By Makoto Ishii, MD, PhD
Assistant Professor, Department of Neurology, Peter O’Donnell Jr. Brain Institute, Center for Hypothalamic Research, Department of Internal Medicine, University of Texas Southwestern Medical Center
SYNOPSIS: In a longitudinal multicenter, nested case-control study of cognitive normal participants from China, the time courses of key Alzheimer’s disease biomarkers were identified during the 20 years preceding clinical diagnosis of sporadic Alzheimer’s disease.
SOURCE: Jia J, Ning Y, Chen M, et al. Biomarker changes during 20 years preceding Alzheimer’s disease. N Engl J Med 2024;390:712-722.
With the recent advances in imaging and fluid biomarkers, it now is possible to accurately identify individuals with Alzheimer’s disease pathology prior to the development of clinical symptoms. Although these biomarkers can improve the accuracy of diagnosing Alzheimer’s disease, determining how changes in these biomarkers are related to when the clinical symptoms develop has been challenging. Previous studies have proposed biomarker trajectories by examining those with autosomal dominant Alzheimer’s disease, which accounts for only a small proportion of Alzheimer’s disease and may not accurately reflect the progression in sporadic Alzheimer’s disease. The biomarker studies in sporadic Alzheimer’s disease have been largely cross-sectional or longitudinal studies with short follow-up periods, which may not be sufficient to take into consideration the years and decades it takes to develop Alzheimer’s disease.
To address this gap in our knowledge, Jia and colleagues conducted a longitudinal, multicenter, nested case-control study of Alzheimer’s disease biomarkers in cognitively normal participants enrolled in the China Cognition and Aging Study. A total of 648 participants who developed Alzheimer’s disease were matched with 648 participants who remained cognitively intact. Temporal trajectories of cerebrospinal fluid (CSF) biomarkers (i.e., amyloid-beta 42, amyloid-beta 42 to amyloid-beta 40 ratio, phosphorylated tau181, total tau, and neurofilament light chain), hippocampal volume assessed by 3.0 Tesla structural magnetic resonance imaging (MRI), and cognitive testing were analyzed. The median follow-up was 19.9 years.
The earliest biomarker changes were seen with amyloid-beta. Approximately 18 years before the diagnosis of Alzheimer’s disease, significantly lower CSF amyloid-beta 42 levels were seen in those with Alzheimer’s disease compared to normal controls. This was followed by differences in the CSF amyloid-beta 42 to amyloid-beta 40 ratio seen at 14 years before the diagnosis of Alzheimer’s disease. Following the changes in amyloid-beta biomarkers were tau biomarkers, with differences between the two groups in CSF levels of phosphorylated tau181 and total tau occurring at an estimated 11 and 10 years, respectively, before diagnosis.
Differences between the two groups in CSF levels of neurofilament light chain, a nonspecific marker of neurodegeneration, were seen at nine years before diagnosis, while differences in hippocampal volumes were seen eight years prior to diagnosis. Finally, differences in cognitive function as measured by Clinical Dementia Rating Sum of Boxes scores between the two groups were observed approximately six years before diagnosis. Interestingly, the rate of change in the individual biomarkers between the two groups appeared to initially increase followed by a slowing in the rate of change as cognition worsened.
COMMENTARY
This notable study by Jia and colleagues confirms the long preclinical stage in Alzheimer’s disease that has been seen in earlier studies. It further confirms the order and trajectory of changes in Alzheimer’s disease biomarkers, with amyloidosis occurring first, followed by tau pathology, neurodegeneration, and, finally, cognitive decline. Elucidating the timing of these changes in biomarkers and pathophysiological events has implications in clinical practice and in future clinical trials.
For clinical practice, it is not hard to imagine a precision medicine approach in the future where patterns of biomarkers can be used to inform individual patients about not only the relative risk but the possible timeline to developing Alzheimer’s disease. For future clinical trials, biomarker data potentially could be used to model the trajectories of the pathophysiological changes in an individual study participant to help identify whether a therapeutic intervention altered the trajectory of expected pathophysiological events and the development of Alzheimer’s disease.
Strengths of this study include the relatively large number of participants with repeated CSF and imaging biomarker data and an impressive 20-year follow-up. Limitations of this study include omission of individuals with a family history of Alzheimer’s disease. Although this was done to help enrich for sporadic Alzheimer’s disease, it does diminish apolipoprotein E e4 carriers in the cohort and makes it difficult to generalize the findings to those with a family history, which may be a large proportion of patients seen in the clinic.
Furthermore, since the study was conducted solely in a Chinese population, these findings may not be generalizable to other racial and ethnic groups. However, it is important to note that there are relatively fewer studies in Asians and it highlights the need to conduct similar studies in a diverse range of racial and ethnic groups. Additionally, while a 20-year follow-up is considered a significant strength of the study, there may be a bias, since those who participated in the study may have had the superior health, education, or general health awareness needed to participate in such a lengthy study. Finally, the CSF biomarkers used in this study may not be readily available in many cases. Therefore, similar studies using recently developed plasma and other more accessible biomarkers will be needed.
As we continue to increase our understanding of the early pathophysiological events in Alzheimer’s disease, the day when precision medicine approaches are used for the prevention and treatment of Alzheimer’s disease is becoming closer to a reality.
