A new study led by researchers at Vanderbilt Health has identified medical conditions that often precede an Alzheimer’s disease diagnosis. The findings, published in the journal Alzheimer’s Research & Therapy , could open opportunities to develop interventions that reduce Alzheimer’s disease risk.
Alzheimer’s disease is a neurodegenerative disorder that develops over decades. Some health conditions in midlife, such as hypertension, hyperlipidemia and stroke, have been linked to an increased risk of Alzheimer’s disease later in life, but the list of medical conditions that predict Alzheimer’s disease development is limited.
“If we know the full inventory of medical conditions that predict Alzheimer’s disease development 10 or more years later, we can potentially intervene before clinical symptoms of memory and/or cognitive impairment become apparent,” said Xue Zhong , PhD, research assistant professor of Medicine in the Division of Genetic Medicine and Clinical Pharmacology. “It is projected that delaying the onset of Alzheimer’s disease by just five years could cut the incidence rate in half.”
Zhong is co-corresponding author of the study with Nancy Cox , PhD, professor of Medicine.
To systematically identify medical conditions associated with the development of Alzheimer’s disease, the researchers analyzed de-identified electronic health records (EHRs) from two independent databases. They used MarketScan, a U.S. claim-based database with over 150 million individuals, as a discovery cohort and Vanderbilt Health’s EHR system, which includes about 3 million patients, as an independent cohort to validate the discovery cohort findings.
The researchers identified 43,508 individuals with an Alzheimer’s disease diagnosis (cases) and 419,455 age- and sex-matched controls in the MarketScan database and 1,320 cases and 12,720 matched controls in the Vanderbilt Health system.
By tracking EHRs over a 10-year window before an Alzheimer’s disease diagnosis and comparing the EHRs between cases and controls, the researchers identified medical conditions that occur more frequently in those who later developed Alzheimer’s disease. They found more than 70 conditions that appeared in both databases, which were dominated by:
Endocrine/metabolic conditions (e.g., Type 2 diabetes)
The investigators used data from two large-scale DNA biobanks (Vanderbilt Health’s BioVU and UK Biobank) to assess genetic underpinnings of these conditions in relation to Alzheimer’s disease genetics. They identified 19 conditions that are either associated with individual genomic risk variants or with a polygenic risk score for Alzheimer’s disease.
The authors note that EHR associations do not prove a causal role for the conditions, but they do offer a data-driven road map for earlier risk recognition and prevention-focused research.
“Longitudinal EHRs offer a powerful view into the decades-long development of Alzheimer’s disease,” Zhong said. “By identifying medical patterns that consistently precede Alzheimer’s disease, we can unlock new opportunities for risk reduction, early intervention and improved patient outcomes.”
Zhong points out that the study confirms hypertension and hypercholesterolemia as risk factors for the development of late-life Alzheimer’s disease, which suggests that addressing these conditions in midlife — by adopting healthier lifestyles or using antihypertensive or lipid-lowering medications — may reduce Alzheimer’s disease risk.
“We also observed an inverse association between cancer and Alzheimer’s disease across both EHR datasets, replicating prior epidemiologic findings,” Zhong said. “We are now investigating the mechanisms underlying this phenomenon, with the goal of generating insights that could inform novel therapeutic strategies for Alzheimer’s disease.”
Joining Zhong and Cox on the study are Zhijun Yin, PhD, MS, Rui Chen, PhD, Kerou Cheng and Bingshan Li, PhD, from Vanderbilt Health; and Gengjie Jia, PhD, and Andrey Rzhetsky, PhD, from the University of Chicago. The research was supported by the National Institutes of Health (grants R01AG069900, U54HG012510, RM1HG009034, R01MH137646, R01AG089717 and R01AG065611) and by a Johnson & Johnson contract.
Alzheimer s Research & Therapy
Longitudinal analysis of electronic health records reveals medical conditions associated with subsequent Alzheimer’s disease development
29-Dec-2025