A team of researchers in the workshop of Professor Lucía Chávez Gutiérrez (Vib-Ku Leuven) pointed to the genetic contribution to the development of Alzheimer’s familial disease and distinguishing how specific mutations act as a clock for predicting the age of the age.

These research conclusions were published in Molecular Neurodegeneration and could help clinical doctors improve early diagnosis and adapt treatment strategies.

Alzheimer’s disease remains one of the most common neurodegenerative disorders, affecting 50 million people worldwide. To date, its exact cause is not yet fully understood.

One of the main visible features in the brain of people with Alzheimer’s disease is the presence of amyloid plaques. These plates are formed in the neurons and consist of clusters of poorly folded amyloid-B fragments (AB, pronounced α-bit). These fragments are produced by a sophisticated molecular treatment system orchestrated by the γ-sekretase enzyme and several basic proteins.

Alzheimer’s familial disease is a rare, early type of disease caused by mutations in three important genes involved in this system: amyloid precursor protein (app), Presenilin 1 (PSEN1) or Presenilin 2 (PSEN2). Their precise role in the disease is not well understood and has been discussed by scientists for several decades.

Understanding more about the relationship between specific types of mutations and the age of the occurrence of familial Alzheimer’s disease could be useful for doctors to make more accurate clinical diagnoses.

“In Alzheimer’s familial disease, patients often develop automatic genetic mutations, but to date doctors have not been able to provide them with more specialized information,” explains Lucia Chavez Gutierrez, team leader and professor at VIB-KU Leuven Center for Brain & Disease University.

“We have developed a method to experimentally control how likely it is a mutation to cause the disease, as well as to predict when it will appear,” he adds.

The gene attached to age

The teacher’s research team recently proved that mutations in the PSEN1 gene are closely linked to the age of onset of Alzheimer’s disease. In the context of the new study, it carried out the same analysis of mutations in all three causal genes: PSEN1, PSEN2 and App, where very clear correlations were found between specific mutations and the age of onset of familial Alzheimer’s disease.

“When we gather all our data, we will have a much clearer picture of how each of the causal genes contributes to the development of Alzheimer’s familial disease – we can measure the exact contribution of each gene and even predict when the first symptoms will occur,”

It is already known to scientists that the accumulation of larger AB peptides in the brain may be involved in the activation of molecular and cellular programs leading to the appearance of Alzheimer’s disease. In this study, the researchers observed direct and linear relationships between the ratio of AB and the age of the disease.

These parallel relationships were shifted according to the gene, which indicates the presence of a common pathogenic mechanism with a different manifestation time per gene.

“Our data predicts that a 12% displacement in the profile of AB peptides could delay the age of starting Alzheimer’s disease for up to five years,” the professor says.

“This highlights the potential of the treatments aimed at the c-securetase in the brain to create smaller AB figures and in turn delay or prevent the onset of the disease,” he notes.

Strategies

In addition to a deeper understanding of the mechanism of the disease, scientists developed a framework for evaluating the pathogenesis of genetic mutations and the influence of environmental factors or modifications.

“We have developed a predictor of starting age, which could pave the way for personalized approaches to diagnosis and treatment in Alzheimer’s familial disease,” said the first author of the study.

“In the future, this can help clinical doctors design more efficient strategies for early diagnosis and treatment of patients with genetic forms of the disease. Our workshop is now focusing on further research aimed at developing treatments using this model. “