ApoE2 and protective molecular signatures in Alzheimer’s disease and aging
- PI
- Kulminski, Alexander
- DAR ID
- 10104
- Initial Approval Date
- July 10, 2019
- Current DAR Status
- Active
- PI Institution
- Duke University
- PI Institution Country
- United States
- PI Institution Type
- Non-Profit
Requested Datasets (8)
NG00067Alzheimer's Disease Sequencing Project Umbrella StudyNG00022ADC1 - Alzheimer's Disease Center Dataset 1NG00023ADC2 - Alzheimer's Disease Center Dataset 2NG00024ADC3 - Alzheimer's Disease Center Dataset 3NG00068ADC4 - Alzheimer's Disease Center Dataset 4NG00069ADC5 - Alzheimer's Disease Center Dataset 5NG00070ADC6 - Alzheimer's Disease Center Dataset 6NG00071ADC7 - Alzheimer's Disease Center Dataset 7
Research Use Statement
Objective: to identify personalized polygenic profiles, comprised of the APOE e2 allele, other SNPs in the APOE region, and SNPs spread through the entire genome, with stronger protection in aging and Alzheimer’s Disease (AD) framework, and identify the role of AD risk factors in these profiles using ADSP and 10 more studies. Study design: Aim 1 will identify molecular signatures of aging-related traits (AD, cardiovascular diseases, longevity, etc.), defined as differences in linkage disequilibrium (LD) patterns between affected and unaffected subjects using methods of LD analysis. In Aim 2 we will dissect heterogeneity in the molecular signatures using methods of stratification analyses. We will examine the impact of age at onset, sex, race/ethnicity, Braak stage, AD risk factors (diabetes, lipids, hypertension, body mass index, education), and other factors. Aim 3 will identify personalized polygenic profiles of aging-related traits using traditional and advanced bio-demographic methods. In Aim 4 we will perform bioinformatics analysis and characterize transcription pathways using summary statistics and individual-level data from the expression quantitative trait loci studies. In some cases, we may need to pool several datasets to increase power of the analyses in a mega sample. This will be done by pooling individuals’ records for genotypes and selected phenotypes described above from different studies. This pooling will not create any additional risks to participants because neither genetic nor phenotypic information for the same individual will increase.
This research is consistent with data use restrictions for ADSP. We will not conduct non-genetic research, will not investigate individual pedigree structures, population origins, ancestry, individual participant genotypes, perceptions of racial/ethnic identity, variables that could be considered as stigmatizing an individual or group, or issues such as non-maternity. The research is designed to protect data confidentiality and follow local and institutional policies and procedures for data handling. The results of this research will be broadly shared with the scientific community.
This research is consistent with data use restrictions for ADSP. We will not conduct non-genetic research, will not investigate individual pedigree structures, population origins, ancestry, individual participant genotypes, perceptions of racial/ethnic identity, variables that could be considered as stigmatizing an individual or group, or issues such as non-maternity. The research is designed to protect data confidentiality and follow local and institutional policies and procedures for data handling. The results of this research will be broadly shared with the scientific community.
Non-Technical Summary
Increasing population of the elderly individuals worldwide raises serious concerns about burden of geriatric conditions in future, especially Alzheimer’s disease, cardiovascular diseases, and other common aging-related diseases. These diseases can cluster in families suggesting that they can have genetic origin. Understanding their genetic origin could lead to breakthrough in preventing or curing such diseases. Despite continuing efforts, understanding their genetic basis remains very limited. Particular problem is to better understand genetic basis of Alzheimer’s disease, its relationship to other aging-related diseases, and identify genetic variants which could help protect against such diseases. This project focuses on identifying personalized polygenic profiles involving the Alzheimer’s disease protective genetic variant, so-called APOE e2 allele, which could strengthen protective effects against Alzheimer’s disease and investigate which factors can improve this protection. This research will facilitate the development of interventional strategies aiming to promote healthy aging.
Reported Publications (7)
Publications shown are those reported by investigators through NIAGADS DAR reporting and renewal processes and may not represent a complete list of publications associated with the project.
- Complex genetic interactions affect susceptibility to Alzheimer's disease risk in the BIN1 and MS4A6A loci. Nazarian A, et al. GeroScience. 2025. PMID: 39751715
- Resistance and resilience to tau pathology in Alzheimer's disease: Effects of age, sex, and APOE alleles. Loika Y, et al. Alzheimer's & dementia (Amsterdam, Netherlands). 2024. PMID: 39398945
- TOMM40 and APOC1 variants differentiate the impacts of the APOE ε4 allele on Alzheimer's disease risk across sexes, ages, and ancestries. Kulminski AM, et al. Alzheimer's & dementia (Amsterdam, Netherlands). 2024. PMID: 38912305
- Inter- and intra-chromosomal modulators of the APOE ɛ2 and ɛ4 effects on the Alzheimer's disease risk. Nazarian A, et al. GeroScience. 2023. PMID: 35809216
- Genome-wide analysis identified abundant genetic modulators of contributions of the apolipoprotein E alleles to Alzheimer's disease risk. Nazarian A, et al. Alzheimer's & dementia : the journal of the Alzheimer's Association. 2022. PMID: 34978151
- Exome-wide age-of-onset analysis reveals exonic variants in ERN1 and SPPL2C associated with Alzheimer's disease. He L, et al. Translational psychiatry. 2021. PMID: 33637690
- Fast Algorithms for Conducting Large-Scale GWAS of Age-at-Onset Traits Using Cox Mixed-Effects Models. He L, et al. Genetics. 2020. PMID: 32132097