Data-Driven Analysis of Age, Sex, and Tissue Effects on Gene Expression Variability in Alzheimer's Disease

CSF proteomic profiling with amyloid/tau positivity identifies distinctive sex-different alteration of multiple proteins involved in Alzheimer's disease

In Alzheimer's disease (AD), the most common cause of dementia, females have higher prevalence and faster progression, but sex-specific molecular findings in AD are limited. Here, we comprehensively examined and validated 7,006 aptamers targeting 6,162 proteins in cerebral spinal fluid (CSF) from 2,077 amyloid/tau positive cases and controls to identify sex-specific proteomic signatures of AD. In discovery (N=1,766), we identified 330 male-specific and 121 female-specific proteomic alternations in CSF (FDR <0.05). These sex-specific proteins strongly predicted amyloid/tau positivity (AUC=0.98 in males; 0.99 in females), significantly higher than those with age, sex, and APOE-ε4 (AUC=0.85). The identified sex-specific proteins were well validated (r≥0.5) in the Stanford study (N=108) and Emory study (N=148). Biological follow-up of these proteins led to sex differences in cell-type specificity, pathways, interaction networks, and drug targets. Male-specific proteins, enriched in astrocytes and oligodendrocytes, were involved in postsynaptic and axon-genesis. The male network exhibited direct connections among 152 proteins and highlighted PTEN, NOTCH1, FYN, and MAPK8 as hubs. Drug target suggested melatonin (used for sleep-wake cycle regulation), nabumetone (used for pain), daunorubicin, and verteporfin for treating AD males. In contrast, female-specific proteins, enriched in neurons, were involved in phosphoserine residue binding including cytokine activities. The female network exhibits strong connections among 51 proteins and highlighted JUN and 14-3-3 proteins (YWHAG and YWHAZ) as hubs. Drug target suggested biperiden (for muscle control of Parkinson's disease), nimodipine (for cerebral vasospasm), quinostatin and ethaverine for treating AD females. Together, our findings provide mechanistic understanding of sex differences for AD risk and insights into clinically translatable interventions.

A case for seeking sex-specific treatments in Alzheimer's disease

There is no satisfactory explanation for the sex-related differences in the incidence of many diseases and this is also true of Alzheimer's disease (AD), where females have a higher lifetime risk of developing the disease and make up about two thirds of the AD patient population. The importance of understanding the cause(s) that account for this disproportionate distribution cannot be overestimated, and is likely to be a significant factor in the search for therapeutic strategies that will combat the disease and, furthermore, potentially point to a sex-targeted approach to treatment. This review considers the literature in the context of what is known about the impact of sex on processes targeted by drugs that are in clinical trial for AD, and existing knowledge on differing responses of males and females to these drugs. Current knowledge strongly supports the view that trials should make assessing sex-related difference in responses a priority with a focus on exploring the sex-stratified treatments.

Transcriptomics Meta-Analysis Reveals Phagosome and Innate Immune System Dysfunction as Potential Mechanisms in the Cortex of Alzheimer's Disease Mouse Strains

Immune-related pathways can affect the immune system directly, such as the chemokine signaling pathway, or indirectly, such as the phagosome pathway. Alzheimer's disease (AD) is reportedly associated with several immune-related pathways. However, exploring its underlying mechanism is challenging in animal studies because AD mouse strains differentially express immune-related pathway characteristics. To overcome this problem, we performed a meta-analysis to identify significant and consistent immune-related AD pathways that are expressed in different AD mouse strains. Next-generation RNA sequencing (RNA-seq) and microarray datasets for the cortex of AD mice from different strains such as APP/PSEN1, APP/PS2, 3xTg, TREM, and 5xFAD were collected from the NCBI GEO database. Each dataset's quality control and normalization were already processed from each original study source using various methods depending on the high-throughput analysis platform (FastQC, median of ratios, RMA, between array normalization). Datasets were analyzed using DESeq2 for RNA-seq and GEO2R for microarray to identify differentially expressed (DE) genes. Significantly DE genes were meta-analyzed using Stouffer's method, with significant genes further analyzed for functional enrichment. Ten datasets representing 20 conditions were obtained from the NCBI GEO database, comprising 116 control and 120 AD samples. The DE analysis identified 284 significant DE genes. The meta-analysis identified three significantly enriched immune-related AD pathways: phagosome, the complement and coagulation cascade, and chemokine signaling. Phagosomes-related genes correlated with complement and immune system. Meanwhile, phagosomes and chemokine signaling genes overlapped with B cells receptors pathway genes indicating potential correlation between phagosome, chemokines, and adaptive immune system as well. The transcriptomic meta-analysis showed that AD is associated with immune-related pathways in the brain's cortex through the phagosome, complement and coagulation cascade, and chemokine signaling pathways. Interestingly, phagosome and chemokine signaling pathways had potential correlation with B cells receptors pathway.

Insights into Sex and Gender Differences in Brain and Psychopathologies Using Big Data

The societal implication of sex and gender (SG) differences in brain are profound, as they influence brain development, behavior, and importantly, the presentation, prevalence, and therapeutic response to diseases. Technological advances have enabled speed up identification and characterization of SG differences during development and in psychopathologies. The main aim of this review is to elaborate on new technological advancements, such as genomics, imaging, and emerging biobanks, coupled with bioinformatics analyses of data generated from these technologies have facilitated the identification and characterization of SG differences in the human brain through development and psychopathologies. First, a brief explanation of SG concepts is provided, along with a developmental and evolutionary context. We then describe physiological SG differences in brain activity and function, and in psychopathologies identified through imaging techniques. We further provide an overview of insights into SG differences using genomics, specifically taking advantage of large cohorts and biobanks. We finally emphasize how bioinformatics analyses of big data generated by emerging technologies provides new opportunities to reduce SG disparities in health outcomes, including major challenges.

Identification of a Novel Eight-Gene Risk Model for Predicting Survival in Glioblastoma: A Comprehensive Bioinformatic Analysis

Glioblastoma (GBM) is one of the most progressive and prevalent cancers of the central nervous system. Identifying genetic markers is therefore crucial to predict prognosis and enhance treatment effectiveness in GBM. To this end, we obtained gene expression data of GBM from TCGA and GEO datasets and identified differentially expressed genes (DEGs), which were overlapped and used for survival analysis with univariate Cox regression. Next, the genes' biological significance and potential as immunotherapy candidates were examined using functional enrichment and immune infiltration analysis. Eight prognostic-related DEGs in GBM were identified, namely CRNDE, NRXN3, POPDC3, PTPRN, PTPRN2, SLC46A2, TIMP1, and TNFSF9. The derived risk model showed robustness in identifying patient subgroups with significantly poorer overall survival, as well as those with distinct GBM molecular subtypes and MGMT status. Furthermore, several correlations between the expression of the prognostic genes and immune infiltration cells were discovered. Overall, we propose a survival-derived risk score that can provide prognostic significance and guide therapeutic strategies for patients with GBM.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Sex difference in biological change and mechanism of Alzheimer’s disease: from macro- to micro-landscape

Alzheimer's disease (AD) is the most common form of dementia and numerous studies reported a higher prevalence and incidence of AD among women. Although women have longer lifetime, longevity does not wholly explain the higher frequency and lifetime risk in women. It is important to understand sex differences in AD pathophysiology and pathogenesis, which could provide foundation for future clinical AD research. Here, we reviewed the most recent and relevant literature on sex differences in biological change of AD from macroscopical neuroimaging to microscopical pathologic change (neuronal degeneration, synaptic dysfunction, amyloid-beta and tau accumulation). We also discussed sex differences in cellular mechanisms related to AD (neuroinflammation, mitochondria dysfunction, oxygen stress, apoptosis, autophagy, blood-brain-barrier dysfunction, gut microbiome alteration, bulk and single cell/nucleus omics) and possible causes underlying these differences including sex-chromosome, sex hormone and hypothalamic-pituitary- adrenal (HPA) axis effects.

Genetic and Epigenetic Sexual Dimorphism of Brain Cells during Aging

In recent years, much of the attention paid to theoretical and applied biomedicine, as well as neurobiology, has been drawn to various aspects of sexual dimorphism due to the differences that male and female brain cells demonstrate during aging: (a) a dimorphic pattern of response to therapy for neurodegenerative disorders, (b) different age of onset and different degrees of the prevalence of such disorders, and (c) differences in their symptomatic manifestations in men and women. The purpose of this review is to outline the genetic and epigenetic differences in brain cells during aging in males and females. As a result, we hereby show that the presence of brain aging patterns in males and females is due to a complex of factors associated with the effects of sex chromosomes, which subsequently entails a change in signal cascades in somatic cells.

Therapeutic Potential of Different Natural Products for the Treatment of Alzheimer’s Disease

A high incidence of dementia (60–80%) and a high rate of memory loss are two of the most common symptoms of Alzheimer's disease (AD), which affects the elderly. Researchers have recommended that traditional Chinese medicine (TCM) and Indian medicines can be used to prevent and cure AD. Several studies have linked neuroinflammation linked to amyloid-β (Aβ) deposition in the brain to the pathophysiology of neurodegenerative disorders. As a result, more research is needed to determine the role of inflammation in neurodegeneration. Increased microglial activation, cytokine production, reactive oxygen species (ROS), and nuclear factor kappa B (NF-κB) all play a role in the inflammatory process of AD. This review focuses on the role of neuroinflammation in neuroprotection and the molecular processes used by diverse natural substances, phytochemicals, and herbal formulations in distinct signaling pathways. Currently, researchers are focusing on pharmacologically active natural compounds with the anti-neuroinflammatory potential, making them a possible contender for treating AD. Furthermore, the researchers investigated the limits of past studies on TCM, Indian Ayurveda, and AD. Numerous studies have been carried out to examine the effects of medicinal whole-plant extracts on AD. Clinical investigations have shown that lignans, flavonoids, tannins, polyphenols, triterpenoids, sterols, and alkaloids have anti-inflammatory, antiamyloidogenic, anticholinesterase, and antioxidant properties. This review summarizes information about numerous medicinal plants and isolated compounds used in the treatment of AD and a list of further references.

Chlamydia pneumoniae can infect the central nervous system via the olfactory and trigeminal nerves and contributes to Alzheimer's disease risk

Chlamydia pneumoniae is a respiratory tract pathogen but can also infect the central nervous system (CNS). Recently, the link between C. pneumoniae CNS infection and late-onset dementia has become increasingly evident. In mice, CNS infection has been shown to occur weeks to months after intranasal inoculation. By isolating live C. pneumoniae from tissues and using immunohistochemistry, we show that C. pneumoniae can infect the olfactory and trigeminal nerves, olfactory bulb and brain within 72 h in mice. C. pneumoniae infection also resulted in dysregulation of key pathways involved in Alzheimer’s disease pathogenesis at 7 and 28 days after inoculation. Interestingly, amyloid beta accumulations were also detected adjacent to the C. pneumoniae inclusions in the olfactory system. Furthermore, injury to the nasal epithelium resulted in increased peripheral nerve and olfactory bulb infection, but did not alter general CNS infection. In vitro, C. pneumoniae was able to infect peripheral nerve and CNS glia. In summary, the nerves extending between the nasal cavity and the brain constitute invasion paths by which C. pneumoniae can rapidly invade the CNS likely by surviving in glia and leading to Aβ deposition.

Sex Differences in Alzheimer's Disease: Insights From the Multiomics Landscape

Alzheimer's disease (AD) has complex etiologies, and the impact of sex on AD varies over the course of disease development. The literature provides some evidence of sex-specific contributions to AD. However, molecular mechanisms of sex-biased differences in AD remain elusive. Multiomics data in tandem with systems biology approaches offer a new avenue to dissect sex-stratified molecular mechanisms of AD and to develop sex-specific diagnostic and therapeutic strategies for AD. Single-cell transcriptomic datasets and cell deconvolution of bulk tissue transcriptomic data provide additional insights into brain cell type-specific impact on sex-biased differences in AD. In this review, we summarize the impact of sex chromosomes and sex hormones on AD, the impact of sex-biased differences during AD development, and the interplay between sex and a major AD genetic risk factor, the APOE ε4 genotype, through the multiomics landscape. Several sex-biased molecular pathways such as neuroinflammation and bioenergetic metabolism have been identified. The importance of sex chromosome and sex hormones, as well as the associated pathways in AD pathogenesis, is further strengthened by findings from omics studies. Future research efforts should integrate the multiomics data from different brain regions and different cell types using systems biology approaches, and leverage the knowledge into a holistic examination of sex differences in AD. Advances in systems biology technologies and increasingly available large-scale multiomics datasets will facilitate future studies dissecting such complex signaling mechanisms to better understand AD pathogenesis in both sexes, with the ultimate goals of developing efficacious sex- and APOE-stratified preventive and therapeutic interventions for AD.

Genome-wide association study of suicidal behaviour severity in mood disorders

OBJECTIVE

Suicide is a major public health problem and it has a prominent genetic component. We performed a genome-wide association study (GWAS) of suicidal behaviour severity.

METHODS

Suicide behaviour severity was assessed within the Schedules for Clinical Assessment in Neuropsychiatry in our mood disorder sample (n = 3506) for the GWAS. We also performed polygenic risk score analyses to explore genetic sharing between suicidal behaviour severity and a number of phenotypes, including bipolar disorder, major depressive disorder, alcoholism, post-traumatic stress disorder, impulsivity, insomnia, educational attainment, loneliness, maltreatment, and amygdala volume.

RESULTS

We did not detect genome-wide significant findings at the single-marker or gene level. We report a number of suggestive single-marker and gene-based findings. Our polygenic risk score analyses did not yield significant findings with these phenotypes.

CONCLUSIONS

Larger sample sizes are required to detect moderate effects.

Methylation factor MRPL15 identified as a potential biological target in Alzheimer's disease

Alzheimer’s disease (AD) is the most common form of dementia. However, the molecular basis of the development and progression of AD is still unclear. To elucidate the molecular processes related to AD, we obtained the expression profiles and analyzed the differentially expressed genes (DEGs). The genes potentially involved in the AD process were identified by PPI network and STEM analysis. The molecular mechanisms related to the recognition of AD were determined by GSEA and enrichment analysis. The differences from immune cells in AD were calculated. The methylation factors were identified by methylation difference analysis. Among them, MRPL15 was identified as suitable for diagnosing AD. Its expression trend had been verified in GSE5281. Importantly, MRPL15 was also a methylation factor. In addition, macrophages and neutrophils were up-regulated in AD patients. This was consistent with previous immune inflammation responses identified as being involved in the development of AD. The results of the present study revealed the genetic changes and molecular mechanisms involved in the process of the development and deterioration of AD patients. The potential AD risk genes and potential biological targets were identified. It provided evidence that immune inflammation and immune cells play an important role in AD.

Alterations in the Expression of the Genes Responsible for the Synthesis of Heparan Sulfate in Brains With Alzheimer Disease

The saccharide chains of heparan sulfate appear to be involved in several aspects Alzheimer disease (AD) pathogenesis. Their structural complexity is due to the expression of different isoenzymes. We studied the differential transcription of heparan sulfate chain biosynthesis in AD brains, analyzing different brain regions in patients with different extents of AD pathology. The transcriptomic study was performed by RT-PCR using samples of amygdala, anterior hippocampus, posterior hippocampus, claustrum, calcarine fissure, globus pallidus and cerebellum from patients with mild, moderate, or severe AD, as well as healthy individuals. Certain heparan sulfate epitopes were also detected by immunohistochemistry. Several genes, across all stages of heparan sulfate synthesis, showed altered transcription in different brain regions of AD patients. The numbers of alterations were greater in in moderate versus mild AD patients. In severe patients, there were fewer alterations in genes related to early stages of biosynthesis, and overexpression of genes involved in late stages. The alterations correlated with progressive brain atrophy, although alterations were more common in the cerebellum. Detection of some heparan sulfate epitopes by immunohistochemistry was consistent with previous studies. In conclusion, transcriptional alterations in the biosynthetic genes of heparan sulfate depend on the brain region and the degree of AD pathology.

Traditional Chinese medicine for anti-Alzheimer's disease: berberine and evodiamine from Evodia rutaecarpa

Alzheimer's disease (AD) is one of the most common diseases in elderly people with a high incidence of dementia at approximately 60-80%. The pathogenesis of AD was quite complicated and currently there is no unified conclusion in the academic community, so no efficiently clinical treatment is available. In recent years, with the development of traditional Chinese medicine (TCM), researchers have proposed the idea of relying on TCM to prevent and treat AD based on the characteristic of multiple targets of TCM. This study reviewed the pathological hypothesis of AD and the potential biomarkers found in the current researches. And the potential targets of berberine and evodiamine from Evodia rutaecarpa in AD were summarized and further analyzed. A compound-targets-pathway network was carried out to clarify the mechanism of action of berberine and evodiamine for AD. Furthermore, the limitations of current researches on the TCM and AD were discussed. It is hoped that this review will provide some references for development of TCM in the prevention and treatment of AD.

Blood DNA methylation signatures to detect dementia prior to overt clinical symptoms

INTRODUCTION

This study determined whether blood DNA methylation (DNAm) patterns differentiate individuals with presymptomatic dementia compared to controls.

METHODS

DNAm was measured in 73 individuals prior to dementia diagnosis and 87 cognitively healthy controls matched for age, sex, smoking, education, and baseline cognition. DNAm was also measured at 3 years follow-up in 25 dementia cases, and 24 controls.

RESULTS

Cases and controls differed in DNAm (unadjusted P < .01) at the time of diagnosis (n = 28,787 probes), and pre-diagnosis (n = 15,111 probes), with cg01404610 (General transcription factor IIA subunit 1 gene) significant after correction for multiple testing. Overall, 1150 probes overlapped between analyses (methylation differences from -10.6% to +11.0%), and effect sizes increased from pre-diagnosis to diagnosis.

DISCUSSION

Discernible blood DNAm signatures are in dementia cases before the appearance of overt clinical symptoms. Blood-based methylation may serve as a potential biomarker of dementia, but further investigation is needed to determine their true clinical utility.

Gene expression microarray public dataset reanalysis in chronic obstructive pulmonary disease

Chronic obstructive pulmonary disease (COPD) was classified by the Centers for Disease Control and Prevention in 2014 as the 3^rd leading cause of death in the United States (US). The main cause of COPD is exposure to tobacco smoke and air pollutants. Problems associated with COPD include under-diagnosis of the disease and an increase in the number of smokers worldwide. The goal of our study is to identify disease variability in the gene expression profiles of COPD subjects compared to controls, by reanalyzing pre-existing, publicly available microarray expression datasets. Our inclusion criteria for microarray datasets selected for smoking status, age and sex of blood donors reported. Our datasets used Affymetrix, Agilent microarray platforms (7 datasets, 1,262 samples). We re-analyzed the curated raw microarray expression data using R packages, and used Box-Cox power transformations to normalize datasets. To identify significant differentially expressed genes we used generalized least squares models with disease state, age, sex, smoking status and study as effects that also included binary interactions, followed by likelihood ratio tests (LRT). We found 3,315 statistically significant (Storey-adjusted q-value <0.05) differentially expressed genes with respect to disease state (COPD or control). We further filtered these genes for biological effect using results from LRT q-value <0.05 and model estimates’ 10% two-tailed quantiles of mean differences between COPD and control), to identify 679 genes. Through analysis of disease, sex, age, and also smoking status and disease interactions we identified differentially expressed genes involved in a variety of immune responses and cell processes in COPD. We also trained a logistic regression model using the common array genes as features, which enabled prediction of disease status with 81.7% accuracy. Our results give potential for improving the diagnosis of COPD through blood and highlight novel gene expression disease signatures.

Microarray Gene Expression Dataset Re-analysis Reveals Variability in Influenza Infection and Vaccination

Influenza, a communicable disease, affects thousands of people worldwide. Young children, elderly, immunocompromised individuals and pregnant women are at higher risk for being infected by the influenza virus. Our study aims to highlight differentially expressed genes in influenza disease compared to influenza vaccination, including variability due to age and sex. To accomplish our goals, we conducted a meta-analysis using publicly available microarray expression data. Our inclusion criteria included subjects with influenza, subjects who received the influenza vaccine and healthy controls. We curated 18 microarray datasets for a total of 3,481 samples (1,277 controls, 297 influenza infection, 1,907 influenza vaccination). We pre-processed the raw microarray expression data in R using packages available to pre-process Affymetrix and Illumina microarray platforms. We used a Box-Cox power transformation of the data prior to our down-stream analysis to identify differentially expressed genes. Statistical analyses were based on linear mixed effects model with all study factors and successive likelihood ratio tests (LRT) to identify differentially-expressed genes. We filtered LRT results by disease (Bonferroni adjusted p < 0.05) and used a two-tailed 10% quantile cutoff to identify biologically significant genes. Furthermore, we assessed age and sex effects on the disease genes by filtering for genes with a statistically significant (Bonferroni adjusted p < 0.05) interaction between disease and age, and disease and sex. We identified 4,889 statistically significant genes when we filtered the LRT results by disease factor, and gene enrichment analysis (gene ontology and pathways) included innate immune response, viral process, defense response to virus, Hematopoietic cell lineage and NF-kappa B signaling pathway. Our quantile filtered gene lists comprised of 978 genes each associated with influenza infection and vaccination. We also identified 907 and 48 genes with statistically significant (Bonferroni adjusted p < 0.05) disease-age and disease-sex interactions, respectively. Our meta-analysis approach highlights key gene signatures and their associated pathways for both influenza infection and vaccination. We also were able to identify genes with an age and sex effect. This gives potential for improving current vaccines and exploring genes that are expressed equally across ages when considering universal vaccinations for influenza.