New research published in Molecular Neurodegeneration has revealed that mutations in three genes known to cause familial Alzheimer’s disease can predict when symptoms will begin. By analyzing how these mutations alter the production of amyloid-beta peptides in the brain, scientists found that each mutation acts like a molecular clock—shifting the age at which individuals develop dementia. These findings provide a deeper understanding of the disease and could help clinicians better estimate onset and develop targeted treatments.
While most cases of Alzheimer’s disease appear sporadically in old age, a small percentage of people inherit gene mutations that almost guarantee early-onset dementia. These familial cases are usually linked to mutations in one of three genes: PSEN1, PSEN2, or APP. People with these mutations typically develop symptoms well before age 65. Studying this form of Alzheimer’s helps researchers understand the biological processes that drive the disease and offers a window into possible interventions.
The team led by Professor Lucía Chávez Gutiérrez at VIB-KU Leuven has previously shown that mutations in PSEN1 influence the timing of Alzheimer’s symptoms through their effects on gamma-secretase—an enzyme complex that processes a protein called APP into fragments known as amyloid-beta peptides. These peptides accumulate in the brain and form sticky plaques, a hallmark of Alzheimer’s pathology. In the current study, the researchers expanded their investigation to include mutations in PSEN2 and the transmembrane region of APP, aiming to understand whether similar molecular changes could predict when symptoms will start.
To do this, the researchers conducted a biochemical analysis of 28 mutations in PSEN2 and 19 mutations in the APP gene. These included mutations known to be pathogenic, as well as others of unclear or benign significance. The team introduced these mutations into cell models and measured how they affected the production of different types of amyloid-beta peptides. They focused particularly on the ratio of shorter, less harmful peptides to longer, more toxic ones. This ratio is known to influence the likelihood and speed of plaque formation in the brain.
What they found was striking. For both PSEN2 and APP, changes in peptide ratios correlated with the age at which people developed Alzheimer’s symptoms. In other words, the greater the shift toward harmful peptide production, the earlier the onset. These relationships were linear, meaning that even small changes in peptide balance could predict meaningful changes in when symptoms would appear. In PSEN2 mutations, the correlation explained about half of the variation in age of onset; for APP, the correlation was even stronger.
Interestingly, although PSEN1, PSEN2, and APP mutations disrupted peptide processing in similar ways, they did not all trigger symptoms at the same age. On average, PSEN2 mutations led to disease 27 years later than PSEN1 mutations, while APP mutations delayed onset by about 8 years. These differences suggest that each gene contributes differently to disease progression, possibly because of differences in where and how these proteins function in brain cells.
In some cases, the predicted age of onset based on peptide ratios did not match up with what had been observed in patients. This discrepancy was especially apparent in PSEN2 and APP carriers. Some people developed symptoms earlier or later than expected, which could be due to other genetic or environmental factors that influence disease onset. For example, certain families with the same mutation had members who showed symptoms decades apart. These variations could point to protective or harmful modifiers of the disease—factors that are not yet fully understood but could open new doors for therapy.
The study also explored one particular outlier: extremely inactivating mutations in PSEN1. These mutations were expected to be highly pathogenic because they caused a strong shift toward toxic peptide production. Yet, surprisingly, they were associated with delayed onset of Alzheimer’s symptoms. This paradox may be explained by the fact that these mutations also reduce the total amount of peptide produced, somewhat balancing out their harmful effects. This finding raises the possibility that simply altering the quantity of enzyme activity—not just the quality of peptide products—can influence disease timing.
The researchers used their peptide ratio models to predict onset age for each mutation, then compared those predictions with actual clinical data. While the models worked well in many cases, they also revealed significant outliers. These mismatches suggest that other mechanisms, such as changes in gene expression or RNA splicing, could affect how much of the mutant protein is made in the brain. For example, some PSEN2 mutations showed lower stability or expression of the harmful allele, which might explain why symptoms occurred later than expected.
In the case of APP, some mutations not only altered peptide ratios but also increased the tendency of these peptides to clump together. This aggregation property, particularly in mutations affecting specific amino acid positions, could accelerate the formation of plaques independently of the ratio shifts. These extra factors might account for why some individuals developed symptoms much earlier than predicted based solely on gamma-secretase activity.
By comparing all three genes—PSEN1, PSEN2, and APP—the study provided a unified model of familial Alzheimer’s disease. All three show a linear relationship between molecular changes and symptom onset, but each has a distinct baseline due to how much each gene contributes to amyloid-beta production. These insights suggest that even small therapeutic shifts in peptide balance could significantly delay symptom onset. For example, changing the peptide ratio by just 12% could theoretically delay onset by five years in some cases.
The research offers hope for the development of targeted treatments. Modulators of gamma-secretase activity that promote the production of shorter, less toxic peptides are currently in development. These drugs could potentially slow or prevent Alzheimer’s in people with high genetic risk, and perhaps even in the broader population with sporadic forms of the disease.
The study, “Spectrum of γ-Secretase dysfunction as a unifying predictor of ADAD age at onset across PSEN1, PSEN2 and APP causal genes,” was authored by Sara Gutiérrez Fernández, Cristina Gan Oria, Dieter Petit, Wim Annaert, John M. Ringman, Nick C. Fox, Natalie S. Ryan, and Lucía Chávez-Gutiérrez.