Application of Fourier transform infrared spectroscopy to detect biochemical changes in blood serum of obese patients

• Published in: Journal of biophotonics Vol. 16; no. 6; pp. e202200388 - n/a
• Main Authors: Guleken, Zozan, Çeçen, Serpil, Ceylan, Zeynep, Jakubczyk, Paweł, Depciuch, Joanna
• Format: Journal Article
• Language: English
• Published: Weinheim WILEY‐VCH Verlag GmbH & Co. KGaA 01.06.2023; Wiley Subscription Services, Inc
• Subjects: anthropometric; Anthropometry; Biochemical characteristics; Biochemistry; Biomarkers; Blood; Body fat; Body mass index; Body measurements; Body size; chemometric method; Cholesterol; Fourier transform infrared spectroscopy; Fourier transforms; Infrared spectroscopy; lipid profile; Lipids; Obesity; Phosphonates; principal component analysis; Principal components analysis; Risk factors; Spectrum analysis; Triglycerides; Fourier transform infrared spectroscopy; anthropometric; obesity; principal component analysis; chemometric method; lipid profile
• ISSN: 1864-063X; 1864-0648; 1864-0648
• DOI: 10.1002/jbio.202200388

Obesity is frequently a significant risk factor for multiple obesity‐associated diseases that have been increasing in prevalence worldwide. Anthropometric data such as body mass index, fat, and fat mass values are assessed for obesity. Therefore, we aimed to propose two Fourier transform infrared (FT‐IR) spectral regions, 800–1800 cm−1 and 2700–3000 cm−1, as sensitive potential band assignments for obesity‐related biochemical changes. A total of 134 obese (n = 89) and controls (n = 45) biochemical characteristics and clinical parameters indicative of obesity were evaluated. The FT‐IR spectra of dried blood serum were measured. Anthropometric data of the obese have the highest body mass index, %fat, and fat mass values compared to the healthy group (p < 0.01). Also, the triglyceride and high‐density lipoprotein cholesterol levels were higher than in healthy subjects (p < 0.01). Principal component analysis (PCA) technique successfully distinguished obese and control groups in the fingerprint, accounting for 98.5% and 99.9% of the total variability (800–1800 cm−1) and lipids (2700–3000 cm−1) regions presented as 2D and 3D score plots. The loading results indicated that peaks corresponding to phosphonate groups, glucose, amide I, and lipid groups were shifted in the obese group, indicating their potential as biomarkers of obesity. This study suggests that FTIR analysis based on PCA can provide a detailed and reliable method for the analysis of blood serum in obese patients. Fourier transform infrared (FTIR) spectra of blood are difficult to differentiate by simple statistical tests, mainly when this technique is used for a diagnostic approach. Consequently, it is necessary to use multivariate analyses. Here, we presented the possibility of distinguishing blood collected from obese and healthy patients by FTIR in combination with principal component analysis. Furthermore, we showed that it is possible to correlate blood biochemical parameters with individual FTIR peaks.