Differential sensitivity of human neurons carrying μ opioid receptor (MOR) N40D variants in response to ethanol.
- Authors
- Scarnati, Matthew S; Boreland, Andrew J; Joel, Marisa; Hart, Ronald P; Pang, Zhiping P
- Year
- 2020
- Journal
- Alcohol (Fayetteville, N.Y.)
- PMID
- 32561311
- DOI
- 10.1016/j.alcohol.2020.05.004
- PMCID
- PMC7958146
The acute and chronic effects of alcohol on the brain and behavior are linked to alterations in inhibitory synaptic transmission. Alcohol's most consistent effect at the synaptic level is probably a facilitation of γ-aminobutyric acid (GABA) release, as seen from several rodent studies. The impact of alcohol on GABAergic neurotransmission in human neurons is unknown, due to a lack of a suitable experimental model. Human neurons can also be used to model effects of genetic variants linked with alcohol use disorders (AUDs). The A118G single nucleotide polymorphism (SNP rs1799971) of the OPRM1 gene encoding the N40D (D40 minor allele) mu-opioid receptor (MOR) variant has been linked with individuals who have an AUD. However, while N40D is clearly associated with other drugs of abuse, involvement with AUDs is controversial. In this study, we employed Ascl1-and Dlx2-induced inhibitory neuronal cells (AD-iNs) generated from human iPS cell lines carrying N40D variants, and investigated the impact of ethanol acutely and chronically on GABAergic synaptic transmission. We found that N40 AD-iNs display a stronger facilitation (versus D40) of spontaneous and miniature inhibitory postsynaptic current frequency in response to acute ethanol application. Quantitative immunocytochemistry of Synapsin 1 synaptic puncta revealed a similar synapse number between N40 and D40 iNs, suggesting an ethanol modulation of presynaptic GABA release without affecting synapse density. Interestingly, D40 iNs exposed to chronic intermittent ethanol application caused a significant increase in mIPSC frequency, with only a modest enhancement observed in N40 iNs. These data suggest that the MOR genotype may confer differential sensitivity to synaptic output, which depends on ethanol exposure time and concentration for AD-iNs and may help explain alcohol dependence in individuals who carry the MOR D40 SNPs. Furthermore, this study supports the use of human neuronal cells carrying risk-associated genetic variants linked to disease, as in vitro models to assay the synaptic actions of alcohol on human neuronal cells.
Generation of GABAergic-induced neuronal (iN) cells from human isogenic iPS cell lines for MOR genetic variants N40 and D40.(A) Experimental design. Schedule of experiments required for direct conversion of iPS cells to GABAergic-induced neurons (AD-iNs) (B) Oct 4 (green), Tra-1–60 (red), and DAPI (blue) immunocytochemistry (ICC) for N40 and D40 isogenic iPS cells depicting pluripotency (scale = 50 μm) (C) MAP2 (red) and Synapsin (green) ICC of iN cells generated from N40 and D40 isogenic iPS cell lines (scale = 10 μm) (D) Immunofluorescence of MAP2 (red) and GAD 67 (green) of iN cells produced from N40 and D40 isogenic iPS cell lines (scale = 10 μm).
The MOR genetic variant N40D does not affect synapse formation in human AD-iNs.(A) Top: Representative confocal images of N40 AD-iNs that were employed for Intellicount analysis. MAP2 (red), Synapsin (green), and Merged images (scale = 20 μm). Bottom: Representative confocal images of D40 AD-iNs that were employed for Intellicount analysis. MAP2 (red), Synapsin (green), and Merged images (scale = 20 μm) (B) Zoomed-in images of the boxed areas in (A) (scale = 2 μm) (C) Quantifications of MAP2-correlated synapse density, synapse size, and staining intensity (Synapsin and MAP2) are not different between genotypes. Average MAP2 area (μm2) is significantly different between iNs harboring N40D MOR allelic variants (***p < 0.001). Paired t test was used to evaluate within-genotype statistical differences (*p < 0.05, **p < 0.01, ***p < 0.001) (NS = no statistical significance found).
Acute ethanol application causes an increase in the overall inhibitory tone in human iNs carrying MOR N40.(A) Representative traces of sIPSCs recorded before [N40 (black) and D40 (blue)] and after acute 40 mM ethanol application (red) (B) Jittered-X graph illustrating the changes in sIPSC frequency in response to acute ethanol application for N40 and D40 AD-iNs. These data are relative to control sIPSC responses (dotted line). Each data point is a recording from an individual iN (C) Quantification of sIPSC frequency changes in response to acute 40 mM ethanol application for iPS-derived N40 and D40 AD-iNs; data are normalized to control (N40EtOH vs. control: p = 0.5; D40EtOH vs. control: p = 0.8) (N40EtOH vs. D40EtOH: p = 0.1) (D) Quantification of sIPSC amplitude changes in response to acute 40 mM ethanol application for iPS-derived N40 and D40 AD-iNs; data are normalized to control (N40EtOH vs. control: p = 0.9; D40EtOH vs. control: p = 0.7) (N40EtOH vs. D40EtOH: p = 0.9) (E) Average sIPSC control frequency comparing N40 to D40 AD-iNs (N40EtOH vs. D40EtOH: p = 0.3) (F) Quantification of average sIPSC rise time changes in response to acute 40 mM ethanol application for iPS cell-derived N40 and D40 AD-iNs (N40EtOH vs. control: p = 0.7; D40EtOH vs. control: p = 0.9; N40 vs. D40 controls: p = 0.2; N40EtOH vs. D40EtOH: p = 0.2) (G) Quantification of average sIPSC decay time changes in response to acute 40 mM ethanol application for iPS cell-derived N40 and D40 AD-iNs (N40EtOH vs. control: p = 0.7; D40EtOH vs. control: p = 0.9; N40 vs. D40 controls: *p ≤ 0.5; N40EtOH vs. D40EtOH: p = 0.09). Data are depicted as means ± SEM. Numbers of cells/number of independently generated cultures analyzed are depicted within the bars. Paired t test was used to evaluate within-genotype statistical differences, and one-way ANOVA was used to evaluate between-genotype statistical differences (*p < 0.05, **p < 0.01, ***p < 0.001) (NS = no statistical significance found).
Acute ethanol application increases miniature GABA release in AD-iNs harboring MOR N40.(A) Representative traces of mIPSCs recorded before [N40 (black) and D40 (blue)] and after acute 40 mM ethanol application (red) (B) Jittered-X graph illustrating the changes in mIPSC frequency in response to acute ethanol application for N40 and D40 AD-iNs. These data are relative to control sIPSC responses (dotted line). Each data point is a recording from an individual iN (C) Quantification of mIPSC frequency changes in response to acute 40 mM ethanol application for iPS-derived N40 and D40 AD-iNs; data are normalized to control (N40EtOH vs. control: p = 0.5, D40EtOH vs. control: p = 0.8) (N40EtOH vs. D40EtOH: *p ≤ 0.05) (D) Quantification of mIPSC amplitude changes in response to acute 40 mM ethanol application for iPS-derived N40 and D40 AD-iNs; data are normalized to control (N40EtOH vs. control: p = 0.2; D40EtOH vs. control: p = 0.7) (N40EtOH vs. D40EtOH: p = 0.1) (E) Average mIPSC control frequency comparing N40 to D40 AD-iNs (N40EtOH vs. D40EtOH: p = 0.4) (F) Quantification of average mIPSC rise time changes in response to acute 40 mM ethanol application for iPS cell-derived N40 and D40 AD-iNs (N40EtOH vs. control: p = 0.8; D40EtOH vs. control: p = 0.8; N40 vs. D40 controls: p = 0.7; N40EtOH vs. D40EtOH: p = 0.7) (G) Quantification of average mIPSC decay time changes in response to acute 40 mM ethanol application for iPS cell-derived N40 and D40 AD-iNs (N40EtOH vs. control: p = 0.8; D40EtOH vs. control: p = 0.4; N40 vs. D40 controls: p = 0.2; N40EtOH vs. D40EtOH: p = 0.5). Data are depicted as means ± SEM. Numbers of cells/number of independently generated cultures analyzed are depicted within the bars. Paired t test was used to evaluate within-genotype statistical differences, and one-way ANOVA was used to evaluate between-genotype statistical differences (*p < 0.05, **p < 0.01, ***p < 0.001) (NS = no statistical significance found).
10-day chronic intermittent ethanol (CIE) application selectively increases GABAergic transmission in MOR D40 iNs.(A) Experimental design. Ctrl, control; iNs were treated with glial-conditioned medium with the indicated components daily for a period of 10 days. CIE, chronic intermittent ethanol; iNs were treated with the same medium as control, supplemented with 75 mM ethanol, daily for a period of 10 days (saw tooth red line represents decreasing ethanol concentration as a result of evaporation; red arrows indicate addition of fresh 75 mM ethanol). Following day 10, mIPSCs were recorded: Ctrl iNs were recorded in HEPES recording medium with the indicated components. CIE iNs were recorded in HEPES recording medium supplemented with 40 mM ethanol (acute application) (B) Evaporation of ethanol was examined in culture dishes not containing neural cells by measurement of medium ethanol concentrations (Control, 40 mM, and 75 mM) at 0, 12, and 24 h post-ethanol addition using an AM1 Alcohol Analyzer (C) Half-life of ethanol was determined by plotting the log of the fraction remaining, normalized to initial ethanol concentration. The linear regression fit is plotted as a line (***p value of the fit40mM < 0.001; ***p value of the fit75mM < 0.001). The half-life was calculated from the slope of the fit, as −log (2)/slope (t1/2 for 40 mM = 9.51 h with a 95% confidence interval of 8.85–10.27 h; r2 = 0.984) (t1/2 for 75 mM = 7.05 h with a 95% confidence interval of 6.77–7.34 h; r2 = 0.995) (D) Representative traces of mIPSCs recorded before [N40 (black) and D40 (blue)] and after CIE exposure + 40 mM ethanol acute re-application (red) (E) Quantification of average mIPSC frequency changes in response to CIE and acute 40 mM ethanol re-application for iPS-derived N40 and D40 AD-iNs. Each dot (data point) is a recording from an individual iN (N40EtOH vs. control: p = 0.2; D40EtOH vs. control: ***p ≤ 0.001); (N40EtOH vs. D40EtOH: # # #p ≤ 0.001) (F) Quantification of average mIPSC amplitude changes in response to CIE and acute 40 mM ethanol re-application for iPS-derived N40 and D40 AD-iNs. Each dot (data point) is a recording from an individual iN (N40EtOH vs. control: p = 0.4; D40EtOH vs. control: p = 0.8); (N40EtOH vs. D40EtOH: p = 0.08). Numbers of cells/number of independently generated cultures analyzed are depicted within the bars. Paired t test was used to evaluate within-genotype statistical differences, and one-way ANOVA was used to evaluate between-genotype statistical differences (*p < 0.05, **p < 0.01, ***p < 0.001) (NS = no statistical significance found).
| Name | Type |
|---|---|
| 118AA mice local | cohort |
| 118GG mice local | cohort |
| A118 local | variant |
| A118G SNP | variant |
| AA genotype OPRM1 local | variant |
| accutase | drug |
| Acute alcohol effect local | phenotype |
| Acute ethanol application local | drug |
| acute withdrawal | phenotype |
| addiction | phenotype |
| AD-iN cells local | cohort |
| AD-iNs local | cohort |
| AD-iNs local | phenotype |
| alcohol | phenotype |
| alcohol abuse | phenotype |
| alcohol dependence | phenotype |
| alcoholism | phenotype |
| alcohol sensitivity | phenotype |
| Alcohol Use Disorder | phenotype |
| alcohol use disorders | phenotype |
| Alexa Fluor 488 | drug |
| Alexa Fluor 546 local | drug |
| Ara-C | drug |
| Ascl1 | gene |
| ATP-magnesium local | drug |
| AUD | phenotype |
| average MAP2 area local | phenotype |
| B27 supplement | drug |
| basolateral amygdala | anatomy |
| Bdnf | gene |
| BSA | drug |
| CaCl2 | drug |
| central amygdala | anatomy |
| cerebellum | anatomy |
| chicken anti-MAP2 local | drug |
| Chronic alcohol effect local | phenotype |
| chronic ethanol exposure | phenotype |
| CIE | drug |
| CIE exposure local | cohort |
| CNQX | drug |
| Conditioned glial medium local | drug |
| Control AD-iNs local | cohort |
| controls | cohort |
| CRISPR/Cas9 | drug |
| CsCl local | drug |
| CsOH local | drug |
| D40 local | cohort |
| D40 local | variant |
| D40 AD-iNs local | cohort |
| D40 iNs local | cohort |
| DAMGO | drug |
| DAPI | drug |
| Decreased spontaneous action potential firing frequency local | phenotype |
| Dlx2 | gene |
| dopamine | drug |
| dorsal striatum | anatomy |
| doxycycline | drug |
| drinks per week | phenotype |
| drug dependence | phenotype |
| EGTA | drug |
| eIPSC | phenotype |
| endogenous opioids | drug |
| ethanol consumption | phenotype |
| ethanol dependence | phenotype |
| Exogenous MOR-specific agonists local | drug |
| G118 local | variant |
| GABA | phenotype |
| GABAA receptor | drug |
| GABAB receptor | drug |
| GABAergic presynaptic terminals local | anatomy |
| GABAergic synapses local | anatomy |
| GABAergic synaptic release local | phenotype |
| GAD1 | gene |
| GDNF | drug |
| GG genotype OPRM1 local | variant |
| glucose | drug |
| glutamate | drug |
| glutamine | drug |
| goat anti-chicken IgY-Alexa Fluor 546 local | drug |
| goat anti-mouse IgG-Alexa Fluor 546 local | drug |
| goat anti-rabbit IgG-Alexa Fluor 488 local | drug |
| GTP-sodium local | drug |
| HEPES | drug |
| hippocampus | anatomy |
| human alcoholics | phenotype |
| Human drinkers local | phenotype |
| human-induced pluripotent (iPS) cells local | cohort |
| hygromycin | drug |
| iN cells local | drug |
| Increased inhibitory synaptic release local | phenotype |
| Increased mIPSC frequency | phenotype |
| Increased sIPSC frequency | phenotype |
| inhibitory tone local | phenotype |
| Inhibitory tone local | phenotype |
| iNs local | cohort |
| iPS cells local | drug |
| Isogenic iPS cell lines local | cohort |
| Isogenic stem cell lines local | cohort |
| KCl | drug |
| K-gluconate | drug |
| KOH | drug |
| lentivirus | drug |
| MAP2 | gene |
| matrigel | drug |
| Mesolimbic dopamine neurocircuitry local | anatomy |
| MgCl2 | drug |
| Minimum Essential Medium local | drug |
| mIPSC amplitude | phenotype |
| mIPSC frequency | phenotype |
| monkeys | cohort |
| MOR local | gene |
| MOR D40 local | variant |
| MOR humanized mice local | cohort |
| MOR N40 local | variant |
| MOR N40D local | variant |
| mouse anti-Gad-67 local | drug |
| mouse anti-Oct4 local | drug |
| mouse anti-Tra-1-60 local | drug |
| mTesR | drug |
| mTeSR medium local | drug |
| mu opioid receptor (MOR) local | drug |
| N40 local | cohort |
| N40 local | variant |
| N40 AD-iNs local | cohort |
| N40 iNs local | cohort |
| naltrexone | drug |
| NaOH | drug |
| Neurobasal | drug |
| neurobasal medium | drug |
| neuronal excitability | phenotype |
| Neurophysiological differences local | phenotype |
| neuropsychiatric disorders | phenotype |
| neurotransmitter release | phenotype |
| NMDA receptor subunit genes local | gene |
| normal goat serum | drug |
| NT3 | drug |
| Oct4 | gene |
| opioid receptor agonist | drug |
| OPRM1 | cohort |
| OPRM1 A118G | cohort |
| OPRM1 D40 local | variant |
| OPRM1 N40 local | variant |
| OPRM1 N40D local | variant |
| OPRM1 N40D variant local | variant |
| paraformaldehyde | drug |
| Patient-derived iPS cells local | cohort |
| phosphocreatine | drug |
| picrotoxin | drug |
| POU5F1 | gene |
| Primary glial culture local | cohort |
| PTX | drug |
| puromycin | drug |
| rabbit anti-Synapsin local | drug |
| reward system | anatomy |
| Rock inhibitor | drug |
| Rodent overexpression models local | cohort |
| rs1799971 | variant |
| rs1799971 G-allele local | variant |
| rtTa | drug |
| sAP amplitude local | phenotype |
| sAP frequency local | phenotype |
| sIPSC amplitude local | phenotype |
| sIPSC decay time local | phenotype |
| sIPSC frequency local | phenotype |
| sIPSC rise time local | phenotype |
| sIPSCs | phenotype |
| spinal cord | anatomy |
| SYN1 | gene |
| synapsin | gene |
| synaptic function | phenotype |
| synaptic number local | phenotype |
| tetrodotoxin | drug |
| TRA-1-60 | phenotype |
| Triton X-100 | drug |
| TUBB3 | gene |
| ventral tegmental area | anatomy |
| Y27632 local | drug |
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In this knowledge base
| Title | Year | PMID |
|---|---|---|
| Alcohol reverses the effects of KCNJ6 (GIRK2) noncoding variants on excitability of human glutamatergic neurons. | 2023 | 36207584 |
External
| Title | Authors | Journal | Year | Link |
|---|---|---|---|---|
| Advancing substance use disorder biology by studying underlying gene x environment interactions. | Sidamon-Eristoff AE et al. | — | 2026 | → |
| Ethanol induces neuroimmune dysregulation and soluble TREM2 generation in a human iPSC neuron, astrocyte, microglia triculture model. | Boreland AJ et al. | — | 2026 | → |
| Microelectrode arrays cultured with in vitro neural networks for motion control tasks: encoding and decoding progress and advances. | Hua S et al. | — | 2025 | → |
| Polygenic risk for alcohol use disorder affects cellular responses to ethanol exposure in a human microglial cell model. | Li X et al. | — | 2024 | → |
| Upregulated GIRK2 Counteracts Ethanol-Induced Changes in Excitability and Respiration in Human Neurons. | Prytkova I et al. | — | 2024 | → |
| 5. Collaborative Study on the Genetics of Alcoholism: Functional genomics. | Gameiro-Ros I et al. | — | 2023 | → |
| Alcohol reverses the effects of KCNJ6 (GIRK2) noncoding variants on excitability of human glutamatergic neurons. | Popova D et al. | — | 2023 | → |
| Methods for shipping live primary cortical and hippocampal neuron cultures from postnatal mice. | Sammoura FM et al. | — | 2023 | → |
| Whole Cell Patch Clamp Electrophysiology in Human Neuronal Cells. | Gabriel R et al. | — | 2023 | → |
| Optimized splitting of mixed-species RNA sequencing data. | Song X et al. | — | 2022 | → |
| The effects of others' drinking on the harms to children in Thailand: Lessons from the WHO-ThaiHealth project. | Preampruchcha P et al. | — | 2022 | → |
| Characterization hiPSC-derived neural progenitor cells and neurons to investigate the role of NOS1AP isoforms in human neuron dendritogenesis. | Crosta CM et al. | — | 2020 | → |