Metabolic fingerprinting of human plasma in dementia: A pilot study of metabolome decomposition
Related Experiment Video
Updated: Sep 19, 2025
Semi-Targeted Ultra-High-Performance Chromatography Coupled to Mass Spectrometry Analysis of Phenolic Metabolites in Plasma of Elderly Adults
Published on: April 22, 2022
Kambiz Gilany1, Akram Tayanloo-Beik2, Moloud Payab3
1Department of Integrative Oncology, Breast Cancer Research Center, Motamed Cancer Institute, The Academic Center for Education, Culture and Research (ACECR), Tehran, Iran; Reproductive Immunology Research Center, Avicenna Research Institute, The Academic Center for Education, Culture and Research (ACECR), Tehran, Iran.
Background:
As the number of people with dementia grows, it becomes even more important to improve how it is diagnosed and treated. Metabolomics, the study of small molecule metabolites in biological systems, helps us learn a lot about dementia by revealing changes in the brain's systems through blood plasma research.
Objective:
The objective of this study is to clarify the changes in metabolism that are linked to dementia. This will be achieved by using metabolic fingerprinting techniques on human plasma to differentiate between patients with dementia and individuals who have normal cognitive function.
Methods:
This study used data from the Birjand Longitudinal Aging Study and high-tech Raman Spectroscopy, as well as multivariate statistical methods such as PCA and OPLS-DA. The study looked at 34 people with dementia and 34 people who did not have any cognitive damage.
Results:
Metabolic fingerprints distinguished two groups with extremely distinct metabolic characteristics. Main findings demonstrate that oxidative stress and energy metabolism metabolites have changed significantly. OPLS-DA distinguished healthy and dementia samples with high accuracy and sensitivity. Both the expected high model accuracy and the clear score plot split confirmed this.
Conclusion:
The metabolic deviations detected offer a deeper understanding of the biochemical processes associated with dementia. These results enhance our understanding of dementia-related biochemical changes and underscore the exploratory potential of Raman-based metabolomic fingerprinting as a complementary, non-invasive approach for identifying broader functional group-level alterations.
