A recent study in Heliyon investigated the use of serum Raman spectroscopy (SRS) as a diagnostic tool for detecting and classifying congenital heart defects (CHDs) by identifying unique spectral signatures associated with different subtypes. Conducted at the Sri Sathya Sai Sanjeevani Centre in India, the research aimed to develop a minimally invasive and precise method for diagnosing CHDs.
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Background
CHDs are among the most common birth defects worldwide, contributing significantly to the global health burden. As a result, the United Nations has included reducing neonatal and child mortality in its Sustainable Development Goals (SDGs).
However, despite this focus, effective screening for early CHD detection remains inadequate, particularly in developing countries. An estimated 1.3 million children are born with CHDs annually, highlighting the urgent need for reliable diagnostic tools.
Raman spectroscopy, a vibrational technique, has emerged as a valuable tool in biomedical research because it can provide a molecular 'fingerprint' of samples through inelastic photon scattering.
This non-destructive, highly sensitive method requires minimal preparation and can detect subtle molecular changes in complex biological samples like blood serum. It is especially useful for identifying serum metabolome alterations associated with disease progression and severity in heart conditions.
About the Research
The study recruited 42 CHD patients (18 males and 24 females) aged 0 to 30 years and 20 healthy subjects (10 males and 10 females) aged 0 to 12 years from the Sri Sathya Sai Sanjeevani Centre.
Patients were further categorized into acyanotic (atrial septal defect (ASD), ventricular septal defect (VSD)) and cyanotic (tetralogy of Fallot (TOF)) subtypes based on echocardiographic and cardiac catheterization results. This diverse sample allowed for a comprehensive analysis of the spectral differences among CHD subtypes.
Serum samples from all participants were analyzed using a WITec 300 R alpha confocal Raman instrument, optimized for serum analysis. The spectral data underwent multivariate analyses, including principal component analysis (PCA), principal component-linear discriminant analysis (PC-LDA), multivariate curve resolution-alternating least squares (MCR-ALS), and leave-one-out cross-validation (LOOCV).
These methods aimed to identify patterns distinguishing CHD patients from healthy controls and among CHD subtypes.
Research Findings
The Raman spectral analysis revealed unique biochemical signatures that differentiated CHD patients from healthy controls and across various CHD subtypes. MCR-ALS analysis showed significant variations in protein- and lipid-related spectral components among the groups.
Component 1, characterized by protein-related bands, differed significantly between patients with ASD and TOF, indicating distinct molecular mechanisms. Component 3, also associated with protein features, was notably altered between healthy controls and TOF patients. In contrast, Component 4, characterized by lipid-related bands, showed significant differences between healthy controls and TOF patients.
PCA and PC-LDA models effectively distinguished CHD patients from healthy controls and stratified CHD subtypes. The PC-LDA model, comparing all CHD cases with healthy controls, achieved a sensitivity of 76.19 % and a specificity of 70 %. For acyanotic (VSD and ASD) and cyanotic (TOF) subtypes, classification accuracies were 78.13 % and 80 %, respectively. Further comparisons among individual subtypes (ASD vs. VSD, ASD vs. TOF, and VSD vs. TOF) showed even higher accuracies, up to 92 %.
These results indicate SRS's potential as a diagnostic tool for distinguishing CHD subtypes and supporting targeted interventions.
Applications
SRS offers a promising minimally invasive approach for CHD detection and classification. By identifying specific spectral signatures for different subtypes, it provides insight into their molecular mechanisms and pathophysiology.
The high classification accuracies achieved by the PC-LDA models further demonstrate SRS's potential as a rapid and objective diagnostic method, potentially helping develop novel biomarkers and a deeper understanding of the associated biochemical changes.
The diagnostic accuracy and speed of SRS could be particularly beneficial in settings with limited access to traditional imaging techniques. Its non-invasive nature is also advantageous for children and patients who may be uncomfortable with invasive procedures.
Conclusion
Serum-based Raman spectroscopy proved to be an effective diagnostic tool for CHDs, accurately classifying and distinguishing between various subtypes. Its high accuracy, particularly in differentiating cyanotic from acyanotic CHDs, highlights its clinical potential. Further research should focus on refining the method and exploring its applicability to other medical conditions.
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Journal Reference
Joshi, R., et al. (2024). Serum Raman spectroscopy: Unearthing the snapshot of distinct metabolic profile in patients with congenital heart defects (CHDs). Heliyon. DOI: 10.1016/j.heliyon.2024.e34575, https://www.sciencedirect.com/science/article/pii/S2405844024106068
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