Study reveals potential drug links to Dementia risk

By Dr. Chinta SidharthanReviewed by Lily Ramsey, LLMJan 23 2025

Analysis of millions of patient records suggests potential benefits from antimicrobials and harms from antipsychotics.

Study: Data-driven discovery of associations between prescribed drugs and dementia risk: A systematic review. Image Credit: Orawan Pattarawimonchai/Shutterstock.com

In a recent study published in Alzheimer’s & Dementia, a team of scientists systematically reviewed data-driven research on how prescribed medications may influence dementia risk.

They analyzed the medical records of over 130 million individuals and identified drug classes potentially linked to higher or lower dementia risk. These findings could help guide drug repurposing strategies and inform prevention efforts in dementia-related diseases.

Background

Dementia affects millions worldwide and poses a significant global health challenge, causing substantial personal and economic burdens. Current treatments primarily address symptoms with limited success in altering disease progression.

Moreover, the efforts to develop effective disease-modifying therapies also face numerous challenges due to the complex pathways underlying dementia.

Advances in identifying potential pathogenic mechanisms, such as protein misfolding and inflammation, highlight possible therapeutic targets. In recent times, repurposing existing drugs that have already been approved for use in other medical conditions offers a promising avenue.

These medications may interact with dementia-related biological pathways, providing benefits beyond their original indications.

However, although certain drug classes, including anti-inflammatory agents and vaccinations, have shown potential, the findings remain inconsistent, necessitating systematic investigations to uncover consistent patterns that support effective prevention and therapeutic strategies.

About the study

The present systematic review used a comprehensive search strategy, targeting studies that investigated associations between medications prescribed for various diseases and dementia risk using a data-driven approach. The team searched numerous databases, covering records up to August 2023, without language restrictions.

The eligible studies were those that analyzed large datasets, such as electronic health records and administrative claims, using machine learning and statistical modeling to identify patterns. The studies included in the review all has a study population of adults diagnosed with all-cause dementia or subtypes, as defined by standardized criteria.

Specific focus was placed on medications prescribed to cohorts ranging from thousands to millions of participants, with follow-up durations spanning years. Data extraction involved variables such as sample size, predictors, outcomes, and analysis techniques.

However, the methodologies varied widely among the 14 included studies. Techniques included logistic regression, random forests, and other machine-learning models. Some studies focused exclusively on medications, while others included broader features, such as demographics and medical histories. Medication effects were assessed based on prescription frequency, time of use, and associated dementia risk. The review used tools to control bias and ensure high-quality assessment across studies.

Key findings

The study found that specific drug classes were associated with changes in dementia risk. Medications such as antimicrobials, anti-inflammatory drugs, as well as vaccines, were linked to reduced dementia risk, while others, such as antipsychotics and certain diabetes medications, were associated with increased risk of dementia.

The review found that certain medications were consistently associated with significant effects on dementia risk, both protective and adverse. Antibiotics, antivirals, and anti-inflammatory drugs emerged as protective, with hazard ratios indicating notable reductions in the likelihood of developing dementia. These findings highlighted the potential role of addressing inflammation and infections as part of dementia prevention strategies.

Similarly, vaccines for diseases such as hepatitis and typhoid showed associations with reduced dementia risk, suggesting that immune modulation may offer protective benefits against cognitive decline.

In contrast, the researchers uncovered concerning associations between frequent use of antipsychotics and benzodiazepines and an elevated risk of dementia. These results aligned with previous evidence indicating the long-term neurological risks of these drug classes and underscored the need for careful evaluation of their use, particularly in populations at risk for cognitive impairment.

Meanwhile, medications targeting vascular and metabolic pathways, including antihypertensives and statins, showed mixed outcomes. The impact of these drugs on dementia risk varied depending on the specific medication and demographic factors, which indicated the need for more precise investigations to determine their role in dementia prevention.

The data-driven approach in the studies improved the identification of patterns across diverse datasets while confirming previous findings and revealing new drug candidates. However, the associations varied by study design, medication classification systems, and population demographics, which higlighted the need for targeted clinical trials to elucidate mechanisms underlying these associations.

Conclusions

To summarize, the reviewers reported on the complex interplay between medications prescribed for various health conditions or diseases and dementia risk and revealed opportunities for drug repurposing. While certain medications showed promise in reducing the risk of dementia, the review found that others require caution due to potential adverse associations.

These findings highlighted the value of data-driven research in identifying therapeutic candidates and informing clinical decisions. The scientists believe that future work should focus on validating these associations through experimental studies and advancing our understanding of their underlying biological mechanisms.