# Hypertensive Disorders of Pregnancy and Subsequent Risk of Vascular Dementia, Alzheimer's Disease, or Related Dementia: A Retrospective Cohort Study Taking into Account Mid-Life Mediating Factors.

> **NIH NIH K01** · UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH · 2020 · $124,188

## Abstract

PROJECT SUMMARY/ABSTRACT
This is an application for a K01 award for Dr. Karen Schliep, a tenure-line Assistant Professor of Public Health
at the University of Utah. Dr. Schliep is establishing herself as a young investigator in women’s life-course
epidemiology, specifically in a novel area of aging research—to improve our understanding of women’s
increased risk of Alzheimer’s disease (AD) and related dementias (RD) and create women-specific
interventions to mitigate risk and improve outcomes. This award will allow Dr. Schliep to achieve her goal of
research independence by providing her support to accomplish the following training aims: 1) develop
expertise in biomedical informatics and population-based research methods; 2) gain experience in the
conduction of clinical cognitive health assessments; 3) enhance knowledge of modifiable factors affecting
women’s mid- and late-life cognitive health; and 4) expand skills to independently lead and manage a
successful research program. Dr. Schliep has assembled a mentoring team comprising a primary mentor, Dr.
Michael Varner, an obstetrician and nationally renowned maternal-fetal medicine investigator with expertise in
pregnancy complications including hypertensive disorders of pregnancy (HDP), and two co-mentors: Dr.
Norman Foster, a cognitive neurologist and geriatric neurologist and recognized leader in dementia research,
and Dr. Ken Smith, an internationally known expert in population-based analyses and genetic/family
epidemiology. Dr. Schliep has five advisors with expertise in classification modeling, ADRD neuropsychology,
mid-life women’s health, longitudinal and survival data analysis, and chronic disease epidemiology.
 Little is known regarding the association between HDP, estimated to complicate 2–8% of all pregnancies,
and long-term adverse maternal neurological outcomes with similar inflammatory vascular etiologies, including
ADRD. An estimated 5.4 million Americans currently suffer from ADRD, two-thirds of whom are women. As the
US aging population increases, prevalence of dementia is expected to approach 13.2 to 16.0 million cases by
2050. Why ADRD disproportionately affects women is not known. Dr. Schliep’s research objective is to develop
classification models for the various dementia subtypes (including AD, vascular dementia, Lewy body
dementia, and frontotemporal dementia) to analyze longitudinal, individual-level data to better understand how
HDP may increase a woman’s risk for ADRD. Dr. Schliep will accomplish this through the following research
aims: 1) increase accuracy of ADRD diagnoses within health administrative databases; and 2) investigate the
association between HDP and ADRD, and mid-life mediating factors. The proposal’s expected outcomes
include 1) a novel method to accurately capture dementia cases within large linked health administrative
databases; 2) clarity on how HDP may be linked with specific dementia subtypes; and 3) skills, experience,
and preliminary data for Dr....

## Key facts

- **NIH application ID:** 9892855
- **Project number:** 1K01AG058781-01A1
- **Recipient organization:** UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH
- **Principal Investigator:** Karen C. Schliep
- **Activity code:** K01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $124,188
- **Award type:** 1
- **Project period:** 2020-09-01 → 2025-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9892855

## Citation

> US National Institutes of Health, RePORTER application 9892855, Hypertensive Disorders of Pregnancy and Subsequent Risk of Vascular Dementia, Alzheimer's Disease, or Related Dementia: A Retrospective Cohort Study Taking into Account Mid-Life Mediating Factors. (1K01AG058781-01A1). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/9892855. Licensed CC0.

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