# Statistical and computational methods for integrative analysis of Alzheimer's Disease genetics

> **NIH NIH R01** · STANFORD UNIVERSITY · 2022 · $705,965

## Abstract

Project Summary/Abstract
Genetic factors play an important role in the development of Alzheimer's disease. While much progress has
been made in Alzheimer’s disease genetics, the role of noncoding variants is largely unknown. The noncoding
genome covers ~98% of the human genome and includes elements that regulate when, where, and to what
degree protein-coding genes (e.g. APOE) are transcribed. The objective of this proposal will be to focus
specifically on the analysis of whole-genome sequencing studies of Alzheimer’s disease, in order to identify
rare noncoding variants and characterize their role in Alzheimer’s disease pathogenesis. We will attain our
objective via an innovative approach, combining whole-genome sequencing, epigenetic technologies and
multi-layered phenotypic data such as imaging and biomarkers. This will lead to a unique combination of
methodologies for the analysis of noncoding variants, allowing for absence of natural units (e.g. genes) for
testing (Aim 1), integration of multi-layer information for enhancing power (Aim 2), and biologically
meaningful interpretation of association signals (Aim 3). The proposed methods will be applied to a total of
roughly 20,000 whole genomes unifying the Alzheimer's Disease Neuroimaging Initiative (ADNI), the
Alzheimer's Disease Sequencing Project (ADSP), the Religious Orders Study and Memory and Aging Project
(ROSMAP) and a newly established cohort, the Stanford Extreme Phenotypes in Alzheimer's Disease (StEP
AD). We expect that the application of the proposed methods will significantly improve our understanding of the
genetic architecture of Alzheimer's disease and, critically, provide a set of well-defined, novel targets for the
development of genomic-driven medicine.

## Key facts

- **NIH application ID:** 10411994
- **Project number:** 5R01AG066206-04
- **Recipient organization:** STANFORD UNIVERSITY
- **Principal Investigator:** Zihuai He
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $705,965
- **Award type:** 5
- **Project period:** 2019-09-15 → 2024-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10411994

## Citation

> US National Institutes of Health, RePORTER application 10411994, Statistical and computational methods for integrative analysis of Alzheimer's Disease genetics (5R01AG066206-04). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10411994. Licensed CC0.

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