Study identifies biomarkers that could guide precision medicine in Alzheimer’s disease

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University of Arizona April 28 news

This discovery may be related to late-haired Alzheimer’s Personalized medicine provides important insights into Haimer’s disease, a complex neurodegenerative disorder characterized by multiple stages of progression including cognitive decline.

“One of the most interesting findings from our study was the identification of key drivers of metabolic pathways when patient groups were separated by gender and APOE gene These metabolic pathways can differentiate Alzheimer’s disease from cognitively normal individuals,” said Rui Chang, Ph.D., member of the University of Arizona Health Sciences Brain Science Innovation Center and lead author of the study. “These patient-specific Metabolic targets will help discover precision treatments for Alzheimer’s patients, something that has never been done in previous studies.”

Dr. Rui Chang

Article titled “Predictive metabolic networks reveal sex- and APOE genotype-specific metabolic signatures and Alzheimer’s The paper “Predictive metabolic networks reveal sex and APOE genotype-specific metabolic signatures and drivers for precision medicine in Alzheimer’s Disease” was recently published in Alzheimer’s Disease In Alzheimers & Dementia, the journal of the MU Association.

Research published on April 28, 2022 in “Alzheimer <215 66 Dementia" (latest impact factor: 215 66 Dementia) The /p>

APOE gene is involved in making a protein that helps carry cholesterol and other types of fat in the blood. There are several genotypes or variants of APOE based on specific genetic variants inherited by an individual. APOEe4 genotype has been identified as a risk factor for Alzheimer’s disease.

Dr. Chang and his research team combined metabolic network models with advanced machine learning methods for the Alzheimer’s Disease Neuroimaging Program ( Computational analysis was performed on 1,517 serum samples provided by the Alzheimer’s Disease Neuroimaging Initiative, ADNI).

First, they identified common metabolic features of late-onset Alzheimer’s disease . Next, they divided the network into clusters by sex to identify sex-specific metabolic changes, and by genotype to identify other metabolic signatures affected by APOEe4 genotype.

Finally, they stratified patients by the intersection of sex and APOEe4 status and found that APOEe4 genotype was able to significantly affect metabolic changes, overwhelming both male and female sex Specificity differences.

In addition, they identified a serum-based panel of metabolic biomarkers strong>, these biomarker panels predict disease status and correlate with clinical cognitive function in each of eight patient subgroups stratified by sex and/or APOEe4 status.

These new patient-specific metabolomes identify key metabolic drivers of late-onset Alzheimer’s disease that can be assessed as therapeutic targets.These findings have the potential to greatly improve Accelerates drug development for Alzheimer’s disease while providing outcome measures for clinical trials.

“Dr. “This studyprovides an initial but critical step in the development of personalized and precision treatments for patients,” said Roberta Diaz Brinton, Ph.D., director of the Brain Science Innovation Center and professor of pharmacology. Computational network models to identify targeted therapies for patients provide operational strategies to achieve this goal. ”

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Source: University of Arizona Health Sciences

Study identifies biomarkers that could guide precision medicine therapies for Alzheimer’s disease


Chang, R, Trushina, E, Zhu, K, et al. Predictive metabolic networks reveal sex- and APOE genotype-specific metabolic signatures and drivers for precision medicine in Alzheimer’s disease. Alzheimer’s Dement. 2022; 1- 14. https://


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