# NIH grant: Cognitive Risk Profiles Among Aging Veterans: Harnessing Big Data for Precision Medicine (1IK2RD001192-01A1) — retained record

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[original source ↗](https://reporter.nih.gov/project-details/1IK2RD001192-01A1)

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NIH grant 1IK2RD001192-01A1: Cognitive Risk Profiles Among Aging Veterans: Harnessing Big Data for Precision Medicine
Institute: {'code': 'VA', 'abbreviation': 'VA', 'name': 'Veterans Affairs', 'admin_org_id': '12500964', 'admin_funding_url': ''}. PI: Francesca Veanna Lopez. Award: $.
Start: 2026-10-01T00:00:00.
Significance to VA: The overall goal of the proposed study is to examine how risk factor combinations relate to
late life cognitive impairment and Alzheimer’s disease (AD) and related dementias (ADRD) among Veterans.
Nearly 34% of Veterans have metabolic syndrome (MetS) and traumatic brain injury (TBI), yet these risk factors
are often studied in isolation rather than considering their potential cumulative and synergistic effects to cognitive
health. Within the context of ADRD, MetS and TBI share similar mechanisms like cerebrovascular dysfunction
and neuroinflammation that may accelerate cognitive dysfunction, particularly among Veterans with genetic
vulnerability to ADRD (apolipoprotein E [APOE] ε4 allele, polygenic risk scores [PRS]). Given Veterans often
present with multiple, co-occurring risk factors, it is insufficient to study risk factors in isolation. Rather, it is
necessary to move toward a more comprehensive, integrated model to optimize individualized prediction of risk.
Innovation and Impact: The proposed study is innovative in its precision medicine approach, integrating
multiple, often overlooked risk factors (MetS, TBI, and ADRD genetic risk variants) to holistically examine their
cumulative and synergistic effects on Veteran cognitive health. By leveraging existing, large-scaled VA
investments like the Million Veteran Program (MVP) in combination with the VA electronic health record (EHR),
this study will address critical gaps in both research and Veteran healthcare. This work not only advances
scientific understanding of MetS as an ADRD risk factor but also sets a new standard for precision aging. Insights
into how these factors interact to exacerbate ADRD risk could inform therapeutic studies targeting
neurobiological mechanisms of cognitive impairment. The scalable findings have the potential to transform
individualized risk prediction and ADRD intervention/prevention efforts that could benefit high-risk populations
beyond Veterans and reinforce VA as a global leader in ADRD precision medicine. Specific Aims: The proposed
study aims to (1) phenotype MetS using data-driven approaches; (2) examine the interaction between MetS and
TBI on cognitive (cross-sectional, longitudinal) and ADRD (longitudinal) outcomes; and (3) explore the
moderating effect of ADRD genetic risk. The central hypothesis is that ADRD genetic risk variants make the
brain more vulnerable to cerebrovascular dysfunction and neuroinflammation particularly in the presence of MetS
and TBI, which in turn accelerates cognitive dysfunction. Methodology: This study will harness genomic and
clinical information via MVP and EHR to determine ADRD genetic risk (APOE, AD PRS), MetS, TBI, and
ADRD/cognitive outcomes. Next, this study will systematically interrogate how risk factor combinations relate to
cognitive and ADRD outcomes in one of the largest and most representative Veteran cohorts to date. Path to
Translation/Implementation: This study’s risk models will enable earlier identification of high-risk Veterans and
inform targeted interventions (combinations of cognitive training, pharmacotherapy, and/or lifestyle changes). By
integrating into clinical guidelines, risk models could inform pilot programs and decision-support tools to identify
high risk Veterans, ensuring high quality and targeted care. Candidate: This CDA-2 will also provide the applicant
with training and support necessary to advance toward independence as a patient-centered researcher within
the VA. The applicant’s long-term career goal is to improve prediction of individualized risk to sustain functional
independence and quality of life for Veterans as they age. Findings will inform the applicant’s future VA grant
applications focused on refining risk prediction models and investigating neural mechanisms. Training goals
include hands-on training and formal coursework on how vascular-metabolic systems, genetics, and TBI
contribute to cognitive aging and ADRD risk using advanced statistical methods and large-scaled data to inform
precision care for Veterans, as well as academic career and professional development. The applicant is
supported by a strong research environment with the necessary resources and infrastructure for successful
execution of study aims, and a distinguished mentorship team with specific expertise in proposed areas of study.
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