Application of Fourier transform infrared spectroscopy to detect biochemical changes in blood serum of obese patients.
Zozan GulekenSerpil ÇeçenZeynep CeylanPaweł JakubczykJoanna DepciuchPublished in: Journal of biophotonics (2023)
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.
Keyphrases
- weight loss
- obese patients
- bariatric surgery
- metabolic syndrome
- adipose tissue
- insulin resistance
- roux en y gastric bypass
- weight gain
- type diabetes
- body mass index
- gastric bypass
- high fat diet induced
- fatty acid
- physical activity
- risk factors
- body composition
- glycemic control
- risk assessment
- skeletal muscle
- magnetic resonance
- machine learning
- optical coherence tomography
- human health