There are many active research projects accessing and applying shared ADNI data. Use the search above to find specific research focuses on the active ADNI investigations. This information is requested annually as a requirement for data access.
| Principal Investigator | |
| Principal Investigator's Name: | Valerie Dorsant Ardon |
| Institution: | Indiana University Purdue University Indianapolis IUPUI |
| Department: | Neurology |
| Country: | |
| Proposed Analysis: | SPECIFIC AIMS Alzheimer’s disease (AD) is the most prevalent neurodegenerative disease and the most diagnosed cause of dementia worldwide. It is estimated by the World Health Organization (WHO) that the burden of disease doubled in 2019 compared to 2000 and it is considered the 7th cause of death in the United States of America 1. This disease has a major impact in quality of life of the affected individuals, their caregivers, the healthcare system, and society. According to the Alzheimer’s Association in USA more than 6.5 million people suffer from the disease totaling a cost to the nation of more than 321 billion dollars2 with few treatment options that slow down discreetly the progression of disease and no curative alternatives. This has led to the development of multiple initiatives and studies to broaden our knowledge of AD. The Alzheimer’s Disease Neuroimaging Initiative (ADNI) is a study that currently runs its 4th iteration and for the past 17 years has had the objective to increase the available knowledge on AD3. Unfortunately, there is a general underrepresentation of diverse populations shown by the low enrollments of Black/African American and Hispanic/Latino individuals, mainly due to stringent enrollment criteria that reduces the amount of allowed comorbidities, frequently seen in these populational groups4. The inclusion of ethnic groups with different ancestries is important. Works from other authors have compared the Caucasian non-Latino population with African American/Black and Hispanic/Latino population finding differential risk factors for the development of AD in each one of these groups, this leads to believe that environmental and genetic background play a role in specific risk. For this reason, there have been new Initiatives to increase diversity in ADNI including the conformation of the Diversity Equity and Inclusion Committee and the ADNI study Diversity Task Force5 that not only recruit individuals from Underrepresented population groups, but also incentives the increase in diversity in the research teams associated with the data acquisition and analysis to help to identify specific risk factors associated with AD diagnosis and progression in these populational groups. Specifically, it has been previously established that African American/Black and Hispanic-Latino populations have a lower risk of developing AD from APOE E4 compared to Asian and Caucasian non-Hispanic populations, it is hypothesized that this effect is caused by differential genomic background surrounding the ApoE locus 6. Among these factors, in July 2022 was published a paper by Rajabli et al. describing in non-ADNI datasets that the rs10423769_A SNP is a variant that confers protection in these 2 minoritarian groups7. The study of this SNP in the ADNI dataset will provide additional validation to the relevance of this SNP in the context of ancestry specific AD risk. Our central hypothesis is that the SNP rs10423769_A will confer a reduced risk in non-Caucasian populations from ADNI in the context of ApoE4 genotype driven by variations in local ancestry of genomic regions surrounding the ApoE4 locus. Specific aims We plan to test the hypothesis through the following specific aims • Specific aim 1: Obtain a population structure of participants from African America/Black, Caucasian, and Hispanic/Latino populational groups from the ADNI database using Local and Global ancestry. • Specific Aim 2: Analyze the ApoE4 and rs10423769_A carrier status from these individuals. • Specific Aim 3: Establish the OR for the diagnosis of AD and progression from Mild cognitive impairment (MCI) to AD for the 3 populational groups. Expected results We expect to obtain a differential Odds ratio for the diagnostic status of AD in Caucasian non-Hispanic, African American/Black and Hispanic-Latino individuals that confer a decreased risk of diagnosis or progression to Alzheimer’s disease in individuals from underrepresented ethnic groups from samples obtained from the ADNI cohort. A. SIGNIFICANCE The available knowledge of specific risk and protective factors is limited regarding the diagnosis of AD and progression from MCI to AD in minoritarian populations. This study will validate a new described SNP that confers specific protection of the effect of ApoE4 status in 3 ethnic groups from the ADNI initiative: Caucasian non-Hispanic, Hispanic/Latino and African American. The short-term goal of this project is to increase the knowledge of rs10423769_A as a protective factor for the development of AD in minoritarian groups in the context of APOE4 carrier status. Additionally, the long-term goal of this project is to increase the knowledge of the differences seen in the clinical setting between ethnic groups This work is considered of relevance because of the high burden of disease caused by AD worldwide making it a public health problem, this will also be an opportunity for genetic analysis training of a graduate student. B. APPROACH • Specific aim 1: Obtain a population structure of participants from African America/Black, Caucasian, and Hispanic/Latino populational groups from the ADNI database using Local and Global ancestry. For this purpose, we will obtain retrospective data available in the ADNI database that contains SNP array results from the Illumina HumanOmniExpress BeadChip, Illumina Human610-Quad BeadChip and Illumina Omni 2.5M (WGS Platform). Quality control steps will be perform using PLINK v2.0. Here, we will select the ancestral population reference that is most adequate for the studied sample using the Human Genome Diversity Project (HGDP) and 1000 Genomes project databases. Principal component analysis will assist in the identification of the Population structure and it will be determined Globally and Locally using RFmix8 and TRACTOR packages. • Specific Aim 2: Analyze the ApoE4 and rs10423769_A carrier status from these individuals. The status of ApoE and rs10423769_A will be determined from the information from the SNP arrays and samples will be filtered and independently analyzed regarding each of the genotypes. • Specific Aim 3: Establish the OR for the diagnosis of AD and progression from Mild cognitive impairment (MCI) to AD for the 3 populational groups. Interaction analysis will be used to establish the relationship between the rs10423769_A and ApoE3/E3, ApoE3/E4 and ApoE4/E4 genotypes corresponding to a dosage model. The false discovery rate will be controlled with the use of Benjamini and Hochberg statistical method for multiple testing. C. Pitfalls and alternatives. One limiting factor is limited subjects from minoritarian groups, restricting the analysis to specific SNP will increase statistical power. Also, the analysis of complex datasets requires individuals with high bioinformatic skills, for this purpose, the laboratory has a group of experts highly trained in genomic data analysis that can assist the graduate students with mentorship. Future directions will be to broaden the analysis to other SNPs that can help to understand risk factors associated with AD. REFERENCES 1. Global health estimates: Leading causes of DALYs. https://www.who.int/data/gho/data/themes/mortality-and-global-health-estimates/global-health-estimates-leading-causes-of-dalys. 2. Alzheimer’s Facts and Figures Report | Alzheimer’s Association. https://www.alz.org/alzheimers-dementia/facts-figures. 3. Petersen, R. C. et al. Alzheimer’s Disease Neuroimaging Initiative (ADNI): Clinical characterization. Neurology 74, 201 (2010). 4. Weiner, M. W. et al. Increasing participant diversity in AD research: Plans for digital screening, blood testing, and a community-engaged approach in the Alzheimer’s Disease Neuroimaging Initiative 4. Alzheimer’s & Dement. n/a,. 5. In Its Latest Iteration, ADNI Broadens Diversity | ALZFORUM. https://www.alzforum.org/news/community-news/its-latest-iteration-adni-broadens-diversity. 6. Kunkle, B. W. et al. Novel Alzheimer Disease Risk Loci and Pathways in African American Individuals Using the African Genome Resources Panel. JAMA Neurol. 78, 102 (2021). 7. Rajabli, F. et al. A locus at 19q13.31 significantly reduces the ApoE ε4 risk for Alzheimer’s Disease in African Ancestry. PLOS Genet. 18, e1009977 (2022). 8. Maples, B. K., Gravel, S., Kenny, E. E. & Bustamante, C. D. RFMix: A Discriminative Modeling Approach for Rapid and Robust Local-Ancestry Inference. Am. J. Hum. Genet. 93, 278 (2013). |
| Additional Investigators |
