# Discovering causal genes, brain regions and other risk factors for Alzheimer'a disease

> **NIH NIH R01** · UNIVERSITY OF MINNESOTA · 2022 · $622,592

## Abstract

Summary
 Alzheimer's disease (AD) affects over 44 million individuals worldwide, and the number is projected to triple
by 2050. However, currently there is no cure for AD. Observational epidemiology studies have identiﬁed some
modiﬁable lifestyle-related risk factors associated with AD; if these risk factors are indeed causal to, but not just
effects of, AD, they can be targeted in interventions to reduce the incidence of AD. To alleviate the challenges
facing observational studies with likely confounding and reverse causation, we develop and apply a suite of novel,
robust and powerful causal inference methods by integrating the large amount of existing large-scale GWAS of
AD and other traits. Speciﬁcally, ﬁrst, going beyond existing two-sample Mendelian randomization (2SMR), we
will develop the following new methods that are more powerful and more robust with less stringent modeling
assumptions: transcriptome-wide association studies in the presence of confounding and invalid instrumental
variables, co-localization detection of causal genetic variants for multiple traits, and orienting the causal direction
between two traits using multiple (possibly correlated) genetic variants as instrumental variables. Second, we will
adapt and apply both the new and existing methods to multiple large-scale GWAS datasets with AD and other
molecular/imaging/clinical traits to comprehensively search and identify not only AD target genes, but also brain
areas and their functional connectivities, and other risk factors, that are putatively causal to AD. As a byproduct,
we will develop and distribute software implementing the proposed methods.

## Key facts

- **NIH application ID:** 10358645
- **Project number:** 5R01AG065636-03
- **Recipient organization:** UNIVERSITY OF MINNESOTA
- **Principal Investigator:** Wei Pan
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $622,592
- **Award type:** 5
- **Project period:** 2020-03-01 → 2025-02-21

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10358645

## Citation

> US National Institutes of Health, RePORTER application 10358645, Discovering causal genes, brain regions and other risk factors for Alzheimer'a disease (5R01AG065636-03). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10358645. Licensed CC0.

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