Personalised Alzheimer's Treatment Through Fingerprints

New research could offer a way to deliver personalised treatments to patients with neurological disease. (Credit: Pixabay)

Personalised medicine has been a goal of researchers and doctors for a long time. Now, researchers have developed what they call a personalised Therapeutic Intervention Fingerprint (pTIF), for patients with neurological disease. 

The research is published in the journal Neuroimage.

The pTIF predicts the effectiveness of targeting specific biological factors (brain amyloid/tau deposition, inflammation, neuronal functional dysregulation) for controlling the evolution of the patient’s disease.

Led by the study’s first author, Yasser Iturria-Medina, researchers at the Montreal Neurological Institute and Hospital of McGill University and the Ludmer Centre for Neuroinformatics and Mental Health used computational brain modelling and artificial intelligence techniques to analyse the neurological data from 331 Alzheimer’s patients and healthy controls. The data included multiple modes of positron emission tomography (PET) and magnetic resonance imaging (MRI).

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From this, Iturria-Medina and colleagues were able to categorise patients into their TIF subtypes, according to the potentially most beneficial factor-specific interventions.

The authors verified these subtypes were relevant by comparing them to the patients’ individual genetic profiles. They found patients in the same pTIF subtype had similar gene expression, meaning the mechanism in which genes affect their physiology is similar.

Because drugs to control disease progression would have to modify gene expression and brain properties at the same time, drugs tailored to pTIF subtypes would be much more effective than drugs designed to treat all Alzheimer’s disease patients.

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This is the first study to pinpoint a direct link between brain dynamics, predicted therapeutic responses, and molecular and cognitive alterations in patients.

Using pTIF subtypes, drugs can be designed for a patient’s unique gene expression profile and phenotypic brain characteristics, which is a major advancement in personalised medicine. It could also improve the effectiveness and reduce the cost of clinical drug trials if used as a method to select patients.

“In keeping with the tenets of personalised medicine, the introduced framework could lead to more effective medical care, decreased undesired secondary effects, and substantial reduction of pharmaceutical/clinical costs associated with clinical trials, thereby accelerating the creation-evaluation cycle of new therapeutic agents,” says Iturria-Medina.

“Our future work will focus on applying the pTIF to other neurological disorders, extensively validating it, and, importantly, making the resulting analytic tools available to the international community, via open-access platforms,” Iturria-Medina says.

 


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