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An Untargeted LC-MS based approach for identification of altered metabolites in blood plasma of rheumatic heart disease patients.

ABSTRACT: Rheumatic heart disease (RHD) is often considered as a disease of developing countries and India is the home of about 40% of RHD patients. Environment seems to play a major role in its causation. Since gene environment interactions can lead to alterations of various metabolic pathways, identification of altered metabolites can help in understanding the various pathways leading to RHD. Blood plasma samples from 51 RHD and 49 healthy controls were collected for the study. Untargeted metabolomics approach was used to identify the metabolites that are altered in RHD patients. Data showed 25 altered metabolites among RHD patients. These altered metabolites were those involved in Purine, Glutamine, Glutamate, Pyrimidine, Arginine, Proline and Linoleic metabolism. Thus, the present study illuminates metabolic alterations among RHD patients which can help in determining the potential therapeutic targets.

SUBMITTER: Das S

PROVIDER: S-EPMC8960827 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature

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An Untargeted LC-MS based approach for identification of altered metabolites in blood plasma of rheumatic heart disease patients.

Das Soumi S Kumar Yashwant Y Sharma Shruti S Ray Ruma R Arava Sudheer S Seth Sandeep S Agarwal Aman A Sharma Gautam G

Scientific reports 20220328 1

Rheumatic heart disease (RHD) is often considered as a disease of developing countries and India is the home of about 40% of RHD patients. Environment seems to play a major role in its causation. Since gene environment interactions can lead to alterations of various metabolic pathways, identification of altered metabolites can help in understanding the various pathways leading to RHD. Blood plasma samples from 51 RHD and 49 healthy controls were collected for the study. Untargeted metabolomics a ...[more]

PMID: 35347173

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Project description:Assessing human exposure to commonly used, highly toxic, but non-persistent organophosphates (OPs) is challenging because these toxicants are readily biotransformed into dialkyl phosphates (DAPs) and other metabolites. Growing hair accumulates toxicants and their metabolites, which makes hair a valuable non-invasively sampled matrix that can be used to retrospectively examine chemical exposure. However, the efficient quantification of hydrophilic DAP compounds in hair is challenging due to complex hair matrix effects. To improve upon existing methods, we first examined the acid dissociation constants (pKa) of DAPs and amino acids (major components in hair) and identified the best pH conditions for minimizing matrix effects. We hypothesized that under basic pH conditions DAPs and amino acids would be negatively charged and have weak interactions favorable to DAP dissociation from the matrix. To test this, we compared the efficiency of various pH conditions of suitable solvents to extract six DAPs from hair samples, and we quantified these DAPs using liquid chromatography-tandem mass spectroscopy (LC-MS/MS). As expected, a basic extraction (methanol with 2% NH4OH) approach had the highest extraction efficiency and yielded satisfactory recoveries for all six DAPs (72%-152%) without matrix effects. Additionally, the alkaline extract can be directly injected into the LC-MS/MS. This relatively rapid and simple procedure allowed us to process up to 90 samples per week with reproducible results. To our knowledge, this is the first method to quantify all six DAPs simultaneously in hair using LC-MS/MS with electrospray ionization (ESI) in negative ion mode. Finally, we demonstrated the feasibility of measuring DAP levels in hair samples from patients affected with amyotrophic lateral sclerosis (ALS), a neurodegenerative disease potentially linked to OP exposure. Due to our optimized solvent extraction process, the method we have developed is compatible with the rapidity and sensitivity needed for hair analysis applied to population biomonitoring.

Dataset Information

An Untargeted LC-MS based approach for identification of altered metabolites in blood plasma of rheumatic heart disease patients.

Publications

An Untargeted LC-MS based approach for identification of altered metabolites in blood plasma of rheumatic heart disease patients.

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