Screening for Alzheimer’s Disease Using Saliva: A New Approach Based on Machine Learning and Raman Hyperspectroscopy

Ralbovsky, Nicole M.; Halámková, Lenka; Wall, Kathryn; Anderson‐Hanley, Cay; Lednev, Igor K.

doi:10.3233/jad-190675

Cited by 53 publications

(51 citation statements)

References 43 publications

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“…15 – 17 These conventional techniques have been largely superseded by optical spectroscopy methods, such as those based on Raman scattering, that are less time consuming, do not require specific preliminary preparation of the samples, and have good sensitivity and specificity. Raman spectroscopy has been used to identify AD biomarkers in blood serum 8 , 18 , 19 and saliva, 20 and to investigate basic aggregation mechanisms of amyloids. 21 Raman spectroscopy 22 – 25 and surface-enhanced Raman spectroscopy (SERS) 26 have also been used to investigate human tears mainly to diagnose eye diseases.…”

Section: Introductionmentioning

confidence: 99%

Surface-enhanced Raman spectroscopy of tears: toward a diagnostic tool for neurodegenerative disease identification

et al. 2020

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Significance: A noninvasive method based on surface-enhanced Raman spectroscopy (SERS) of tears was proposed as a support for diagnosing neurodegenerative pathologies, including different forms of dementia and Alzheimer's disease (AD). In this field, timely and reliable discrimination and diagnosis are critical aspects for choosing a valid medical therapy, and new methods are highly required. Aim: The aim is to evince spectral differences in SERS response of human tears from AD affected, mild cognitive impaired (MCI), and healthy control (Ctr) subjects. Approach: Human tears were characterized by SERS coupled with multivariate data analysis. Thirty-one informed subjects (Ctr, MCI, and AD) were considered. Results: Average SERS spectra from Ctr, MCI, and AD subjects evidenced differences related to lactoferrin and lysozyme protein components. Quantitative changes were also observed by determining the intensity ratio between selected bands. We also constructed a classification model that discriminated among AD, MCI, and Ctr subjects. The model was built using the scores obtained by performing principal component analysis on specific spectral regions (i-PCA). Conclusions: The results are very encouraging with interesting perspectives for medical applications as support of clinical diagnosis and discrimination of AD from other forms of dementia.

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Section: Introductionmentioning

confidence: 99%

Surface-enhanced Raman spectroscopy of tears: toward a diagnostic tool for neurodegenerative disease identification

et al. 2020

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“…In addition, the size effect has more impact below n = 20 as the sensitivity and specificity values were very random, although the essential statistical parameters were considered in the evaluation for clinical utility. Consequently, other vs. studies using saliva, were not included in this review, due to a number of patients less than 20 per group, and concerning other diseases, such as burning mouth syndrome [ 41 ], asthma [ 42 ], Alzheimer’s disease [ 43 ], chronic renal failure [ 44 ], ovarian cancer [ 45 ], various infections, e.g., influenza [ 46 ] or pseudomonas [ 47 ], and cystic fibrosis [ 48 ]. Therefore, out of the 267 studies, only 18 satisfied the criteria according to the PRISMA guidelines.…”

Section: Discussionmentioning

confidence: 99%

Vibrational Spectroscopy Saliva Profiling as Biometric Tool for Disease Diagnostics: A Systematic Literature Review

et al. 2020

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Saliva is a biofluid that can be considered as a “mirror” reflecting our body’s health status. Vibrational spectroscopy, Raman and infrared, can provide a detailed salivary fingerprint that can be used for disease biomarker discovery. We propose a systematic literature review based on the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines to evaluate the potential of vibrational spectroscopy to diagnose oral and general diseases using saliva as a biological specimen. Literature searches were recently conducted in May 2020 through MEDLINE-PubMed and Scopus databases, without date limitation. Finally, over a period of 10 years, 18 publications were included reporting on 10 diseases (three oral and seven general diseases), with very high diagnostic performance rates in terms of sensitivity, specificity, and accuracy. Thirteen articles were related to six different cancers of the following anatomical sites: mouth, nasopharynx, lung, esophagus, stomach, and breast. The other diseases investigated and included in this review were periodontitis, Sjögren’s syndrome, diabetes, and myocardial infarction. Moreover, most articles focused on Raman spectroscopy (n = 16/18) and more specifically surface-enhanced Raman spectroscopy (n = 12/18). Interestingly, vibrational spectroscopy appears promising as a rapid, label-free, and non-invasive diagnostic salivary biometric tool. Furthermore, it could be adapted to investigate subclinical diseases—even if developmental studies are required.

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“…Raman hyperspectroscopy has shown great potential to diagnose many diseases including cancers, 15 , 16 Alzheimer’s disease, 17 – 19 and others. 20 , 21 Raman hyperspectroscopy involves collecting multiple Raman spectra from a sample to better characterize its inherent heterogeneity and understand its biochemical composition.…”

Section: Introductionmentioning

confidence: 99%

Diagnosis of a model of Duchenne muscular dystrophy in blood serum of mdx mice using Raman hyperspectroscopy

Ralbovsky

Dey

Galfano

et al. 2020

Sci Rep

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Duchenne muscular dystrophy (DMD) is the most common and severe form of muscular dystrophy and affects boys in infancy or early childhood. Current methods for diagnosing DMD are often laborious, expensive, invasive, and typically diagnose the disease late in its progression. In an effort to improve the accuracy and ease of diagnosis, this study focused on developing a novel method for diagnosing DMD which combines Raman hyperspectroscopic analysis of blood serum with advanced statistical analysis. Partial least squares discriminant analysis was applied to the spectral dataset acquired from blood serum of a mouse model of Duchenne muscular dystrophy (mdx) and control mice. crossvalidation showed 95.2% sensitivity and 94.6% specificity for identifying diseased spectra. These results were verified via external validation, which achieved 100% successful classification accuracy at the donor level. this proof-of-concept study presents Raman hyperspectroscopic analysis of blood serum as an easy, fast, non-expensive, and minimally invasive detection method for distinguishing control and mdx model mice, with a strong potential for clinical diagnosis of DMD. Duchenne muscular dystrophy (DMD) is a progressive form of muscular dystrophy which typically affects male infants. DMD is an X-chromosome linked recessive disorder caused by a loss of function of the dystrophin gene of 2.3 million base pairs, which results in progressive weakness and atrophy of the skeletal and cardiac muscles. 1,2 The issues associated with DMD are severe, worsen overtime, and greatly impact the well-being of the afflicted individual. In fact, secondary complications due to DMD, including cardiac and respiratory muscle problems, can lead to life-threatening conditions. 3 Although there is no cure, limited treatment regimens exist for DMD which can slow the progression of the symptoms associated with the disease. Diagnosing DMD typically involves evaluating family history as well as conducting blood tests to assess the levels of specific muscle enzymes in the blood. Although the inheritance of the disease is through an X-linked recessive pattern, there are cases where DMD occurs in families who have no history of it. The complicated pattern of inheriting DMD suggests a need for additional testing. Blood tests often monitor the level of serum creatine phosphokinase (CPK), however, this test can only detect the disease in later stages and is generally nonspecific, as high levels of CPK can be found in an individual's blood after experiencing a heart attack, drinking alcohol in excess, or participating in strenuous exercise. 4-9 Electromyography can confirm muscle weakness without pinpointing a direct cause of it. 10 Muscle biopsies can differentiate muscular dystrophies from other muscle diseases, 11 however biopsy examinations can be both expensive and invasive. Further, biopsies and genetic testing are typically pursued only after other options have been exhausted, resulting in the disease being diagnosed in its later stages. Because DMD is progressiv...

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Screening for Alzheimer’s Disease Using Saliva: A New Approach Based on Machine Learning and Raman Hyperspectroscopy

Cited by 53 publications

References 43 publications

Surface-enhanced Raman spectroscopy of tears: toward a diagnostic tool for neurodegenerative disease identification

Surface-enhanced Raman spectroscopy of tears: toward a diagnostic tool for neurodegenerative disease identification

Vibrational Spectroscopy Saliva Profiling as Biometric Tool for Disease Diagnostics: A Systematic Literature Review

Diagnosis of a model of Duchenne muscular dystrophy in blood serum of mdx mice using Raman hyperspectroscopy

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