Gene Expression and Methylation Analysis of ABCA7 in Patients with Alzheimer's Disease

Classifying Alzheimer's disease and normal subjects using machine learning techniques and genetic-environmental features

BACKGROUND

Alzheimer's disease (AD) is complicated by multiple environmental and polygenetic factors. The accuracy of artificial neural networks (ANNs) incorporating the common factors for identifying AD has not been evaluated.

METHODS

A total of 184 probable AD patients and 3773 healthy individuals aged 65 and over were enrolled. AD-related genes (51 SNPs) and 8 environmental factors were selected as features for multilayer ANN modeling. Random Forest (RF) and Support Vector Machine with RBF kernel (SVM) were also employed for comparison. Model results were verified using traditional statistics.

RESULTS

The ANN achieved high accuracy (0.98), sensitivity (0.95), and specificity (0.96) in the intrinsic test for AD classification. Excluding age and genetic data still yielded favorable results (accuracy: 0.97, sensitivity: 0.94, specificity: 0.96). The assigned weights to ANN features highlighted the importance of mental evaluation, years of education, and specific genetic variations (CASS4 rs7274581, PICALM rs3851179, and TOMM40 rs2075650) for AD classification. Receiver operating characteristic analysis revealed AUC values of 0.99 (intrinsic test), 0.60 (TWB-GWA), and 0.72 (CG-WGS), with slightly lower AUC values (0.96, 0.80, 0.52) when excluding age in ANN. The performance of the ANN model in AD classification was comparable to RF, SVM (linear kernel), and SVM (RBF kernel).

CONCLUSION

The ANN model demonstrated good sensitivity, specificity, and accuracy in AD classification. The top-weighted SNPs for AD prediction were CASS4 rs7274581, PICALM rs3851179, and TOMM40 rs2075650. The ANN model performed similarly to RF and SVM, indicating its capability to handle the complexity of AD as a disease entity.

Identification of candidate DNA methylation biomarkers related to Alzheimer's disease risk by integrating genome and blood methylome data

Alzheimer disease (AD) is a common neurodegenerative disease with a late onset. It is critical to identify novel blood-based DNA methylation biomarkers to better understand the extent of the molecular pathways affected in AD. Two sets of blood DNA methylation genetic prediction models developed using different reference panels and modelling strategies were leveraged to evaluate associations of genetically predicted DNA methylation levels with AD risk in 111,326 (46,828 proxy) cases and 677,663 controls. A total of 1,168 cytosine-phosphate-guanine (CpG) sites showed a significant association with AD risk at a false discovery rate (FDR) < 0.05. Methylation levels of 196 CpG sites were correlated with expression levels of 130 adjacent genes in blood. Overall, 52 CpG sites of 32 genes showed consistent association directions for the methylation-gene expression-AD risk, including nine genes (CNIH4, THUMPD3, SERPINB9, MTUS1, CISD1, FRAT2, CCDC88B, FES, and SSH2) firstly reported as AD risk genes. Nine of 32 genes were enriched in dementia and AD disease categories (P values ranged from 1.85 × 10-4 to 7.46 × 10-6), and 19 genes in a neurological disease network (score = 54) were also observed. Our findings improve the understanding of genetics and etiology for AD.

Association of Blood-Based DNA Methylation Markers With Late-Onset Alzheimer Disease: A Potential Diagnostic Approach

BACKGROUND AND OBJECTIVES

There is an urgent need to identify novel noninvasive biomarkers for Alzheimer disease (AD) diagnosis. Recent advances in blood-based measurements of phosphorylated tau (pTau) species are promising but still insufficient to address clinical needs. Epigenetics has been shown to be helpful to better understand AD pathogenesis. Epigenetic biomarkers have been successfully implemented in other medical disciplines, such as oncology. The objective of this study was to explore the diagnostic accuracy of a blood-based DNA methylation marker panel as a noninvasive tool to identify patients with late-onset Alzheimer compared with age-matched controls.

METHODS

A case-control study was performed. Blood DNA methylation levels at 46 cytosine-guanine sites (21 genes selected after a comprehensive literature search) were measured by bisulfite pyrosequencing in patients with "probable AD dementia" following National Institute on Aging and the Alzheimer's Association guidelines (2011) and age-matched and sex-matched controls recruited at Neurology Department-University Hospital of Navarre, Spain, selected by convenience sampling. Plasma pTau181 levels were determined by Simoa technology. Multivariable logistic regression analysis was performed to explore the optimal model to discriminate patients with AD from controls. Furthermore, we performed a stratified analysis by sex.

RESULTS

The final study cohort consisted of 80 patients with AD (age: median [interquartile range] 79 [11] years; 58.8% female) and 100 cognitively healthy controls (age 77 [10] years; 58% female). A panel including DNA methylation levels at NXN, ABCA7, and HOXA3 genes and plasma pTau181 significantly improved (area under the receiver operating characteristic curve 0.93, 95% CI 0.89-0.97) the diagnostic performance of a single pTau181-based model, adjusted for age, sex, and APOE ɛ4 genotype. The sensitivity and specificity of this panel were 83.30% and 90.00%, respectively. After sex-stratified analysis, HOXA3 DNA methylation levels showed consistent association with AD.

DISCUSSION

These results highlight the potential translational value of blood-based DNA methylation biomarkers for noninvasive diagnosis of AD.

REGISTRATION INFORMATION

Research Ethics Committee of the University Hospital of Navarre (PI17/02218).

ABCA7-Associated Clinical Features and Molecular Mechanisms in Alzheimer's Disease

Alzheimer's disease (AD) is the most common type of neurodegenerative disease and its pathogenesis is still unclear. Genetic factors are thought to account for a large proportion of the overall AD phenotypes. ATP-binding cassette transporter A7 (ABCA7) is one of the most important risk gene for AD. Multiple forms of ABCA7 variants significantly increase the risk of AD, such as single-nucleotide polymorphisms, premature termination codon variants, missense variants, variable number tandem repeat, mutations, and alternative splicing. AD patients with ABCA7 variants usually exhibit typical clinical and pathological features of traditional AD with a wide age of onset range. ABCA7 variants can alter ABCA7 protein expression levels and protein structure to affect protein functions such as abnormal lipid metabolism, amyloid precursor protein (APP) processing, and immune cell function. Specifically, ABCA7 deficiency can cause neuronal apoptosis by inducing endoplasmic reticulum stress through the PERK/eIF2α pathway. Second, ABCA7 deficiency can increase Aβ production by upregulating the SREBP2/BACE1 pathway and promoting APP endocytosis. In addition, the ability of microglia to phagocytose and degrade Aβ is destroyed by ABCA7 deficiency, leading to reduced clearance of Aβ. Finally, disturbance of lipid metabolism may also be an important method by which ABCA7 variants influence the incidence rate of AD. In the future, more attention should be given to different ABCA7 variants and ABCA7 targeted therapies for AD.

Gene Expression Profiling as a Novel Diagnostic Tool for Neurodegenerative Disorders

There is a lack of effective diagnostic biomarkers for neurodegenerative disorders (NDDs). Here, we established gene expression profiles for diagnosing Alzheimer’s disease (AD), Parkinson’s disease (PD), and vascular (VaD)/mixed dementia. Patients with AD had decreased APOE, PSEN1, and ABCA7 mRNA expression. Subjects with VaD/mixed dementia had 98% higher PICALM mRNA levels, but 75% lower ABCA7 mRNA expression than healthy individuals. Patients with PD and PD-related disorders showed increased SNCA mRNA levels. There were no differences in mRNA expression for OPRK1, NTRK2, and LRRK2 between healthy subjects and NDD patients. APOE mRNA expression had high diagnostic accuracy for AD, and moderate accuracy for PD and VaD/mixed dementia. PSEN1 mRNA expression showed promising accuracy for AD. PICALM mRNA expression was less accurate as a biomarker for AD. ABCA7 and SNCA mRNA expression showed high-to-excellent diagnostic accuracy for AD and PD, and moderate-to-high accuracy for VaD/mixed dementia. The APOE E4 allele reduced APOE expression in patients with different APOE genotypes. There was no association between PSEN1, PICALM, ABCA7, and SNCA gene polymorphisms and expression. Our study suggests that gene expression analysis has diagnostic value for NDDs and provides a liquid biopsy alternative to current diagnostic methods.

Bioinformatics and Next-Generation Data Analysis for Identification of Genes and Molecular Pathways Involved in Subjects with Diabetes and Obesity

Background and Objectives: A subject with diabetes and obesity is a class of the metabolic disorder. The current investigation aimed to elucidate the potential biomarker and prognostic targets in subjects with diabetes and obesity. Materials and Methods: The next-generation sequencing (NGS) data of GSE132831 was downloaded from Gene Expression Omnibus (GEO) database. Functional enrichment analysis of DEGs was conducted with ToppGene. The protein-protein interactions network, module analysis, target gene-miRNA regulatory network and target gene-TF regulatory network were constructed and analyzed. Furthermore, hub genes were validated by receiver operating characteristic (ROC) analysis. A total of 872 DEGs, including 439 up-regulated genes and 433 down-regulated genes were observed. Results: Second, functional enrichment analysis showed that these DEGs are mainly involved in the axon guidance, neutrophil degranulation, plasma membrane bounded cell projection organization and cell activation. The top ten hub genes (MYH9, FLNA, DCTN1, CLTC, ERBB2, TCF4, VIM, LRRK2, IFI16 and CAV1) could be utilized as potential diagnostic indicators for subjects with diabetes and obesity. The hub genes were validated in subjects with diabetes and obesity. Conclusion: This investigation found effective and reliable molecular biomarkers for diagnosis and prognosis by integrated bioinformatics analysis, suggesting new and key therapeutic targets for subjects with diabetes and obesity.

SNP-by-CpG Site Interactions in ABCA7 Are Associated with Cognition in Older African Americans

SNPs in ABCA7 confer the largest genetic risk for Alzheimer's Disease (AD) in African Americans (AA) after APOE ε4. However, the relationship between ABCA7 and cognitive function has not been thoroughly examined. We investigated the effects of five known AD risk SNPs and 72 CpGs in ABCA7, as well as their interactions, on general cognitive function (cognition) in 634 older AA without dementia from Genetic Epidemiology Network of Arteriopathy (GENOA). Using linear mixed models, no SNP or CpG was associated with cognition after multiple testing correction, but five CpGs were nominally associated (p < 0.05). Four SNP-by-CpG interactions were associated with cognition (FDR q < 0.1). Contrast tests show that methylation is associated with cognition in some genotype groups (p < 0.05): a 1% increase at cg00135882 and cg22271697 is associated with a 0.68 SD decrease and 0.14 SD increase in cognition for those with the rs3764647 GG/AG (p = 0.004) and AA (p = 2 × 10-4) genotypes, respectively. In addition, a 1% increase at cg06169110 and cg17316918 is associated with a 0.37 SD decrease (p = 2 × 10-4) and 0.33 SD increase (p = 0.004), respectively, in cognition for those with the rs115550680 GG/AG genotype. While AD risk SNPs in ABCA7 were not associated with cognition in this sample, some have interactions with proximal methylation on cognition.

Prediction of Alzheimer’s Disease Using Patterns of Methylation Levels in Key Immunologic-Related Genes

Background: DNA methylation is expected to become a kind of new diagnosis and treatment method of Alzheimer’s disease (AD). Neuroinflammation- and immune-related pathways represent one of the major genetic risk factors for AD. Objective: We aimed to investigate DNA methylation levels of 7 key immunologic-related genes in peripheral blood and appraise their applicability in the diagnosis of AD. Methods: Methylation levels were obtained from 222 participants (101 AD, 72 MC, 49 non-cognitively impaired controls). Logistic regression models for diagnosing AD were established after least absolute shrinkage and selection operator (LASSO) and best subset selection (BSS), evaluated by respondent working curve and decision curve analysis for sensitivity. Results: Six differentially methylated positions (DMPs) in the MCI group and 64 in the AD group were found, respectively. Among them, there were 2 DMPs in the MCI group and 30 DMPs in the AD group independent of age, gender, and APOE4 carriers (p <  0.05). AD diagnostic prediction models differentiated AD from normal controls both in a training dataset (LASSO: 8 markers, including methylation levels at ABCA7_1040077, CNR1_88166293, CX3CR1_39322324, LRRK2_40618505, LRRK2_40618493, NGFR_49496745, TARDBP_11070956, TARDBP_11070840, area under the curve [AUC] = 0.81; BSS: 2 markers, including methylation levels at ABCA7_1040077 and CX3CR1_39322324, AUC = 0.80) and a testing dataset (AUC = 0.84, AUC = 0.82, respectively). Conclusion: Our work indicated that methylation levels of 7 key immunologic-related genes (ABCA7, CNR1, CX3CR1, CSF1 R, LRRK2, NGFR, and TARDBP) in peripheral blood was altered in AD and the models including methylation of immunologic-related genes biomarkers improved prediction of AD.

Dietary Restriction and Rapamycin Affect Brain Aging in Mice by Attenuating Age-Related DNA Methylation Changes

The fact that dietary restriction (DR) and long-term rapamycin treatment (RALL) can ameliorate the aging process has been reported by many researchers. As the interface between external and genetic factors, epigenetic modification such as DNA methylation may have latent effects on the aging rate at the molecular level. To understand the mechanism behind the impacts of dietary restriction and rapamycin on aging, DNA methylation and gene expression changes were measured in the hippocampi of different-aged mice. Examining the single-base resolution of DNA methylation, we discovered that both dietary restriction and rapamycin treatment can maintain DNA methylation in a younger state compared to normal-aged mice. Through functional enrichment analysis of genes in which DNA methylation or gene expression can be affected by DR/RALL, we found that DR/RALL may retard aging through a relationship in which DNA methylation and gene expression work together not only in the same gene but also in the same biological process. This study is instructive for understanding the maintenance of DNA methylation by DR/RALL in the aging process, as well as the role of DR and RALL in the amelioration of aging.

Pharmacogenomics of Alzheimer's Disease: Novel Strategies for Drug Utilization and Development

Alzheimer's disease (AD) is a priority health problem in developed countries with a high cost to society. Approximately 20% of direct costs are associated with pharmacological treatment. Over 90% of patients require multifactorial treatments, with risk of adverse drug reactions (ADRs) and drug-drug interactions (DDIs) for the treatment of concomitant diseases such as hypertension (>25%), obesity (>70%), diabetes mellitus type 2 (>25%), hypercholesterolemia (40%), hypertriglyceridemia (20%), metabolic syndrome (20%), hepatobiliary disorder (15%), endocrine/metabolic disorders (>20%), cardiovascular disorder (40%), cerebrovascular disorder (60-90%), neuropsychiatric disorders (60-90%), and cancer (10%).For the past decades, pharmacological studies in search of potential treatments for AD focused on the following categories: neurotransmitter enhancers (11.38%), multitarget drugs (2.45%), anti-amyloid agents (13.30%), anti-tau agents (2.03%), natural products and derivatives (25.58%), novel synthetic drugs (8.13%), novel targets (5.66%), repository drugs (11.77%), anti-inflammatory drugs (1.20%), neuroprotective peptides (1.25%), stem cell therapy (1.85%), nanocarriers/nanotherapeutics (1.52%), and other compounds (<1%).Pharmacogenetic studies have shown that the therapeutic response to drugs in AD is genotype-specific in close association with the gene clusters that constitute the pharmacogenetic machinery (pathogenic, mechanistic, metabolic, transporter, pleiotropic genes) under the regulatory control of epigenetic mechanisms (DNA methylation, histone/chromatin remodeling, microRNA regulation). Most AD patients (>60%) are carriers of over ten pathogenic genes. The genes that most frequently (>50%) accumulate pathogenic variants in the same AD case are A2M (54.38%), ACE (78.94%), BIN1 (57.89%), CLU (63.15%), CPZ (63.15%), LHFPL6 (52.63%), MS4A4E (50.87%), MS4A6A (63.15%), PICALM (54.38%), PRNP (80.7059), and PSEN1 (77.19%). There is also an accumulation of 15 to 26 defective pharmagenes in approximately 85% of AD patients. About 50% of AD patients are carriers of at least 20 mutant pharmagenes, and over 80% are deficient metabolizers for the most common drugs, which are metabolized via the CYP2D6, CYP2C9, CYP2C19, and CYP3A4/5 enzymes.The implementation of pharmacogenetics can help optimize drug development and the limited therapeutic resources available to treat AD, and personalize the use of anti-dementia drugs in combination with other medications for the treatment of concomitant disorders.

PICALM mRNA Expression in the Blood of Patients with Neurodegenerative Diseases and Geriatric Depression

BACKGROUND

Phosphatidylinositol-binding clathrin assembly protein (PICALM) is a validated genetic risk factor for late-onset Alzheimer's disease (AD) and is associated with other neurodegenerative diseases. However, PICALM expression in the blood of neurodegenerative diseases remains elusive.

OBJECTIVE

This study aimed to assess the usefulness of PICALM expression levels in the blood of patients with AD, Parkinson's disease (PD), dementia with Lewy bodies (DLB), and geriatric major depressive disorder (MDD) as a diagnostic biomarker.

METHODS

In total, 45, 20, 21, and 19 patients with AD, PD, DLB, and geriatric MDD, respectively, and 54 healthy controls (HCs) were enrolled in the study. Expression data from Gene Expression Omnibus database (GSE97760), (GSE133347) and (GSE98793), (GSE48350), and (GSE144459) were used to validate the ability of biomarkers in the blood of patients with AD, PD, geriatric MDD, and a postmortem human AD brain and animal model of AD (3xTg-AD mouse), respectively.

RESULTS

PICALM mRNA expression in human blood was significantly increased in patients with AD compared with that in HCs. PICALM mRNA expression and age were negatively correlated only in patients with AD. PICALM mRNA expression in human blood was significantly lower in patients with PD than in HCs. No changes in PICALM mRNA expression were found in patients with DLB and geriatric MDD.

CONCLUSION

PICALM mRNA expression in blood was higher in patients with AD, but lower in patients with PD, which suggests that PICALM mRNA expression in human blood may be a useful biomarker for differentiating neurodegenerative diseases and geriatric MDD.

Roles and Mechanisms of DNA Methylation in Vascular Aging and Related Diseases

Vascular aging is a pivotal risk factor promoting vascular dysfunction, the development and progression of vascular aging-related diseases. The structure and function of endothelial cells (ECs), vascular smooth muscle cells (VSMCs), fibroblasts, and macrophages are disrupted during the aging process, causing vascular cell senescence as well as vascular dysfunction. DNA methylation, an epigenetic mechanism, involves the alteration of gene transcription without changing the DNA sequence. It is a dynamically reversible process modulated by methyltransferases and demethyltransferases. Emerging evidence reveals that DNA methylation is implicated in the vascular aging process and plays a central role in regulating vascular aging-related diseases. In this review, we seek to clarify the mechanisms of DNA methylation in modulating ECs, VSMCs, fibroblasts, and macrophages functions and primarily focus on the connection between DNA methylation and vascular aging-related diseases. Therefore, we represent many vascular aging-related genes which are modulated by DNA methylation. Besides, we concentrate on the potential clinical application of DNA methylation to serve as a reliable diagnostic tool and DNA methylation-based therapeutic drugs for vascular aging-related diseases.

Epigenetics: Recent Advances and Its Role in the Treatment of Alzheimer's Disease

Objective: This review summarizes recent findings on the epigenetics of Alzheimer's disease (AD) and provides therapeutic strategies for AD.

Methods: We searched the following keywords: “genetics,” “epigenetics,” “Alzheimer's disease,” “DNA methylation,” “DNA hydroxymethylation,” “histone modifications,” “non-coding RNAs,” and “therapeutic strategies” in PubMed.

Results: In this review, we summarizes recent studies of epigenetics in AD, including DNA methylation/hydroxymethylation, histone modifications, and non-coding RNAs. There are no consistent results of global DNA methylation/hydroxymethylation in AD. Epigenetic genome-wide association studies show that many differentially methylated sites exist in AD. Several studies investigate the role of histone modifications in AD; for example, histone acetylation decreases, whereas H3 phosphorylation increases significantly in AD. In addition, non-coding RNAs, such as microRNA-16 and BACE1-antisense transcript (BACE1-AS), are associated with the pathology of AD. These epigenetic changes provide us with novel insights into the pathogenesis of AD and may be potential therapeutic strategies for AD.

Conclusion: Epigenetics is associated with the pathogenesis of AD, including DNA methylation/hydroxymethylation, histone modifications, and non-coding RNAs, which provide potential therapeutic strategies for AD.

Lower DNA methylation levels in CpG island shores of CR1, CLU, and PICALM in the blood of Japanese Alzheimer's disease patients

The aim of the present study was to (1) investigate the relationship between late-onset Alzheimer’s disease (AD) and DNA methylation levels in six of the top seven AD-associated genes identified through a meta-analysis of recent genome wide association studies, APOE, BIN1, PICALM, CR1, CLU, and ABCA7, in blood, and (2) examine its applicability to the diagnosis of AD. We examined methylation differences at CpG island shores in the six genes using Sanger sequencing, and one of two groups of 48 AD patients and 48 elderly controls was used for a test or replication analysis. We found that methylation levels in three out of the six genes, CR1, CLU, and PICALM, were significantly lower in AD subjects. The combination of CLU methylation levels and the APOE genotype classified AD patients with AUC = 0.84 and 0.80 in the test and replication analyses, respectively. Our study implicates methylation differences at the CpG island shores of AD-associated genes in the onset of AD and suggests their diagnostic value.

Identifying Blood Transcriptome Biomarkers of Alzheimer's Disease Using Transgenic Mice

The testing of pathological biomarkers of Alzheimer's disease (AD), such as amyloid beta and tau, is time-consuming, expensive, and invasive. Here, we used 3xTg-AD mice to identify and validate putative novel blood transcriptome biomarkers of AD that can potentially be identified in the blood of patients. mRNA was extracted from the blood and hippocampus of 3xTg-AD and control mice at different ages and used for microarray analysis. Network and functional analyses revealed that the differentially expressed genes between AD and control mice modulated the immune and neuroinflammation systems. Five novel gene transcripts (Cdkn2a, Apobec3, Magi2, Parp3, and Cass4) showed significant increases with age, and their expression in the blood was collated with that in the hippocampus only in AD mice. We further assessed previously identified candidate biomarker genes. The expression of Trem1 and Trem2 in both the blood and brain was significantly increased with age. Decreased Tomm40 and increased Pink1 mRNA levels were observed in the mouse blood. The changes in the expression of Snca and Apoe mRNA in the mouse blood and brain were similar to those found in human AD blood. Our results demonstrated that the immune and neuroinflammatory system is involved in the pathophysiologies of aging and AD and that the blood transcriptome might be useful as a biomarker of AD.

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.

Pharmacogenomics of Cognitive Dysfunction and Neuropsychiatric Disorders in Dementia

Symptomatic interventions for patients with dementia involve anti-dementia drugs to improve cognition, psychotropic drugs for the treatment of behavioral disorders (BDs), and different categories of drugs for concomitant disorders. Demented patients may take >6-10 drugs/day with the consequent risk for drug-drug interactions and adverse drug reactions (ADRs >80%) which accelerate cognitive decline. The pharmacoepigenetic machinery is integrated by pathogenic, mechanistic, metabolic, transporter, and pleiotropic genes redundantly and promiscuously regulated by epigenetic mechanisms. CYP2D6, CYP2C9, CYP2C19, and CYP3A4/5 geno-phenotypes are involved in the metabolism of over 90% of drugs currently used in patients with dementia, and only 20% of the population is an extensive metabolizer for this tetragenic cluster. ADRs associated with anti-dementia drugs, antipsychotics, antidepressants, anxiolytics, hypnotics, sedatives, and antiepileptic drugs can be minimized by means of pharmacogenetic screening prior to treatment. These drugs are substrates, inhibitors, or inducers of 58, 37, and 42 enzyme/protein gene products, respectively, and are transported by 40 different protein transporters. APOE is the reference gene in most pharmacogenetic studies. APOE-3 carriers are the best responders and APOE-4 carriers are the worst responders; likewise, CYP2D6-normal metabolizers are the best responders and CYP2D6-poor metabolizers are the worst responders. The incorporation of pharmacogenomic strategies for a personalized treatment in dementia is an effective option to optimize limited therapeutic resources and to reduce unwanted side-effects.

The combined risk effect among BIN1, CLU, and APOE genes in Alzheimer's disease

Genome-wide associations studies (GWAS) are detecting new variants associated with late-onset of Alzheimer’s disease (LOAD), a multifactorial neurodegenerative disorder. The variants rs744373 BIN1, rs11136000 CLU and rs3764650 ABCA7 uncovered by GWAS led to different AD pathways, such as metabolism, trafficking and endocytosis of lipids and inflammation. However, most of the association studies did not replicate these variants with significance. This could be due to a small power effect evident when these variants are tested independently with LOAD. Therefore, we aimed to investigate whether the combination of different variants would additively modify the risk of association with LOAD that is observed in GWAS. We performed an association study testing pairwise variants in metabolism, trafficking and endocytosis of lipid (rs429358 and rs7412 APOE, rs744373 BIN1, rs3764650 ABCA7 and rs11136000 CLU) pathways with LOAD in samples from southeastern Brazil. Our data suggest a risk effect for LOAD between APOE with CLU and APOE with BIN1 genes.

ABCA7 Gene Expression and Genetic Association Study in Schizophrenia

INTRODUCTION

Although ATP-binding cassette sub-family A member 7 gene (ABCA7) is known to be associated with Alzheimer's disease, the relationship between ABCA7 and schizophrenia has been unknown.

METHODS

Schizophrenia patients (n = 50; 24 males, 62.1 ± 0.50 years old) and age- and sex-matched healthy controls (n = 50) were recruited for the mRNA analysis. Additionally, a case-control study for the rs3764650 genotypes was performed with 1308 samples (control subjects; n = 527, schizophrenia patients; n = 781). All participants were Japanese, unrelated to each other, and living in the same area.

RESULTS

The distributions of the rs3764650 genotypes in schizophrenia patients were not different from that of controls. However, the ABCA7 mRNA expression levels in schizophrenia patients were significantly higher than those in controls by a logistic regression analysis. Additionally, the ABCA7 mRNA expression levels in schizophrenia patients were correlated with the rs3764650 genotypes in a dose-dependent manner.

DISCUSSION

The ABCA7 mRNA expression levels in peripheral blood with the rs3764650 genotypes may be related to pathological mechanisms in schizophrenia and may be a biological marker for schizophrenia.

The role of ABCA7 in Alzheimer's disease: evidence from genomics, transcriptomics and methylomics

Genome-wide association studies (GWAS) originally identified ATP-binding cassette, sub-family A, member 7 (ABCA7), as a novel risk gene of Alzheimer’s disease (AD). Since then, accumulating evidence from in vitro, in vivo, and human-based studies has corroborated and extended this association, promoting ABCA7 as one of the most important risk genes of both early-onset and late-onset AD, harboring both common and rare risk variants with relatively large effect on AD risk. Within this review, we provide a comprehensive assessment of the literature on ABCA7, with a focus on AD-related human -omics studies (e.g. genomics, transcriptomics, and methylomics). In European and African American populations, indirect ABCA7 GWAS associations are explained by expansion of an ABCA7 variable number tandem repeat (VNTR), and a common premature termination codon (PTC) variant, respectively. Rare ABCA7 PTC variants are strongly enriched in AD patients, and some of these have displayed inheritance patterns resembling autosomal dominant AD. In addition, rare missense variants are more frequent in AD patients than healthy controls, whereas a common ABCA7 missense variant may protect from disease. Methylation at several CpG sites in the ABCA7 locus is significantly associated with AD. Furthermore, ABCA7 contains many different isoforms and ABCA7 splicing has been shown to associate with AD. Besides associations with disease status, these genetic and epigenetic ABCA7 markers also showed significant correlations with AD endophenotypes; in particular amyloid deposition and brain morphology. In conclusion, human-based –omics studies provide converging evidence of (partial) ABCA7 loss as an AD pathomechanism, and future studies should make clear if interventions on ABCA7 expression can serve as a valuable therapeutic target for AD.

TREM1 mRNA Expression in Leukocytes and Cognitive Function in Japanese Patients with Alzheimer's Disease

BACKGROUND

Triggering receptor expressed on myeloid cells 2 (TREM2) activates the innate immune system, promotes phagocytosis by microglia, and is associated with Alzheimer's disease (AD). The possible role of a related molecule, TREM1, in AD remains unknown.

OBJECTIVE

We investigated a possible role for TREM1 in AD by determining the gene expression and methylation levels of TREM1 in leukocytes from AD patients.

METHODS

Fifty patients with AD and 50 age-matched healthy controls were enrolled. AD patients underwent a battery of neuropsychiatric tests. Peripheral blood samples were obtained from each participant, RNA and DNA were extracted, and samples were assessed for TREM1 mRNA expression and methylation rates at three CpG sites in the TREM1 promoter.

RESULTS

TREM1 mRNA expression levels in AD patients were significantly higher than those in controls (p = 0.008). TREM1 mRNA expression levels were not correlated with sex, age, duration of illness, APOE genotype, donepezil treatment, or scores of most neuropsychiatric tests. TREM1 mRNA expression levels in AD patients were correlated with the total score of the Montgomery-Åsberg Depression Rating Scale (p = 0.047, r = - 0.344). Methylation rates at the three CpG sites were significantly lower in AD patients than in controls. We also found a significant correlation between TREM1 mRNA expression and TREM1 DNA methylation rates (p < 0.001).

CONCLUSION

TREM1 may be associated with the immune responses in AD, and along with hypomethylation at CpG sites in the TREM1 promoter, may become part of a biomarker panel for AD pathogenesis.

Pharmacoepigenomic Interventions as Novel Potential Treatments for Alzheimer's and Parkinson's Diseases

Cerebrovascular and neurodegenerative disorders affect one billion people around the world and result from a combination of genomic, epigenomic, metabolic, and environmental factors. Diagnosis at late stages of disease progression, limited knowledge of gene biomarkers and molecular mechanisms of the pathology, and conventional compounds based on symptomatic rather than mechanistic features, determine the lack of success of current treatments, including current FDA-approved conventional drugs. The epigenetic approach opens new avenues for the detection of early presymptomatic pathological events that would allow the implementation of novel strategies in order to stop or delay the pathological process. The reversibility and potential restoring of epigenetic aberrations along with their potential use as targets for pharmacological and dietary interventions sited the use of epidrugs as potential novel candidates for successful treatments of multifactorial disorders involving neurodegeneration. This manuscript includes a description of the most relevant epigenetic mechanisms involved in the most prevalent neurodegenerative disorders worldwide, as well as the main potential epigenetic-based compounds under investigation for treatment of those disorders and their limitations.

Phenotypic Heterogeneity in Dementia: A Challenge for Epidemiology and Biomarker Studies

Dementia can result from a number of distinct diseases with differing etiology and pathophysiology. Even within the same disease, there is considerable phenotypic heterogeneity with varying symptoms and disease trajectories. Dementia diagnosis is thus very complex, time-consuming, and expensive and can only be made definitively post-mortem with histopathological confirmation. These inherent difficulties combined with the overlap of some symptoms and even neuropathological features, present a challenging problem for research in the field. This has likely hampered progress in epidemiological studies of risk factors and preventative interventions, as well as genetic and biomarker research. Resource limitations in large epidemiologically studies mean that limited diagnostic criteria are often used, which can result in phenotypically heterogeneous disease states being grouped together, potentially resulting in misclassification bias. When biomarkers are identified for etiologically heterogeneous diseases, they will have low specificity for any utility in clinical practice, even if their sensitivity is high. We highlight several challenges in in the field which must be addressed for the success of future genetic and biomarker studies, and may be key to the development of the most effective treatments. As a step toward achieving this goal, defining the dementia as a biological construct based on the presence of specific pathological features, rather than clinical symptoms, will enable more precise predictive models. It has the potential to lead to the discovery of novel genetic variants, as well as the identification of individuals at heightened risk of the disease, even prior to the appearance of clinical symptoms.

An intronic VNTR affects splicing of ABCA7 and increases risk of Alzheimer's disease

Mutations leading to premature termination codons in ATP-Binding Cassette Subfamily A Member 7 (ABCA7) are high penetrant risk factors of Alzheimer’s disease (AD). The influence of other genetic variants in ABCA7 and downstream functional mechanisms, however, is poorly understood. To address this knowledge gap, we investigated tandem repetitive regions in ABCA7 in a Belgian cohort of 1529 AD patients and control individuals and identified an intronic variable number tandem repeat (VNTR). We observed strong association between VNTR length and a genome-wide associated signal for AD in the ABCA7 locus. Expanded VNTR alleles were highly enriched in AD patients [odds ratio = 4.5 (1.3–24.2)], and VNTR length inversely correlated with amyloid β_1–42 in cerebrospinal fluid and ABCA7 expression. In addition, we identified three novel ABCA7 alternative splicing events. One isoform in particular—which is formed through exon 19 skipping—lacks the first nucleotide binding domain of ABCA7 and is abundant in brain tissue. We observed a tight correlation between exon 19 skipping and VNTR length. Our findings underline the importance of studying repetitive DNA in complex disorders and expand the contribution of genetic and transcript variation in ABCA7 to AD.

Peripheral DNA methylation, cognitive decline and brain aging: pilot findings from the Whitehall II imaging study

Aim:

The present study investigated the link between peripheral DNA methylation (DNAm), cognitive impairment and brain aging.

Methods:

We tested the association between blood genome-wide DNAm profiles using the Illumina 450K arrays, cognitive dysfunction and brain MRI measures in selected participants of the Whitehall II imaging sub-study.

Results:

Eight differentially methylated regions were associated with cognitive impairment. Accelerated aging based on the Hannum epigenetic clock was associated with mean diffusivity and global fractional anisotropy. We also identified modules of co-methylated loci associated with white matter hyperintensities. These co-methylation modules were enriched among pathways relevant to β-amyloid processing and glutamatergic signaling.

Conclusion:

Our data support the notion that blood DNAm changes may have utility as a biomarker for cognitive dysfunction and brain aging.

Blood DNA methylation as a potential biomarker of dementia: A systematic review

Dementia is a major public health issue with rising prevalence rates, but many individuals remain undiagnosed. Accurate and timely diagnosis is key for the optimal targeting of interventions. A noninvasive, easily measurable peripheral biomarker would have greatest utility in population-wide diagnostic screening. Epigenetics, including DNA methylation, is implicated in dementia; however, it is unclear whether epigenetic changes can be detected in peripheral tissue. This study aimed to systematically review the evidence for an association between dementia and peripheral DNA methylation. Forty-eight studies that measured DNA methylation in peripheral blood were identified, and 67% reported significant associations with dementia. However, most studies were underpowered and limited by their case-control design. We emphasize the need for future longitudinal studies on large well-characterized populations, measuring epigenetic patterns in asymptomatic individuals. A biomarker detectable in the preclinical stages of the disease would have the greatest utility in future intervention and treatment trials.