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

Exploring post-bariatric plasma metabolic changes using ATR-FTIR spectroscopy: Clinical insights and molecular perspectives

Bariatric surgery offers effective treatment of obesity, yet the full metabolic response of the organism remains unclear. Attenuated Total Reflection Fourier Transform Infrared spectroscopy (ATR-FTIR) allows to track the most detailed biochemical alterations in biofluids on a molecular level. This study aimed to utilize ATR-FTIR spectroscopy for monitoring changes of the metabolic profile of plasma in post-bariatric surgery patients and compare this profile to healthy individuals. Twenty patients with morbid obesity underwent bariatric procedures, resulting in improvement of anthropometric parameters. Laboratory biomarkers showed favorable changes: decreased triglycerides and glucose. PCA analysis of ATR-FTIR spectroscopy data revealed evolution of the plasma metabolic parameters towards those which characterize the healthy group, while the metabolic profile in the baseline group was different - lipid-associated infrared bands primarily drove this differentiation. Semiquantitative analysis of the selected bands revealed distinct spectral profiles with increased total lipid contributions in baseline as compared to follow-up and control. In turn, protein conformation showed increased β-sheet/α-helix ratios and altered secondary protein structures in follow-up. Tyrosine-ascribed region intensity attained the lowest value in baseline. C-O moieties and polysaccharides were elevated in follow-up. Alterations in protein structures were potentially influenced by supplementation and inflammation resolution, while lower tyrosine levels in obesity suggest oxidative stress involvement. Above findings highlight FTIR's potential in revealing impact of bariatric surgery on various elements of the metabolic profile. The multifaceted insight on plasma composition provided by FTIR shows significant improvements of this metabolic profile in post-surgery patients already six months after the intervention.

Application of fourier transform infrared vibrational spectroscopy in identifying early biochemical changes in lipid profiles of individuals undergoing Roux-en-y gastric bypass

BACKGROUND

Fourier transform infrared spectroscopy (FTIR) is an analytical technique increasingly applied in biological analysis. This study investigates the application of FTIR to identify early biochemical changes, particularly in lipid profiles, in individuals undergoing Roux-en-Y gastric bypass (RYGB).

METHODS

An observational study involving patients from a university hospital's Bariatric and Metabolic Surgery Program, with evaluations performed before (T0) and two months after (T1) RYGB. Biochemical parameters, anthropometric data, and body composition were assessed. FTIR spectra were pre-processed and analyzed using Principal Component Analysis and Partial Least Squares Discriminant Analysis. The normality of the data was evaluated using the Kolmogorov-Smirnov test, followed by paired T-tests or Wilcoxon tests as appropriate. Spearman correlation analysis of spectral information with biochemical parameters was also performed. A significance level of p < 0.05 was set for all tests. The university hospital's Research Ethics Committee approved the study (protocol CAAE 59075722.7.0000.5071).

RESULTS

The study evaluated 29 individuals (86.2% female) with a mean age of 41.2 ± 7.8 years. Significant differences were observed in anthropometric parameters and body composition (p < 0.001). Additionally, early improvements in the lipid profile were noted, with significant decreases in triglycerides, total cholesterol, and LDL cholesterol (p < 0.05) just two months post-surgery. FTIR identified correlations between biochemical parameters and specific spectral regions at T0 and T1. Notably, serum triglycerides showed a significant correlation with the lipid-specific spectral region (1796-1685 cm- 1) at both time points (p < 0.05).

CONCLUSION

FTIR can effectively monitor biochemical changes in RYGB surgery patients. The spectral range associated with lipid functional groups (1796 -1675 cm⁻¹) showed a significant relationship with serum triglyceride levels before and after RYGB. Additionally, various biochemical parameters exhibited strong correlations with other spectral regions, implying that the serum spectral profile can indicate biochemical variations at different post-surgery stages.

TRIAL REGISTRATION

Brazilian Registry of Clinical Trials (Rebec), September 5, 2022, protocol RBR-26chs2g.

Relationship between amide ratio assessed by Fourier-transform infrared spectroscopy: A biomarker candidate for polycythemia vera disease

The study utilized Fourier transform infrared (FTIR) spectroscopy coupled with chemometrics to investigate protein composition and structural changes in the blood serum of patients with polycythemia vera (PV). Principal component analysis (PCA) revealed distinct biochemical properties, highlighting elevated absorbance of phospholipids, amides, and lipids in PV patients compared to healthy controls. Ratios of amide I/amide II and amide I/amide III indicated alterations in protein structures. Support vector machine analysis and receiver operating characteristic curves identified amide I as a crucial predictor of PV, achieving 100% accuracy, sensitivity, and specificity, while amide III showed a lower predictive value (70%). PCA analysis demonstrated effective differentiation between PV patients and controls, with key wavenumbers including amide II, amide I, and CH lipid vibrations. These findings underscore the potential of FTIR spectroscopy for diagnosing and monitoring PV.

Comparative and Predictive Analysis of Clinical and Metabolic Features of Anorexia Nervosa and Bulimia Nervosa

Background

Eating disorders have become increasingly prevalent over the years; the age at which they appear has decreased, and they can lead to serious illness or death. Therefore, the number of studies on the matter has increased. Eating disorders like anorexia nervosa (AN) and bulimia nervosa (BN) are affected by many factors including mental illnesses that can have serious physical and psychological consequences. Accordingly, the present study aimed to compare the clinical and metabolic features of patients with AN and BN and identify potential biomarkers for distinguishing between the two disorders.

Methods

Clinical data of 41 participants who sought treatment for eating disorders between 2012 and 2022, including 29 AN patients and 12 BN patients, were obtained from NPIstanbul Brain Hospital in Istanbul, Turkey. The study included the clinical variables of both outpatient and inpatient treatments. Principal component analysis (PCA) was utilized to gain insights into differentiating AN and BN patients based on clinical characteristics, while machine learning techniques were applied to identify eating disorders.

Findings

The study found that thyroid hormone levels in patients with AN and BN were influenced by non-thyroidal illness syndrome (NTIS), which could be attributed to various factors, including psychiatric disorders, substance abuse, and medication use. Lipid profile comparisons revealed higher triglyceride levels in the BN group (P<0.05), indicating increased triglyceride synthesis and storage as an energy source. Liver function tests showed lower levels of aspartate aminotransferase (AST) and alanine aminotransferase (ALT) in BN patients (P<0.05), while higher prolactin levels (P<0.05) suggested an altered hypothalamic-pituitary-gonadal axis. Imbalances in minerals such as calcium and magnesium (P<0.05) were observed in individuals with eating disorders. PCA effectively differentiated AN and BN patients based on clinical features, and the Naïve Bayes (NB) model showed promising results in identifying eating disorders.

Conclusion

The findings of the study provide important insights into AN and BN patients' clinical features and may help guide future research and treatment strategies for these conditions.

Chemical changes in childhood obesity blood as a marker of the disease. A Raman-based machine learning study

Obesity in children is a global problem, leading to different medical conditions that may contribute to metabolic syndrome and increase the risk of diabetes, dyslipidemia, hypertension, and cardiovascular diseases in future health. Metabolic disorders are the results of the body's chemical process. The changes in the chemical compositions could be determined by Raman spectroscopy. Therefore, in this study, we measured blood collected from children with obesity to show chemical changes caused by obesity disease. Moreover, we will also show characteristic Raman peaks/regions, which could be used as a marker of obesity, not other metabolic syndromes. Children with obesity had higher glucose levels, proteins, and lipids than the control ones. Furthermore, it was noticed that the ratio between CO and C-H is 0.23 in control patients and 0.31 in children with obesity, as well as the ratio between amide II and amide I was 0.72 in control and 1.15 in obesity, which suggests an imbalance in these two fractions in childhood obesity. PCA with discrimination analyses showed that the accuracy, selectivity, and specificity of Raman spectroscopy in differentiation between childhood obesity and healthy children was between 93% and 100%. There is an increased risk of metabolic changes in childhood obesity with higher glucose levels, lipids, and proteins in children with obesity. Also, there were differences in the ratio between proteins and lipids functional groups and glucose, amide II, and amide I vibrations as a marker of obesity. The results of the study offer valuable insights into potential alterations in protein structure and lipid composition in children with obesity, emphasizing the importance of considering metabolic changes beyond traditional anthropometric, measurements.