Transethnic genome-wide scan identifies novel Alzheimer's disease loci

APOE Promoter Polymorphism-219T/G is an Effect Modifier of the Influence of APOE ε4 on Alzheimer's Disease Risk in a Multiracial Sample

Variants in the APOE gene region may explain ethnic differences in the association of Alzheimer’s disease (AD) with ε4. Ethnic differences in allele frequencies for three APOE region SNPs (single nucleotide polymorphisms) were identified and tested for association in 19,398 East Asians (EastA), including Koreans and Japanese, 15,836 European ancestry (EuroA) individuals, and 4985 African Americans, and with brain imaging measures of cortical atrophy in sub-samples of Koreans and EuroAs. Among ε4/ε4 individuals, AD risk increased substantially in a dose-dependent manner with the number of APOE promoter SNP rs405509 T alleles in EastAs (TT: OR (odds ratio) = 27.02, p = 8.80 × 10⁻⁹⁴; GT: OR = 15.87, p = 2.62 × 10⁻⁹) and EuroAs (TT: OR = 18.13, p = 2.69 × 10⁻¹⁰⁸; GT: OR = 12.63, p = 3.44 × 10⁻⁶⁴), and rs405509-T homozygotes had a younger onset and more severe cortical atrophy than those with G-allele. Functional experiments using APOE promoter fragments demonstrated that TT lowered APOE expression in human brain and serum. The modifying effect of rs405509 genotype explained much of the ethnic variability in the AD/ε4 association, and increasing APOE expression might lower AD risk among ε4 homozygotes.

Paradigms of Dynamic Control of Thyroid Hormone Signaling

Thyroid hormone (TH) molecules enter cells via membrane transporters and, depending on the cell type, can be activated (i.e., T4 to T3 conversion) or inactivated (i.e., T3 to 3,3'-diiodo-l-thyronine or T4 to reverse T3 conversion). These reactions are catalyzed by the deiodinases. The biologically active hormone, T3, eventually binds to intracellular TH receptors (TRs), TRα and TRβ, and initiate TH signaling, that is, regulation of target genes and other metabolic pathways. At least three families of transmembrane transporters, MCT, OATP, and LAT, facilitate the entry of TH into cells, which follow the gradient of free hormone between the extracellular fluid and the cytoplasm. Inactivation or marked downregulation of TH transporters can dampen TH signaling. At the same time, dynamic modifications in the expression or activity of TRs and transcriptional coregulators can affect positively or negatively the intensity of TH signaling. However, the deiodinases are the element that provides greatest amplitude in dynamic control of TH signaling. Cells that express the activating deiodinase DIO2 can rapidly enhance TH signaling due to intracellular buildup of T3. In contrast, TH signaling is dampened in cells that express the inactivating deiodinase DIO3. This explains how THs can regulate pathways in development, metabolism, and growth, despite rather stable levels in the circulation. As a consequence, TH signaling is unique for each cell (tissue or organ), depending on circulating TH levels and on the exclusive blend of transporters, deiodinases, and TRs present in each cell. In this review we explore the key mechanisms underlying customization of TH signaling during development, in health and in disease states.

CpG-related SNPs in the MS4A region have a dose-dependent effect on risk of late-onset Alzheimer disease

CpG‐related single nucleotide polymorphisms (CGS) have the potential to perturb DNA methylation; however, their effects on Alzheimer disease (AD) risk have not been evaluated systematically. We conducted a genome‐wide association study using a sliding‐window approach to measure the combined effects of CGSes on AD risk in a discovery sample of 24 European ancestry cohorts (12,181 cases, 12,601 controls) from the Alzheimer's Disease Genetics Consortium (ADGC) and replication sample of seven European ancestry cohorts (7,554 cases, 27,382 controls) from the International Genomics of Alzheimer's Project (IGAP). The potential functional relevance of significant associations was evaluated by analysis of methylation and expression levels in brain tissue of the Religious Orders Study and the Rush Memory and Aging Project (ROSMAP), and in whole blood of Framingham Heart Study participants (FHS). Genome‐wide significant (p < 5 × 10⁻⁸) associations were identified with 171 1.0 kb‐length windows spanning 932 kb in the APOE region (top p < 2.2 × 10⁻³⁰⁸), five windows at BIN1 (top p = 1.3 × 10⁻¹³), two windows at MS4A6A (top p = 2.7 × 10⁻¹⁰), two windows near MS4A4A (top p = 6.4 × 10⁻¹⁰), and one window at PICALM (p = 6.3 × 10^‐9). The total number of CGS‐derived CpG dinucleotides in the window near MS4A4A was associated with AD risk (p = 2.67 × 10⁻¹⁰), brain DNA methylation (p = 2.15 × 10⁻¹⁰), and gene expression in brain (p = 0.03) and blood (p = 2.53 × 10⁻⁴). Pathway analysis of the genes responsive to changes in the methylation quantitative trait locus signal at MS4A4A (cg14750746) showed an enrichment of methyltransferase functions. We confirm the importance of CGS in AD and the potential for creating a functional CpG dosage‐derived genetic score to predict AD risk.

Evaluation of the Common Molecular Basis in Alzheimer's and Parkinson's Diseases

Alzheimer's disease (AD) and Parkinson's disease (PD) are the most common neurodegenerative disorders related to aging. Though several risk factors are shared between these two diseases, the exact relationship between them is still unknown. In this paper, we analyzed how these two diseases relate to each other from the genomic, epigenomic, and transcriptomic viewpoints. Using an extensive literature mining, we first accumulated the list of genes from major genome-wide association (GWAS) studies. Based on these GWAS studies, we observed that only one gene (HLA-DRB5) was shared between AD and PD. A subsequent literature search identified a few other genes involved in these two diseases, among which SIRT1 seemed to be the most prominent one. While we listed all the miRNAs that have been previously reported for AD and PD separately, we found only 15 different miRNAs that were reported in both diseases. In order to get better insights, we predicted the gene co-expression network for both AD and PD using network analysis algorithms applied to two GEO datasets. The network analysis revealed six clusters of genes related to AD and four clusters of genes related to PD; however, there was very low functional similarity between these clusters, pointing to insignificant similarity between AD and PD even at the level of affected biological processes. Finally, we postulated the putative epigenetic regulator modules that are common to AD and PD.

Non-coding variability at the APOE locus contributes to the Alzheimer's risk

Alzheimer’s disease (AD) is a leading cause of mortality in the elderly. While the coding change of APOE-ε4 is a key risk factor for late-onset AD and has been believed to be the only risk factor in the APOE locus, it does not fully explain the risk effect conferred by the locus. Here, we report the identification of AD causal variants in PVRL2 and APOC1 regions in proximity to APOE and define common risk haplotypes independent of APOE-ε4 coding change. These risk haplotypes are associated with changes of AD-related endophenotypes including cognitive performance, and altered expression of APOE and its nearby genes in the human brain and blood. High-throughput genome-wide chromosome conformation capture analysis further supports the roles of these risk haplotypes in modulating chromatin states and gene expression in the brain. Our findings provide compelling evidence for additional risk factors in the APOE locus that contribute to AD pathogenesis.

Several studies show that APOE-ε4 coding variants are associated with Alzheimer’s disease (AD) risk. Here, Zhou et al. perform fine-mapping of the APOE region and find AD risk haplotypes with non-coding variants in the PVRL2 and APOC1 regions that are associated with relevant endophenotypes.

Osteogenesis depends on commissioning of a network of stem cell transcription factors that act as repressors of adipogenesis

Mesenchymal (stromal) stem cells (MSCs) constitute populations of mesodermal multipotent cells involved in tissue regeneration and homeostasis in many different organs. Here we performed comprehensive characterization of the transcriptional and epigenomic changes associated with osteoblast and adipocyte differentiation of human MSCs. We demonstrate that adipogenesis is driven by considerable remodeling of the chromatin landscape and de novo activation of enhancers, whereas osteogenesis involves activation of preestablished enhancers. Using machine learning algorithms for in silico modeling of transcriptional regulation, we identify a large and diverse transcriptional network of pro-osteogenic and antiadipogenic transcription factors. Intriguingly, binding motifs for these factors overlap with SNPs related to bone and fat formation in humans, and knockdown of single members of this network is sufficient to modulate differentiation in both directions, thus indicating that lineage determination is a delicate balance between the activities of many different transcription factors.

Genetic meta-analysis of diagnosed Alzheimer's disease identifies new risk loci and implicates Aβ, tau, immunity and lipid processing

Risk for late-onset Alzheimer's disease (LOAD), the most prevalent dementia, is partially driven by genetics. To identify LOAD risk loci, we performed a large genome-wide association meta-analysis of clinically diagnosed LOAD (94,437 individuals). We confirm 20 previous LOAD risk loci and identify five new genome-wide loci (IQCK, ACE, ADAM10, ADAMTS1, and WWOX), two of which (ADAM10, ACE) were identified in a recent genome-wide association (GWAS)-by-familial-proxy of Alzheimer's or dementia. Fine-mapping of the human leukocyte antigen (HLA) region confirms the neurological and immune-mediated disease haplotype HLA-DR15 as a risk factor for LOAD. Pathway analysis implicates immunity, lipid metabolism, tau binding proteins, and amyloid precursor protein (APP) metabolism, showing that genetic variants affecting APP and Aβ processing are associated not only with early-onset autosomal dominant Alzheimer's disease but also with LOAD. Analyses of risk genes and pathways show enrichment for rare variants (P = 1.32 × 10-7), indicating that additional rare variants remain to be identified. We also identify important genetic correlations between LOAD and traits such as family history of dementia and education.

Sex Differences in the Genetic Architecture of Alzheimer's Disease

PURPOSE OF REVIEW

Summarize sex-specific contributors to the genetic architecture of Alzheimer's disease (AD).

RECENT FINDINGS

There are sex differences in the effects of Apolipoprotein E (APOE), genes along the APOE pathway, and genes along the neurotrophic signaling pathway in predicting AD. Reported sex differences are largely driven by stronger associations among females. Evidence also suggests that genetic predictors of amyloidosis are largely shared across sexes, while sex-specific genetic effects emerge downstream of amyloidosis and drive the clinical manifestation of AD.

SUMMARY

There is a lack of comprehensive assessments of sex differences in genome-wide analyses of AD and a need for more systematic reporting a sex-stratified genetic effects. The emerging emphasis on sex as a biological variable provides an opportunity for transdisciplinary collaborations aimed at addressing major analytical challenges that have hampered advancements in the field. Ultimately, sex-specific genetic association studies represent a logical first step towards precision medicine.

A statistical framework for cross-tissue transcriptome-wide association analysis

Transcriptome-wide association analysis is a powerful approach to studying the genetic architecture of complex traits. A key component of this approach is to build a model to impute gene expression levels from genotypes by using samples with matched genotypes and gene expression data in a given tissue. However, it is challenging to develop robust and accurate imputation models with a limited sample size for any single tissue. Here, we first introduce a multi-task learning method to jointly impute gene expression in 44 human tissues. Compared with single-tissue methods, our approach achieved an average of 39% improvement in imputation accuracy and generated effective imputation models for an average of 120% more genes. We describe a summary-statistic-based testing framework that combines multiple single-tissue associations into a powerful metric to quantify the overall gene-trait association. We applied our method, called UTMOST (unified test for molecular signatures), to multiple genome-wide-association results and demonstrate its advantages over single-tissue strategies.

GWAS and Beyond: Using Omics Approaches to Interpret SNP Associations

PURPOSE OF REVIEW

Neurodegenerative diseases, neuropsychiatric disorders, and related traits have highly complex etiologies but are also highly heritable and identifying the causal genes and biological pathways underlying these traits may advance the development of treatments and preventive strategies. While many genome-wide association studies (GWAS) have successfully identified variants contributing to polygenic neurodegenerative and neuropsychiatric phenotypes including Alzheimer's disease (AD), schizophrenia (SCZ), and bipolar disorder (BPD) amongst others, interpreting the biological roles of significantly-associated variants in the genetic architecture of these traits remains a significant challenge. Here we review several 'omics' approaches which attempt to bridge the gap from associated genetic variants to phenotype by helping define the functional roles of GWAS loci in the development of neuropsychiatric disorders and traits.

RECENT FINDINGS

Several common 'omics' approaches have been applied to examine neuropsychiatric traits, such as nearest-gene mapping, trans-ethnic fine mapping, annotation enrichment analysis, transcriptomic analysis, and pathway analysis, and each of these approaches has strengths and limitations in providing insight into biological mechanisms. One popular emerging method is the examination of tissue-specific genetically-regulated gene expression (GReX), which aggregates the genetic variants' effects at the gene-level. Furthermore, proteomic, metabolomic, and microbiomic studies and phenome-wide association studies will further enhance our understanding of neuropsychiatric traits.

SUMMARY

GWAS has been applied to neuropsychiatric traits for a decade, but our understanding about the biological function of identified variants remains limited. Today, technological advancements have created analytical approaches for integrating transcriptomics, metabolomics, proteomics, pharmacology and toxicology as tools for understanding the functional roles of genetics variants. These data, as well as the broader clinical information provided by electronic health records, can provide additional insight and complement genomic analyses.

Protective Variants in Alzheimer's Disease

PURPOSE OF REVIEW

Over the last decade over 40 loci have been associated with risk of Alzheimer's disease (AD). However, most studies have either focused on identifying risk loci or performing unbiased screens without a focus on protective variation in AD. Here, we provide a review of known protective variants in AD and their putative mechanisms of action. Additionally, we recommend strategies for finding new protective variants.

RECENT FINDINGS

Recent Genome-Wide Association Studies have identified both common and rare protective variants associated with AD. These include variants in or near APP, APOE, PLCG2, MS4A, MAPT-KANSL1, RAB10, ABCA1, CCL11, SORL1, NOCT, SCL24A4-RIN3, CASS4, EPHA1, SPPL2A, and NFIC.

SUMMARY

There are very few protective variants with functional evidence and a derived allele with a frequency below 20%. Additional fine mapping and multi-omic studies are needed to further validate and characterize known variants as well as specialized genome-wide scans to identify novel variants.

Comparison of methods for multivariate gene-based association tests for complex diseases using common variants

Complex diseases are usually associated with multiple correlated phenotypes, and the analysis of composite scores or disease status may not fully capture the complexity (or multidimensionality). Joint analysis of multiple disease-related phenotypes in genetic tests could potentially increase power to detect association of a disease with common SNPs (or genes). Gene-based tests are designed to identify genes containing multiple risk variants that individually are weakly associated with a univariate trait. We combined three multivariate association tests (O'Brien method, TATES, and MultiPhen) with two gene-based association tests (GATES and VEGAS) and compared performance (type I error and power) of six multivariate gene-based methods using simulated data. Data (n = 2000) for genetic sequence and correlated phenotypes were simulated by varying causal variant proportions and phenotype correlations for various scenarios. These simulations showed that two multivariate association tests (TATES and MultiPhen, but not O'Brien) paired with VEGAS have inflated type I error in all scenarios, while the three multivariate association tests paired with GATES have correct type I error. MultiPhen paired with GATES has higher power than competing methods if the correlations among phenotypes are low (r < 0.57). We applied these gene-based association methods to a GWAS dataset from the Alzheimer's Disease Genetics Consortium containing three neuropathological traits related to Alzheimer disease (neuritic plaque, neurofibrillary tangles, and cerebral amyloid angiopathy) measured in 3500 autopsied brains. Gene-level significant evidence (P < 2.7 × 10^-6) was identified in a region containing three contiguous genes (TRAPPC12, TRAPPC12-AS1, ADI1) using O'Brien and VEGAS. Gene-wide significant associations were not observed in univariate gene-based tests.

Association analysis of polymorphisms in STARD6 and near ECHDC3 in Alzheimer's disease patients carrying the APOE ε4 Allele

BACKGROUND AND PURPOSE

Lipid metabolism plays an important role in Alzheimer's disease (AD), and recent evidence suggests that single nucleotide polymorphisms (SNPs) in the StAR-related lipid transfer domain 6 (STARD6) and near the enzyme enoyl CoA hydratase domain containing 3 (ECHDC3) gene are related to plasma lipid levels or lipid traits in AD.

MATERIALS AND METHODS

To identify whether the variants in or near the STARD6 and ECHDC3 genes contribute to AD susceptibility, we carried out an association analysis of STARD6 rs10164112 and ECHDC3 rs7920721 in combination with the apolipoprotein E (APOE) ε4 allele in a case-control study (278 cases, 509 controls) in China.

RESULTS

We identified that SNP rs10164112 in the STARD6 gene was a risk factor associated with AD and the APOE ε4 carriers (all P<0.05) after Bonferroni correction. However, multivariate logistic regression analysis indicated that only the minor T allele of STARD6 rs10164112 combined with the APOE ε4 allele increased the risk of AD under the additive and dominant models (additive model: P=0.0078, OR=1.988, 95 % CI: 1.198-3.298; dominant model: P=0.0172, OR=2.169, 95% CI: 1.147-4.102).

CONCLUSION

These results suggest that the rs10164112-T allele is not an independent risk factor for AD patients. However, in combination with the APOE ε4 allele, the rs10164112-T allele has been found to be a risk factor for AD in the Han Chinese population reported in this study.

Meta-analysis of Alzheimer's disease on 9,751 samples from Norway and IGAP study identifies four risk loci

A large fraction of genetic risk factors for Alzheimer's Disease (AD) is still not identified, limiting the understanding of AD pathology and study of therapeutic targets. We conducted a genome-wide association study (GWAS) of AD cases and controls of European descent from the multi-center DemGene network across Norway and two independent European cohorts. In a two-stage process, we first performed a meta-analysis using GWAS results from 2,893 AD cases and 6,858 cognitively normal controls from Norway and 25,580 cases and 48,466 controls from the International Genomics of Alzheimer's Project (IGAP), denoted the discovery sample. Second, we selected the top hits (p < 1 × 10^-6) from the discovery analysis for replication in an Icelandic cohort consisting of 5,341 cases and 110,008 controls. We identified a novel genomic region with genome-wide significant association with AD on chromosome 4 (combined analysis OR = 1.07, p = 2.48 x 10^-8). This finding implicated HS3ST1, a gene expressed throughout the brain particularly in the cerebellar cortex. In addition, we identified IGHV1-68 in the discovery sample, previously not associated with AD. We also associated USP6NL/ECHDC3 and BZRAP1-AS1 to AD, confirming findings from a follow-up transethnic study. These new gene loci provide further evidence for AD as a polygenic disorder, and suggest new mechanistic pathways that warrant further investigation.

Network-based approach to identify molecular signatures and therapeutic agents in Alzheimer's disease

Alzheimer's disease (AD) is a dynamic degeneration of the brain with progressive dementia. Considering the uncertainties in its molecular mechanism, in the present study, we employed network-based integrative analyses, and aimed to explore the key molecules and their associations with small drugs to identify potential biomarkers and therapeutic agents for the AD. First of all, we studied a transcriptome dataset and identified 1521 differentially expressed genes (DEGs). Integration of transcriptome data with protein-protein and transcriptional regulatory interactions resulted with central (hub) proteins (UBA52, RAC1, CREBBP, AR, RPS11, SMAD3, RPS6, RPL12, RPL15, and UBC), regulatory transcription factors (FOXC1, GATA2, YY1, FOXL1, NFIC, E2F1, USF2, SRF, PPARG, and JUN) and microRNAs (mir-335-5p, mir-26b-5p, mir-93-5p, mir-124-3p, mir-17-5p, mir-16-5p, mir-20a-5p, mir-92a-3p, mir-106b-5p, and mir-192-5p) as key signaling and regulatory molecules associated with transcriptional changes for the AD. Considering these key molecules as potential therapeutic targets and Connectivity Map (CMap) architecture, candidate small molecular agents (such as STOCK1N-35696) were identified as novel potential therapeutics for the AD. This study presents molecular signatures at RNA and protein levels which might be useful in increasing discernment of the molecular mechanisms, and potential drug targets and therapeutics to design effective treatment strategies for the AD.

Genetic Variants Associated With Neurodegenerative Diseases Regulate Gene Expression in Immune Cell CD14+ Monocytes

Until now, large-scale genome-wide association studies have identified 94 genes associated with Alzheimer's disease, Parkinson's disease, and multiple sclerosis. Expression quantitative trait locus (eQTL) analysis showed that six genetic variants around six of these 94 genes could drive both disease susceptibility and altered expression of six nearby genes including CD33 (rs3865444), PILRB (rs1476679), NUP160 (rs10838725), LRRK2 (rs76904798), RGS1 (rs1323292), and METTL21B (rs701006). However, two of these six genetic variants rs1476679 and rs76904798 variants could regulate the expression of PILRB and LRRK2 only in the human monocyte-derived microglia-like (MDMi) cells, but not in human peripheral blood monocytes. Here, we aim to verify these findings using another two eQTL datasets in human peripheral blood immune cell CD14+ monocytes. The results that showed that rs1476679 and rs76904798 variants or their proxy variants could significantly regulate the expression of PILRB and LRRK2 in immune cell CD14+ monocytes and human peripheral blood. We believe that these findings provide important supplementary information about the regulatory mechanisms by which both variants influence PILRB and LRRK2 gene expression and neurodegenerative disease risk.

Systematic Analysis and Biomarker Study for Alzheimer's Disease

Revealing the relationship between dysfunctional genes in blood and brain tissues from patients with Alzheimer’s Disease (AD) will help us to understand the pathology of this disease. In this study, we conducted the first such large systematic analysis to identify differentially expressed genes (DEGs) in blood samples from 245 AD cases, 143 mild cognitive impairment (MCI) cases, and 182 healthy control subjects, and then compare these with DEGs in brain samples. We evaluated our findings using two independent AD blood datasets and performed a gene-based genome-wide association study to identify potential novel risk genes. We identified 789 and 998 DEGs common to both blood and brain of AD and MCI subjects respectively, over 77% of which had the same regulation directions across tissues and disease status, including the known ABCA7, and the novel TYK2 and TCIRG1. A machine learning classification model containing NDUFA1, MRPL51, and RPL36AL, implicating mitochondrial and ribosomal function, was discovered which discriminated between AD patients and controls with 85.9% of area under the curve and 78.1% accuracy (sensitivity = 77.6%, specificity = 78.9%). Moreover, our findings strongly suggest that mitochondrial dysfunction, NF-κB signalling and iNOS signalling are important dysregulated pathways in AD pathogenesis.

Influence of ADAM10 Polymorphisms on Plasma Level of Soluble Receptor for Advanced Glycation End Products and The Association With Alzheimer's Disease Risk

To determine the role of A disintegrin and metalloproteinase 10 (ADAM10) in genetic susceptibility to Alzheimer's disease (AD) in a representative Chinese sample, we genotyped 362 AD patients and 370 healthy controls for the rs514049A/C and rs653765C/T polymorphisms in the ADAM10 promoter using the SNaPshot technique. We also examined the potential impact of these polymorphisms on the plasma level of soluble receptor for advanced glycation end products (sRAGE), a decoy receptor whose reduction has been associated with a higher risk of AD. Additionally, a meta-analysis was performed using the present study and the largest GWAS from the International Genomics of Alzheimer's Project (IGAP). No significant differences were found in the distributions of genotypes or alleles between AD patients and control subjects. However, age-at-onset stratification analysis revealed that there were significant differences in the genotypes (P = 0.015) and alleles (P = 0.006) of the rs653765 SNP. Furthermore, patients with the rs653765 CC genotype showed a lower ADAM10 level and a faster cognitive deterioration than those in patients with the CT/TT genotype in late-onset AD (LOAD), and the rs653765 CC polymorphism was able to regulate the production of the ADAM10 substrate sRAGE. In contrast, the rs514049 polymorphism was not statistically associated with AD. In the meta-analysis, we observed that both rs514049 (A allele vs. C allele, P = 0.002) and rs653765 (C allele vs. T allele, P = 0.004) were associated with AD risk. The present study indicated that the rs653765 polymorphism might be associated with the risk and development of LOAD; in particular, the risk genotype, CC, may decrease the expression of ADAM10, influencing the plasma levels of sRAGE, and thus may be correlated with the clinical progression of AD.

Paired Immunoglobulin-like Type 2 Receptor Alpha G78R variant alters ligand binding and confers protection to Alzheimer's disease

Paired Immunoglobulin-like Type 2 Receptor Alpha (PILRA) is a cell surface inhibitory receptor that recognizes specific O-glycosylated proteins and is expressed on various innate immune cell types including microglia. We show here that a common missense variant (G78R, rs1859788) of PILRA is the likely causal allele for the confirmed Alzheimer’s disease risk locus at 7q21 (rs1476679). The G78R variant alters the interaction of residues essential for sialic acid engagement, resulting in >50% reduced binding for several PILRA ligands including a novel ligand, complement component 4A, and herpes simplex virus 1 (HSV-1) glycoprotein B. PILRA is an entry receptor for HSV-1 via glycoprotein B, and macrophages derived from R78 homozygous donors showed significantly decreased levels of HSV-1 infection at several multiplicities of infection compared to homozygous G78 macrophages. We propose that PILRA G78R protects individuals from Alzheimer’s disease risk via reduced inhibitory signaling in microglia and reduced microglial infection during HSV-1 recurrence.

Alzheimer’s disease (AD) is a devastating neurodegenerative disorder resulting from a complex interaction of environmental and genetic risk factors. Despite considerable progress in defining the genetic component of AD risk, understanding the biology of common variant associations is a challenge. We find that PILRA G78R (rs1859788) is the likely AD risk variant from the 7q21 locus (rs1476679) and PILRA G78R reduces PILRA endogenous and exogenous ligand binding. Our study highlights a new immune signaling axis in AD and suggests a role for exogenous ligands (HSV-1). Further, we have identified that reduced function of a negative regulator of microglia and neutrophils is protective from AD risk, providing a new candidate therapeutic target.

Re-thinking Alzheimer's disease therapeutic targets using gene-based tests

Background

Alzheimer's disease (AD) is a devastating condition with no known effective drug treatments. Existing drugs only alleviate symptoms. Given repeated expensive drug failures, we assessed systematically whether approved and investigational AD drugs are targeting products of genes strongly associated with AD and whether these genes are targeted by existing drugs for other indications which could be re-purposed.

Methods

We identified genes strongly associated with late-onset AD from the loci of genetic variants associated with AD at genome-wide-significance and from a gene-based test applied to the most extensively genotyped late-onset AD case (n = 17,008)-control (n = 37,154) study, the International Genomics of Alzheimer's Project. We used three gene-to-drug cross-references, Kyoto Encyclopedia of Genes and Genomes, Drugbank and Drug Repurposing Hub, to identify genetically validated targets of AD drugs and any existing drugs or nutraceuticals targeting products of the genes strongly associated with late-onset AD.

Findings

A total of 67 autosomal genes (forming 9 gene clusters) were identified as strongly associated with late-onset AD, 28 from the loci of single genetic variants, 51 from the gene-based test and 12 by both methods. Existing approved or investigational AD drugs did not target products of any of these 67 genes. Drugs for other indications targeted 11 of these genes, including immunosuppressive disease-modifying anti-rheumatic drugs targeting PTK2B gene products.

Interpretation

Approved and investigational AD drugs are not targeting products of genes strongly associated with late-onset AD. However, other drugs targeting products of these genes exist and could perhaps be re-purposing to combat late-onset AD after further scrutiny.

Alzheimer's Disease and Rheumatoid Arthritis: A Mendelian Randomization Study

Alzheimer’s disease (AD) is the most common neurodegenerative disease. In recent years, multiple pathway analyses of AD genome-wide association studies (GWAS) have been conducted, and provided strong support for immune pathways in AD. Rheumatoid arthritis (RA) is a chronic autoimmune disease. It is reported that antirheumatic drugs had protective effect on dementia in RA patients. However, observational studies have reported a controversial inverse relationship between AD and RA. In addition, Mendelian randomization studies have also been performed to evaluate the association of RA with AD. However, these studies reported inconsistent association of RA with AD. Until now, it is still unclear that AD is a causally associated with RA. Here, we performed a Mendelian randomization study to investigate the causal association of AD with RA. We analyzed the large-scale AD GWAS dataset (74,046 individuals) and RA GWAS dataset (58,284 individuals) from the European descent. However, we did not identify any significant association of AD with RA using inverse-variance weighted meta-analysis (IVW), weighted median regression and MR-Egger regression.

Shared Biological Pathways Between Alzheimer's Disease and Ischemic Stroke

Alzheimer's disease (AD) and ischemic stroke (IS) are an immense socioeconomic burden worldwide. There is a possibility that shared genetic factors lead to their links at epidemiological and pathophysiological levels. Although recent genome-wide association studies (GWAS) have provided profound insights into the genetics of AD and IS, no shared genetic variants have been identified to date. This prompted us to initiate this study, which sought to identify shared pathways linking AD and IS. We took advantage of large-scale GWAS summary data of AD (17,008 AD cases and 37,154 controls) and IS (10,307 cases and 19,326 controls) to conduct pathway analyses using genetic pathways from multiple well-studied databases, including GO, KEGG, PANTHER, Reactome, and Wikipathways. Collectively, we discovered that AD and IS shared 179 GO categories (56 biological processes, 95 cellular components, and 28 molecular functions); and the following pathways: six KEGG pathways; two PANTHER pathways; four Reactome pathways; and one in Wikipathways pathway. The more fine-grained GO terms were mainly summarized into different functional categories: transcriptional and post-transcriptional regulation, synapse, endocytic membrane traffic through the endosomal system, signaling transduction, immune process, multi-organism process, protein catabolic metabolism, and cell adhesion. The shared pathways were roughly classified into three categories: immune system; cancer (NSCLC and glioma); and signal transduction pathways involving the cadherin signaling pathway, Wnt signaling pathway, G-protein signaling and downstream signaling mediated by phosphoinositides (PIPs). The majority of these common pathways linked to both AD and IS were supported by convincing evidence from the literature. In conclusion, our findings contribute to a better understanding of common biological mechanisms underlying AD and IS and serve as a guide to direct future research.

Targeted Sequencing of Alzheimer Disease Genes in African Americans Implicates Novel Risk Variants

The genetic architecture of late-onset Alzheimer disease (AD) in African Americans (AAs) differs from that in persons of European ancestry. In addition to APOE, genome-wide association studies (GWASs) of AD in AA samples have implicated ABCA7, COBL, and SLC10A2 as AA-AD risk genes. Previously, we identified by whole exome sequencing a small number of AA AD cases and subsequent genotyping in a large AA sample of AD cases and controls association of AD risk with a pair of rare missense variants in AKAP9. In this study, we performed targeted deep sequencing (including both introns and exons) of approximately 100 genes previously linked to AD or AD-related traits in an AA cohort of 489 AD cases and 472 controls to find novel AD risk variants. We observed association with an 11 base-pair frame-shift loss-of-function (LOF) variant in ABCA7 (rs567222111) for which the evidence was bolstered when combined with data from a replication AA cohort of 484 cases and 484 controls (OR = 2.42, p = 0.022). We also found association of AD with a rare 9 bp deletion (rs371245265) located very close to the AKAP9 transcription start site (rs371245265, OR = 10.75, p = 0.0053). The most significant findings were obtained with a rare protective variant in F5 (OR = 0.053, p = 6.40 × 10^-5), a gene that was previously associated with a brain MRI measure of hippocampal atrophy, and two common variants in KIAA0196 (OR = 1.51, p<8.6 × 10^-5). Gene-based tests of aggregated rare variants yielded several nominally significant associations with KANSL1, CNN2, and TRIM35. Although no associations passed multiple test correction, our study adds to a body of literature demonstrating the utility of examining sequence data from multiple ethnic populations for discovery of new and impactful risk variants. Larger sample sizes will be needed to generate well-powered epidemiological investigations of rare variation, and functional studies are essential for establishing the pathogenicity of variants identified by sequencing.

A genetic variant near adaptor-related protein complex 2 alpha 2 subunit gene is associated with coronary artery disease in a Chinese population

Background

Adaptor-related protein complex 2 alpha 2 subunit (AP2A2) gene encodes a protein-a subunit of the AP-2 adaptor protein complex. Evidence has revealed that benzodiazepine receptor-associated protein 1 (BZRAP1) is abundant in the hippocampus with potential effects on brain diseases. Recently, an epidemiological study reported that two variants (rs7396366 and rs2526378) closest to the AP2A2 and BZRAP1 genes are associated with higher plasma lipids and Alzheimer’s disease. Whether the two single nucleotide polymorphisms (SNPs) are actually relevant to coronary artery disease (CAD) and CAD severity remains elusive. Our aim was to assess whether these two SNPs are relevant to CAD and its severity in a Chinese population.

Methods

Three hundred and thirty-five patients with documented CAD (282 stable CAD, 28 non-ST-segment elevation myocardial infarction, 25 ST-segment elevation myocardial infarction), and 372 non-CAD controls were included in the study. The participants were divided into two groups according to coronary angiography results. CAD patients were further demarcated into subgroups with one-, two-, or three-vessel stenosis. Genotypes at rs7396366 and rs2526378 were examined using polymerase chain reaction-ligase detection reaction. The association between these two SNPs with CAD and its severity were analyzed.

Results

The frequency of the rs7396366 TT genotype was significantly higher in CAD patients than in controls (13.7% vs. 7.8%, 95% CI: 1.15–3.07, P = 0.014). Subjects with a variant genotype T allele had an increased risk of CAD compared with G allele carriers (additive model: 95% CI: 1.21–3.35, P = 0.008). After adjustment for traditional cardiovascular risk factors, analysis of the dominant models involving rs7396366 also showed that T allele carriers had a significantly higher risk for CAD than G allele carriers had (dominant model: OR 1.48, 95% CI: 1.03–2.14, P = 0.035). Age, sex, type 2 diabetes mellitus, fasting plasma glucose, and the TT genotype in rs7396366 were significantly associated with three-vessel lesions. Despite these significant outcomes of rs7396366, information on rs2526378 showed no significant difference between CAD patients and non-CAD controls.

Conclusion

Our results show that the T allele and TT genotype in rs7396366, closest to the AP2A2 gene, are linked to an increased risk of CAD and its severity in a Chinese population.

Electronic supplementary material

The online version of this article (10.1186/s12872-018-0905-2) contains supplementary material, which is available to authorized users.

Genome-wide association study of Alzheimer's disease endophenotypes at prediagnosis stages

INTRODUCTION

Genetic associations for endophenotypes of Alzheimer's disease (AD) in cognitive stages preceding AD have not been thoroughly evaluated.

METHODS

We conducted genome-wide association studies for AD-related endophenotypes including hippocampal volume, logical memory scores, and cerebrospinal fluid Aβ42 and total/phosphorylated tau in cognitively normal (CN), mild cognitive impairment, and AD dementia subjects from the Alzheimer's Disease Neuroimaging Initiative study.

RESULTS

In CN subjects, study-wide significant (P < 8.3 × 10-9) loci were identified for total tau near SRRM4 and C14orf79 and for hippocampal volume near MTUS1. In mild cognitive impairment subjects, study-wide significant association was found with single nucleotide polymorphisms (SNPs) near ZNF804B for logical memory test of delayed recall scores. We found consistent expression patterns of C14orf40 and MTUS1 in carriers with risk alleles of expression SNPs and in brains of AD patients, compared with in the noncarriers and in brains of controls.

DISCUSSION

Our findings for AD-related brain changes before AD provide insight about early AD-related biological processes.

A Common DIO2 Polymorphism and Alzheimer Disease Dementia in African and European Americans

Context

A common single nucleotide polymorphism in DIO2, Thr92AlaD2, has been associated with a transcriptome typically found in neurodegenerative diseases in postmortem human brain tissue.

Objective

To determine whether Thr92AlaD2 is associated with incident Alzheimer disease (AD).

Design

Population-based study; human brain tissue microarray.

Setting

Community-based cohorts from Chicago and northeastern Illinois and religious clergymen from across the United States constituted the primary population. A representative sample of the U.S. population was used for secondary analyses.

Participants

3054 African Americans (AAs) and 9304 European Americans (EAs).

Main Outcome Measure

Incident AD.

Results

In the primary population, AAs with Thr92AlaD2 had 1.3 times [95% confidence interval (CI), 1.02 to 1.68; P = 0.048] greater odds of developing AD. AAs from a second population with Thr92AlaD2 showed a trend toward increased odds of dementia (odds ratio, 1.33; 95% CI, 0.99 to 1.78; P = 0.06) and 1.35 times greater odds of developing cognitive impairment not demented (CIND; 95% CI, 1.09 to 1.67; P = 0.006). Meta-analysis showed that AAs with Thr92AlaD2 had 1.3 times increased odds of developing AD/dementia (95% CI, 1.07 to 1.58; P = 0.008). In EAs, no association was found between Thr92AlaD2 and AD, dementia, or CIND. Microarray of AA brain tissue identified transcriptional patterns linked to AD pathogenesis.

Conclusions

Thr92AlaD2 was associated with molecular markers known to underlie AD pathogenesis in AAs, translating to an observed phenotype of increased odds of developing AD/dementia in AAs in these populations. Thr92AlaD2 might represent one factor contributing to racial discrepancies in incident AD.

One for all and all for One: Improving replication of genetic studies through network diffusion

Improving accuracy in genetic studies would greatly accelerate understanding the genetic basis of complex diseases. One approach to achieve such an improvement for risk variants identified by the genome wide association study (GWAS) approach is to incorporate previously known biology when screening variants across the genome. We developed a simple approach for improving the prioritization of candidate disease genes that incorporates a network diffusion of scores from known disease genes using a protein network and a novel integration with GWAS risk scores, and tested this approach on a large Alzheimer disease (AD) GWAS dataset. Using a statistical bootstrap approach, we cross-validated the method and for the first time showed that a network approach improves the expected replication rates in GWAS studies. Several novel AD genes were predicted including CR2, SHARPIN, and PTPN2. Our re-prioritized results are enriched for established known AD-associated biological pathways including inflammation, immune response, and metabolism, whereas standard non-prioritized results were not. Our findings support a strategy of considering network information when investigating genetic risk factors.

Integrating multiple types of -omics data is a rapidly growing research area due in part to the increasing amount of diverse and publicly accessible data. In this study, we demonstrated that integration of genetic association and protein interaction data using a network diffusion approach measurably improves reproducibility of top candidate genes. Application of this approach to Alzheimer disease (AD) using a large dataset assembled by the Alzheimer’s Disease Genetics Consortium identified several novel candidate AD genes that are supported by pre-existing knowledge of AD pathobiology. Our findings support a strategy of considering network information when investigating genetic risk factors. Finally, we developed a transparent and easy-to-use R package that can facilitate the extension of our methodology to other phenotypes for which genetic data are available.

Genome-wide pleiotropy analysis of neuropathological traits related to Alzheimer's disease

BACKGROUND

Simultaneous consideration of two neuropathological traits related to Alzheimer's disease (AD) has not been attempted in a genome-wide association study.

METHODS

We conducted genome-wide pleiotropy analyses using association summary statistics from the Beecham et al. study (PLoS Genet 10:e1004606, 2014) for AD-related neuropathological traits, including neuritic plaque (NP), neurofibrillary tangle (NFT), and cerebral amyloid angiopathy (CAA). Significant findings were further examined by expression quantitative trait locus and differentially expressed gene analyses in AD vs. control brains using gene expression data.

RESULTS

Genome-wide significant pleiotropic associations were observed for the joint model of NP and NFT (NP + NFT) with the single-nucleotide polymorphism (SNP) rs34487851 upstream of C2orf40 (alias ECRG4, P = 2.4 × 10^-8) and for the joint model of NFT and CAA (NFT + CAA) with the HDAC9 SNP rs79524815 (P = 1.1 × 10^-8). Gene-based testing revealed study-wide significant associations (P ≤ 2.0 × 10^-6) for the NFT + CAA outcome with adjacent genes TRAPPC12, TRAPPC12-AS1, and ADI1. Risk alleles of proxy SNPs for rs79524815 were associated with significantly lower expression of HDAC9 in the brain (P = 3.0 × 10^-3), and HDAC9 was significantly downregulated in subjects with AD compared with control subjects in the prefrontal (P = 7.9 × 10^-3) and visual (P = 5.6 × 10^-4) cortices.

CONCLUSIONS

Our findings suggest that pleiotropy analysis is a useful approach to identifying novel genetic associations with complex diseases and their endophenotypes. Functional studies are needed to determine whether ECRG4 or HDAC9 is plausible as a therapeutic target.

Untangling Genetic Risk for Alzheimer's Disease

Alzheimer's disease (AD) is a genetically heterogeneous neurodegenerative disorder caused by fully penetrant single gene mutations in a minority of cases, while the majority of cases are sporadic or show modest familial clustering. These cases are of late onset and likely result from the interaction of many genes and the environment. More than 30 loci have been implicated in AD by a combination of linkage, genome-wide association, and whole genome/exome sequencing. We have learned from these studies that perturbations in endolysosomal, lipid metabolism, and immune response pathways substantially contribute to sporadic AD pathogenesis. We review here current knowledge about functions of AD susceptibility genes, highlighting cells of the myeloid lineage as drivers of at least part of the genetic component in late-onset AD. Although targeted resequencing utilized for the identification of causal variants has discovered coding mutations in some AD-associated genes, a lot of risk variants lie in noncoding regions. Here we discuss the use of functional genomics approaches that integrate transcriptomic, epigenetic, and endophenotype traits with systems biology to annotate genetic variants, and to facilitate discovery of AD risk genes. Further validation in cell culture and mouse models will be necessary to establish causality for these genes. This knowledge will allow mechanism-based design of novel therapeutic interventions in AD and promises coherent implementation of treatment in a personalized manner.

Genetics of Alzheimer's Disease: the Importance of Polygenic and Epistatic Components

PURPOSE OF REVIEW

We aimed to summarize the recent advances in genetic findings of Alzheimer's disease (AD), focusing on traditional single-marker and gene approaches and non-traditional ones, i.e., polygenic and epistatic components.

RECENT FINDINGS

Genetic studies have progressed over the last few decades from linkage to genome-wide association studies (GWAS), and most recently studies utilizing high-throughput sequencing. So far, GWASs have identified several common variants characterized by small effect sizes (besides APOE-ε4). Sequencing has facilitated the study of rare variants with larger effects. Nevertheless, missing heritability for AD remains extensive; a possible explanation might lie in the existence of polygenic and epistatic components. We review findings achieved by single-marker approaches, but also polygenic and epistatic associations. The latter two are critical, yet-underexplored mechanisms. Genes involved in complex diseases are likely regulated by mechanisms and pathways involving many other genes, an aspect potentially missed by traditional approaches.

Systematic tissue-specific functional annotation of the human genome highlights immune-related DNA elements for late-onset Alzheimer's disease

Continuing efforts from large international consortia have made genome-wide epigenomic and transcriptomic annotation data publicly available for a variety of cell and tissue types. However, synthesis of these datasets into effective summary metrics to characterize the functional non-coding genome remains a challenge. Here, we present GenoSkyline-Plus, an extension of our previous work through integration of an expanded set of epigenomic and transcriptomic annotations to produce high-resolution, single tissue annotations. After validating our annotations with a catalog of tissue-specific non-coding elements previously identified in the literature, we apply our method using data from 127 different cell and tissue types to present an atlas of heritability enrichment across 45 different GWAS traits. We show that broader organ system categories (e.g. immune system) increase statistical power in identifying biologically relevant tissue types for complex diseases while annotations of individual cell types (e.g. monocytes or B-cells) provide deeper insights into disease etiology. Additionally, we use our GenoSkyline-Plus annotations in an in-depth case study of late-onset Alzheimer's disease (LOAD). Our analyses suggest a strong connection between LOAD heritability and genetic variants contained in regions of the genome functional in monocytes. Furthermore, we show that LOAD shares a similar localization of SNPs to monocyte-functional regions with Parkinson's disease. Overall, we demonstrate that integrated genome annotations at the single tissue level provide a valuable tool for understanding the etiology of complex human diseases. Our GenoSkyline-Plus annotations are freely available at http://genocanyon.med.yale.edu/GenoSkyline.