Metabolic Approach Helps Determine Risk of AD

By LabMedica International staff writers
Posted on 29 May 2017

Measurement of metabolites in saliva samples has been suggested as a noninvasive approach for determining risk of developing Alzheimer's disease.

Metabolomics is the study of chemical processes involving metabolites, while the metabolome represents the collection of all metabolites in a biological cell, tissue, organ, or organism that are the end products of cellular processes.

Investigators at Beaumont Health employed an NMR metabolomics procedure to biochemically profile saliva samples collected from 12 healthy-controls, eight mild cognitive impairment (MCI) sufferers, and nine Alzheimer's disease (AD) patients.

A total of 57 metabolites was positively identified and accurately quantified, and significant concentration changes were found in 22 metabolites in the saliva of MCI and AD patients compared to controls. These results demonstrated the potential for using metabolomics and saliva for the early diagnosis of AD.

Senior author Dr. Stewart Graham, assistant professor of medicine at Beaumont Health, said, “We used metabolomics, a newer technique to study molecules involved in metabolism. Our goal was to find unique patterns of molecules in the saliva of our study participants that could be used to diagnose Alzheimer’s disease in the earliest stages, when treatment is considered most effective. Presently, therapies for Alzheimer’s are initiated only after a patient is diagnosed and treatments offer modest benefits.”

“Our team’s study demonstrated the potential for using metabolomics and saliva for the early diagnosis of Alzheimer’s disease,” said Dr. Graham. “Given the ease and convenience of collecting saliva, the development of accurate and sensitive biomarkers would be ideal for screening those at greatest risk of developing Alzheimer’s. In fact, unlike blood or cerebrospinal fluid, saliva is one of the most noninvasive means of getting cellular samples and it is also inexpensive.”

The study was published in the May 16, 2017, online edition of the Journal of Alzheimer’s Disease.