a new algorithm to help detect people at risk · Inserm, Science for health

At the Bordeaux population health research center, a team Inserm developed a model which allows, based on biological and clinical data, to predict the risk of presenting a pathological threshold of amyloid deposits in the brain. Easily used in patients who have memory problems without suffering from dementia, this model could help identify people at risk of developing Alzheimer’s disease.

Alzheimer’s disease is characterized by the presence of protein deposits – peptides beta amyloids – in the brains of patients. These deposits form plaques which lead to damage and destruction of neurons involved in memory and cognitive functions. Knowing that their formation begins several years before the first symptoms appear, their early detection could allow treatment of early forms of Alzheimer’s disease: several drugs or drug candidates target these deposits to slow progression. of the disease. Among them, antibody monoclonal drugs are already authorized in several regions of the world, including one in Europe. Other drugs are being evaluated, and people who have a pathological threshold for amyloid deposits are selected to participate in these clinical trials. This shows the importance of being able to easily measure these deposits in the brain of patients.

Currently, this measurement is carried out from a sample of cerebrospinal fluid obtained by lumbar puncture, or by a sophisticated imaging examination (TEP-amyloid). “ These two methods are invasive, expensive, and not easily accessible routinely. We looked for an alternative method that was easier to access, which could be offered to as many people as possible. This is how we thought of developing a predictive model of a pathological threshold of amyloid deposits, based on sociodemographic, biological or even clinical criteria. », explains Carole Dufouil, Inserm research director at the Bordeaux research center population health.

The Memento Cohort

For this, the team used data from the Memento study. Launched in 2011, it included 2,323 patients recruited from the Memory Resources and Research Centers (CMRR), who consulted due to a mild cognitive disorder or a subjective cognitive complaint. They agreed to be followed for five years, to allow scientists to look for determinants and possible warning signs of Alzheimer’s disease in them. To this end, a homogeneous and standardized collection of sociodemographic, biological, clinical, and imaging (MRI) data was carried out for each participant. The Bordeaux team tested six predictive models on a sample of 853 of them, in whom a determination of amyloid deposits had been carried out.

The six models integrated a common base of sociodemographic data (age, sex, body mass index or level of education) and cognitive data (results on four standard tests assessing memory and fonction cognitive). Each additionally integrated different specific markers of Alzheimer’s disease: genetic (presence of the ApoE4 allele of the apolipoprotein E gene which predisposes to the disease), blood (concentration in the blood of different forms of amyloid beta and Tau, Ab42/40 and pTau 181, associated with the risk of presenting the disease) or imaging (hippocampal atrophy observed by MRI, microhemorrhages cerebral). “ By gradually adding new markers, we were able to evaluate their contribution to predicting the presence of amyloid deposits. », Explains Lisa Le Scouarnec, first author of this work.

A validated model

Two models have been shown to be strongly predictive of a pathological threshold for amyloid deposits: those that include apolipoprotein E gene status and/or biomarkers blood. The researchers were then able to validate their algorithms in a second cohort, theAmsterdam Dementia Cohortalso composed of patients who complained of memory problems and whose amyloid deposit dosage was known. “ This validation confirmed the relevance and the possibility of generalizing our modelsspecifies Lisa Le Scouarnec. But given that the determination of the status of the apolipoprotein E gene is not yet routinely available and that its generalization poses ethical questions in the absence of effective treatment, we recommend the use of one that only includes blood biomarkers linked to Alzheimer’s disease, in addition to common core variables. »

But in practice, how to use this model? “ Its sensitivity and specificity do not match those of traditional examinations by imaging or lumbar puncture », Clarifies Lisa Le Scouarnec straight away. However, they are sufficient to exclude the existence of a risk in certain patients: “ Concretely, in a population identical to the Memento cohort, in which approximately a quarter of individuals present a pathological threshold for amyloid deposits, the use of this model would make it possible to avoid additional examinations in approximately 30% of people. “, she believes. The team will continue to improve the performance of this new tool by testing the addition of new blood biomarkers, starting with pTau217 (another form of the Tau protein). “ Ultimately, our goal is to offer a tool that is easy and quick to implement to replace current screening techniques. », concludes Lisa Le Scouarnec.

Carole Dufouil leads the team Translational research in population health (PHARes) in Bordeaux population health (BPH, unit 1219 Inserm/University of Bordeaux). Lisa Le Scouarnec, epidemiologist and biostatistician, is a doctoral student in her team and at the Bordeaux clinical investigation center (CIC 1401 Inserm/CHU de Bordeaux).

Source : L. Le Scouarnec et al. Development and assessment of algorithms for predicting brain amyloid positivity in a population without dementia. Alz Res TherapyOctober 11, 2024; doi:10.1186/s13195-024–01595-5

Author: A.R.

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