# Cardiometabolic Risk Factors and Risk of Dementia

> **NIH NIH R03** · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · 2020 · $78,250

## Abstract

Project Summary/Abstract
The cause of dementia is unknown, but it is considered to be a multifactorial disease, resulting from the
interaction of both genetic and environmental factors, which contribute to its occurrence and expression.
Genome­wide association studies and population­based studies have confirmed that the ε4 allele of APOE is
the strongest genetic risk factor for dementia. However, APOE ε4 is thought to be responsible for less than
50% of dementia risk, suggesting that environmental factors contribute to development of dementia in the
genetically predisposed. Given the absence of sufficient treatment options for dementia, strategies to prevent
or delay the disease onset are urgently needed. Among potentially modifiable determinants of dementia,
appropriate control of cardiometabolic risk factors [Body Mass Index (BMI), systolic and diastolic blood
pressure, diabetes and hypercholesterolemia] could be a primary strategy to reduce the incidence of dementia.
However, cardiometabolic risk factors in later life have been inconsistently associated with dementia with both
increased and decreased risk for dementia. The reasons for this discordance in findings are unclear and
perhaps partially due to not only the differing lengths of follow­up between the assessments of cardiometabolic
risk factors and dementia onset (reverse causation bias), but also population heterogeneity. Prior studies have
used either one­time baseline cardiometabolic risk factor measurements or longitudinal measurements
targeting only on mean­level changes (i.e., population average trajectory) with only one trajectory while
ignoring population heterogeneity. We propose to use a nested case­control design with group­based
trajectory analysis approach to analyze a large, multisite, longitudinal aging and dementia dataset—Uniform
Data Set (UDS) provided by the National Alzheimer’s Coordinating Center (NACC). Aim 1): To apply a nested
case­control approach to identify distinct trajectories of cardiometabolic risk factors preceding the diagnosis of
dementia (up to 15 years) and matched control group using group­based trajectory model, and to examine the
effects of distinct trajectories of cardiometabolic risk factors, APOE genotype, and their interaction on the risk
of dementia using matched case­control subsamples nested in UDS cohort. Aim 2): To investigate the reverse
causation bias for the associations between cardiometabolic risk factors and dementia in aim 1. Aim 3). To
explore whether the trajectories of cardiometabolic risk factors and their interaction with APOE genotype on the
risk of dementia differ by race, sex, baseline age, and Alzheimer’s disease (AD) subtype.

## Key facts

- **NIH application ID:** 10030347
- **Project number:** 1R03AG068413-01
- **Recipient organization:** UNIVERSITY OF PITTSBURGH AT PITTSBURGH
- **Principal Investigator:** Dianxu Ren
- **Activity code:** R03 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $78,250
- **Award type:** 1
- **Project period:** 2020-09-30 → 2022-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10030347

## Citation

> US National Institutes of Health, RePORTER application 10030347, Cardiometabolic Risk Factors and Risk of Dementia (1R03AG068413-01). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10030347. Licensed CC0.

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