APOE
apolipoprotein E
The protein encoded by this gene is a major apoprotein of the chylomicron. It binds to a specific liver and peripheral cell receptor, and is essential for the normal catabolism of triglyceride-rich lipoprotein constituents. This gene maps to chromosome 19 in a cluster with the related apolipoprotein C1 and C2 genes. Mutations in this gene result in familial dysbetalipoproteinemia, or type III hyperlipoproteinemia (HLP III), in which increased plasma cholesterol and triglycerides are the consequence of impaired clearance of chylomicron and VLDL remnants.
provided by RefSeq
Biological Domains
APP Metabolism, Apoptosis, Endolysosome, Immune Response, Lipid Metabolism, Metal Binding and Homeostasis, Oxidative Stress, Proteostasis, Structural Stabilization, Synapse, Tau Homeostasis, Vasculature
Pharos Class
Tbio
Summary of Evidence
This tab shows an overview of how the selected gene is associated with AD.
Genetic Association with LOAD
Indicates whether or not this gene shows significant genetic association with Late Onset AD (LOAD) based on evidence from multiple studies compiled by the ADSP Gene Verification CommitteeTrueBrain eQTL
Indicates whether or not this gene locus has a significant expression Quantitative Trait Locus (eQTL) based on an AMP-AD consortium studyTrueRNA Expression Change in AD Brain
Indicates whether or not this gene shows significant differential expression in at least one brain region based on AMP-AD consortium work. See ‘EVIDENCE’ tab.TrueProtein Expression Change in AD Brain
Indicates whether or not this gene shows significant differential protein expression in at least one brain region based on AMP-AD consortium work. See ‘EVIDENCE’ tab.TrueNominated Target
Indicates whether or not this gene has been submitted as a nominated target to Agora.True
AD Risk Scores
About AD Risk Scores
The TREAT-AD Center at Emory-Sage-SGC has developed a Target Risk Score (TRS) to objectively rank the potential involvement of specific genes in AD. The TRS is derived by summing two component risk scores, the Genetic Risk Score and the Multi-omic Risk Score, each of which is derived from a meta-analysis of multiple harmonized data sets. More information about the methodology used to define these risk scores is available here.
AD Risk Scores for APOE
The TRS for APOE, along with the component Genetic and Multi-omic Risk Scores, is shown here. The scores for APOE are superimposed on the genome-wide score distributions. If No Data is Currently Available is displayed for a score, that score was not calculated for APOE.
Biological Domain Classification
About Biological Domains
A biological domain represents a standardized area of biology defined by a set of discrete, biologically coherent GO terms. The TREAT-AD Center at Emory-Sage-SGC has defined nineteen biological domains associated with AD, and objectively mapped genes to those biological domains using GO term annotations. More information about the methodology used to define AD biological domains, and to generate genome-wide biological domain mappings, is available here.
Biological Domains for APOE
Select a biological domain on the left to see the list of GO terms that link APOE to it on the right. The percentage value displayed next to the currently selected biological domain indicates the proportion of APOE's total unique GO terms that map to the biological domain. The ratio displayed on the right indicates how many of the biological domain's total GO terms APOE is annotated with.
BIOLOGICAL DOMAIN MAPPINGS
LINKING GO TERMS FOR LIPID METABOLISM (46/812)
- Cholesterol catabolic process
- Cholesterol efflux
- Cholesterol homeostasis
- Cholesterol metabolic process
- Cholesterol transfer activity
- Chylomicron remnant
- Discoidal high-density lipoprotein particle
- Fatty acid homeostasis
- High-density lipoprotein particle
- High-density lipoprotein particle assembly
- High-density lipoprotein particle clearance
- High-density lipoprotein particle remodeling
- Intermediate-density lipoprotein particle
- Intermembrane lipid transfer
- Lipid binding
- Lipid transport
- Lipid transport involved in lipid storage
- Lipid transporter activity
- Lipoprotein biosynthetic process
- Lipoprotein catabolic process
- Lipoprotein metabolic process
- Lipoprotein particle
- Lipoprotein particle binding
- Long-chain fatty acid transport
- Low-density lipoprotein particle
- Low-density lipoprotein particle receptor binding
- Low-density lipoprotein particle remodeling
- Negative regulation of cholesterol biosynthetic process
- Negative regulation of cholesterol efflux
- Negative regulation of lipid biosynthetic process
- Negative regulation of lipid transport across blood-brain barrier
- Negative regulation of phospholipid efflux
- Negative regulation of triglyceride metabolic process
- Phospholipid binding
- Phospholipid efflux
- Positive regulation of cholesterol efflux
- Positive regulation of cholesterol metabolic process
- Positive regulation of lipid biosynthetic process
- Positive regulation of lipid transport across blood-brain barrier
- Positive regulation of phospholipid efflux
- Regulation of cholesterol metabolic process
- Reverse cholesterol transport
- Triglyceride homeostasis
- Triglyceride metabolic process
- Very-low-density lipoprotein particle
- Very-low-density lipoprotein particle remodeling
RNA Expression
The results shown on this page are derived from a harmonized RNA-seq analysis of post-mortem brains from AD cases and controls. The samples were obtained from three human cohort studies across a total of nine different brain regions.
Overall Expression of APOE Across Brain Regions
This plot depicts the median expression of the selected gene across brain regions, as measured by RNA-seq read counts per million (CPM) reads. Meaningful expression is considered to be a log2 CPM greater than log2(5), depicted by the red line in the plot.
Differential Expression of APOE Across Brain Regions
After selecting a statistical model, you will be able to see whether the selected gene is differentially expressed between AD cases and controls. The box plot depicts how the differential expression of the selected gene of interest (purple dot) compares with expression of other genes in a given tissue. Summary statistics for each tissue can be viewed by hovering over the purple dots. Meaningful differential expression is considered to be a log2 fold change value greater than 0.263, or less than -0.263.
AD Diagnosis (males and females)
Consistency of Change in Expression
This forest plot indicates the estimate of the log fold change with standard errors across the brain regions in the model chosen using the filter above. Genes that show consistent patterns of differential expression will have similar log-fold change value across brain regions.
AD Diagnosis (males and females)
Correlation of APOE with Hallmarks of AD
This plot depicts the association between expression levels of the selected gene in the DLPFC and three phenotypic measures of AD. An odds ratio > 1 indicates a positive correlation and an odds ratio < 1 indicates a negative correlation. Statistical significance and summary statistics for each phenotype can be viewed by hovering over the dots.
Similarly Expressed Genes
The network diagram below is based on a coexpression network analysis of RNA-seq data from AD cases and controls. The network analysis uses an ensemble methodology to identify genes that show similar coexpression across individuals.
The color of the edges and nodes indicates how frequently significant coexpression was identified. Each node represents a different gene and the amount of edges within the network. Darker edges represent coexpression in more brain regions.
APOE
The protein encoded by this gene is a major apoprotein of the chylomicron. It binds to a specific liver and peripheral cell receptor, and is essential for the normal catabolism of triglyceride-rich lipoprotein constituents. This gene maps to chromosome 19 in a cluster with the related apolipoprotein C1 and C2 genes. Mutations in this gene result in familial dysbetalipoproteinemia, or type III hyperlipoproteinemia (HLP III), in which increased plasma cholesterol and triglycerides are the consequence of impaired clearance of chylomicron and VLDL remnants. [provided by RefSeq, Jun 2016].
Proteomics
Proteomic analyses of post-mortem brains show whether protein products of APOE are differentially expressed between AD cases and controls. Each box plot depicts how the differential expression of the protein(s) of interest (purple dot) compares with expression of other proteins in a given brain region. Summary statistics for each tissue can be viewed by hovering over the purple dots.
Targeted SRM Differential Protein Expression
Selected Reaction Monitoring (SRM) data was generated from the DLPFC region of post-mortem brains of over 1000 individuals from multiple human cohort studies.
Note that only a single SRM result is available for a given gene, as the probes used for this experiment were designed to match multiple protein products derived from each targeted gene.
Genome-wide Differential Protein Expression
Select a protein from the dropdown menu to see whether it is differentially expressed between AD cases and controls.
The assay-specific box plots below depict how the differential expression of the selected protein of interest (purple dot) compares with expression of other proteins in each brain region that was assayed. Assay-specific summary statistics for each brain region can be viewed by hovering over the purple dot.
Multiple proteins may map to a single gene. Results from both TMT and LFQ assays are provided, however results for some proteins may be available for only one of the assays.
TMT Differential Protein Expression
Tandem mass tagged (TMT) data was generated from the DLPFC region of post-mortem brains of 400 individuals from the ROSMAP cohort.
Note that proteins may not be detected in this brain region; for these proteins, the plot will show no data.
LFQ Differential Protein Expression
Liquid-free quantification (LFQ) data was generated from post-mortem brains of more than 500 individuals. Samples were taken from four human cohort studies, representing four different brain regions.
Note that proteins may not be detected in all four brain regions; for these proteins, the plot will show fewer than four brain regions.
Metabolomics
The results shown on this page are derived from an analysis of metabolite levels from AD cases and controls. The samples were obtained from approximately 1400 individuals from the ADNI study. Metabolites are associated with genes using genetic mapping and the metabolite with the highest genetic association is shown for each gene.
Mapping of Metabolites to APOE
No metabolomic data is currently available.
Genetic mapping revealed that the top metabolite associated with APOE is PC aa C38:3, with a p-value of 0.000052.
Levels of PC aa C38:3 by Disease Status
This plot shows differences in metabolite levels in AD cases (AD) and cognitively-normal individuals (CN). This comparison is not significantly different with a p-value of 0.12.
Target Enabling Resources
Use these links to discover the Target Enabling Resources for APOE that are currently available, under development, or planned.
Drug Development Resources
These external sites provide information and resources related to drug development.
Additional Resources
These external sites provide additional information about therapeutic targets for AD and related dementias.
Evidence Supporting the Nomination of APOE
This gene has been nominated as a potential target for AD. Nominated targets are obtained from several sources, including the National Institute on Aging's Accelerating Medicines Partnership in Alzheimer's Disease (AMP-AD) consortium. Targets have been identified using computational analyses of high-dimensional genomic, proteomic and/or metabolomic data derived from human samples.
AMP-AD: Arizona State University
The ASU team, led by Ben Readhead, uses multi-omic profiling, 3D-cerebral organoids and CRISPR-Cas9 approaches to understand the role of pathogens in the etiology and progression of Alzheimer's disease.
Why was the target selected?
Gene identified in HSV-1 infection study whereby HSV-1 induced intracellular Abeta accumulation and phosphorylated Tau, and transcriptomic changes that are enriched for a permissive set of AD GWAS associated genes. Genes included in this nomination are within that leading edge of AD GWAS genes that are significantly perturbed by HSV1 within this experiment. Rank is based on ordered absolute logFC following HSV-1 infection
Predicted therapeutic direction
Unknown.
The type of data used and analyses done to identify target
RNA-seq on HSV1 infected cerebral organoids
Cohort study data: VirusResilience
Initial date of nomination
2023
Planned Experimental Validation
Validation studies ongoing
AMP-AD: Duke University
The Duke AMP-AD team, led by Rima Kaddurah-Daouk, focuses on taking an integrated metabolomics-genetics-imaging systems approach to define network failures in Alzheimer's disease.
Why was the target selected?
Among the top-scoring genes according to a combination of composite scores from the AD atlas (genetics score and metabolomics score) and the TREAT-AD consortium (genetics score and RNA-seq/proteomics score). These scores are evolving, currently we put highest weight on metabolic evidence linking to AD in brain tissue and blood.
Predicted therapeutic direction
Unknown.
The type of data used and analyses done to identify target
AMP-AD multi-omics data. Full listing available at www.adatlas.org.
Initial date of nomination
2023
Planned Experimental Validation
Not prioritized for experimental validation
Learn more about the target nomination processAMP-AD: The Mayo Clinic - University of Florida - The Institute for Systems Biology
The Mayo-UFL-ISB AMP-AD team, led by Nilufer Ertekin-Taner, Todd Golde, Nathan Price, and Steven Younkin, includes three institutions: the University of Florida, the Institute for Systems Biology, and the Mayo Clinic Jacksonville. The focus of the team is to identify therapeutic targets within the innate immune signaling cascade in Alzheimer's disease that can be safely manipulated to provide disease modification.
Why was the target selected?
Plaque/dystrophic neurite targets
Predicted therapeutic direction
Unknown
The type of data used and analyses done to identify target
Proteome Data From APP Mice/Genetics/Human Data
Cohort study data: APP Mice
Initial date of nomination
2018
Planned Experimental Validation
not prioritized for experimental validation
Learn more about the target nomination processAMP-AD: The Roussos Lab at the Icahn School of Medicine at Mount Sinai
The Icahn School of Medicine at Mount Sinai AMP-AD team lead by Panos Roussos, Vahram Haroutunian, John Fullard, Gabriel Hoffman, Donghoon Lee, and Jaro Bendl focuses on changes of immune markers underlying the etiology of Alzheimer's disease.
Why was the target selected?
Genes are upregulated in AD based on single cell analysis of microglia subtypes
Predicted therapeutic direction
Antagonism predicted to reduce disease progression.
The type of data used and analyses done to identify target
scRNAseq and snRNAseq in microglia
Cohort study data: HBI_scRNAseq
Initial date of nomination
2023
Planned Experimental Validation
Not prioritized for experimental validation
TREAT-AD: Emory University - Sage Bionetworks - Structural Genomics Consortium
The mission of the Emory-Sage-Structural Genomics Consortium (SGC) TREAT-AD center is to diversify the portfolio of drug targets in Alzheimer's disease (AD). We aim to catalyze research into biological pathways that have been associated with disease from deep molecular profiling and bioinformatic evaluation of AD in the human brain within the National Institute on Aging's (NIA) Accelerating Medicines Partnership-Alzheimer's Disease (AMP-AD) consortium. Many of these potential AD drug targets are predicted to reside among the thousands of human proteins that historically have received little attention and for which there are few reagents, such as quality-verified antibodies, cell lines, assays or chemical probes. To catalyze their investigation, we are developing and openly distributing experimental tools, including chemical probes, for broad use in the evaluation of a diverse set of novel AD targets.
Why was the target selected?
This target is found within a TMT proteomics network module that was highly correlated with cognition. This module (Module 42) contains several novel AD targets, including SMOC1 and MDK.
Predicted therapeutic direction
Unknown. APOE is linked with numerous functions that may modify neurodegenerative processes, including cholesterol clearance from brain, regulation of innate immune response, and amyloid sedimentation and plaque formation.
The type of data used and analyses done to identify target
TMT proteomics network.
Cohort study data: Banner, ROSMAP, MSBB, Emory
Initial date of nomination
2024
Planned Experimental Validation
validation studies ongoing
Learn more about the target nomination process