Serum metabolomics analysis in patients with alcohol dependence
ObjectiveAlcohol dependence (AD) is a chronic recurrent mental disease caused by long-term drinking. It is one of the most prevalent public health problems. However, AD diagnosis lacks objective biomarkers. This study was aimed to shed some light on potential biomarkers of AD patients by investigati...
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| Format: | Article |
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Frontiers Media S.A.
2023-04-01
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| Series: | Frontiers in Psychiatry |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fpsyt.2023.1151200/full |
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| author | Yanjie Zhang Yanjie Zhang Yajun Sun Yajun Sun Qin Miao Qin Miao Shilong Guo Qi Wang Qi Wang Tianyuan Shi Tianyuan Shi Xinsheng Guo Xinsheng Guo Shuai Liu Shuai Liu Guiding Cheng Guiding Cheng Chuansheng Wang Chuansheng Wang Ruiling Zhang Ruiling Zhang |
| author_facet | Yanjie Zhang Yanjie Zhang Yajun Sun Yajun Sun Qin Miao Qin Miao Shilong Guo Qi Wang Qi Wang Tianyuan Shi Tianyuan Shi Xinsheng Guo Xinsheng Guo Shuai Liu Shuai Liu Guiding Cheng Guiding Cheng Chuansheng Wang Chuansheng Wang Ruiling Zhang Ruiling Zhang |
| author_sort | Yanjie Zhang |
| collection | DOAJ |
| description | ObjectiveAlcohol dependence (AD) is a chronic recurrent mental disease caused by long-term drinking. It is one of the most prevalent public health problems. However, AD diagnosis lacks objective biomarkers. This study was aimed to shed some light on potential biomarkers of AD patients by investigating the serum metabolomics profiles of AD patients and the controls.MethodsLiquid chromatography-mass spectrometry (LC–MS) was used to detect the serum metabolites of 29 AD patients (AD) and 28 controls. Six samples were set aside as the validation set (Control: n = 3; AD group: n = 3), and the remaining were used as the training set (Control: n = 26; AD group: n = 25). Principal component analysis (PCA) and partial least squares discriminant analysis (PCA-DA) were performed to analyze the training set samples. The metabolic pathways were analyzed using the MetPA database. The signal pathways with pathway impact >0.2, value of p <0.05, and FDR < 0.05 were selected. From the screened pathways, the metabolites whose levels changed by at least 3-fold were screened. The metabolites with no numerical overlap in their concentrations in the AD and the control groups were screened out and verified with the validation set.ResultsThe serum metabolomic profiles of the control and the AD groups were significantly different. We identified six significantly altered metabolic signal pathways, including protein digestion and absorption; alanine, aspartate, and glutamate metabolism; arginine biosynthesis; linoleic acid metabolism; butanoate metabolism; and GABAergic synapse. In these six signal pathways, the levels of 28 metabolites were found to be significantly altered. Of these, the alterations of 11 metabolites changed by at least 3-fold compared to the control group. Of these 11 metabolites, those with no numerical overlap in their concentrations between the AD and the control groups were GABA, 4-hydroxybutanoic acid, L-glutamic acid, citric acid and L-glutamine.ConclusionThe metabolite profile of the AD group was significantly different from that of the control group. GABA, 4-hydroxybutanoic acid, L-glutamic acid, citric acid, and L-glutamine could be used as potential diagnostic markers for AD. |
| first_indexed | 2024-04-09T17:40:25Z |
| format | Article |
| id | doaj.art-2fa0ef007a6048ba9cb5c0e270ed0b1f |
| institution | Directory Open Access Journal |
| issn | 1664-0640 |
| language | English |
| last_indexed | 2024-04-09T17:40:25Z |
| publishDate | 2023-04-01 |
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| series | Frontiers in Psychiatry |
| spelling | doaj.art-2fa0ef007a6048ba9cb5c0e270ed0b1f2023-04-17T05:58:12ZengFrontiers Media S.A.Frontiers in Psychiatry1664-06402023-04-011410.3389/fpsyt.2023.11512001151200Serum metabolomics analysis in patients with alcohol dependenceYanjie Zhang0Yanjie Zhang1Yajun Sun2Yajun Sun3Qin Miao4Qin Miao5Shilong Guo6Qi Wang7Qi Wang8Tianyuan Shi9Tianyuan Shi10Xinsheng Guo11Xinsheng Guo12Shuai Liu13Shuai Liu14Guiding Cheng15Guiding Cheng16Chuansheng Wang17Chuansheng Wang18Ruiling Zhang19Ruiling Zhang20Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, ChinaHenan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang, ChinaDepartment of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, ChinaDepartment of Scientific Research, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, ChinaDepartment of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, ChinaDepartment of Addiction, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, ChinaDepartment of Oncology, The Third Affiliated Hospital of Xinxiang Medical University, Xinxiang, ChinaDepartment of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, ChinaHenan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang, ChinaDepartment of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, ChinaHenan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang, ChinaDepartment of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, ChinaHenan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang, ChinaDepartment of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, ChinaHenan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang, ChinaDepartment of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, ChinaHenan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang, ChinaDepartment of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, ChinaHenan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang, ChinaDepartment of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, ChinaHenan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang, ChinaObjectiveAlcohol dependence (AD) is a chronic recurrent mental disease caused by long-term drinking. It is one of the most prevalent public health problems. However, AD diagnosis lacks objective biomarkers. This study was aimed to shed some light on potential biomarkers of AD patients by investigating the serum metabolomics profiles of AD patients and the controls.MethodsLiquid chromatography-mass spectrometry (LC–MS) was used to detect the serum metabolites of 29 AD patients (AD) and 28 controls. Six samples were set aside as the validation set (Control: n = 3; AD group: n = 3), and the remaining were used as the training set (Control: n = 26; AD group: n = 25). Principal component analysis (PCA) and partial least squares discriminant analysis (PCA-DA) were performed to analyze the training set samples. The metabolic pathways were analyzed using the MetPA database. The signal pathways with pathway impact >0.2, value of p <0.05, and FDR < 0.05 were selected. From the screened pathways, the metabolites whose levels changed by at least 3-fold were screened. The metabolites with no numerical overlap in their concentrations in the AD and the control groups were screened out and verified with the validation set.ResultsThe serum metabolomic profiles of the control and the AD groups were significantly different. We identified six significantly altered metabolic signal pathways, including protein digestion and absorption; alanine, aspartate, and glutamate metabolism; arginine biosynthesis; linoleic acid metabolism; butanoate metabolism; and GABAergic synapse. In these six signal pathways, the levels of 28 metabolites were found to be significantly altered. Of these, the alterations of 11 metabolites changed by at least 3-fold compared to the control group. Of these 11 metabolites, those with no numerical overlap in their concentrations between the AD and the control groups were GABA, 4-hydroxybutanoic acid, L-glutamic acid, citric acid and L-glutamine.ConclusionThe metabolite profile of the AD group was significantly different from that of the control group. GABA, 4-hydroxybutanoic acid, L-glutamic acid, citric acid, and L-glutamine could be used as potential diagnostic markers for AD.https://www.frontiersin.org/articles/10.3389/fpsyt.2023.1151200/fullalcohol dependenceliquid chromatography-mass spectrometry (LC–MS)metabolic signal pathwaysmultivariate statistical analysispotential biomarkers |
| spellingShingle | Yanjie Zhang Yanjie Zhang Yajun Sun Yajun Sun Qin Miao Qin Miao Shilong Guo Qi Wang Qi Wang Tianyuan Shi Tianyuan Shi Xinsheng Guo Xinsheng Guo Shuai Liu Shuai Liu Guiding Cheng Guiding Cheng Chuansheng Wang Chuansheng Wang Ruiling Zhang Ruiling Zhang Serum metabolomics analysis in patients with alcohol dependence Frontiers in Psychiatry alcohol dependence liquid chromatography-mass spectrometry (LC–MS) metabolic signal pathways multivariate statistical analysis potential biomarkers |
| title | Serum metabolomics analysis in patients with alcohol dependence |
| title_full | Serum metabolomics analysis in patients with alcohol dependence |
| title_fullStr | Serum metabolomics analysis in patients with alcohol dependence |
| title_full_unstemmed | Serum metabolomics analysis in patients with alcohol dependence |
| title_short | Serum metabolomics analysis in patients with alcohol dependence |
| title_sort | serum metabolomics analysis in patients with alcohol dependence |
| topic | alcohol dependence liquid chromatography-mass spectrometry (LC–MS) metabolic signal pathways multivariate statistical analysis potential biomarkers |
| url | https://www.frontiersin.org/articles/10.3389/fpsyt.2023.1151200/full |
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