# The role of toxic and essential metal mixtures, and co-exposures to social stressors, in cognitive aging, mild cognitive impairment, and novel epigenetic age biomarkers: The Baltimore Memory Study

> **NIH NIH K99** · JOHNS HOPKINS UNIVERSITY · 2022 · $98,296

## Abstract

PROJECT SUMMARY
Environmental toxicants are understudied modifiable risk factors for cognitive decline and dementia. Toxic
metals, and some essential trace elements, are well-known neurotoxicants and have been linked to cognitive
decline. Evaluating the joint actions of environmental exposures may elucidate shared physiologic pathways
and may inform policy. Populations with documented health disparities may be especially vulnerable to such
pathways due to higher cumulative exposure to environmental hazards and social stressors like poverty,
discrimination, or unsafe neighborhoods. Growing evidence suggests that novel epigenetic markers of DNA
methylation age predict a host of aging-related outcomes. Few studies have examined whether environmental
toxicants, individually or as a mixture, predict DNA methylation age acceleration. To address these gaps, the
Candidate proposes new aims in the Baltimore Memory Study, a study of cognitive and cardiovascular aging in
50- to 70-year-old residents of Baltimore, with diversity in race/ethnicity and socioeconomic status. The overall
objective of this proposal is to determine whether co-exposures to environmental toxicants and contextual
(neighborhood) stressors are linked to cognitive function, mild cognitive impairment, novel epigenetic
biomarkers. In the K99 phase, Dr. Moon will take advantage of existing bone lead biomarkers and chronic
stress measures to estimate whether the causal association of lead on longitudinal cognitive function (Aim 1)
or mild cognitive impairment (Aim 2) is modified by either a theory-based scale of neighborhood psychosocial
hazards or hypothalamic-pituitary-adrenal-axis dysfunction, measured by saliva cortisol. To complete these
aims and prepare for independence, Dr. Moon will train in four methodologic areas: cognitive aging
epidemiology, mixture and causal inference models, co-exposures to social stressors, and epigenetics through
formal coursework and mentoring. These training goals will be completed under the guidance of a strong
mentoring and advisory team (Drs. Schwartz, Buckley, Gross, Dean, and Ladd-Acosta). This Pathway in
Independence Award is critical to achieving Dr. Moon's long-term goal of becoming an independent
investigator with expertise on the environmental determinants of aging-related disease, particularly cognitive
aging outcomes, and evaluating how co-occurring social stressors contribute to health disparities. In the R00
phase, Dr. Moon will take advantage of stored biospecimens, measuring toxic and essential metals in urine
and genome-scale DNA methylation in blood. Using this new data, she will determine the independent joint
and effects of a mixture of metals on cognitive aging (cognitive function and mild cognitive impairment) (Aim 3)
and on DNA methylation age acceleration (Aim 4). The proposed training and aims will provide further
evidence that social and environmental factors must be addressed together to eliminate disparities in aging
and prelim...

## Key facts

- **NIH application ID:** 10428366
- **Project number:** 5K99ES031998-02
- **Recipient organization:** JOHNS HOPKINS UNIVERSITY
- **Principal Investigator:** Katherine A Moon
- **Activity code:** K99 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $98,296
- **Award type:** 5
- **Project period:** 2021-06-13 → 2024-02-29

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10428366

## Citation

> US National Institutes of Health, RePORTER application 10428366, The role of toxic and essential metal mixtures, and co-exposures to social stressors, in cognitive aging, mild cognitive impairment, and novel epigenetic age biomarkers: The Baltimore Memory Study (5K99ES031998-02). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10428366. Licensed CC0.

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