# Alzheimer's Disease Genetics Consortium

> **NIH NIH U01** · UNIVERSITY OF PENNSYLVANIA · 2021 · $4,015,616

## Abstract

The goal of the Alzheimer's Disease Genetics Consortium (ADGC) is to completely resolve the genetics of
Alzheimer's disease (AD). We will identify both common and rare variants to cause AD, alter AD risk, and
protect against AD. To this goal, the ADGC will continue to aggregate large numbers of multiethnic cohorts,
harmonized genetic and phenotype data, and perform coordinated analyses of both early and late-onset AD
genetics, and mild cognitive impairment. The rationale for genetic studies is to predict who will develop AD,
understand disease mechanism, and identify new therapeutic targets. This last reason is the most critical.
Most ongoing drug trials target the Aβ peptide, the main component of amyloid plaques, and more recently tau,
the protein that aggregates in neurofibrillary tangles (NFTs). However, though some Aβ-targeting therapies
are promising, no disease modifying therapies exist. Even if these approaches are successful, multiple
therapies may be needed to reach the ultimate goal of AD prevention. Thus, new targets are needed. Genetic
studies are one method of identifying new drug targets. Targets supported by genetic evidence are 2-3 more
likely to succeed than those without. For this reason, until therapies that effectively prevent AD at a cost that
permits widespread use in all countries, we need additional genetic studies.
To completely resolve AD genetics and develop new therapeutic targets, we will execute the following aims.
Aim 1 is to expand exiting cohorts and add new cohorts for genetic analyses. We will focus on assembling a
multiethnic data set. We will expand Caucasian samples, Caribbean Hispanics, non-Caribbean Hispanics,
African Americans, Asians and subjects from India. Aims 2 is generate array genotyping and whole genome
sequence (WGS) data for all cohorts, and generate imputation panels from WGS AD data These reference
panels with publically available panels will be used to impute all samples. Aim 3 is gene discovery using all
available data including WES and WGA data in genome-wide analyses. We will analyze multiple ethnic groups
separately and in trans-ethnic analyses. Aim 4 is to perform genome-wide analysis of AD-related phenotypes
including cardiovascular traits, cognitive phenotypes, MRI imaging, amyloid and tau PET imaging, and
neuropathology phenotypes. Aim 5 is post-association analyses. We will use bioinformatics approaches and
partner with other investigators using biochemical approaches to link association loci to specific genes.
Methods include genome-wide Capture-C and ATACSeq and massively parallel reporter assays. We will use
pathway and gene cluster approaches and co-expression networks to interpret the biological significance of
genes identified by this and other studies. In addition, we will continue to promote young investigators, and
work with international collaborators such as IGAP to increase the sample size and approaches used.

## Key facts

- **NIH application ID:** 10137858
- **Project number:** 5U01AG032984-12
- **Recipient organization:** UNIVERSITY OF PENNSYLVANIA
- **Principal Investigator:** GERARD DAVID SCHELLENBERG
- **Activity code:** U01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $4,015,616
- **Award type:** 5
- **Project period:** 2009-04-01 → 2025-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10137858

## Citation

> US National Institutes of Health, RePORTER application 10137858, Alzheimer's Disease Genetics Consortium (5U01AG032984-12). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10137858. Licensed CC0.

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