Revealing Metabolic Perturbation Following Heavy Methamphetamine Abuse by Human Hair Metabolomics and Network Analysis
Methamphetamine (MA) is a highly addictive central nervous system stimulant. Drug addiction is not a static condition but rather a chronically relapsing disorder. Hair is a valuable and stable specimen for chronic toxicological monitoring as it retains toxicants and metabolites. The primary focus of...
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doaj-e7572ed103324c0fb18ab06269a3aba22020-11-25T03:55:01ZengMDPI AGInternational Journal of Molecular Sciences1661-65961422-00672020-08-01216041604110.3390/ijms21176041Revealing Metabolic Perturbation Following Heavy Methamphetamine Abuse by Human Hair Metabolomics and Network AnalysisSuji Kim0Won-Jun Jang1Hyerim Yu2Jihyun Kim3Sang-Ki Lee4Chul-Ho Jeong5Sooyeun Lee6College of Pharmacy, Keimyung University, 1095 Dalgubeoldaero, Dalseo-gu, Daegu 42601, KoreaCollege of Pharmacy, Keimyung University, 1095 Dalgubeoldaero, Dalseo-gu, Daegu 42601, KoreaCollege of Pharmacy, Keimyung University, 1095 Dalgubeoldaero, Dalseo-gu, Daegu 42601, KoreaNational Forensic Service, 10, Ipchun-ro, Wonju, Gangwon-do 26460, KoreaNational Forensic Service, 10, Ipchun-ro, Wonju, Gangwon-do 26460, KoreaCollege of Pharmacy, Keimyung University, 1095 Dalgubeoldaero, Dalseo-gu, Daegu 42601, KoreaCollege of Pharmacy, Keimyung University, 1095 Dalgubeoldaero, Dalseo-gu, Daegu 42601, KoreaMethamphetamine (MA) is a highly addictive central nervous system stimulant. Drug addiction is not a static condition but rather a chronically relapsing disorder. Hair is a valuable and stable specimen for chronic toxicological monitoring as it retains toxicants and metabolites. The primary focus of this study was to discover the metabolic effects encompassing diverse pathological symptoms of MA addiction. Therefore, metabolic alterations were investigated in human hair following heavy MA abuse using both targeted and untargeted mass spectrometry and through integrated network analysis. The statistical analyses (<i>t</i>-test, variable importance on projection score, and receiver-operator characteristic curve) demonstrated that 32 metabolites (in targeted metabolomics) as well as 417 and 224 ion features (in positive and negative ionization modes of untargeted metabolomics, respectively) were critically dysregulated. The network analysis showed that the biosynthesis or metabolism of lipids, such as glycosphingolipids, sphingolipids, glycerophospholipids, and ether lipids, as well as the metabolism of amino acids (glycine, serine and threonine; cysteine and methionine) is affected by heavy MA abuse. These findings reveal crucial metabolic effects caused by MA addiction, with emphasis on the value of human hair as a diagnostic specimen for determining drug addiction, and will aid in identifying robust diagnostic markers and therapeutic targets.https://www.mdpi.com/1422-0067/21/17/6041methamphetaminedrug addictionmetabolomicsnetwork analysishairlipid metabolism |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Suji Kim Won-Jun Jang Hyerim Yu Jihyun Kim Sang-Ki Lee Chul-Ho Jeong Sooyeun Lee |
spellingShingle |
Suji Kim Won-Jun Jang Hyerim Yu Jihyun Kim Sang-Ki Lee Chul-Ho Jeong Sooyeun Lee Revealing Metabolic Perturbation Following Heavy Methamphetamine Abuse by Human Hair Metabolomics and Network Analysis International Journal of Molecular Sciences methamphetamine drug addiction metabolomics network analysis hair lipid metabolism |
author_facet |
Suji Kim Won-Jun Jang Hyerim Yu Jihyun Kim Sang-Ki Lee Chul-Ho Jeong Sooyeun Lee |
author_sort |
Suji Kim |
title |
Revealing Metabolic Perturbation Following Heavy Methamphetamine Abuse by Human Hair Metabolomics and Network Analysis |
title_short |
Revealing Metabolic Perturbation Following Heavy Methamphetamine Abuse by Human Hair Metabolomics and Network Analysis |
title_full |
Revealing Metabolic Perturbation Following Heavy Methamphetamine Abuse by Human Hair Metabolomics and Network Analysis |
title_fullStr |
Revealing Metabolic Perturbation Following Heavy Methamphetamine Abuse by Human Hair Metabolomics and Network Analysis |
title_full_unstemmed |
Revealing Metabolic Perturbation Following Heavy Methamphetamine Abuse by Human Hair Metabolomics and Network Analysis |
title_sort |
revealing metabolic perturbation following heavy methamphetamine abuse by human hair metabolomics and network analysis |
publisher |
MDPI AG |
series |
International Journal of Molecular Sciences |
issn |
1661-6596 1422-0067 |
publishDate |
2020-08-01 |
description |
Methamphetamine (MA) is a highly addictive central nervous system stimulant. Drug addiction is not a static condition but rather a chronically relapsing disorder. Hair is a valuable and stable specimen for chronic toxicological monitoring as it retains toxicants and metabolites. The primary focus of this study was to discover the metabolic effects encompassing diverse pathological symptoms of MA addiction. Therefore, metabolic alterations were investigated in human hair following heavy MA abuse using both targeted and untargeted mass spectrometry and through integrated network analysis. The statistical analyses (<i>t</i>-test, variable importance on projection score, and receiver-operator characteristic curve) demonstrated that 32 metabolites (in targeted metabolomics) as well as 417 and 224 ion features (in positive and negative ionization modes of untargeted metabolomics, respectively) were critically dysregulated. The network analysis showed that the biosynthesis or metabolism of lipids, such as glycosphingolipids, sphingolipids, glycerophospholipids, and ether lipids, as well as the metabolism of amino acids (glycine, serine and threonine; cysteine and methionine) is affected by heavy MA abuse. These findings reveal crucial metabolic effects caused by MA addiction, with emphasis on the value of human hair as a diagnostic specimen for determining drug addiction, and will aid in identifying robust diagnostic markers and therapeutic targets. |
topic |
methamphetamine drug addiction metabolomics network analysis hair lipid metabolism |
url |
https://www.mdpi.com/1422-0067/21/17/6041 |
work_keys_str_mv |
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