As the global population ages, the incidence of neurodegenerative diseases such as Alzheimer's disease (AD) is rapidly increasing. By 2050, the global population of people over the age of 60 is expected to double, reaching 2.1 billion individuals, while those over 80 is expected to triple, reaching 426 million (1). Cases of dementia are also estimated to nearly triple, reaching 153 million individuals (2).
Early diagnosis may change the trajectory of the disease, allowing for interventions to slow cognitive decline and improve quality of life. However, established testing methods, such as positron emission tomography (PET) and cerebrospinal fluid (CSF) analysis through lumbar puncture, are costly, invasive, and not widely available.
Developing a more accessible, less invasive, and cost-effective blood-based AD test is a global priority. For these biomarker tests to be adopted worldwide, they must work reliably across populations and in accordance with current methods (3). Aligning standards for new and old tests is crucial for credibility and success, which means including diverse samples from various races and ethnicities. Given the complex, multifaceted nature of AD, combining these blood tests with established imaging and fluid tests could improve how we diagnose, predict, and monitor the disease (4).
However, the complexity of AD could make diagnosis very difficult as each case varies depending on the patients’ genetic makeup, symptoms, and how the disease progresses. A test that works for one person might not for another. While amyloid plaques and tau tangles are present in all AD cases, differences in race, gender, and even environmental factors like air pollution can affect when and how the disease progresses (5).
Like many diseases, an AD diagnosis is not one-size-fits-all. If we only study AD in a single group, we will only learn about it in that population. Including people from diverse backgrounds helps us see all the ways the disease can appear. However, most current biomarker tests are based on White volunteers, and a 2022 study found that these tests might misdiagnose non-White individuals (6).
Developing dependable and accurate blood tests for Alzheimer’s requires studying how biomarker levels vary across different populations, especially among groups that have been underrepresented in research. Using a broader, more diverse dataset makes the tests more robust and ensures they accurately reflect the varied ways the disease appears in people.
The future of AD biomarker development depends on strong, cross-sector partnerships and focusing on patient needs. Working with organizations like the Davos Alzheimer’s Collaborative (DAC) and the Global Alzheimer’s Platform Foundation (GAP) gives researchers access to diverse, well-documented patient groups. This collaboration lets scientists study many biomarkers in people from different ethnic, racial, and geographic backgrounds, potentially improving Alzheimer’s trials. For example, DAC’s group includes Koreans at every stage of Alzheimer’s, while GAP’s group covers all stages and includes at least 25 percent from underrepresented communities. Both groups are clearly defined and use imaging to confirm the disease stage, which helps ensure accurate comparisons.
The development of a blood-based Alzheimer’s test will not happen overnight, but with continued investment in research and inclusivity, it is an achievable goal. As we work toward this future, we must remain committed to the idea that healthcare, particularly in the fight against AD, should leave no one behind.
Newsletters
Receive the latest analytical scientist news, personalities, education, and career development – weekly to your inbox.
References
- WHO, “Ageing and Health” (2024). Available at: https://www.who.int/news-room/fact-sheets/detail/ageing-and-health.
- GBD 2019 Dementia Forecasting Collaborators, Lancet Public Health, 7, 2 (2022). PMID: 34998485.
- O Hansson et al., Alzheimers Dement, 18, 12 (2022). PMID: 35908251.
- MT Ferretti et al., Nat Rev Neurol (2025). PMID: 39774246.
- J Manuello et al., Nat Commun, 15 (2024). PMID: 38538590.
- MT Ashford et al., Alzheimers Dement, 18, 12 (2022). PMID: 35213778.