A review of biospectroscopy coupled with chemometrics for Alzheimer’s disease diagnosis

Abstract

One of the biggest challenges of current tests for Alzheimer’s disease (AD) diagnosis is the development of high-performance, inexpensive, minimally invasive, and rapid tools that can be used in real-time. Biospectroscopic techniques coupled with chemometrics have shown these characteristics and can help to identify pathological changes in AD before the first symptom. In this review article, we highlight biospectroscopy studies coupled with chemometrics for the classification and diagnosis of Alzheimer’s disease (AD) from 1995 to September 2022. A total of 29 studies were found with the spectroscopic techniques of infrared (IR) (12/29), Raman (10/29), molecular fluorescence (2/29), and nuclear magnetic resonance (NMR) (6/29). The nature of the sample analyzed included human brain tissues (3/29), human biofluids (21/29), rats brain tissue (1/29), mice brain tissues (2/29), and mice biofluids (2/29). In studies with human participants, we considered everyone eligible without any exclusion criteria regarding the number of participants. The main chemometric approaches (preprocessing methods, feature extraction, and classification) and figures of merit used in these biospectroscopy studies are discussed. Most studies worked with 1st order algorithms and only one study with 2nd order algorithms. Using blood-based biofluids and saliva, biospectroscopy coupled with chemometrics was demonstrated to be a high-performance, minimally invasive, and label-free method.

Keywords:

• Alzheimer’s disease
• biospectroscopy
• chemometrics
• biofluids

Acknowledgments

R.F. dos Santos would like to thank the Postgraduation Program in Chemistry at the Federal University of Rio Grande do Norte (PPGQ-UFRN) and the Federal Institute of Education, Science, and Technology of Rio Grande do Norte (IFRN).

Authors’ contributions

R.F.S wrote the manuscript. M.P. and K.M.G.L. – conceptualization, planning and writing of the manuscript.

Disclosure statement

No conflict of interest has been reported by the authors.

Additional information

Funding

K.M.G. Lima was supported by CNP Brazil [Grant 305562/2020-7].