Analysis of Blood DNA and RNA Improves Identification of Alzheimer’s Disease Patients

Professors Youngho Park and Jungmin Pyeon’s Team at Seoul National University Bundang Hospital Develops Integrated Genomic and Transcriptomic Model
Consistent Performance Demonstrated in Analyses of U.S. ADNI and Korean Patient Groups
Potential

A study has found that analyzing both genomic (DNA) and transcriptomic (RNA) information from blood samples allows for more accurate identification of Alzheimer’s disease patients.

(From left) Youngho Park, Professor of Neurology at Seoul National University Bundang Hospital; Jungmin Pyeon, Professor; Jiyoon Hwang, Researcher; Gwangsik Roh, Professor at Indiana University. Seoul National University Bundang Hospital

The research team, led by Professors Youngho Park and Jungmin Pyeon, and researcher Jiyun Hwang from the Department of Neurology at Seoul National University Bundang Hospital, along with Professor Gwangsik Noh from Indiana University in the United States, announced on the 22nd that they confirmed the effectiveness of integrating DNA data—which reflects innate genetic risk—and RNA data—which represents current gene activity—to distinguish Alzheimer’s disease patients more effectively.

Alzheimer’s disease is a representative degenerative brain disorder in which amyloid-beta and abnormal tau proteins accumulate in the brain, leading to gradual deterioration of memory and cognitive functions. To date, there are medical limitations in completely halting the progression of the disease or restoring already damaged cognitive abilities, so treatments primarily focus on alleviating symptoms and slowing progression.

The problem is that by the time cognitive decline becomes noticeable, degeneration and damage to the brain associated with Alzheimer’s disease may have already been progressing for an extended period. Such changes may begin several years—or even up to 20 years—before clear symptoms appear. Therefore, identifying patients at the earliest possible stage is considered a critical task.

However, current precise diagnostic methods for Alzheimer’s disease, such as positron emission tomography (PET) or cerebrospinal fluid tests, face practical limitations for population-wide screening due to high costs and invasive procedures. This underscores the need for simpler and more affordable ways to identify high-risk individuals.

Recently, studies have been conducted to distinguish Alzheimer’s patients by utilizing genetic information obtained from blood tests. Among these, the research team hypothesized that simultaneously analyzing genomic information—showing innate genetic risk based on DNA—and transcriptomic information—indicating current gene activity based on RNA—would enhance discriminatory power. Such integrated research had been rare in Korea, and previous approaches using only one type of information had limited performance.

The researchers analyzed blood genomic and transcriptomic test results from a total of 486 individuals, including 313 participants from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) in the United States and 173 from Seoul National University Bundang Hospital. They converted and combined these results into Alzheimer’s disease risk scores and used them as an indicator to distinguish the disease.

As a result of the analysis, the proportion of Alzheimer’s disease patients in the high-risk group (with high scores for both genomics and transcriptomics) was 56% in the ADNI group and 80% at Seoul National University Bundang Hospital. In the low-risk group (with low scores for both), the actual patient rates were 17% and 14%, respectively, demonstrating effective discrimination of patients.

Even after adjusting for variables such as age, the group with high scores for both genomic and transcriptomic data was found to be 2.53 times (ADNI) and 3.39 times (Seoul National University Bundang Hospital) more likely to be diagnosed with Alzheimer’s disease than those in the low-score group, indicating that the combined model outperformed models using either data set alone.

This study validates the effectiveness of a method that integrates inherited genetic vulnerability and current gene activity from blood tests. The consistent improvement in discrimination observed in two groups with different racial backgrounds suggests that this approach could evolve into a technology for the early identification of high-risk individuals for Alzheimer’s disease.

Professor Youngho Park of Neurology at Seoul National University Bundang Hospital explained, "Genomic information serves as a blueprint of innate genes, while transcriptomic information reflects the current patterns of gene activity. Our results confirm that a model analyzing both is more effective in identifying actual patients than models analyzing only one." He added, "To detect Alzheimer’s disease early, it is first necessary to have clues indicating whether an individual is in a high-risk group. We will continue research to determine whether the combined genomic and transcriptomic model can be used as a tool to select candidates for further precise testing in the future."

This research was published in the international journal ‘Alzheimer’s & Dementia.’

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