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1H NMR Using Metabolic Study in Body Fluids for Diagnosis of Cryptococcal Meningitis in Adults
Pushpa Yadav1,2, Manodeep Sen2, Janmejai K Srivastava1
1Amity Institute of Biotechnology, Amity University, Lucknow, Uttar Pradesh, India.
Background:
Cryptococcal meningitis is considered to affect HIV patients and those with impaired immune systems. Early identification and treatment are the keys to decreasing morbidity and mortality related to CM. Using 1H NMR spectroscopy, a prospective case-control study will assess the metabolic profile of adults' serum, urine, and CSF.
Methodology:
The present multicentric study was conducted at Lucknow. The study included 150 participants, out of which there were 31 cryptococcal meningitis cases, 34 positive meningitis controls, and the rest, 85, were disease controls.
Result:
The discriminant function analysis (DFA) of the three biofluids was used to find significant metabolites between the cases and the control group collectively. A group categorization between control group and the cases in serum, urine, and CSF samples was also made possible by the NMR spectral bin-based orthogonal signal correction and principal component analysis score plots of important metabolites produced from DFA. The cases group had a higher proportion of patients with higher CSF protein levels than the positive control group (BM and TM). Acetone was found among urine samples in both control samples, i.e., positive and negative.
Conclusion:
This is the first study to explore biomarkers in serum, urine, and CSF in addition to radiological features and clinical symptoms. Hence, a quick, non-invasive prognosis and diagnosis of cryptococcal meningitis in adults can be made using clinical and microbiological investigation, as well as metabolomic analysis of urine samples. This study shows that urine can be used as a biofluid to differentiate between Cryptococcus meningitis in adults. However, when compared to the negative control, our sample size was significantly smaller, necessitating further confirmation on a larger sample size.
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