These diseases could predict Alzheimer’s

A new study led by researchers at Vanderbilt Health in the United States has identified medical conditions that often precede the diagnosis of Alzheimer’swhich could open opportunities to develop interventions that reduce the risk of suffering from the disease, as published in the journal Alzheimer’s Research & Therapy.

Alzheimer’s disease is a neurodegenerative disorder that develops over decades and some midlife conditions, such as hypertension, hyperlipidemia and strokehave been linked to an increased risk of developing it later in life, but the list of medical conditions that predict its development is limited.

“If we know the full inventory of medical conditions that predict the development of Alzheimer’s disease 10 or more years later, we could intervene before clinical symptoms of cognitive or memory impairment manifest -explains Dr. Xue Zhong, associate research professor of Medicine in the Division of Genetic Medicine and Clinical Pharmacology and co-author of the study. It is projected that Delaying the onset of Alzheimer’s disease by just five years could reduce the incidence rate by half“.

To systematically identify medical conditions associated with the development of Alzheimer’s diseasethe researchers analyzed Anonymous electronic health records (EHRs) from two independent databases. They used MarketScan, a US claims-based database with more than 150 million peopleas the discovery cohort, and the Vanderbilt Health EHR system, which includes approximately 3 million patients, as an independent cohort to validate the discovery cohort findings.

They identified 43,508 people diagnosed with Alzheimer’s disease (cases) and 419,455 controls matched by age and sex in the MarketScan database and 1,320 cases and 12,720 matched controls at Vanderbilt Health System.

By tracking electronic health records (EHRs) over a 10-year period before Alzheimer’s diagnosis and comparing EHRs between cases and controls, researchers identified more common medical conditions in those who later developed Alzheimer’s.

So, They found more than 70 conditions in both databasesdominated by mental health conditions (e.g., depression and severe neuropsychiatric symptoms such as paranoia/psychosis and suicidal ideation); neurological and sleep-related conditions (insomnia, hypersomnia and sleep apnea); cardiovascular/circulatory conditions (essential hypertension, cerebral atherosclerosis and cerebral ischemia) and endocrine/metabolic conditions (type 2 diabetes).

They used data from two large-scale DNA biobanks (Vanderbilt Health BioVU and UK Biobank) to evaluate the genetic basis of these conditions in relation to the genetics of Alzheimer’s disease. They identified 19 conditions associated with individual genomic risk variants or a polygenic risk score for Alzheimer’s disease.

The authors point out that EHR associations do not prove a causal role for conditionsbut they do offer a data-driven roadmap for early risk recognition and prevention-focused research.

“Longitudinal electronic medical records offer a striking view of the development of Alzheimer’s disease over decades,” says Zhong. By identifying medical patterns that systematically precede to Alzheimer’s disease, “We can uncover new opportunities for risk reduction, early intervention, and improved patient outcomes.”

In this sense, Zhong, co-author of the study along with Dr. Nancy Cox, professor of Medicine, points out that the study confirms that Hypertension and hypercholesterolemia are risk factors for the development of Alzheimer’s disease in old age, suggesting that addressing these conditions in middle age (by adopting healthier lifestyles or using antihypertensive or lipid-lowering medications) may reduce the risk of Alzheimer’s disease.

“We also observed a inverse association between cancer and Alzheimer’s disease in both EHR data sets, which replicates previous epidemiological findings -Zhong highlights-. “We are currently investigating the mechanisms underlying this phenomenon, with the aim of generating information that can inform new therapeutic strategies for Alzheimer’s disease.”