Neurotoxicity and Underlying Mechanisms of Endogenous Neurotoxins

Cao, Yanlu; Li, Bo; Ismail, Nafissa; Smith, Kevin B.; Li, Tianmei; Dai, Ruitong; Deng, Yulin

doi:10.3390/ijms222312805

Cited by 22 publications

(23 citation statements)

References 115 publications

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“…For example, MR studies rely on the assumption that the genetic variant does not affect the disease outcome except through exposure. However, the inactive ALDH2 genotype may increase the risk of depression by pathways other than alcohol exposure, such as pathways that involve endogenous aldehydes 21 . Moreover, inactive ALDH2 may act as an effect modifier that enhances alcohol toxicity in the brain.…”

Section: Discussionmentioning

confidence: 99%

The alcohol flushing response is associated with the risk of depression

Jeon

Kang

Cho

et al. 2022

Sci Rep

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The alcohol flushing response is experienced by 36–45% of East Asians after they consume a small amount of alcohol. Because individuals with this response are unable to metabolize the toxic acetaldehyde derived from alcohol effectively, the response offers a potential indicator of the health risks associated with alcohol intake. Depression is a major health problem linked to alcohol consumption; it might also be associated with the alcohol flushing response. Therefore, we examined the association between the alcohol flushing response and the risk of depression in the general population of South Korea. Our analysis included 139,380 participants and used data from the 2019 Korean Community Health Survey. Only current drinkers were considered in the analysis. The relationship between the alcohol flushing response and depression was evaluated by logistic regression analysis using SAS 9.4. Of the participants, more than one-third were current flushers; compared to never flushers, current flushers had a significantly greater risk of depression (adjusted odds ratio [AOR] 1.23, 95% confidence interval [CI] 1.12–1.34, P < 0.001). Former flushers did not exhibit a risk of depression. The risk of depression was significantly greater among alcohol flushers who drank < 15 g alcohol/day (< 5 g alcohol/day: AOR 1.20, 95% CI 1.07–1.35, P = 0.002; 5–14.9 g alcohol/day: AOR 1.39, 95% CI 1.13–1.70, P = 0.002). In conclusion, a large number of South Koreans experience the alcohol flushing response; compared with never flushers, current flushers are more likely to develop depression with a small dose of alcohol (< 15 g alcohol/day).

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Section: Discussionmentioning

confidence: 99%

The alcohol flushing response is associated with the risk of depression

Jeon

Kang

Cho

et al. 2022

Sci Rep

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“…Because IDO1 generates kynurenine from tryptophan, the cellular concentrations of tryptophan and kynurenine are decreased and increased by IDO1 expression, respectively. It has been reported that kynurenine induces several neurological and immunological alterations [ 45 , 46 ]. However, excess tryptophan overcame the antiviral activity of IDO1.…”

Section: Discussionmentioning

confidence: 99%

IDO1, FAT10, IFI6, and GILT Are Involved in the Antiretroviral Activity of γ-Interferon and IDO1 Restricts Retrovirus Infection by Autophagy Enhancement

Kubo

Yasui

Izumida

et al. 2022

Cells

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Gamma-interferon (γ-IFN) significantly inhibits infection by replication-defective viral vectors derived from the human immunodeficiency virus type 1 (HIV-1) or murine leukemia virus (MLV) but the underlying mechanism remains unclear. Previously we reported that knockdown of γ-IFN-inducible lysosomal thiolreductase (GILT) abrogates the antiviral activity of γ-IFN in TE671 cells but not in HeLa cells, suggesting that other γ-IFN-inducible host factors are involved in its antiviral activity in HeLa cells. We identified cellular factors, the expression of which are induced by γ-IFN in HeLa cells, using a microarray, and analyzed the effects of 11 γ-IFN-induced factors on retroviral vector infection. Our results showed that the exogenous expression of FAT10, IFI6, or IDO1 significantly inhibits both HIV-1- and MLV-based vector infections. The antiviral activity of γ-IFN was decreased in HeLa cells, in which the function of IDO1, IFI6, FAT10, and GILT were simultaneously inhibited. IDO1 is an enzyme that metabolizes an essential amino acid, tryptophan. However, IDO1 did not restrict retroviral vector infection in Atg3-silencing HeLa cells, in which autophagy did not occur. This study found that IDO1, IFI6, FAT10, and GILT are involved in the antiviral activity of γ-IFN, and IDO1 inhibits retroviral infection by inducing autophagy.

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“…1 In certain circumstances, chemicals can also cause cell necrosis or apoptosis, leading to neuronal loss and causing neuropathy, and this neuronal loss is often irreversible and may lead to holistic encephalopathy. 2 If only subpopulations of neurons are affected, this may lead to the loss of specific functions of the nervous system. An example is the compound MPTP ( degeneration of nigrostriatal dopaminergic neurons, which in turn produces Parkinson's-like symptoms.…”

Section: ■ Introductionmentioning

confidence: 99%

“…Generally, the neurotoxicity can be induced by several different patterns, including causing neuronal lesions, targeting axons and causing axonal lesions, inducing myelin lesions, and affecting neurotransmission . In certain circumstances, chemicals can also cause cell necrosis or apoptosis, leading to neuronal loss and causing neuropathy, and this neuronal loss is often irreversible and may lead to holistic encephalopathy . If only subpopulations of neurons are affected, this may lead to the loss of specific functions of the nervous system.…”

Section: Introductionmentioning

confidence: 99%

Machine Learning Modeling and Insights into the Structural Characteristics of Drug-Induced Neurotoxicity

Zhao

Sun

Zhang

et al. 2022

J. Chem. Inf. Model.

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Neurotoxicity can be resulted from many diverse clinical drugs, which has been a cause of concern to human populations across the world. The detection of drug-induced neurotoxicity (DINeurot) potential with biological experimental methods always required a lot of budget and time. In addition, few studies have addressed the structural characteristics of neurotoxic chemicals. In this study, we focused on the computational modeling for drug-induced neurotoxicity with machine learning methods and the insights into the structural characteristics of neurotoxic chemicals. Based on the clinical drug data with neurotoxicity effects, we developed 35 different classifiers by combining five different machine learning methods and seven fingerprint packages. The bestperforming model achieved good results on both 5-fold cross-validation (balanced accuracy of 76.51%, AUC value of 0.83, and MCC value of 0.52) and external validation (balanced accuracy of 83.63%, AUC value of 0.87, and MCC value of 0.67). The model can be freely accessed on the web server DINeuroTpredictor (http://dineurot.sapredictor.cn/). We also analyzed the distribution of several key molecular properties between neurotoxic and non-neurotoxic structures. The results indicated that several physicochemical properties were significantly different between the neurotoxic and non-neurotoxic compounds, including molecular polar surface area (MPSA), AlogP, the number of hydrogen bond acceptors (nHAcc) and donors (nHDon), the number of rotatable bonds (nRotB), and the number of aromatic rings (nAR). In addition, 18 structural alerts responsible for chemical neurotoxicity were identified. The structural alerts have been integrated with our web server SApredictor (http://www.sapredictor.cn). The results of this study could provide useful information for the understanding of the structural characteristics and computational prediction for chemical neurotoxicity.

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Neurotoxicity and Underlying Mechanisms of Endogenous Neurotoxins

Cited by 22 publications

References 115 publications

The alcohol flushing response is associated with the risk of depression

The alcohol flushing response is associated with the risk of depression

IDO1, FAT10, IFI6, and GILT Are Involved in the Antiretroviral Activity of γ-Interferon and IDO1 Restricts Retrovirus Infection by Autophagy Enhancement

Machine Learning Modeling and Insights into the Structural Characteristics of Drug-Induced Neurotoxicity

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