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Cited by 118Single-cell and spatial transcriptomicsAlcohol Consumption and Health EffectsSubstance Abuse Treatment and Outcomes

Single cell transcriptome profiling of the human alcohol-dependent brain

Open access
Brenner, Eric, Tiwari, Gayatri R, Kapoor, Manav, Liu, Yunlong, Brock, Amy, Mayfield, R Dayne·2020·Human Molecular Genetics
DOI 10.1093/hmg/ddaa038PMC PMC7206851

Published version of a preprint

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Abstract

Alcoholism remains a prevalent health concern throughout the world. Previous studies have identified transcriptomic patterns in the brain associated with alcohol dependence in both humans and animal models. But none of these studies have systematically investigated expression within the unique cell types present in the brain. We utilized single nucleus RNA sequencing (snRNA-seq) to examine the transcriptomes of over 16 000 nuclei isolated from the prefrontal cortex of alcoholic and control individuals. Each nucleus was assigned to one of seven major cell types by unsupervised clustering. Cell type enrichment patterns varied greatly among neuroinflammatory-related genes, which are known to play roles in alcohol dependence and neurodegeneration. Differential expression analysis identified cell type-specific genes with altered expression in alcoholics. The largest number of differentially expressed genes (DEGs), including both protein-coding and non-coding, were detected in astrocytes, oligodendrocytes and microglia. To our knowledge, this is the first single cell transcriptome analysis of alcohol-associated gene expression in any species and the first such analysis in humans for any addictive substance. These findings greatly advance the understanding of transcriptomic changes in the brain of alcohol-dependent individuals.

AI snapshot

Written from the paper’s full text.

TL;DR

This study used single-nucleus RNA sequencing to profile over 16,000 nuclei from prefrontal cortex of alcohol-dependent and control donors, identifying cell type-specific transcriptomic changes associated with alcoholism. It reports the first single-cell transcriptome analysis of alcohol-associated gene expression in human brain, with the largest differential expression signal in glial cells.

Key findings

  • snRNA-seq of 16,305 nuclei from 7 donors (4 controls, 3 alcohol dependent) identified seven major brain cell types; cell type proportions did not differ between alcoholics and controls (lowest p=0.27 for GABAergic neurons).
  • Differential expression analysis found 916 DEGs at FDR<0.25 and 253 at FDR<0.05, with the largest DEG counts in astrocytes (206), oligodendrocytes, and microglia; endothelial cells had 0 DEGs. Both protein-coding and non-coding DEGs were present in every cell type with more than two total DEGs.
  • Of 85 Neuroinflammation Signaling Pathway genes, 79 were detected and 68 were detected in more than 20 nuclei, with enrichment varying by cell type. The top astrocyte DEG was AC008957.2, a lncRNA antisense to SLC1A3; SLC1A3 was also upregulated in astrocytes at FDR=0.07, and four neuroinflammation-associated DEGs in astrocytes had FDR<0.11.
  • Compared with a bulk PFC RNA-seq dataset (65 alcoholics, 73 controls), all non-microglia cell types were more similar to bulk than microglia; among 33 microglial DEGs, only SLC11A1 was also significant in the bulk data.

Methods

  • Droplet-based snRNA-seq (10x Genomics 3′) was performed on frozen postmortem prefrontal cortex; nuclei with >20% mitochondrial UMI counts were removed, yielding 16,305 nuclei from 7 donors.
  • Analysis used scanpy: normalization with scran size factors, highly variable genes, PCA on top 50 PCs, nearest-neighbor graph construction, and Louvain clustering at resolution 0.1; clusters were annotated with canonical brain cell type markers.
  • Differential expression used pseudobulk transcriptomes per cell type and donor with DESeq2 and batch as a covariate; DEGs were called at FDR<0.25 and FDR<0.05, and IPA was used for pathway analysis.

Limitations

  • The authors state that the sample size of 7 donors limits statistical power, particularly for genes with smaller effect sizes, though they argue it does not preclude meaningful inferences.
  • Evident from the text: all donors in Supplementary Table 1 are male, only prefrontal cortex was profiled, and one sample (647) was prepared in a different batch using a slightly different nuclei isolation protocol, which may limit generalizability and introduce technical variation.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.1093/hmg/ddaa038

Cites

51 of 51 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Claims the paper makes

0 of 31 cited sources checked · 0 supported · 0 flagged

  • Findingown data

    Nuclei did not separate by the donor or batch from which they were isolated.

    “Nuclei did not separate by the donor or batch from which they were isolated, indicating that any sample-specific gene expression patterns that may be present were of minimal impact ( Fig 1A, Fig S1 ).”
    Quote in the paperSubstantial claim
  • Findingcitation

    The clusters were annotated to seven major brain cell types: excitatory neurons, astrocytes, oligodendrocytes, inhibitory/GABAergic neurons, oligodendrocyte progenitor cells, microglia, and endothelial cells.

    “We then annotated the clusters using the following markers of major brain cell types that are consistently detected in single cell/nucleus transcriptomics studies (7,8,20,23,24) : excitatory neurons, astrocytes, oligodendrocytes, inhibitory/GABAergic neurons, oligodendrocyte progenitor cells (OPCs), microglia, and endothelial cells ( Fig 1C-D ).”
    Quote in the paperSubstantial claim0 of 3 sources checked
    • cites [7] Nagy, 2019, Single-nucleus RNA sequencing shows convergent evidence from different cell types for altered synaptic plasticity in major depressive disorder, bioRxiv

      Not checked in the free run.

    • cites [8] Mathys, 2019, Single-cell transcriptomic analysis of Alzheimer’s disease, Nature source

      Not checked in the free run.

    • cites [20] Erickson, 2018, Astrocyte-specific transcriptome responses to chronic ethanol consumption, Pharmacogenomics J. source

      Not checked in the free run.

  • Findingown data

    Using snRNA-seq, the authors profiled the transcriptomes of 16,305 nuclei extracted from frozen prefrontal cortex samples of 4 control and 3 alcohol dependent individuals.

    “Using single nucleus RNA-seq (snRNA-seq), a popular scRNA-seq alternative for analyzing frozen brain tissue (9)(10)(11)(12)(13)(14)(15)(16)(17)(18) , we profiled the transcriptomes of 16,305 nuclei extracted from frozen prefrontal cortex (PFC) samples of 4 control and 3 alcohol dependent individuals.”
    Quote in the paperSubstantial claim
  • Findingown data

    The dataset was comprised of transcriptomes of 16,305 nuclei from seven donors (four control donors and three donors with alcohol dependence).

    “The dataset was comprised of transcriptomes of 16,305 nuclei from seven donors (four control donors and three donors with alcohol dependence) ( Table S2 ).”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites Table S2

      Not checked in the free run.

  • Findingown data

    Unsupervised, graph-based clustering yielded eight clusters.

    “In order to identify transcriptomically-distinct groups of nuclei, we performed unsupervised, graph-based clustering, yielding eight clusters ( Fig 1B ).”
    Quote in the paperNot a substantial claim
  • May combine two claims. 15
  • Classified as probably not a substantial claim. 7

  • May combine two claims.

    Findingown data

    Two clusters corresponded with GABAergic neurons while all other clusters corresponded to a single cell type.

    “Two clusters corresponded with GABAergic neurons while all other clusters corresponded to a single cell type.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    The top DEG in astrocytes was AC008957.2, a lncRNA that is antisense to the gene encoding SLC1A3.

    “Interestingly, the top DEG in astrocytes was AC008957.2, a lncRNA that is antisense to the gene encoding SLC1A3 , a glutamate uptake transporter that plays important roles in the neurocircuitry of addiction (38)(39)(40) .”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    There were large differences in DEG counts among the different cell types, with endothelial cells having 0 and astrocytes having 206 DEGs.

    “There were large differences in DEG counts among the different cell types, with endothelial cells having 0 and astrocytes having 206 DEGs.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Expression of some neuroinflammatory genes was fairly pervasive across cell types while other genes exhibited relative enrichment in one or two specific cell types.

    “Expression of some genes was fairly pervasive across cell types (e.g.HMGB1 ) while other genes exhibited relative enrichment in one or two specific cell types (e.g.SNCA in excitatory neurons, BCL2 in astrocytes, P2RX7 in oligodendrocytes,”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    The authors identified a total of 916 DEGs at FDR<0.25 and 253 at FDR<0.05.

    “We identified a total of 916 DEGs at FDR<0.25 and 253 at FDR<0.05 ( Fig 3A ).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    One of the top DEGs in this pathway was CACNA1A, which was downregulated in astrocytes and upregulated in microglia.

    “One of the top DEGs in this pathway was CACNA1A , which was downregulated in astrocytes and upregulated in microglia.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    Of the 85 human genes directly listed in the Neuroinflammation Signaling Pathway in the IPA database, 79 were detected in the snRNA-seq dataset, and 68 were detected in more than 20 nuclei.

    “Of the 85 human genes directly listed in the Neuroinflammation Signaling Pathway in the IPA database, 79 were detected in our snRNA-seq dataset, and 68 were detected in more than 20 nuclei.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingcitation

    Proportions of the different cell types were comparable to other snRNA-seq studies, with neurons (particularly excitatory neurons) over-represented relative to non-neuronal cell types.

    “Proportions of the different cell types were comparable to other snRNA-seq studies (8,23) with neurons (particularly excitatory neurons) being over-represented relative to non-neuronal cell types ( Fig S2 ).”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites [8] Mathys, 2019, Single-cell transcriptomic analysis of Alzheimer’s disease, Nature source

      Not checked in the free run.

    • cites [23] Lake, 2018, Integrative single-cell analysis of transcriptional and epigenetic states in the human adult brain, Nat. Biotechnol. source

      Not checked in the free run.

  • May combine two claims.

    Findingown data

    Every cell type displayed relative enrichment of different genes linked to neuroinflammation, a process associated with excessive alcohol use.

    “Every cell type displayed relative enrichment of different genes linked to neuroinflammation, a process associated with excessive alcohol use.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingown data

    FAS expression is lower in astrocytes relative to endothelial cells.

    “For example, expression of FAS is lower in astrocytes relative to endothelial cells; however, FAS is known to be active in both astrocytes (29) and endothelial cells (30) .”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationreasoning

    The bulk tissue homogenate approach likely masks differences in gene expression patterns among specific cells and heterogeneity from cell-to-cell variation within a given cell type.

    “This approach likely masks differences in gene expression patterns among specific cells, as well as heterogeneity from cell-to-cell variation within a given cell type.”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim. May combine two claims.

    Premisecitation

    The prefrontal cortex is involved in executive function and is an important substrate in the reward circuitry associated with development of alcohol dependence.

    “The PFC is involved in executive function and is an important substrate in the reward circuitry associated with development of alcohol dependence (19) .”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [19] Ball, 2011, Executive functions and prefrontal cortex: a matter of persistence?, Front. Syst. Neurosci. source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Premisecitation

    SLC1A3 is a glutamate uptake transporter that plays important roles in the neurocircuitry of addiction.

    “Interestingly, the top DEG in astrocytes was AC008957.2, a lncRNA that is antisense to the gene encoding SLC1A3 , a glutamate uptake transporter that plays important roles in the neurocircuitry of addiction (38)(39)(40) .”
    Quote in the paperNot a substantial claim0 of 3 sources checked
    • cites [38] Bell, 2016, Ethanol-associated changes in glutamate reward neurocircuitry: a minireview of clinical and preclinical genetic findings, Prog. Mol. Biol. Transl. Sci. source

      Not checked in the free run.

    • cites [39] Kashem, 2019, GLAST (GLutamate and ASpartate transporter) in human prefrontal cortex; interactome in healthy brains and the expression of GLAST in brains of chronic alcoholics, Neurochem. Int. source

      Not checked in the free run.

    • cites [40] Spencer, 2017, Glutamate transport: a new bench to bedside mechanism for treating drug abuse, Int. J. Neuropsychopharmacol. source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    FAS is known to be active in both astrocytes and endothelial cells.

    “For example, expression of FAS is lower in astrocytes relative to endothelial cells; however, FAS is known to be active in both astrocytes (29) and endothelial cells (30) .”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites [29] Choi, 1999, Fas ligand and Fas are expressed constitutively in human astrocytes and the expression increases with IL-1, IL-6, TNF-alpha, or IFN-gamma, J. Immunol. Baltim. Md 1950

      Not checked in the free run.

    • cites [30] Sata, 2000, Vascular endothelial cells and smooth muscle cells differ in expression of Fas and Fas ligand and in sensitivity to Fas ligand-induced cell death: implications for vascular disease and therapy, Arterioscler. Thromb. Vasc. Biol. source

      Not checked in the free run.

  • Classified as probably not a substantial claim.

    Premisecitation

    Bulk and scRNA-seq studies often exclude non-coding RNAs from their analyses.

    “Bulk and scRNA-seq studies often exclude non-coding RNAs from their analyses (3,8,35) .”
    Quote in the paperSubstantial claim0 of 3 sources checked
    • cites [3] Kapoor, 2019, Analysis of whole genome-transcriptomic organization in brain to identify genes associated with alcoholism, Transl. Psychiatry source

      Not checked in the free run.

    • cites [8] Mathys, 2019, Single-cell transcriptomic analysis of Alzheimer’s disease, Nature source

      Not checked in the free run.

    • cites [35] Luecken, 2019, Current best practices in single-cell RNA-seq analysis: a tutorial, Mol. Syst. Biol. source

      Not checked in the free run.

  • May combine two claims.

    Premisecitation

    SLC1A3 was downregulated with alcohol consumption in mouse astrocytes but upregulated in the human alcoholic brain.

    “SLC1A3 (also called “ GLAST ”) was downregulated with alcohol consumption in mouse astrocytes (20,21) but upregulated in the human alcoholic brain (39) .”
    Quote in the paperNot a substantial claim0 of 3 sources checked
    • cites [20] Erickson, 2018, Astrocyte-specific transcriptome responses to chronic ethanol consumption, Pharmacogenomics J. source

      Not checked in the free run.

    • cites [21] Erickson, 2019, Glial gene networks associated with alcohol dependence, Sci. Rep. source

      Not checked in the free run.

    • cites [39] Kashem, 2019, GLAST (GLutamate and ASpartate transporter) in human prefrontal cortex; interactome in healthy brains and the expression of GLAST in brains of chronic alcoholics, Neurochem. Int. source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Other studies have also found that microglial expression, in general, is particularly underrepresented in bulk transcriptomes, relative to that of other brain cell types.

    “Other studies have also found that microglial expression, in general, is particularly underrepresented in bulk transcriptomes, relative to that of other brain cell types (8,42) .”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites [8] Mathys, 2019, Single-cell transcriptomic analysis of Alzheimer’s disease, Nature source

      Not checked in the free run.

    • cites [42] Kelley, 2018, Variation among intact tissue samples reveals the core transcriptional features of human CNS cell classes, Nat. Neurosci. source

      Not checked in the free run.

  • May combine two claims.

    Study design and conductcitation

    A small sample size in a single cell genomics study does affect statistical power, but does not preclude the possibility of drawing meaningful inferences of cell type gene expression in the human brain.

    “A small sample size in a single cell genomics study does affect statistical power, but does not preclude the possibility of drawing meaningful inferences of cell type gene expression in the human brain (9,41) .”
    Quote in the paperSubstantial claim0 of 2 sources checked
    • cites [9] Del-Aguila, 2019, A single-nuclei RNA sequencing study of Mendelian and sporadic AD in the human brain, Alzheimers Res. Ther. source

      Not checked in the free run.

    • cites [41] Boldog, 2018, Transcriptomic and morphophysiological evidence for a specialized human cortical GABAergic cell type, Nat. Neurosci. source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S2 (checkable). May combine two claims.

    Premisecitation

    The importance of ncRNAs is becoming increasingly apparent, not only in alcohol dependence but in brain physiology in general.

    “However, the importance of ncRNAs is becoming increasingly apparent, not only in alcohol dependence (36) , but in brain physiology in general (37) , and these RNAs were therefore included in our data.”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites [36] Mayfield, 2017, Emerging roles for ncRNAs in alcohol use disorders, Alcohol Fayettev. N source

      Not checked in the free run.

    • cites [37] Zampa, 2019, Non-coding RNAs: the gatekeepers of neural network activity, Curr. Opin. Neurobiol. source

      Not checked in the free run.

19 of 19

  • The paper relies on this without support.

    Transcriptomic responses to chronic alcohol exposure or any other abused drug have not been studied at the cellular level in the human brain.

    “To our knowledge, transcriptomic responses to chronic alcohol exposure or any other abused drug have not been studied at the cellular level in the human brain.”
1 of 1

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Within the compendium, fourteen studies had control groups that included six or more samples.

    “Within our compendium, we identified a total of fourteen studies with control groups that included six or more samples5,6,15,49–59.”

    From Confronting false discoveries in single-cell differential expression (2021) · cites this paper as [55]

    The Results and Discussion section (page unavailable) says this study included four control donors, not six or more. The Conclusions section likewise describes seven donors in total: three with alcohol dependence and four controls. This source therefore cannot support its inclusion as a study meeting the stated control-group threshold; it does not address the compendium-wide count of fourteen. (LLM, conf=0.91)

    Checked by a reasoning model — may be wrong.

    Experimental — accuracy not yet measured

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

Each contradiction between two passages listed here was confirmed by an independent check.

  • One alcohol-dependent donor is listed as having DSM-IV alcohol abuse

    Minor

    The paper says alcohol dependence was diagnosed using DSM-IV criteria, but the first alcoholic donor (780) is listed under DSM-IV as having substance abuse, while the other two are listed as having substance dependence. This conflicts with treating all three as DSM-IV alcohol-dependent donors.

1 of 1

Cites

Flagged first, then by citations

Research works printed but not linked: 3

  1. Alcohol Facts and Statistics, 2011, Alcohol Facts and Statistics
  2. Customer Developed Protocols, Customer Developed Protocols
  3. Psychiatric Genomics Consortium Downloads, Psychiatric Genomics Consortium Downloads

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Related

Authors
Brenner, E., Tiwari, G. R., Kapoor, M., Liu, Y., Brock, A., & Mayfield, R. D.
Affiliations
  • The University of Texas at Austin (US)
  • Icahn School of Medicine at Mount Sinai (US)
  • Indiana University School of Medicine (US)
Corresponding author
Mayfield, R Dayne
ORCID
Venue
Human Molecular Genetics
Publisher
Oxford University Press (OUP)
Published
2020-03-06
Volume
29
Issue
7
Pages
1144-1153
ISSN
  • 0964-6906 (ISSN-L)
  • 1460-2083
DOI
10.1093/hmg/ddaa038
PMC
PMC7206851
OpenAlex
W3009993943
Cited by
118
References
51
Citations by year
2026: 12 · 2025: 25 · 2024: 20 · 2023: 32 · 2022: 13 · 2021: 14 · 2020: 1 · 2012: 1
FWCI
4.87
Type
journal article
Language
en
Open access
Licence
Locations
  • Human Molecular Genetics (publishedVersion)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
  • PubMed Central (publishedVersion)
  • PubMed (publishedVersion)
  • IUScholarWorks (Indiana University) (submittedVersion)
Funders
National Institutes of Health (U01-AA020926, R01-AA012404)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
  • Health Sciences › Medicine › Pathology and Forensic Medicine › Alcohol Consumption and Health Effects
  • Health Sciences › Medicine › Epidemiology › Substance Abuse Treatment and Outcomes
Keywords
alcoholism, prefrontal cortex, single-nucleus RNA sequencing, cell type-specific gene expression, neuroinflammation, astrocytes, oligodendrocytes, microglia, differentially expressed genes, non-coding RNA, brain transcriptome
MeSH terms
Ethanol, Alcoholism, Animals, Astrocytes, Brain, Humans, Prefrontal Cortex, Sequence Analysis, RNA, Microglia, Computational Biology, Gene Expression Profiling, Single-Cell Analysis, Transcriptome

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