# Project 1: Alcohol use and AD/ADRD risk: innovative methods and data for new insights

> **NIH NIH P01** · BOSTON UNIVERSITY MEDICAL CAMPUS · 2024 · $655,214

## Abstract

PROJECT SUMMARY
The effects of alcohol use on Alzheimer’s Disease and Alzheimer’s Disease Related Disorders (AD/ADRD)
remain uncertain. Long hypothesized to have a J-shaped relationship, with the best cognitive outcomes among
light drinkers, growing evidence suggests that benefits of even ”low-risk” drinking are unlikely. Yet, there is not
clear quantification of how low-risk or moderate alcohol consumption (considered unhealthy but not constituting
alcohol use disorder) affects AD/ADRD risk. Drinking is extremely common and modifiable via clinical and
policy interventions. Estimates of the adverse effects of heavy drinking on AD/ADRD also vary widely. The
recent Lancet Review estimation of the population attributable fraction (PAF) for AD/ADRD associated with
alcohol use was based on a small number of studies that may not be generalizable. The population impact of
alcohol use may be substantially underestimated. Individual studies of alcohol use are potentially biased due to
confounding, reverse causation, or measurement error. We propose coordinated analyses across ten diverse
clinical and population cohorts. Working with the TIME-AD Cores, we will triangulate evidence from doubly-
robust g-methods, genetic instrumental variables (IVs), and policy IV analyses to derive the best possible
estimates on the effects of alcohol use on AD/ADRD risk. Kaiser Permanente Northern California electronic
health record (EHR) data for over a million older adults are augmented with embedded surveys and
genotyping. We additionally use data from the UK Biobank, All of US, and multiple cohorts with detailed,
repeated assessments of alcohol use, confounders, and cognition. We adopt a systematic approach to
interrogating potential biases by comparing patterns across populations, study designs, and identification
approaches. Uncertainty in estimates will be characterized using quantitative bias analysis. We propose four
aims: Aim 1. Assess how low-risk alcohol use, unhealthy alcohol use, and alcohol use disorder, compared to
no alcohol use, affect AD/ADRD risk, triangulating across study designs and data sources. Aim 2. Evaluate
heterogeneity in the effects of different quantities and patterns of drinking on AD/ADRD risk, evaluating type
(e.g., beer, red wine, white wine, spirits), frequency-quantity pattern (e.g., drinks per month, binge drinking
episodes), problem-drinking (e.g., ”blackout drinking”), and duration (e.g., years of consumption). Aim 3.
Evaluate how the effects of alcohol use on AD/ADRD risk vary in relation to other risk factors for AD/ADRD
risk, i.e., heterogeneity across characteristics of the person using alcohol, such as genetic risk, cardiometabolic
comorbidities, gender, race/ethnicity, education, social isolation, cannabis use, or medication use. Aim 4:
Evaluate the extent to which disparities in dementia incidence across social strata are attributable to
differences in alcohol consumption or could be ameliorated by changes in drinking. Using ...

## Key facts

- **NIH application ID:** 10934714
- **Project number:** 1P01AG082653-01A1
- **Recipient organization:** BOSTON UNIVERSITY MEDICAL CAMPUS
- **Principal Investigator:** Medellena Maria Glymour
- **Activity code:** P01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $655,214
- **Award type:** 1
- **Project period:** 2024-09-15 → 2029-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10934714

## Citation

> US National Institutes of Health, RePORTER application 10934714, Project 1: Alcohol use and AD/ADRD risk: innovative methods and data for new insights (1P01AG082653-01A1). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10934714. Licensed CC0.

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