A new study led by researchers at Vanderbilt Health has identified a range of medical conditions that frequently appear years before a person is diagnosed with Alzheimer’s disease. The research, published in the journal Alzheimer’s Research & Therapy, suggests that recognising these conditions earlier in life could help scientists and clinicians develop strategies to reduce the risk of Alzheimer’s or delay its onset. By identifying patterns in large health datasets, the study provides new insight into the long development process of the disease and highlights potential opportunities for earlier intervention.
Alzheimer’s disease is a progressive neurodegenerative condition that develops slowly over decades, gradually affecting memory, thinking and behaviour. Previous research has already linked certain midlife health issues to a higher risk of developing Alzheimer’s later in life. Conditions such as high blood pressure, elevated cholesterol levels and stroke have been identified as important risk factors. However, researchers say that the full range of medical conditions that might signal increased Alzheimer’s risk has remained relatively limited. The new study aimed to expand that list and identify additional health conditions that may appear long before clinical symptoms become noticeable.
“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 or cognitive impairment become apparent,” said Xue Zhong, PhD, research assistant professor of Medicine in the Division of Genetic Medicine and Clinical Pharmacology. Zhong explained that delaying the onset of Alzheimer’s disease by even five years could significantly reduce the number of people affected. Some projections suggest that such a delay could cut the overall incidence of the disease by about half. Zhong served as co-corresponding author of the study alongside Nancy Cox, PhD, professor of Medicine.
To systematically identify medical conditions associated with Alzheimer’s development, the research team analysed de-identified electronic health records from two large and independent databases. The first was the MarketScan claims database, which contains health information from more than 150 million individuals across the United States. The second was the electronic health record system at Vanderbilt Health, which includes approximately three million patients. The MarketScan dataset served as the discovery cohort, allowing researchers to identify potential associations, while the Vanderbilt dataset was used to validate the findings independently.
Within the MarketScan database, researchers identified 43,508 individuals who had received an Alzheimer’s diagnosis and compared them with 419,455 individuals of similar age and sex who had not developed the disease. In the Vanderbilt Health dataset, the team analysed 1,320 Alzheimer’s cases and 12,720 matched control participants. By examining medical records covering the decade before an Alzheimer’s diagnosis and comparing patterns between the two groups, researchers were able to identify health conditions that appeared more frequently among people who later developed Alzheimer’s.
The analysis revealed more than seventy medical conditions that consistently appeared in both databases before an Alzheimer’s diagnosis. Many of these fell into several broad categories. Mental health conditions were common, including depression and severe neuropsychiatric symptoms such as paranoia, psychosis and suicidal thoughts. Neurological and sleep-related issues also appeared frequently, including insomnia, hypersomnia and sleep apnoea. Cardiovascular and circulatory conditions, such as essential hypertension, cerebral atherosclerosis and cerebral ischaemia, were also identified. In addition, endocrine and metabolic conditions — particularly type 2 diabetes — were among the potential indicators.
To explore possible genetic links, researchers analysed data from two large DNA biobanks: Vanderbilt Health’s BioVU and the UK Biobank. They identified nineteen conditions that were associated either with individual genetic risk variants or with a broader polygenic risk score linked to Alzheimer’s disease. Although the associations found in electronic health records do not prove that these conditions directly cause Alzheimer’s, the researchers say the findings provide a valuable roadmap for earlier risk recognition and prevention-focused research. The study also confirmed well-known risk factors such as hypertension and high cholesterol, suggesting that managing these conditions in midlife through healthier lifestyles or medication could help reduce Alzheimer’s risk. Interestingly, the researchers also observed an inverse relationship between cancer and Alzheimer’s disease — a pattern previously reported in epidemiological studies — and they are now investigating the biological mechanisms behind this phenomenon in hopes of uncovering new therapeutic possibilities.
More information: Xue Zhong et al, Longitudinal analysis of electronic health records reveals medical conditions associated with subsequent Alzheimer’s disease development, Alzheimer’s Research & Therapy. DOI: 10.1186/s13195-025-01914-4
Journal information: Alzheimer’s Research & Therapy Provided by Vanderbilt University Medical Center
