ('CpG') methylation in 17 pediatric concussion isolated cases and 18 unaffected controls using Illumina Infinium MethylationEPIC assay. Pathway analysis was performed using Ingenuity Pathway Analysis to help elucidate the epigenetic and molecular mechanisms of the disorder. Area under the receiver operating characteristics (AUC) curves and FDR p-values were calculated for mTBI detection based on CpG methylation levels. Multiple Artificial Intelligence (AI) platforms including Deep Learning (DL), the newest form of AI, were used to predict concussion based on i) CpG methylation markers alone, and ii) combined epigenetic, clinical and demographic predictors. We found 449 CpG sites (473 genes), those were statistically significantly methylated in mTBI compared to controls. There were four CpGs with excellent individual accuracy (AUC ≥ 0.90-1.00) while 119 displayed good accuracy (AUC ≥ 0.80-0.89) for the prediction of mTBI. The CpG methylation changes ≥10% were observed in many CpG loci after concussion suggesting biological significance. Pathway analysis identified several biologically important neurological pathways that were perturbed including those associated with: impaired brain function, cognition, memory, neurotransmission, intellectual disability and behavioral change and associated disorders. The combination of epigenomic and clinical predictors were highly accurate for the detection of concusion using AI techniques. Using DL/AI, a combination of epigenomic and clinical markers had sensitivity and specificity ≧95% for prediction of mTBI. In this novel study, we identified significant methylation changes in multiple genes in response to mTBI. Gene pathways that were epigenetically dysregulated included several known to be involved in neurological function, thus giving biological plausibility to our findings.

Multi-omics signature of brain amyloid deposition in asymptomatic individuals at-risk for Alzheimer's disease: The INSIGHT-preAD study

BACKGROUND

One of the biggest challenge in Alzheimer's disease (AD) is to identify pathways and markers of disease prediction easily accessible, for prevention and treatment. Here we analysed blood samples from the INveStIGation of AlzHeimer's predicTors (INSIGHT-preAD) cohort of elderly asymptomatic individuals with and without brain amyloid load.

METHODS

We performed blood RNAseq, and plasma metabolomics and lipidomics using liquid chromatography-mass spectrometry on 48 individuals amyloid positive and 48 amyloid negative (SUVr cut-off of 0·7918). The three data sets were analysed separately using differential gene expression based on negative binomial distribution, non-parametric (Wilcoxon) and parametric (correlation-adjusted Student't) tests. Data integration was conducted using sparse partial least squares-discriminant and principal component analyses. Bootstrap-selected top-ten features from the three data sets were tested for their discriminant power using Receiver Operating Characteristic curve. Longitudinal metabolomic analysis was carried out on a subset of 22 subjects.

FINDINGS

Univariate analyses identified three medium chain fatty acids, 4-nitrophenol and a set of 64 transcripts enriched for inflammation and fatty acid metabolism differentially quantified in amyloid positive and negative subjects. Importantly, the amounts of the three medium chain fatty acids were correlated over time in a subset of 22 subjects (p < 0·05). Multi-omics integrative analyses showed that metabolites efficiently discriminated between subjects according to their amyloid status while lipids did not and transcripts showed trends. Finally, the ten top metabolites and transcripts represented the most discriminant omics features with 99·4% chance prediction for amyloid positivity.

INTERPRETATION

This study suggests a potential blood omics signature for prediction of amyloid positivity in asymptomatic at-risk subjects, allowing for a less invasive, more accessible, and less expensive risk assessment of AD as compared to PET studies or lumbar puncture. FUND: Institut Hospitalo-Universitaire and Institut du Cerveau et de la Moelle Epiniere (IHU-A-ICM), French Ministry of Research, Fondation Alzheimer, Pfizer, and Avid.

Identification of molecular signatures and pathways to identify novel therapeutic targets in Alzheimer's disease: Insights from a systems biomedicine perspective

Alzheimer's disease (AD) is a progressive neurodegenerative disease characterized by the accumulation of amyloid plaques and neurofibrillary tangles in the brain. However, there are no peripheral biomarkers available that can detect AD onset. This study aimed to identify the molecular signatures in AD through an integrative analysis of blood gene expression data. We used two microarray datasets (GSE4226 and GSE4229) comparing peripheral blood transcriptomes of AD patients and controls to identify differentially expressed genes (DEGs). Gene set and protein overrepresentation analysis, protein-protein interaction (PPI), DEGs-Transcription Factors (TFs) interactions, DEGs-microRNAs (miRNAs) interactions, protein-drug interactions, and protein subcellular localizations analyses were performed on DEGs common to the datasets. We identified 25 common DEGs between the two datasets. Integration of genome scale transcriptome datasets with biomolecular networks revealed hub genes (NOL6, ATF3, TUBB, UQCRC1, CASP2, SND1, VCAM1, BTF3, VPS37B), common transcription factors (FOXC1, GATA2, NFIC, PPARG, USF2, YY1) and miRNAs (mir-20a-5p, mir-93-5p, mir-16-5p, let-7b-5p, mir-708-5p, mir-24-3p, mir-26b-5p, mir-17-5p, mir-193-3p, mir-186-5p). Evaluation of histone modifications revealed that hub genes possess several histone modification sites associated with AD. Protein-drug interactions revealed 10 compounds that affect the identified AD candidate biomolecules, including anti-neoplastic agents (Vinorelbine, Vincristine, Vinblastine, Epothilone D, Epothilone B, CYT997, and ZEN-012), a dermatological (Podofilox) and an immunosuppressive agent (Colchicine). The subcellular localization of molecular signatures varied, including nuclear, plasma membrane and cytosolic proteins. In the present study, it was identified blood-cell derived molecular signatures that might be useful as candidate peripheral biomarkers in AD. It was also identified potential drugs and epigenetic data associated with these molecules that may be useful in designing therapeutic approaches to ameliorate AD.

Human amyloid-β enriched extracts: evaluation of in vitro and in vivo internalization and molecular characterization

BACKGROUND

Intracerebral inoculation of extracts from post-mortem human Alzheimer's disease brains into mice produces a prion-like spreading effect of amyloid-β. The differences observed between these extracts and the synthetic peptide, in terms of amyloid-β internalization and seed and cell-to-cell transmission of cytosolic protein aggregates, suggest that brain extracts contain key contributors that enhance the prion-like effect of amyloid-β. Nevertheless, these potential partners are still unknown due to the complexity of whole brain extracts.

METHODS

Herein, we established a method based on sequential detergent solubilization of post-mortem samples of human brains affected by Alzheimer's disease that strongly enrich amyloid-β aggregates by eliminating 92% of the remaining proteins. Internalization of Aβ1-42 from the enriched AD extracts was evaluated in vitro, and internalization of fluorescent-labeled AD extracts was also investigated in vivo. Furthermore, we carried out a molecular characterization of the Aβ-enriched fraction using label-free proteomics, studying the distribution of representative components in the amygdala and the olfactory cortex of additional human AD brain samples by immunohistochemistry.

RESULTS

Aβ1-42 from the enriched AD extracts are internalized into endothelial cells in vitro after 48 h. Furthermore, accumulation of fluorescent-labeled Aβ-enriched extracts into mouse microglia was observed in vivo after 4 months of intracerebral inoculation. Label-free proteomics (FDR < 0.01) characterization of the amyloid-β-enriched fraction from different post-mortem samples allowed for the identification of more than 130 proteins, several of which were significantly overrepresented (i.e., ANXA5 and HIST1H2BK; p < 0.05) and underrepresented (i.e., COL6A or FN1; p < 0.05) in the samples with Alzheimer's disease. We were also able to identify proteins exclusively observed in Alzheimer's disease (i.e., RNF213) or only detected in samples not affected by the disease (i.e., CNTN1) after the enrichment process. Immunohistochemistry against these proteins in additional tissues revealed their particular distribution in the amygdala and the olfactory cortex in relation to the amyloid-β plaque.

CONCLUSIONS

Identification and characterization of the unique features of these extracts, in terms of amyloid-β enrichment, identification of the components, in vitro and in vivo cell internalization, and tissue distribution, constitute the best initial tool to further investigate the seeding and transmissibility proposed in the prion-like hypothesis of Alzheimer's disease.

HDAC9 Polymorphism Alters Blood Gene Expression in Patients with Large Vessel Atherosclerotic Stroke

The histone deacetylase 9 (HDAC9) polymorphism rs2107595 is associated with an increased risk for large vessel atherosclerotic stroke (LVAS). In humans, there remains a need to better understand this HDAC9 polymorphism's contribution to large vessel stroke. In this pilot study, we evaluated whether the HDAC9 polymorphism rs2107595 is associated with differences in leukocyte gene expression in patients with LVAS. HDAC9 SNP rs2107595 was genotyped in 155 patients (43 LVAS and 112 vascular risk factor controls). RNA isolated from blood was processed on whole genome microarrays. Gene expression was compared between HDAC9 risk allele-positive and risk allele-negative LVAS patients and controls. Functional analysis identified canonical pathways and molecular functions associated with rs2107595 in LVAS. In HDAC9 SNP rs2107595 risk allele-positive LVAS patients, there were 155 genes differentially expressed compared to risk allele-negative patients (fold change > |1.2|, p < 0.05). The 155 genes separated the risk allele-positive and risk allele-negative LVAS patients on a principal component analysis. Pathways associated with HDAC9 risk allele-positive status involved IL-6 signaling, cholesterol efflux, and platelet aggregation. These preliminary data suggest an association with the HDAC9 rs2107595 risk allele and peripheral immune, lipid, and clotting systems in LVAS. Further study is required to evaluate whether these differences are related to large vessel atherosclerosis and stroke risk.

Early Life Stress and Epigenetics in Late-onset Alzheimer's Dementia: A Systematic Review

Involvement of life stress in Late-Onset Alzheimer's Disease (LOAD) has been evinced in longitudinal cohort epidemiological studies, and endocrinologic evidence suggests involvements of catecholamine and corticosteroid systems in LOAD. Early Life Stress (ELS) rodent models have successfully demonstrated sequelae of maternal separation resulting in LOAD-analogous pathology, thereby supporting a role of insulin receptor signalling pertaining to GSK-3beta facilitated tau hyper-phosphorylation and amyloidogenic processing. Discussed are relevant ELS studies, and findings from three mitogen-activated protein kinase pathways (JNK/SAPK pathway, ERK pathway, p38/MAPK pathway) relevant for mediating environmental stresses. Further considered were the roles of autophagy impairment, neuroinflammation, and brain insulin resistance. For the meta-analytic evaluation, 224 candidate gene loci were extracted from reviews of animal studies of LOAD pathophysiological mechanisms, of which 60 had no positive results in human LOAD association studies. These loci were combined with 89 gene loci confirmed as LOAD risk genes in previous GWAS and WES. Of the 313 risk gene loci evaluated, there were 35 human reports on epigenomic modifications in terms of methylation or histone acetylation. 64 microRNA gene regulation mechanisms were published for the compiled loci. Genomic association studies support close relations of both noradrenergic and glucocorticoid systems with LOAD. For HPA involvement, a CRHR1 haplotype with MAPT was described, but further association of only HSD11B1 with LOAD found; however, association of FKBP1 and NC3R1 polymorphisms was documented in support of stress influence to LOAD. In the brain insulin system, IGF2R, INSR, INSRR, and plasticity regulator ARC, were associated with LOAD. Pertaining to compromised myelin stability in LOAD, relevant associations were found for BIN1, RELN, SORL1, SORCS1, CNP, MAG, and MOG. Regarding epigenetic modifications, both methylation variability and de-acetylation were reported for LOAD. The majority of up-to-date epigenomic findings include reported modifications in the well-known LOAD core pathology loci MAPT, BACE1, APP (with FOS, EGR1), PSEN1, PSEN2, and highlight a central role of BDNF. Pertaining to ELS, relevant loci are FKBP5, EGR1, GSK3B; critical roles of inflammation are indicated by CRP, TNFA, NFKB1 modifications; for cholesterol biosynthesis, DHCR24; for myelin stability BIN1, SORL1, CNP; pertaining to (epi)genetic mechanisms, hTERT, MBD2, DNMT1, MTHFR2. Findings on gene regulation were accumulated for BACE1, MAPK signalling, TLR4, BDNF, insulin signalling, with most reports for miR-132 and miR-27. Unclear in epigenomic studies remains the role of noradrenergic signalling, previously demonstrated by neuropathological findings of childhood nucleus caeruleus degeneration for LOAD tauopathy.

Lipopolysaccharide Associates with Amyloid Plaques, Neurons and Oligodendrocytes in Alzheimer's Disease Brain: A Review

This review proposes that lipopolysaccharide (LPS, found in the wall of all Gram-negative bacteria) could play a role in causing sporadic Alzheimer’s disease (AD). This is based in part upon recent studies showing that: Gram-negative E. coli bacteria can form extracellular amyloid; bacterial-encoded 16S rRNA is present in all human brains with over 70% being Gram-negative bacteria; ultrastructural analyses have shown microbes in erythrocytes of AD patients; blood LPS levels in AD patients are 3-fold the levels in control; LPS combined with focal cerebral ischemia and hypoxia produced amyloid-like plaques and myelin injury in adult rat cortex. Moreover, Gram-negative bacterial LPS was found in aging control and AD brains, though LPS levels were much higher in AD brains. In addition, LPS co-localized with amyloid plaques, peri-vascular amyloid, neurons, and oligodendrocytes in AD brains. Based upon the postulate LPS caused oligodendrocyte injury, degraded Myelin Basic Protein (dMBP) levels were found to be much higher in AD compared to control brains. Immunofluorescence showed that the dMBP co-localized with β amyloid (Aβ) and LPS in amyloid plaques in AD brain, and dMBP and other myelin molecules were found in the walls of vesicles in periventricular White Matter (WM). These data led to the hypothesis that LPS acts on leukocyte and microglial TLR4-CD14/TLR2 receptors to produce NFkB mediated increases of cytokines which increase Aβ levels, damage oligodendrocytes and produce myelin injury found in AD brain. Since Aβ_1–42 is also an agonist for TLR4 receptors, this could produce a vicious cycle that accounts for the relentless progression of AD. Thus, LPS, the TLR4 receptor complex, and Gram-negative bacteria might be treatment or prevention targets for sporadic AD.

Autophagy and Alzheimer's Disease: From Molecular Mechanisms to Therapeutic Implications

Alzheimer’s disease (AD) is the most common cause of progressive dementia in the elderly. It is characterized by a progressive and irreversible loss of cognitive abilities and formation of senile plaques, composed mainly of amyloid β (Aβ), and neurofibrillary tangles (NFTs), composed of tau protein, in the hippocampus and cortex of afflicted humans. In brains of AD patients the metabolism of Aβ is dysregulated, which leads to the accumulation and aggregation of Aβ. Metabolism of Aβ and tau proteins is crucially influenced by autophagy. Autophagy is a lysosome-dependent, homeostatic process, in which organelles and proteins are degraded and recycled into energy. Thus, dysfunction of autophagy is suggested to lead to the accretion of noxious proteins in the AD brain. In the present review, we describe the process of autophagy and its importance in AD. Additionally, we discuss mechanisms and genes linking autophagy and AD, i.e., the mTOR pathway, neuroinflammation, endocannabinoid system, ATG7, BCL2, BECN1, CDK5, CLU, CTSD, FOXO1, GFAP, ITPR1, MAPT, PSEN1, SNCA, UBQLN1, and UCHL1. We also present pharmacological agents acting via modulation of autophagy that may show promise in AD therapy. This review updates our knowledge on autophagy mechanisms proposing novel therapeutic targets for the treatment of AD.

Point-of-Care Devices Using Disease Biomarkers To Diagnose Neurodegenerative Disorders

Neurodegenerative disorders such as Alzheimer's, Parkinson's, and Huntington's diseases are highly prevalent and immensely destructive to the health and well-being of individuals and their families across the globe. Neurodegenerative diseases are characterized by the gradual loss of neural tissue in the central nervous system. Clearly, early diagnosis of the onset of neurodegeneration is vital and beneficial. Current diagnostic methods rely heavily on symptoms or autopsy results, thus overlooking early diagnosis, the only opportunity for amelioration. However, appropriately selected and used biomarker diagnostics provide a solution. This article reviews the development and application of biomarker-related diagnostics for neurodegenerative disease with specific recommendations for point-of-care (POC) methodology. These advantageous approaches may offer a solution to existing obstacles and limitations to neurodegenerative disease treatment.

Analysis of genetic polymorphisms associated with leukoaraiosis in the southern Chinese population: A case-control study

Leukoaraiosis (LA) is a frequent neuroimaging finding commonly observed on brain MRIs of elderly people with prevalence ranging from 50% to 100%. Multiple susceptibility genes or genetic risk factors for LA have been identified in subjects of European descent. Here, we report the first replication study on several common and novel genetic variations in the Chinese population. In this study, a total of 244 subjects (201 LA patients and 43 controls) were enrolled according to our new and strict definition for LA. Subsequently, 6 genetic variants at 5 genes, rs3744028 in TRIM65, rs1055129 in TRIM47, rs1135889 in FBF1, rs1052053 in PMF1, and rs1801133 (C677T) and rs1801131(A1298C) in MTHFR, were selected for genotyping using polymerase chain reaction (PCR)-based pyrosequencing and restriction fragment length polymorphism (RFLP) together with capillary electrophoresis (CE) and agarose gel electrophoresis. Finally, Pearson's χ and multivariate logistic regression tests were used to examine the associations between the genotypes and LA. Among these candidate polymorphisms, except for rs1052053 and rs1801131, rs1135889 (P = 0.012) showed significant associations with LA in the dominant model, and the other 3 SNPs, rs3744028 (P = 0.043), rs1055129 (P = 0.038), and rs1801133 (P = 0.027), showed significant associations with LA in the recessive model. However, these differences no longer remained significant after adjusting for age, gender, hypertension, and diabetes mellitus and applying Bonferroni correction or Sidak correction for multiple testing. These results suggest that the above-mentioned genetic variants are not associated with LA risk. In summary, the study did not replicate the susceptibility of rs3744028, rs1055129, and rs1135889 at the Chr17q25 locus for LA nor did it find any other significant results for rs1052053, rs1801133, and rs1801131 in the Chinese population. It strongly indicated the ethnic differences in the genetics of LA. However, the associations of rs3744028 (TRIM65), rs1055129 (TRIM47), rs1135889 (FBF1), and rs1801133 (MTHFR) with LA before Bonferroni correction and Sidak correction for multiple testing are worth highlighting. Thus, we believe that a genome-wide association study and candidate gene association studies are needed to reassess the previous findings and screen novel risk genes for LA in China.

Perturbation of the transcriptome: implications of the innate immune system in Alzheimer's disease

Alzheimer's disease (AD) is a neurodegenerative disease with broad impact. Although Aβ and tau have been proposed as the key molecules in the disease mechanism, comprehensive understanding of AD pathogenesis requires a systemic view at the genomic level. From studies on the brain transcriptome of AD, we have gradually realized the contribution of the immune system to AD development. Recent explorations on the blood transcriptome of AD patients have revealed robust immune activation in the peripheral blood. The combination of transcriptome studies and other types of studies has further elucidated the roles of specific immune pathways in distinct cell types during AD development and highlighted the critical contributions from immune genes such as TREM2.

Alzheimer's Disease: Genomics and Beyond

Alzheimer's disease (AD) is a major form of senile dementia. Despite the critical roles of Aβ and tau in AD pathology, drugs targeting Aβ or tau have so far reached limited success. The advent of genomic technologies has made it possible to gain a more complete picture regarding the molecular network underlying the disease progression which may lead to discoveries of novel treatment targets. In this review, we will discuss recent progresses in AD research focusing on genome, transcriptome, epigenome, and related subjects. Advancements have been made in the finding of novel genetic risk factors, new hypothesis for disease mechanism, candidate biomarkers for early diagnosis, and potential drug targets. As an integration effort, we have curated relevant data in a database named AlzBase.

AlzBase: an Integrative Database for Gene Dysregulation in Alzheimer's Disease

Alzheimer's disease (AD) affects a significant portion of elderly people worldwide. Although the amyloid-β (Aβ) cascade hypothesis has been the prevailing theory for the molecular mechanism of AD in the past few decades, treatment strategies targeting the Aβ cascade have not demonstrated effectiveness as yet. Thus, elucidating the spatial and temporal evolution of the molecular pathways in AD remains to be a daunting task. To facilitate novel discoveries in this filed, here, we have integrated information from multiple sources for the better understanding of gene functions in AD pathogenesis. Several categories of information have been collected, including (1) gene dysregulation in AD and closely related processes/diseases such as aging and neurological disorders, (2) correlation of gene dysregulation with AD severity, (3) a wealth of annotations on the functional and regulatory information, and (4) network connections for gene-gene relationship. In addition, we have also provided a comprehensive summary for the top ranked genes in AlzBase. By evaluating the information curated in AlzBase, researchers can prioritize genes from their own research and generate novel hypothesis regarding the molecular mechanism of AD. To demonstrate the utility of AlzBase, we examined the genes from the genetic studies of AD. It revealed links between the upstream genetic variations and downstream endo-phenotype and suggested several genes with higher priority. This integrative database is freely available on the web at http://alz.big.ac.cn/alzBase .