Genome-wide association analysis of age-at-onset in Alzheimer's disease

The therapeutic implications of all-in-one AAV-delivered epigenome-editing platform in neurodegenerative disorders

Safely and efficiently controlling gene expression is a long-standing goal of biomedical research, and CRISPR/Cas system can be harnessed to create powerful tools for epigenetic editing. Adeno-associated-viruses (AAVs) represent the delivery vehicle of choice for therapeutic platform. However, their small packaging capacity isn't suitable for large constructs including most CRISPR/dCas9-effector vectors. Thus, AAV-based CRISPR/Cas systems have been delivered via two separate viral vectors. Here we develop a compact CRISPR/dCas9-based repressor system packaged in AAV as a single optimized vector. The system comprises the small Staphylococcus aureus (Sa)dCas9 and an engineered repressor molecule, a fusion of MeCP2's transcription repression domain (TRD) and KRAB. The dSaCas9-KRAB-MeCP2(TRD) vector platform repressed robustly and sustainably the expression of multiple genes-of-interest, in vitro and in vivo, including ApoE, the strongest genetic risk factor for late onset Alzheimer's disease (LOAD). Our platform broadens the CRISPR/dCas9 toolset available for transcriptional manipulation of gene expression in research and therapeutic settings.

REELIN ameliorates Alzheimer's disease, but how?

Alzheimer's disease (AD) is the most prevalent type of dementia; therefore, there is a high demand for therapeutic medication targeting it. In this context, extensive research has been conducted to identify molecular targets for drugs. AD manifests through two primary pathological signs: senile plaques and neurofibrillary tangles, caused by accumulations of amyloid-beta (Aβ) and phosphorylated tau, respectively. Thus, studies concerning the molecular mechanisms underlying AD etiology have primarily focused on Aβ generation and tau phosphorylation, with the anticipation of uncovering a signaling pathway impacting these molecular processes. Over the past two decades, studies using not only experimental model systems but also examining human brains have accumulated fragmentary evidences suggesting that REELIN signaling pathway is deeply involved in AD. Here, we explore REELIN signaling pathway and its involvement in memory function within the brain and review studies investigating molecular connections between REELIN signaling pathway and AD etiology. This review aims to understand how the manipulation (activation) of this pathway might ameliorate the disease's etiology.

All-in-one AAV-delivered epigenome-editing platform: proof-of-concept and therapeutic implications for neurodegenerative disorders

Safely and efficiently controlling gene expression is a long-standing goal of biomedical research, and the recently discovered bacterial CRISPR/Cas system can be harnessed to create powerful tools for epigenetic editing. Current state-of-the-art systems consist of a deactivated-Cas9 nuclease (dCas9) fused to one of several epigenetic effector motifs/domains, along with a guide RNA (gRNA) which defines the genomic target. Such systems have been used to safely and effectively silence or activate a specific gene target under a variety of circumstances. Adeno-associated vectors (AAVs) are the therapeutic platform of choice for the delivery of genetic cargo; however, their small packaging capacity is not suitable for delivery of large constructs, which includes most CRISPR/dCas9-effector systems. To circumvent this, many AAV-based CRISPR/Cas tools are delivered in two pieces, from two separate viral cassettes. However, this approach requires higher viral payloads and usually is less efficient. Here we develop a compact dCas9-based repressor system packaged within a single, optimized AAV vector. The system uses a smaller dCas9 variant derived from Staphylococcus aureus ( Sa ). A novel repressor was engineered by fusing the small transcription repression domain (TRD) from MeCP2 with the KRAB repression domain. The final d Sa Cas9-KRAB-MeCP2(TRD) construct can be efficiently packaged, along with its associated gRNA, into AAV particles. Using reporter assays, we demonstrate that the platform is capable of robustly and sustainably repressing the expression of multiple genes-of-interest, both in vitro and in vivo . Moreover, we successfully reduced the expression of ApoE, the stronger genetic risk factor for late onset Alzheimer's disease (LOAD). This new platform will broaden the CRISPR/dCas9 toolset available for transcriptional manipulation of gene expression in research and therapeutic settings.

Integrative single-nucleus multi-omics analysis prioritizes candidate cis and trans regulatory networks and their target genes in Alzheimer's disease brains

BACKGROUND

The genetic underpinnings of late-onset Alzheimer's disease (LOAD) are yet to be fully elucidated. Although numerous LOAD-associated loci have been discovered, the causal variants and their target genes remain largely unknown. Since the brain is composed of heterogenous cell subtypes, it is imperative to study the brain on a cell subtype specific level to explore the biological processes underlying LOAD.

METHODS

Here, we present the largest parallel single-nucleus (sn) multi-omics study to simultaneously profile gene expression (snRNA-seq) and chromatin accessibility (snATAC-seq) to date, using nuclei from 12 normal and 12 LOAD brains. We identified cell subtype clusters based on gene expression and chromatin accessibility profiles and characterized cell subtype-specific LOAD-associated differentially expressed genes (DEGs), differentially accessible peaks (DAPs) and cis co-accessibility networks (CCANs).

RESULTS

Integrative analysis defined disease-relevant CCANs in multiple cell subtypes and discovered LOAD-associated cell subtype-specific candidate cis regulatory elements (cCREs), their candidate target genes, and trans-interacting transcription factors (TFs), some of which, including ELK1, JUN, and SMAD4 in excitatory neurons, were also LOAD-DEGs. Finally, we focused on a subset of cell subtype-specific CCANs that overlap known LOAD-GWAS regions and catalogued putative functional SNPs changing the affinities of TF motifs within LOAD-cCREs linked to LOAD-DEGs, including APOE and MYO1E in a specific subtype of microglia and BIN1 in a subpopulation of oligodendrocytes.

CONCLUSIONS

To our knowledge, this study represents the most comprehensive systematic interrogation to date of regulatory networks and the impact of genetic variants on gene dysregulation in LOAD at a cell subtype resolution. Our findings reveal crosstalk between epigenetic, genomic, and transcriptomic determinants of LOAD pathogenesis and define catalogues of candidate genes, cCREs, and variants involved in LOAD genetic etiology and the cell subtypes in which they act to exert their pathogenic effects. Overall, these results suggest that cell subtype-specific cis-trans interactions between regulatory elements and TFs, and the genes dysregulated by these networks contribute to the development of LOAD.

Determination of genetic correlation between tobacco smoking and coronary artery disease

Backgrounds

Tobacco smoking is an important risk factor for coronary artery disease (CAD), but the genetic mechanisms linking smoking to CAD remain largely unknown.

Methods

We analyzed summary data from the genome-wide association study (GWAS) of the UK Biobank for CAD, plasma lipid concentrations (n = 184,305), and smoking (n = 337,030) using different biostatistical methods, which included LD score regression and Mendelian randomization (MR).

Results

We identified SNPs shared by CAD and at least one smoking behavior, the genes where these SNPs are located were found to be significantly enriched in the processes related to lipoprotein metabolic, chylomicron-mediated lipid transport, lipid digestion, mobilization, and transport. The MR analysis revealed a positive correlation between smoking cessation and decreased risk for CAD when smoking cessation was considered as exposure (p = 0.001), and a negative correlation between the increased risk for CAD and smoking cessation when CAD was considered as exposure (p = 2.95E-08). This analysis further indicated that genetic liability for smoking cessation increased the risk of CAD.

Conclusion

These findings inform the concomitant conditions of CAD and smoking and support the idea that genetic liabilities for smoking behaviors are strongly associated with the risk of CAD.

Genome-wide association and replication studies for handedness in a Korean community-based cohort

INTRODUCTION

Handedness is a conspicuous characteristic in human behavior, with a worldwide proportion of approximately 90% of people preferring to use the right hand for many tasks. In the Korean population, the proportion of left-handedness is relatively low at approximately 7%-10%, similar to that in other East-Asian cultures in which the use of the left hand for writing and other public activities has historically been oppressed.

METHODS

In this study, we conducted two genome-wide association studies (GWASs) between right-handedness and left-handedness, and between right-handedness and ambidexterity using logistic regression analyses using a Korean community-based cohort. We also performed association analyses with previously reported variants and our findings.

RESULTS

A total of 8806 participants were included for analysis, and the results identified 28 left-handedness-associated and 15 ambidexterity-associated loci; of these, two left-handedness loci (NEIL3 [rs11726465] and SVOPL [rs117495448]) and one ambidexterity locus (PDE8B/WDR41 [rs118077080]) showed near genome-wide significance. Association analyses with previously reported variants replicated ANKS1B (rs7132513) in left-handedness and ANKIB1 (rs2040498) in ambidexterity.

CONCLUSION

The variants and positional candidate genes identified and replicated in this study were largely associated with brain development, cerebral asymmetry, neurological processes, and neuropsychiatric diseases in line with previous findings. As the first East-Asian GWAS related to handedness, these results may provide an intriguing reference for further human neurologic research in the future.

Identification of novel genes for age-at-onset of Alzheimer's disease by combining quantitative and survival trait analyses

INTRODUCTION

Our understanding of the genetic predisposition for age-at-onset (AAO) of Alzheimer's disease (AD) is limited. Here, we sought to identify genes modifying AAO and examined whether any have sex-specific effects.

METHODS

Genome-wide association analysis were performed on imputed genetic data of 9219 AD cases and 10,345 controls from 20 cohorts of the Alzheimer's Disease Genetics Consortium. AAO was modeled from cases directly and as a survival outcome.

RESULTS

We identified 11 genome-wide significant loci (P < 5 × 10-8 ), including six known AD-risk genes and five novel loci, UMAD1, LUZP2, ARFGEF2, DSCAM, and 4q25, affecting AAO of AD. Additionally, 39 suggestive loci showed strong association. Twelve loci showed sex-specific effects on AAO including CD300LG and MLX/TUBG2 for females and MIR4445 for males.

DISCUSSION

Genes that influence AAO of AD are excellent therapeutic targets for delaying onset of AD. Several loci identified include genes with promising functional implications for AD.

Investigation of the independent role of a rare APOE variant (L28P; APOE*4Pittsburgh) in late-onset Alzheimer disease

A rare missense APOE variant (L28P; APOE*4Pittsburgh), which is present only in populations with European ancestry, has been reported to be a risk factor for late-onset Alzheimer's disease (LOAD). However, due to the complete linkage disequilibrium of L28P with APOE*4 (C112R), its independent genetic association is uncertain. The original association study implicating L28P with LOAD risk was carried out in a relatively small sample size. In the current study, we have re-evaluated this association in a large case-control sample of 15,762 White U.S. subjects and investigated its independent effect in APOE 3/4 subjects, as L28P has been observed only in the heterozygous state of APOE*4 carriers and 3/4 is the most common genotype containing the APOE*4 allele. The heterozygous carrier frequency of L28P, all with APOE*4, was about 3-fold higher in AD cases than in cognitively intact controls (0.845% vs. 0.277%). The age- and sex-adjusted meta-analysis odds ratio (OR) was 2.87 (95% CI: 1.34 - 6.13; = 0.0066). Among APOE 3/4 subjects, age- and sex-adjusted meta-analysis OR was 1.53 (95% CI: 0.70 - 3.36; p = 0.28), indicating its effect was independent of APOE*4. The lack of statistical significance appears mainly due to the low power of 4138 subjects with the 3/4 genotype (12% power at α= 0.05) compared to the required sample of 139,088 subjects with the 3/4 genotype to detect an OR of 1.5 at α= 0.05 and 80% power. Our data suggesting that L28P has an independent genetic effect on AD risk is reinforced by earlier experimental findings showing that this mutation leads to significant structural and conformational changes in the ApoE4 molecule and can induce functional defects associated with neuronal Aβ42 accumulation and oxidative stress. Additional functional studies in cell-based systems and animal models will help to delineate its functional significance in the etiology of AD.

[A role of altered inflammation-related gene expression in cerebral small vessel disease with cognitive impairment]

OBJECTIVE

To identify the role of changes in the expression of inflammation-related genes in cerebral microangiopathy/cerebral small vessel disease (cSVD).

MATERIAL AND METHODS

Forty-four cSVD patients (mean age 61.4±9.2) and 11 controls (mean age 57.3±9.7) were studied. Gene expression was assessed on an individual NanoString nCounter panel of 58 inflammation-related genes and 4 reference genes. A set of genes was generated based on converging results of complete genome-wide association studies (GWAS) in cSVD and Alzheimer's disease (AD) and circulating markers associated with vascular wall and Brain lesions in cSVD. RNA was isolated from blood leukocytes and analyzed with the nCounter Analysis System, followed by analysis in nSolver 4.0. Results were verified by real-time PCR.

RESULTS

CSVD patients had a significant decrease in BIN1 (log2FC=-1.272; p=0.039) and VEGFA (log2FC=-1.441; p=0.038) expression compared to controls, which showed predictive ability for cSVD. The cut-off for BIN1 expression was 5.76 a.u. (sensitivity 73%; specificity 75%) and the cut-off for VEGFA expression was 9.27 a.u. (sensitivity 64%; specificity 86%). Reduced expression of VEGFA (p=0.011), VEGFC (p=0.017), CD2AP (p=0.044) was associated with cognitive impairment (CI). There was a significant direct correlation between VEGFC expression and the scores on the Montreal Cognitive Assessment test and between BIN1 and VEGFC expression and delayed memory.

CONCLUSION

The possible prediction of cSVD by reduced expression levels of BIN1, VEGFA and the association of clinically significant CI with reduced VEGFA and VEGFC expression indicate their importance in the development and progression of the disease. The established importance of these genes in the pathogenesis of AD suggests that similar changes in their expression profile in cSVD may be one of the conditions for the comorbidity of the two pathologies.

The APOE-TOMM40 Humanized Mouse Model: Characterization of Age, Sex, and PolyT Variant Effects on Gene Expression

BACKGROUND

The human chromosome 19q13.32 is a gene rich region and has been associated with multiple phenotypes, including late onset Alzheimer's disease (LOAD) and other age-related conditions.

OBJECTIVE

Here we developed the first humanized mouse model that contains the entire TOMM40 and APOE genes with all intronic and intergenic sequences including the upstream and downstream regions. Thus, the mouse model carries the human TOMM40 and APOE genes and their intact regulatory sequences.

METHODS

We generated the APOE-TOMM40 humanized mouse model in which the entire mouse region was replaced with the human (h)APOE-TOMM40 loci including their upstream and downstream flanking regulatory sequences using recombineering technologies. We then measured the expression of the human TOMM40 and APOE genes in the mice brain, liver, and spleen tissues using TaqMan based mRNA expression assays.

RESULTS

We investigated the effects of the '523' polyT genotype (S/S or VL/VL), sex, and age on the human TOMM40- and APOE-mRNAs expression levels using our new humanized mouse model. The analysis revealed tissue specific and shared effects of the '523' polyT genotype, sex, and age on the regulation of the human TOMM40 and APOE genes. Noteworthy, the regulatory effect of the '523' polyT genotype was observed for all studied organs.

CONCLUSION

The model offers new opportunities for basic science, translational, and preclinical drug discovery studies focused on the APOE genomic region in relation to LOAD and other conditions in adulthood.

Six genetically linked mutations in the CD36 gene significantly delay the onset of Alzheimer's disease

The risk of Alzheimer’s disease (AD) has a strong genetic component, also in the case of late-onset AD (LOAD). Attempts to sequence whole genome in large populations of subjects have identified only a few mutations common to most of the patients with AD. Targeting smaller well-characterized groups of subjects where specific genetic variations in selected genes could be related to precisely defined psychological traits typical of dementia is needed to better understand the heritability of AD. More than one thousand participants, categorized according to cognitive deficits, were assessed using 14 psychometric tests evaluating performance in five cognitive domains (attention/working memory, memory, language, executive functions, visuospatial functions). CD36 was selected as a gene previously shown to be implicated in the etiology of AD. A total of 174 polymorphisms were tested for associations with cognition-related traits and other AD-relevant data using the next generation sequencing. Several associations between single nucleotide polymorphisms (SNP’s) and the cognitive deficits have been found (rs12667404 with language performance, rs3211827 and rs41272372 with executive functions, rs137984792 with visuospatial performance). The most prominent association was found between a group of genotypes in six genetically linked and the age at which the AD patients presented with, or developed, a full-blown dementia. The identified alleles appear to be associated with a delay in the onset of LOAD. In silico studies suggested that the SNP’s alter the expression of CD36 thus potentially affecting CD36-related neuroinflammation and other molecular and cellular mechanisms known to be involved in the neuronal loss leading to AD. The main outcome of the study is an identification of a set of six new mutations apparently conferring a distinct protection against AD and delaying the onset by about 8 years. Additional mutations in CD36 associated with certain traits characteristic of the cognitive decline in AD have also been found.

The Big Picture of Neurodegeneration: A Meta Study to Extract the Essential Evidence on Neurodegenerative Diseases in a Network-Based Approach

The common features of all neurodegenerative diseases, including Alzheimer's disease, Parkinson's disease, Amyotrophic Lateral Sclerosis (ALS), and Huntington's disease, are the accumulation of aggregated and misfolded proteins and the progressive loss of neurons, leading to cognitive decline and locomotive dysfunction. Still, they differ in their ultimate manifestation, the affected brain region, and the kind of proteinopathy. In the last decades, a vast number of processes have been described as associated with neurodegenerative diseases, making it increasingly harder to keep an overview of the big picture forming from all those data. In this meta-study, we analyzed genomic, transcriptomic, proteomic, and epigenomic data of the aforementioned diseases using the data of 234 studies in a network-based approach to study significant general coherences but also specific processes in individual diseases or omics levels. In the analysis part, we focus on only some of the emerging findings, but trust that the meta-study provided here will be a valuable resource for various other researchers focusing on specific processes or genes contributing to the development of neurodegeneration.

Greater diffusion restriction in white matter in Preclinical Alzheimer's disease

OBJECTIVE

The Alzheimer's Continuum is biologically defined by beta-amyloid deposition which, at the earliest stages, is superimposed upon white matter degeneration in aging. However, the extent to which these co-occurring changes are characterized is relatively under-explored. The goal of this study was to use Diffusional Kurtosis Imaging (DKI) and biophysical modeling to detect and describe amyloid-related white matter changes in preclinical Alzheimer's disease (AD).

METHODS

Cognitively unimpaired participants ages 45-85 completed brain MRI, amyloid PET (florbetapir), neuropsychological testing, and other clinical measures at baseline in a cohort study. We tested whether beta amyloid-negative (AB-) and -positive (AB+) participants differed on DKI-based conventional (i.e. Fractional Anisotropy [FA], Mean Diffusivity [MD], Mean Kurtosis [MK]) and modeling (i.e. Axonal Water Fraction [AWF], extra-axonal radial diffusivity [D_e,⊥ ]) metrics, and whether these metrics were associated with other biomarkers.

RESULTS

We found significantly greater diffusion restriction (higher FA/AWF, lower MD/ D_e,⊥ ) in white matter in AB+ than AB- (partial η² = 0.08-0.19), more notably in the extra-axonal space within primarily late-myelinating tracts. Diffusion metrics predicted amyloid status incrementally over age (AUC=0.84) with modest yet selective associations, where AWF (a marker of axonal density) correlated with speed/executive functions and neurodegeneration, whereas D_e,⊥ (a marker of gliosis/myelin repair) correlated with amyloid deposition and white matter hyperintensity volume.

INTERPRETATION

These results support prior evidence of a non-monotonic change in diffusion behavior, where an early increase in diffusion restriction is hypothesized to reflect inflammation and myelin repair prior to an ensuing decrease in diffusion restriction, indicating glial and neuronal degeneration. This article is protected by copyright. All rights reserved.

Genomics and Functional Genomics of Alzheimer's Disease

Alzheimer's disease (AD) is a complex and multifactorial neurodegenerative disease. Due to its long clinical course and lack of an effective treatment, AD has become a major public health problem in the USA and worldwide. Due to variation in age-at-onset, AD is classified into early-onset (< 60 years) and late-onset (≥ 60 years) forms with early-onset accounting for only 5-10% of all cases. With the exception of a small number of early-onset cases that are afflicted because of high penetrant single gene mutations in APP, PSEN1, and PSEN2 genes, AD is genetically heterogeneous, especially the late-onset form having a polygenic or oligogenic risk inheritance. Since the identification of APOE as the most significant risk factor for late-onset AD in 1993, the path to the discovery of additional AD risk genes had been arduous until 2009 when the use of large genome-wide association studies opened up the discovery gateways that led the identification of ~ 95 additional risk loci from 2009 to early 2022. This article reviews the history of AD genetics followed by the potential molecular pathways and recent application of functional genomics methods to identify the causal AD gene(s) among the many genes that reside within a single locus. The ultimate goal of integrating genomics and functional genomics is to discover novel pathways underlying the AD pathobiology in order to identify drug targets for the therapeutic treatment of this heterogeneous disorder.

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.

A machine learning approach to brain epigenetic analysis reveals kinases associated with Alzheimer's disease

Alzheimer's disease (AD) is influenced by both genetic and environmental factors; thus, brain epigenomic alterations may provide insights into AD pathogenesis. Multiple array-based Epigenome-Wide Association Studies (EWASs) have identified robust brain methylation changes in AD; however, array-based assays only test about 2% of all CpG sites in the genome. Here, we develop EWASplus, a computational method that uses a supervised machine learning strategy to extend EWAS coverage to the entire genome. Application to six AD-related traits predicts hundreds of new significant brain CpGs associated with AD, some of which are further validated experimentally. EWASplus also performs well on data collected from independent cohorts and different brain regions. Genes found near top EWASplus loci are enriched for kinases and for genes with evidence for physical interactions with known AD genes. In this work, we show that EWASplus implicates additional epigenetic loci for AD that are not found using array-based AD EWASs.

GWAS-Top Polymorphisms Associated With Late-Onset Alzheimer Disease in Brazil: Pointing Out Possible New Culprits Among Non-Coding RNAs

Several genome-wide association studies (GWAS) have been carried out with late-onset Alzheimer's disease (LOAD), mainly in European and Asian populations. Different polymorphisms were associated, but several of them without a functional explanation. GWAS are fundamental for identifying loci associated with diseases, although they often do not point to causal polymorphisms. In this sense, functional investigations are a fundamental tool for discovering causality, although the failure of this validation does not necessarily indicate a non-causality. Furthermore, the allele frequency of associated genetic variants may vary widely between populations, requiring replication of these associations in other ethnicities. In this sense, our study sought to replicate in 150 AD patients and 114 elderly controls from the South Brazilian population 18 single-nucleotide polymorphisms (SNPs) associated with AD in European GWAS, with further functional investigation using bioinformatic tools for the associated SNPs. Of the 18 SNPs investigated, only four were associated in our population: rs769449 (APOE), rs10838725 (CELF1), rs6733839, and rs744373 (BIN1-CYP27C1). We identified 54 variants in linkage disequilibrium (LD) with the associated SNPs, most of which act as expression or splicing quantitative trait loci (eQTLs/sQTLs) in genes previously associated with AD or with a possible functional role in the disease, such as CELF1, MADD, MYBPC3, NR1H3, NUP160, SPI1, and TOMM40. Interestingly, eight of these variants are located within long non-coding RNA (lncRNA) genes that have not been previously investigated regarding AD. Some of these polymorphisms can result in changes in these lncRNAs' secondary structures, leading to either loss or gain of microRNA (miRNA)-binding sites, deregulating downstream pathways. Our pioneering work not only replicated LOAD association with polymorphisms not yet associated in the Brazilian population but also identified six possible lncRNAs that may interfere in LOAD development. The results lead us to emphasize the importance of functional exploration of associations found in large-scale association studies in different populations to base personalized and inclusive medicine in the future.

A Comprehensive Machine Learning Framework for the Exact Prediction of the Age of Onset in Familial and Sporadic Alzheimer's Disease

Machine learning (ML) algorithms are widely used to develop predictive frameworks. Accurate prediction of Alzheimer's disease (AD) age of onset (ADAOO) is crucial to investigate potential treatments, follow-up, and therapeutic interventions. Although genetic and non-genetic factors affecting ADAOO were elucidated by other research groups and ours, the comprehensive and sequential application of ML to provide an exact estimation of the actual ADAOO, instead of a high-confidence-interval ADAOO that may fall, remains to be explored. Here, we assessed the performance of ML algorithms for predicting ADAOO using two AD cohorts with early-onset familial AD and with late-onset sporadic AD, combining genetic and demographic variables. Performance of ML algorithms was assessed using the root mean squared error (RMSE), the R-squared (R2), and the mean absolute error (MAE) with a 10-fold cross-validation procedure. For predicting ADAOO in familial AD, boosting-based ML algorithms performed the best. In the sporadic cohort, boosting-based ML algorithms performed best in the training data set, while regularization methods best performed for unseen data. ML algorithms represent a feasible alternative to accurately predict ADAOO with little human intervention. Future studies may include predicting the speed of cognitive decline in our cohorts using ML.

Genetic Variability in Molecular Pathways Implicated in Alzheimer's Disease: A Comprehensive Review

Alzheimer's disease (AD) is a complex neurodegenerative disease, affecting a significant part of the population. The majority of AD cases occur in the elderly with a typical age of onset of the disease above 65 years. AD presents a major burden for the healthcare system and since population is rapidly aging, the burden of the disease will increase in the future. However, no effective drug treatment for a full-blown disease has been developed to date. The genetic background of AD is extensively studied; numerous genome-wide association studies (GWAS) identified significant genes associated with increased risk of AD development. This review summarizes more than 100 risk loci. Many of them may serve as biomarkers of AD progression, even in the preclinical stage of the disease. Furthermore, we used GWAS data to identify key pathways of AD pathogenesis: cellular processes, metabolic processes, biological regulation, localization, transport, regulation of cellular processes, and neurological system processes. Gene clustering into molecular pathways can provide background for identification of novel molecular targets and may support the development of tailored and personalized treatment of AD.

APOE: The New Frontier in the Development of a Therapeutic Target towards Precision Medicine in Late-Onset Alzheimer's

Alzheimer's disease (AD) has a critical unmet medical need. The consensus around the amyloid cascade hypothesis has been guiding pre-clinical and clinical research to focus mainly on targeting beta-amyloid for treating AD. Nevertheless, the vast majority of the clinical trials have repeatedly failed, prompting the urgent need to refocus on other targets and shifting the paradigm of AD drug development towards precision medicine. One such emerging target is apolipoprotein E (APOE), identified nearly 30 years ago as one of the strongest and most reproduceable genetic risk factor for late-onset Alzheimer's disease (LOAD). An exploration of APOE as a new therapeutic culprit has produced some very encouraging results, proving that the protein holds promise in the context of LOAD therapies. Here, we review the strategies to target APOE based on state-of-the-art technologies such as antisense oligonucleotides, monoclonal antibodies, and gene/base editing. We discuss the potential of these initiatives in advancing the development of novel precision medicine therapies to LOAD.

Quantitative endophenotypes as an alternative approach to understanding genetic risk in neurodegenerative diseases

Endophenotypes, as measurable intermediate features of human diseases, reflect underlying molecular mechanisms. The use of quantitative endophenotypes in genetic studies has improved our understanding of pathophysiological changes associated with diseases. The main advantage of the quantitative endophenotypes approach to study human diseases over a classic case-control study design is the inferred biological context that can enable the development of effective disease-modifying treatments. Here, we summarize recent progress on biomarkers for neurodegenerative diseases, including cerebrospinal fluid and blood-based, neuroimaging, neuropathological, and clinical studies. This review focuses on how endophenotypic studies have successfully linked genetic modifiers to disease risk, disease onset, or progression rate and provided biological context to genes identified in genome-wide association studies. Finally, we review critical methodological considerations for implementing this approach and future directions.

Genome-wide association study of brain amyloid deposition as measured by Pittsburgh Compound-B (PiB)-PET imaging

Deposition of amyloid plaques in the brain is one of the two main pathological hallmarks of Alzheimer's disease (AD). Amyloid positron emission tomography (PET) is a neuroimaging tool that selectively detects in vivo amyloid deposition in the brain and is a reliable endophenotype for AD that complements cerebrospinal fluid biomarkers with regional information. We measured in vivo amyloid deposition in the brains of ~1000 subjects from three collaborative AD centers and ADNI using 11C-labeled Pittsburgh Compound-B (PiB)-PET imaging followed by meta-analysis of genome-wide association studies, first to our knowledge for PiB-PET, to identify novel genetic loci for this endophenotype. The APOE region showed the most significant association where several SNPs surpassed the genome-wide significant threshold, with APOE*4 being most significant (P-meta = 9.09E-30; β = 0.18). Interestingly, after conditioning on APOE*4, 14 SNPs remained significant at P < 0.05 in the APOE region that were not in linkage disequilibrium with APOE*4. Outside the APOE region, the meta-analysis revealed 15 non-APOE loci with P < 1E-05 on nine chromosomes, with two most significant SNPs on chromosomes 8 (P-meta = 4.87E-07) and 3 (P-meta = 9.69E-07). Functional analyses of these SNPs indicate their potential relevance with AD pathogenesis. Top 15 non-APOE SNPs along with APOE*4 explained 25-35% of the amyloid variance in different datasets, of which 14-17% was explained by APOE*4 alone. In conclusion, we have identified novel signals in APOE and non-APOE regions that affect amyloid deposition in the brain. Our data also highlights the presence of yet to be discovered variants that may be responsible for the unexplained genetic variance of amyloid deposition.

Common Factors in Neurodegeneration: A Meta-Study Revealing Shared Patterns on a Multi-Omics Scale

Neurodegenerative diseases such as Alzheimer's disease (AD), Parkinson's disease (PD), Huntington's disease (HD), and amyotrophic lateral sclerosis (ALS) are heterogeneous, progressive diseases with frequently overlapping symptoms characterized by a loss of neurons. Studies have suggested relations between neurodegenerative diseases for many years (e.g., regarding the aggregation of toxic proteins or triggering endogenous cell death pathways). We gathered publicly available genomic, transcriptomic, and proteomic data from 177 studies and more than one million patients to detect shared genetic patterns between the neurodegenerative diseases on three analyzed omics-layers. The results show a remarkably high number of shared differentially expressed genes between the transcriptomic and proteomic levels for all conditions, while showing a significant relation between genomic and proteomic data between AD and PD and AD and ALS. We identified a set of 139 genes being differentially expressed in several transcriptomic experiments of all four diseases. These 139 genes showed overrepresented gene ontology (GO) Terms involved in the development of neurodegeneration, such as response to heat and hypoxia, positive regulation of cytokines and angiogenesis, and RNA catabolic process. Furthermore, the four analyzed neurodegenerative diseases (NDDs) were clustered by their mean direction of regulation throughout all transcriptomic studies for this set of 139 genes, with the closest relation regarding this common gene set seen between AD and HD. GO-Term and pathway analysis of the proteomic overlap led to biological processes (BPs), related to protein folding and humoral immune response. Taken together, we could confirm the existence of many relations between Alzheimer's disease, Parkinson's disease, Huntington's disease, and amyotrophic lateral sclerosis on transcriptomic and proteomic levels by analyzing the pathways and GO-Terms arising in these intersections. The significance of the connection and the striking relation of the results to processes leading to neurodegeneration between the transcriptomic and proteomic data for all four analyzed neurodegenerative diseases showed that exploring many studies simultaneously, including multiple omics-layers of different neurodegenerative diseases simultaneously, holds new relevant insights that do not emerge from analyzing these data separately. Furthermore, the results shed light on processes like the humoral immune response that have previously been described only for certain diseases. Our data therefore suggest human patients with neurodegenerative diseases should be addressed as complex biological systems by integrating multiple underlying data sources.

An exploration of genetic association tests for disease risk and age at onset

Risk genes influence the chance of an individual developing disease over their lifetime, although the age at onset (AAO) genes influence disease timing. These two categories are not disjoint; a gene that influences AAO might also appear to influence the risk. When an allele influences both AAO and risk, a reasonable question is whether we would have more power to detect association using a statistical test based on risk or AAO. To address this question, we compared power analytically for the Cochran-Armitage trend case-control test for risk and a linear regression case-only test for AAO. We also used simulations to compare the power of these tests with a 2-degree of freedom joint test (which combines the risk and AAO statistics) and the Cox proportional hazards survival model testing AAO (with censored data in controls). We found that when there is little heterogeneity, the case-control risk test has more power than the case-only AAO test (with equivalent sample sizes), but when the model is complex (e.g., with heterogeneity or reduced penetrance), the relationship reverses. The joint test generally outperforms the risk or AAO test alone and ultimately is our recommendation as a powerful alternative in many scenarios.

Genome-wide association study of psoriasis in an Egyptian population

Psoriasis is a chronic inflammatory disorder of the skin, with genetic factors reportedly involved in the disease pathogenesis. Numerous studies reported psoriasis candidate genes. However, these tend to involve mostly in the European and Asian populations. Here, we report the first genome-wide association study (GWAS) in an Egyptian population, identifying susceptibility variants for psoriasis using a two-stage case-control design. In the first discovery stage, we carried out a genome-wide association analysis using the Infinium^® Global Screening Array-24 v1.0, on 253 cases and 449 control samples of Egyptian descent. In the second replication stage, 26 single-nucleotide polymorphisms (SNPs) were selected for replication in additional 321 cases and 253 controls. In concordance with the findings from previous studies on other populations, we found a genome-wide significant association between the MHC locus and the disease at rs12199223 (P_comb  = 6.57 × 10^-18 ) and rs1265181 (P_comb  = 1.03 × 10^-10 ). Additionally, we identified a novel significant association with the disease at locus, 4q32.1 (rs12650590, P_comb  = 4.49 × 10^-08 ) in the vicinity of gene GUCY1A3, and multiple suggestive associations, for example rs10832027 (P_comb  = 7.28 × 10^-06 ) and rs3770019 (P_comb  = 1.02 × 10^-05 ). This proposes the existence of important interethnic genetic differences in psoriasis susceptibility. Further studies are necessary to elucidate the downstream pathways of the new candidate loci.

Risk prediction of late-onset Alzheimer's disease implies an oligogenic architecture

Genetic association studies have identified 44 common genome-wide significant risk loci for late-onset Alzheimer's disease (LOAD). However, LOAD genetic architecture and prediction are unclear. Here we estimate the optimal P-threshold (Poptimal) of a genetic risk score (GRS) for prediction of LOAD in three independent datasets comprising 676 cases and 35,675 family history proxy cases. We show that the discriminative ability of GRS in LOAD prediction is maximised when selecting a small number of SNPs. Both simulation results and direct estimation indicate that the number of causal common SNPs for LOAD may be less than 100, suggesting LOAD is more oligogenic than polygenic. The best GRS explains approximately 75% of SNP-heritability, and individuals in the top decile of GRS have ten-fold increased odds when compared to those in the bottom decile. In addition, 14 variants are identified that contribute to both LOAD risk and age at onset of LOAD.

Brain scans from 21,297 individuals reveal the genetic architecture of hippocampal subfield volumes

The hippocampus is a heterogeneous structure, comprising histologically distinguishable subfields. These subfields are differentially involved in memory consolidation, spatial navigation and pattern separation, complex functions often impaired in individuals with brain disorders characterized by reduced hippocampal volume, including Alzheimer's disease (AD) and schizophrenia. Given the structural and functional heterogeneity of the hippocampal formation, we sought to characterize the subfields' genetic architecture. T1-weighted brain scans (n = 21,297, 16 cohorts) were processed with the hippocampal subfields algorithm in FreeSurfer v6.0. We ran a genome-wide association analysis on each subfield, co-varying for whole hippocampal volume. We further calculated the single-nucleotide polymorphism (SNP)-based heritability of 12 subfields, as well as their genetic correlation with each other, with other structural brain features and with AD and schizophrenia. All outcome measures were corrected for age, sex and intracranial volume. We found 15 unique genome-wide significant loci across six subfields, of which eight had not been previously linked to the hippocampus. Top SNPs were mapped to genes associated with neuronal differentiation, locomotor behaviour, schizophrenia and AD. The volumes of all the subfields were estimated to be heritable (h2 from 0.14 to 0.27, all p < 1 × 10^-16) and clustered together based on their genetic correlations compared with other structural brain features. There was also evidence of genetic overlap of subicular subfield volumes with schizophrenia. We conclude that hippocampal subfields have partly distinct genetic determinants associated with specific biological processes and traits. Taking into account this specificity may increase our understanding of hippocampal neurobiology and associated pathologies.

Molecular basis of degenerative spinal disorders from a proteomic perspective (Review)

Intervertebral disc degeneration (IDD) and ligamentum flavum hypertrophy (LFH) are major causes of degenerative spinal disorders. Comparative and proteomic analysis was used to identify differentially expressed proteins (DEPs) in IDD and LFH discs compared with normal discs. Subsequent gene ontology term enrichment analysis and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis of the DEPs in human IDD discs or LFH samples were performed to identify the biological processes and signaling pathways involved in IDD and LFH. The PI3K-AKT signaling pathway, advanced glycation endproducts-receptor for advanced glycation endproducts signaling pathway, p53 signaling pathway, and transforming growth factor-b signaling pathway were activated in disc degeneration. This review summarizes the recently identified DEPs, including prolargin, fibronectin 1, cartilage intermediate layer protein, cartilage oligomeric matrix protein, and collagen types I, II and IV, and their pathophysiological roles in degenerative spinal disorders, and may provide a deeper understanding of the pathological processes of human generative spinal disorders. The present review aimed to summarize significantly changed proteins in degenerative spinal disorders and provide a deeper understanding to prevent these diseases.

Assessment of Molecular Subtypes in Thyrotoxic Periodic Paralysis and Graves Disease Among Chinese Han Adults: A Population-Based Genome-Wide Association Study

IMPORTANCE

Thyrotoxic periodic paralysis (TPP) is a potentially lethal complication of hyperthyroidism. However, only 1 specific susceptibility locus for TPP has been identified. Additional genetic determinants should be detected so that a prediction model can be constructed.

OBJECTIVE

To investigate the genetic architecture of TPP and distinguish TPP from Graves disease cohorts.

DESIGN, SETTING, AND PARTICIPANTS

This population-based case-control study used a 2-stage genome-wide association study to investigate the risk loci of TPP and weighted genetic risk score to construct a TPP prediction model with data from a Chinese Han population recruited in hospitals in China from March 2003 to December 2015. The analysis was conducted from November 2014 to August 2016.

MAIN OUTCOMES AND MEASURES

Loci specifically associated with TPP risk and those shared with Graves disease and prediction model of joint effects of TPP-specific loci.

RESULTS

A total of 537 patients with TPP (mean [SD] age, 35 [11] years; 458 male) 1519 patients with Graves disease and no history of TPP (mean [SD] age, 38 [13] years; 366 male), and 3249 healthy participants (mean [SD] age, 46 [10] years; 1648 male) were recruited from the Han population by hospitals throughout China. Two new TPP-specific susceptibility loci were identified: DCHS2 on 4q31.3 (rs1352714: odds ratio [OR], 1.58; 95% CI, 1.35-1.85; P = 1.24 × 10-8) and C11orf67 on 11q14.1 (rs2186564: OR, 1.50; 95% CI, 1.29-1.74; P = 2.80 × 10-7). One previously reported specific locus was confirmed on 17q24.3 near KCNJ2 (rs312729: OR, 2.08; 95% CI, 1.83-2.38; P = 8.02 × 10-29). Meanwhile, 2 risk loci (MHC and Xq21.1) were shared by Graves disease and TPP. After 2 years of treatment, the ratio of persistent thyrotropin receptor antibody positivity was higher in patients with TPP than in patients with Graves disease and no history of TPP (OR, 3.82; 95% CI, 2.04-7.16; P = 7.05 × 10-6). The prediction model using a weighted genetic risk score and 11 candidate TPP-specific single-nucleotide polymorphisms had an area under the curve of 0.80.

CONCLUSIONS AND RELEVANCE

These findings provide evidence that TPP is a novel molecular subtype of Graves disease. The newly identified loci, along with other previously reported loci, demonstrate the growing complexity of the heritable contribution to TPP pathogenesis. A complete genetic architecture will be helpful to understand the pathophysiology of TPP, and a useful prediction model could prevent the onset of TPP.

Identification of genetic heterogeneity of Alzheimer's disease across age

The risk of APOE for Alzheimer's disease (AD) is modified by age. Beyond APOE, the polygenic architecture may also be heterogeneous across age. We aim to investigate age-related genetic heterogeneity of AD and identify genomic loci with differential effects across age. Stratified gene-based genome-wide association studies and polygenic variation analyses were performed in the younger (60-79 years, N = 14,895) and older (≥80 years, N = 6559) age-at-onset groups using Alzheimer's Disease Genetics Consortium data. We showed a moderate genetic correlation (r_g = 0.64) between the two age groups, supporting genetic heterogeneity. Heritability explained by variants on chromosome 19 (harboring APOE) was significantly larger in younger than in older onset group (p < 0.05). APOE region, BIN1, OR2S2, MS4A4E, and PICALM were identified at the gene-based genome-wide significance (p < 2.73 × 10^-6) with larger effects at younger age (except MS4A4E). For the novel gene OR2S2, we further performed leave-one-out analyses, which showed consistent effects across subsamples. Our results suggest using genetically more homogeneous individuals may help detect additional susceptible loci.

A decade in psychiatric GWAS research

After more than 10 years of accumulated efforts, genome-wide association studies (GWAS) have led to many findings, most of which have been deposited into the GWAS Catalog. Between GWAS's inception and March 2017, the GWAS Catalog has collected 2429 studies, 1818 phenotypes, and 28,462 associated SNPs. We reclassified the psychology-related phenotypes into 217 reclassified phenotypes, which accounted for 514 studies and 7052 SNPs. In total, 1223 of the SNPs reached genome-wide significance. Of these, 147 were replicated for the same psychological trait in different studies. Another 305 SNPs were replicated within one original study. The SNPs rs2075650 and rs4420638 were linked to the most replications within a single reclassified phenotype or very similar reclassified phenotypes; both were associated with Alzheimer's disease (AD). Schizophrenia was associated with 74 within-phenotype SNPs reported in independents studies. Alzheimer's disease and schizophrenia were both linked to some physical phenotypes, including cholesterol and body mass index, through common GWAS signals. Alzheimer's disease also shared risk SNPs with age-related phenotypes such as age-related macular degeneration and longevity. Smoking-related SNPs were linked to lung cancer and respiratory function. Alcohol-related SNPs were associated with cardiovascular and digestive system phenotypes and disorders. Two separate studies also identified a shared risk SNP for bipolar disorder and educational attainment. This review revealed a list of reproducible SNPs worthy of future functional investigation. Additionally, by identifying SNPs associated with multiple phenotypes, we illustrated the importance of studying the relationships among phenotypes to resolve the nature of their causal links. The insights within this review will hopefully pave the way for future evidence-based genetic studies.

Case-control studies of gene-environment interactions. When a case might not be the case

Case-control Genome-Wide Association Studies (GWAS) provide a rich resource for studying the genetic architecture of complex diseases. A key is to elucidate how the genetic effects vary by the environment, what is traditionally defined by Gene-Environment interactions (GxE). The overlooked complication is that multiple, distinct pathophysiologic mechanisms may lead to the same clinical diagnosis and often these mechanisms have distinct genetic bases. In this paper, we first show that using the clinically diagnosed status can lead to severely biased estimates of GxE interactions in situations when the frequency of the pathologic diagnosis of interest, as compared to other diagnoses, depends on the environment. We then propose a pseudo-likelihood solution to correct the bias. Finally, we demonstrate our method in extensive simulations and in a GWAS of Alzheimer's disease.

Data integration for functional annotation of regulatory single nucleotide polymorphisms associated with Alzheimer's disease susceptibility

BACKGROUND

Alzheimer's disease (AD), the most common form of dementia affects 24.3 million people worldwide. More than twenty genetic loci have been associated with AD and a significant number of genetic variants were mapped within these loci. A large proportion of genome wide significant variants lie outside the coding region. However, the plausible function of these variants is still unexplored.

OBJECTIVE

The present study aimed to unravel the regulatory role of proxy single nucleotide polymorphisms (SNPs), to determine their risk of developing AD.

METHODS

The RegulomeDB was employed to predict the regulatory role of proxy SNPs. Protein association network and functional enrichment analysis was performed using String10.5 and gene ontology, respectively.

RESULTS

A total of 451 SNPs were examined through SNAP web portal (r² ≤ 0.80) which returned 2186 proxy SNPs in linkage disequilibrium (LD) with genome wide significant SNPs for AD. Out of 2186 SNPs analyzed in RegulomeDB, 151 had the scores < 3 that indicates the high degree of their potential regulatory function. Further analysis revealed that out of these 151 SNPs, 37 were genome wide significant for AD, 17 were significantly associated with diseases other than AD, 89 were proxy SNPs (not genome wide significant) for various diseases including AD while 8 SNPs were novel proxy SNPs for AD.

CONCLUSION

These findings support the notion that the non-coding variants can be strongly associated with disease risk. Further validation through genome wide association studies will be helpful for the elucidation of their regulatory potential.

Brain properties predict proximity to symptom onset in sporadic Alzheimer's disease

See Tijms and Visser (doi:10.1093/brain/awy113) for a scientific commentary on this article.Alzheimer's disease is preceded by a lengthy 'preclinical' stage spanning many years, during which subtle brain changes occur in the absence of overt cognitive symptoms. Predicting when the onset of disease symptoms will occur is an unsolved challenge in individuals with sporadic Alzheimer's disease. In individuals with autosomal dominant genetic Alzheimer's disease, the age of symptom onset is similar across generations, allowing the prediction of individual onset times with some accuracy. We extend this concept to persons with a parental history of sporadic Alzheimer's disease to test whether an individual's symptom onset age can be informed by the onset age of their affected parent, and whether this estimated onset age can be predicted using only MRI. Structural and functional MRIs were acquired from 255 ageing cognitively healthy subjects with a parental history of sporadic Alzheimer's disease from the PREVENT-AD cohort. Years to estimated symptom onset was calculated as participant age minus age of parental symptom onset. Grey matter volume was extracted from T1-weighted images and whole-brain resting state functional connectivity was evaluated using degree count. Both modalities were summarized using a 444-region cortical-subcortical atlas. The entire sample was divided into training (n = 138) and testing (n = 68) sets. Within the training set, individuals closer to or beyond their parent's symptom onset demonstrated reduced grey matter volume and altered functional connectivity, specifically in regions known to be vulnerable in Alzheimer's disease. Machine learning was used to identify a weighted set of imaging features trained to predict years to estimated symptom onset. This feature set alone significantly predicted years to estimated symptom onset in the unseen testing data. This model, using only neuroimaging features, significantly outperformed a similar model instead trained with cognitive, genetic, imaging and demographic features used in a traditional clinical setting. We next tested if these brain properties could be generalized to predict time to clinical progression in a subgroup of 26 individuals from the Alzheimer's Disease Neuroimaging Initiative, who eventually converted either to mild cognitive impairment or to Alzheimer's dementia. The feature set trained on years to estimated symptom onset in the PREVENT-AD predicted variance in time to clinical conversion in this separate longitudinal dataset. Adjusting for participant age did not impact any of the results. These findings demonstrate that years to estimated symptom onset or similar measures can be predicted from brain features and may help estimate presymptomatic disease progression in at-risk individuals.

Probing the role of PPARγ in the regulation of late-onset Alzheimer's disease-associated genes

Peroxisome proliferator-activated receptor-γ (PPARγ), is a transcription factor that governs pathways, such as lipid metabolism and immune response, that have been implicated in the etiology of LOAD. Previously, we established HepG2-derived cell-lines with stable knockdown of PPARγ gene, and showed an increase in mRNA levels of genes mapped in the APOE linkage disequilibrium (LD) region on chromosome 19q13.32, with the greatest effect observed for APOE-mRNA. Here, we extended the analysis using our PPARγ knockdown model system and investigated the broader effect on expression changes of genes implicated in LOAD via genome wide association studies (GWAS). We applied the nCounter gene expression assay (NanoString) using a panel of twenty-four LOAD-associated genes inferred by proximity to the top significantly associated SNPs. Two independent PPARγ knockdown cell-lines showed changes in mRNA levels of a total of seven genes compared to a control HepG2 cell-line; six of which, ABCA7, APOE, CASS4, CELF1, PTK2B, and ZCWPW1, were upregulated and one, DSG2, was downregulated upon PPARγ knockdown. Our results propose that PPARγ may act as a master regulator of the transcription of several genes involved in LOAD pathogenesis. Our study provided the premise for further analyses including a larger set of genes positioned within a wider range of linkage disequilibrium (LD) regions tagged by all LOAD significantly associated SNPs.

The effects of the TOMM40 poly-T alleles on Alzheimer's disease phenotypes

The TOMM40 poly-T is a polymorphism in intron 6 of the TOMM40 gene, which is adjacent to and in linkage disequilibrium with APOE. Roses et al. identified the association between the length of TOMM40 poly-T with the risk and age of onset of late-onset Alzheimer's disease (LOAD). Following the original discovery, additional studies found associations between the TOMM40 poly-T and LOAD-related phenotypes independent of APOE genotypes, while others did not replicate these associations. Furthermore, the identity of the TOMM40 poly-T risk allele has been controversial between different LOAD-related phenotypes. Here, we propose a framework to address the conflicting findings with respect to the TOMM40 poly-T allele associations with LOAD phenotypes and their functional effects. The framework is used to interpret previous studies as means to gain insights regarding the nature of the risk allele, very long versus short. We suggest that the identity of the TOMM40 poly-T risk allele depends on the phenotype being evaluated, the ages of the study subjects at the time of assessment, and the context of the APOE genotypes. In concluding remarks, we outline future studies that will inform the mechanistic interpretation of the genetic data.

APOE gene and neuropsychiatric disorders and endophenotypes: A comprehensive review

The Apolipoprotein E (APOE) gene is one of the main candidates in neuropsychiatric genetics, with hundreds of studies carried out in order to explore the possible role of polymorphisms in the APOE gene in a large number of neurological diseases, psychiatric disorders, and related endophenotypes. In the current article, we provide a comprehensive review of the structural and functional aspects of the APOE gene and its relationship with brain disorders. Evidence from genome-wide association studies and meta-analyses shows that the APOE gene has been significantly associated with several neurodegenerative disorders. Cellular and animal models show growing evidence of the key role of APOE in mechanisms of brain plasticity and behavior. Future analyses of the APOE gene might find a possible role in other neurological diseases and psychiatric disorders and related endophenotypes. © 2016 Wiley Periodicals, Inc.

Does the Interplay Between Aging and Neuroinflammation Modulate Alzheimer's Disease Clinical Phenotypes? A Clinico-Pathological Perspective

Alzheimer's disease (AD) is a chronic neurodegenerative disorder and is the most common cause of dementia worldwide. Cumulative data suggests that neuroinflammation plays a prominent and early role in AD, and there is compelling data from different research groups of age-associated dysregulation of the neuroimmune system. From the clinical point of view, despite clinical resemblance and neuropathological findings, there are important differences between the group of patients with sporadic early-onset (<65 years old) and late-onset AD (>65 years old). Thus, it seems important to understand the age-dependent relationship between neuroinflammation and the underlying biology of AD in order to identify potential explanations for clinical heterogeneity, interpret biomarkers, and promote the best treatment to different clinical AD phenotypes. The study of the delicate balance between pro-inflammatory or anti-inflammatory sides of immune players in the different ages of onset of AD would be important to understand treatment efficacy in clinical trials and eventually, not only direct treatment to early disease stages, but also the possibility of establishing different treatment approaches depending on the age of the patient. In this review, we would like to summarize what is currently known about the interplay between "normal" age associated inflammatory changes and AD pathological mechanisms, and also the potential differences between early-onset and late-onset AD taking into account the age-related neuroimmune background at disease onset.

Genome-wide significant, replicated and functional risk variants for Alzheimer's disease

Genome-wide association studies (GWASs) have reported numerous associations between risk variants and Alzheimer's disease (AD). However, these associations do not necessarily indicate a causal relationship. If the risk variants can be demonstrated to be biologically functional, the possibility of a causal relationship would be increased. In this article, we reviewed all of the published GWASs to extract the genome-wide significant (p < 5×10-8) and replicated associations between risk variants and AD or AD-biomarkers. The regulatory effects of these risk variants on the expression of a novel class of non-coding RNAs (piRNAs) and protein-coding RNAs (mRNAs), the alteration of proteins caused by these variants, the associations between AD and these variants in our own sample, the expression of piRNAs, mRNAs and proteins in human brains targeted by these variants, the expression correlations between the risk genes and APOE, the pathways and networks that the risk genes belonged to, and the possible long non-coding RNAs (LncRNAs) that might regulate the risk genes were analyzed, to investigate the potential biological functions of the risk variants and explore the potential mechanisms underlying the SNP-AD associations. We found replicated and significant associations for AD or AD-biomarkers, surprisingly, only at 17 SNPs located in 11 genes/snRNAs/LncRNAs in eight genomic regions. Most of these 17 SNPs enriched some AD-related pathways or networks, and were potentially functional in regulating piRNAs and mRNAs; some SNPs were associated with AD in our sample, and some SNPs altered protein structures. Most of the protein-coding genes regulated by the risk SNPs were expressed in human brain and correlated with APOE expression. We conclude that these variants were most robust risk markers for AD, and their contributions to AD risk was likely to be causal. As expected, APOE and the lipoprotein metabolism pathway possess the highest weight among these contributions.

A common haplotype lowers PU.1 expression in myeloid cells and delays onset of Alzheimer's disease

A genome-wide survival analysis of 14,406 Alzheimer's disease (AD) cases and 25,849 controls identified eight previously reported AD risk loci and 14 novel loci associated with age at onset. Linkage disequilibrium score regression of 220 cell types implicated the regulation of myeloid gene expression in AD risk. The minor allele of rs1057233 (G), within the previously reported CELF1 AD risk locus, showed association with delayed AD onset and lower expression of SPI1 in monocytes and macrophages. SPI1 encodes PU.1, a transcription factor critical for myeloid cell development and function. AD heritability was enriched within the PU.1 cistrome, implicating a myeloid PU.1 target gene network in AD. Finally, experimentally altered PU.1 levels affected the expression of mouse orthologs of many AD risk genes and the phagocytic activity of mouse microglial cells. Our results suggest that lower SPI1 expression reduces AD risk by regulating myeloid gene expression and cell function.

Transcriptome-wide piRNA profiling in human brains of Alzheimer's disease

Discovered in the brains of multiple animal species, piRNAs may contribute to the pathogenesis of neuropsychiatric illnesses. The present study aimed to identify brain piRNAs across transcriptome that are associated with Alzheimer's disease (AD). Prefrontal cortical tissues of 6 AD cases and 6 controls were examined for piRNA expression levels using an Arraystar HG19 piRNA array (containing 23,677 piRNAs) and genotyped for 17 genome-wide significant and replicated risk SNPs. We examined whether piRNAs are expressed differently between AD cases and controls and explored the potential regulatory effects of risk SNPs on piRNA expression levels. We identified a total of 9453 piRNAs in human brains, with 103 nominally (p < 0.05) differentially (>1.5 fold) expressed in AD cases versus controls and most of the 103 piRNAs nominally correlated with genome-wide significant risk SNPs. We conclude that piRNAs are abundant in human brains and may represent risk biomarkers of AD.

Age-associated DNA methylation changes in naive CD4+ T cells suggest an evolving autoimmune epigenotype in aging T cells

AIM

We sought to define age-associated DNA methylation changes in naive CD4⁺ T cells.

MATERIALS & METHODS

Naive CD4⁺ T cells were collected from 74 healthy individuals (age 19-66 years), and age-related DNA methylation changes were characterized.

RESULTS

We identified 11,431 age-associated CpG sites, 57% of which were hypermethylated with age. Hypermethylated sites were enriched in CpG islands and repressive transcription factor binding sites, while hypomethylated sites showed T cell specific enrichment in active enhancers marked by H3K27ac and H3K4me1. Our data emphasize cancer-related DNA methylation changes with age, and also reveal age-associated hypomethylation in immune-related pathways, such as T cell receptor signaling, FCγR-mediated phagocytosis, apoptosis and the mammalian target of rapamycin signaling pathway. The MAPK signaling pathway was hypermethylated with age, consistent with a defective MAPK signaling in aging T cells.

CONCLUSION

Age-associated DNA methylation changes may alter regulatory mechanisms and signaling pathways that predispose to autoimmunity.

Association of GWAS Top Genes With Late-Onset Alzheimer's Disease in Colombian Population

OBJECTIVE

The association of variants in CLU, CR1, PICALM, BIN1, ABCA7, and CD33 genes with late-onset Alzheimer's disease (LOAD) was evaluated and confirmed through genome-wide association study. However, it is unknown whether these associations can be replicated in admixed populations.

METHODS

The association of 14 single-nucleotide polymorphisms in those genes was evaluated in 280 LOAD cases and 357 controls from the Colombian population.

RESULTS

In a multivariate analysis using age, gender, APOE∊4 status, and admixture covariates, significant associations were obtained ( P < .05) for variants in BIN1 (rs744373, odds ratio [OR]: 1.42), CLU (rs11136000, OR: 0.66), PICALM (rs541458, OR: 0.69), ABCA7 (rs3764650, OR: 1.7), and CD33 (rs3865444, OR: 1.12). Likewise, a significant interaction effect was observed between CLU and CR1 variants with APOE.

CONCLUSION

This study replicated the associations previously reported in populations of European ancestry and shows that APOE variants have a regulatory role on the effect that variants in other loci have on LOAD, reflecting the importance of gene-gene interactions in the etiology of neurodegenerative diseases.

The effects of PPARγ on the regulation of the TOMM40-APOE-C1 genes cluster

Chromosome 19q13.32 is a gene rich region, and has been implicated in multiple human phenotypes in adulthood including lipids traits, Alzheimer's disease, and longevity. Peroxisome Proliferator Activated Receptor Gamma (PPARγ) is a ligand-activated nuclear transcription factor that plays a role in human complex traits that are also genetically associated with the chromosome 19q13.32 region. Here, we study the effects of PPARγ on the regional expression regulation of the genes clustered within chromosome 19q13.32, specifically TOMM40, APOE, and APOC1, applying two complementary approaches. Using the short hairpin RNA (shRNA) method in the HepG2 cell-line we knocked down PPARγ expression and measured the effect on mRNA expression. We discovered PPARγ knock down increased the levels of TOMM40-, APOE-, and APOC1-mRNAs, with the highest increase in expression observed for APOE-mRNA. To complement the PPARγ knockdown findings we also examined the effects of low doses of PPARγ agonists (nM range) on mRNA expression of these genes. Low (nM) concentrations of pioglitazone (Pio) decreased transcription of TOMM40, APOE, and APOC1 genes, with the lowest mRNA levels for each gene observed at 1.5nM. Similar to the effect of PPARγ knockdown, the strongest response to pioglitazone was also observed for APOE-mRNA, and rosiglitazone (Rosi), another PPARγ agonist, produced results that were consistent with these. In conclusion, our results further established a role for PPARγ in regional transcriptional regulation of chr19q13.32, underpinning the association between PPARγ, the chr19q13.32 genes cluster, and human complex traits and disease.

Genomic variants, genes, and pathways of Alzheimer's disease: An overview

Alzheimer's disease (AD) (MIM: 104300) is a highly heritable disease with great complexity in its genetic contributors, and represents the most common form of dementia. With the gradual aging of the world's population, leading to increased prevalence of AD, and the substantial cost of care for those afflicted, identifying the genetic causes of disease represents a critical effort in identifying therapeutic targets. Here we provide a comprehensive review of genomic studies of AD, from the earliest linkage studies identifying monogenic contributors to early-onset forms of AD to the genome-wide and rare variant association studies of recent years that are being used to characterize the mosaic of genetic contributors to late-onset AD (LOAD), and which have identified approximately ∼20 genes with common variants contributing to LOAD risk. In addition, we explore studies employing alternative approaches to identify genetic contributors to AD, including studies of AD-related phenotypes and multi-variant association studies such as pathway analyses. Finally, we introduce studies of next-generation sequencing, which have recently helped identify multiple low-frequency and rare variant contributors to AD, and discuss on-going efforts with next-generation sequencing studies to develop statistically well- powered and comprehensive genomic studies of AD. Through this review, we help uncover the many insights the genetics of AD have provided into the pathways and pathophysiology of AD. © 2016 Wiley Periodicals, Inc.

Association between DCHS2 gene and mild cognitive impairment and Alzheimer's disease in an elderly Brazilian sample

OBJECTIVES

In 2012, Kamboh and colleagues published a genome-wide association study that identified the DCHS2 gene (rs1466662 T/A) influencing the age at onset of Alzheimer's disease (AD). We aimed to investigate if there is association between the DCHS2 gene and amnestic mild cognitive impairment (aMCI) and AD in a sample of the Brazilian population.

METHODS

143 controls, 79 aMCI and 299 AD patients were selected and submitted to the same protocol of tests. Genotyping was performed using the Real Time PCR RESULTS: Amnestic MCI patients showed a higher prevalence of AA than controls and a lower frequency of TT when compared with controls. We also stratified the sample according to the APOE ε4 status. No difference in DCHS2 genotype or allelic frequency occurred in the APOE ε4 allele carrier subgroup. Amnestic MCI patients showed a higher frequency of AA genotype and a lower frequency of TA and TT when compared with controls in APOE ε4 allele non-carrier subgroup. The allelic distribution followed the same pattern. In AD group, we observed a significant difference with a higher A allelic frequency in AD in this subgroup. A multiple logistic regression demonstrated that in APOE ε4 non-carriers, allele rs1466662 was associated to aMCI group. Different variables were associated with aMCI and AD according to APOE ε4 status in our sample. Low level of education was associated with AD, while diabetes mellitus type 2 was associated with aMCI. Copyright © 2016 John Wiley & Sons, Ltd.

CONCLUSIONS

Our findings suggest a possible role for DCHS2 gene in aMCI and AD.

The effect of schooling on reported age of onset of cognitive decline: A collaborative study

Higher education has been reported to be a protective factor against dementia. We suggest that the strength of a risk factor may be measured by the length of time by which it delays disease onset; therefore, we examined whether people with lower education develop cognitive decline at an earlier age than people with more schooling. The study population was based on patients referred to our Memory Clinics from 1994 to 2004. Analysis of covariance was used to evaluate the effect of schooling on the reported age of memory decline, in patients with mild cognitive impairment (MCI) and in patients diagnosed with Alzheimer's disease (AD). The mean reported age of onset of cognitive decline was unexpectedly lower in patients with higher education than in patients with fewer schooling years, with a relatively small effect size (beta=-0.6), and the effect was more marked in the MCI group. Every year of schooling advanced the reported age of onset by 6months among patients with MCI (t=-6.18, p<.001) and by 3months among patients with AD (t=-2.4, p=0.017). Education may affect the reported age of onset of cognitive decline, but its magnitude is small. It is possible that increased awareness in more educated people leads them to consult earlier; this could explain the paradoxical finding of earlier reported age of onset of cognitive decline in patients with higher education.