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8IDENTIFICATION OF NON-COMMUNICABLE DISEASES WITH RAMAN-BASED OPTICAL AND LIQUID
BIOPSY
IVAN BRATCHENKO', LYUDMILA BRATCHENKO1 YULIA KHRISTOFOROVA1, ELENA TUPIKOVA2, SAHAR AL-SAMMARRAE', PETER LEBEDEV3, DARIA KONOVALOVA3AND VALERY ZAKHAROV'
1Laser and biotechnical .systems department, Samara university, Russia 2Chemistry department, Samara university, Russia 3Therapy department, Samara state medical university, Russia iabratchenko @gmail .com
ABSTRACT
We utilized conventional Raman spectroscopy technique for the analysis of skin tissues and surface enhanced Raman spectroscopy (SERS) for the analysis of blood serum. When classifying subjects by the presence of kidney failure using the PLS-DA method, the most informative Raman spectral bands are 1315 to 1330, 1450 to 1460, 1700 to 1800 cm-1. In general, the performed study demonstrates that for in vivo skin analysis, the conventional Raman spectroscopy can provide the basis for cost-effective and accurate detection of kidney failure and associated metabolic changes in the skin. Application of SERS technique for the analysis of blood serum led to the ROC AUC of 0.983 (0.969 - 0.997; 95%CI) for the discrimination of healthy individuals and patients with kidney failure. For SERS we observe strongly enhanced bands which may be attributed to biochemical components such as nucleic acids (641, 724, 813, 1003, 1210, 1132 and 1450 cm-1), carbohydrates (641, 890 and 1094 cm-1) and lipids (1278 and 1327 cm-1). Raman-based liquid biopsy may be promising in non-communicable diseases identification, as it provides fast and rapid diagnosis.
INTRODUCTION
In modern world practice, promising diagnostic methods are emerging, such as "optical biopsy" and "liquid biopsy", which are used for specific diseases biomarkers detection in biological tissues and fluids [1]. Optical methods have the potential to overcome the limitations of traditional methods of clinical analysis. One of the most promising methods of optical analysis (and optical biopsy) is a Raman spectroscopy, which can contribute to understanding of molecular basis of diseases and creation of new bioanalytical tools for the diagnosis of diseases [2]. Since each type of biological tissue and biofluid has an individual molecular composition and, thus, a unique spectral profile resulting from the transition of a molecule from one vibrational-rotational state to another, a set of such individual states of functional groups of nucleic acids, proteins, lipids and carbohydrates makes it possible to characterize component composition of tissues, which ultimately makes it possible to isolate disease markers.
Along with the use of optical biopsy methods, it is possible to apply a supersensitive technique for analyzing biofluids based on surface-enhanced Raman spectroscopy, which will be most effective for detecting low concentrations of disease markers in biological fluids [3]. In the last decade, the development of nanotechnology has led to the creation of promising tools for solving new problems in the study of various human diseases, which is especially important for effective and targeted treatment and a deeper fundamental understanding of the biochemistry of diseases.
In this study we demonstrate application of conventional Raman spectroscopy for the analysis of skin and application of SERS for serum analysis to determine the presence of non-communicable diseases.
MATERIALS AND METHODS
The study of skin optical biopsy was performed for three groups of subjects: the target group consisting of 85 hemodialysis patients with kidney failure (90 spectra series), the adult control group constituted by 40 healthy volunteers (80 spectra) without systemic diseases and the young control group constituted by 84 healthy volunteers (168 spectra) without systemic diseases. Stimulation of the collected spectra was performed by the laser module (LuxxMaster LML-785.0RB-04, PD-LD, New Jersey) with the central wavelength of 785 nm. The Raman probe (RPB785, InPhotonics, Massachusetts) is able to focus the exciting radiation, as well as to collect and filter the scattered radiation. The focal length of the utilized Raman probe was 7.5 mm with the distance between the tested skin sample and the output lens of the Raman probe of 7 mm. The collected signal was decomposed into a spectrum using a portable spectrometer (QE65Pro, Ocean optics, Florida). Details of the utilized Raman setup and cohort of studied patients maybe found elsewhere [4].
In SERS analysis of blood, we estimated 58 patients with kidney failure and 78 healthy individuals. The collected samples were placed in sterile tubes. Between sampling and direct recording of spectral characteristics, the samples were stored at -14 °C. The experimental setup for blood liquid biopsy includes a spectrometric system (EnSpectr R785, Spektr-M, Chernogolovka, Russia) and a microscope (ADF U300, ADF, China). Focusing the exciting radiation and collecting the scattered radiation were implemented using 50x Objective LMPlan. The stimulation of collected spectra was performed by the laser module with central wavelength 785 nm. A yellow-green sol with a silver concentration of 0.050.1 g/l was obtained by reduction from an aqueous solution of silver nitrate with sodium citrate at a temperature of 95°C for 10 minutes. For SERS testing, a 1/1 silver colloid is added to the serum sample. Initial serum samples and samples of
serum solutions with silver sol in a volume of 6 ^l are applied to aluminum foil and dried for 60 minutes at room temperature.
All spectral data were processed by means of regression analysis. The fact that each tested subject is characterized by spectral data and a priori information on a particular class (the target or the control group) helped us to solve the supervised classification problem. The obtained experimental dataset was subjected to discriminant analysis with the projection on latent structures (PLS-DA). Since the analyzed spectral data are multicollinear, the projection analysis methods can provide a statistically reliable result. The PLS-DA is one of the most common approaches to solving such problems. When constructing the regression model, the informative spectra bands were defined by analyzing the variable importance in the projection (VIP) distribution. VIP makes it possible to assess the impact of individual variables of the predicate matrix array on the model [5].
RESULTS AND DISCUSSION
Figure 1 demonstrates the VIP scores of the Raman spectra matrices in the constructed regression models. Analysis of Figure 1 graphically demonstrates that the spectral bands characteristic of kidney failure does not overlap with the bands that are informative when discriminating healthy skin tissues by age. Application of Raman spectroscopy to investigate the forearm skin has yielded the accuracy of 0.96, sensitivity of 0.94 and specificity of 0.99 in terms of identifying the target subjects with kidney failure. The autofluorescence analysis in the near infrared region identified the patients with kidney failure among healthy volunteers of the same age group with specificity, sensitivity, and accuracy of 0.91, 0.84, and 0.88, respectively. When classifying subjects by the presence of kidney failure using the PLS-DA method, the most informative Raman spectral bands are 1315 to 1330, 1450 to 1460, 1700 to 1800 cm-1. In general, the performed study demonstrates that for in vivo skin analysis, the conventional Raman spectroscopy can provide the basis for cost-effective and accurate detection of kidney failure and associated metabolic changes in the skin.
kidney failure VS adult healthy group young healthy group VS adult heaithy group kidney failure VS whole healthy group Figure 1: VIP-scores of the Raman spectra matrices for: "kidney failure vs adult healthy group " PLS-DA model, "young healthy group vs adult healthy group " PLS-DA model, "kidney failure vs whole healthy group " PLS-DA model
Application of SERS technique for the analysis of blood serum led to the ROC AUC of 0.983 (0.969 - 0.997; 95%CI) for the discrimination of healthy individuals and patients with kidney failure. The most important Raman bands that helps to achieve such performance of PLS-DA classification models are highlighted in Figure 2. For SERS we observe strongly enhanced bands which may be attributed to biochemical components such as nucleic acids (641, 724, 813, 1003, 1210, 1132 and 1450 cm-1), carbohydrates (641, 890 and 1094 cm-1) and lipids (1278 and 1327 cm-1). Several of these bands clearly stand out by the impact of SERS technique at (724, 813, 890, 961 and1132 cm-1) because such bands were undetectable by conventional Raman spectroscopy due to weak intensity. The SERS spectrum of serum with silver nanoparticles showed many dominant vibration bands, indicating a strong interaction between the silver colloids and the serum substances.
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Raman shift, rm-1
Figure 2: VIP-scores of the Raman spectra matrices for discrimination of kidney failure and healthy individuals based
on SERS analysis of blood serum
CONCLUSION
Raman-based optical and liquid biopsy may be promising in non-communicable diseases identification, as it provides fast and rapid diagnosis. The classification performance can be further improved by using more complex analysis approaches as neural network algorithms of Raman spectra analysis [6] or by adding complementary information to the analysis (such as patients' demographics [7]). Important to note, that the proposed approach may be combined with other optical techniques for more precise diseases detection. Proposed Raman systems can be tested for their ability to detect other illness (track diabetes [8, 9] or find cancers [10]) and to find tumors in other organs. However, such novel approaches need to be tested in future large multicenter trials.
ACKNOWLEDGEMENTS
This study was supported by Russian Science Foundation grant No. 21-75-10097. REFERENCES
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