Evidence map›Paper›PMID 42078895›Full record

ArticleResearch square2026

Conserved Cell-Type-Specific Transcriptomic Networks and Regulatory Programs Underlie Alcohol Dependence Across Mouse and Human.

Nihal A Salem, Anna S Warden, Amanda J Roberts, Marisa Roberto, R Dayne Mayfield

Abstract readPreprint
In one paragraph

Article in Research square, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Nihal A SalemWaggoner Center for Alcohol and Addiction Research, The University of Texas at Austin, Austin, TX 78712, USA.ORCID 0000-0001-9973-6437
Anna S WardenWaggoner Center for Alcohol and Addiction Research, The University of Texas at Austin, Austin, TX 78712, USA.
Amanda J RobertsAnimal Models Core Facility, The Scripps Research Institute, La Jolla, CA, 92073, USA.
Marisa RobertoDepartment of Translational Medicine, The Scripps Research Institute, La Jolla, CA, 92073, USA.ORCID 0000-0003-0729-3961
R Dayne MayfieldWaggoner Center for Alcohol and Addiction Research, The University of Texas at Austin, Austin, TX 78712, USA.ORCID 0000-0002-8045-1789

Funding

Viral Vector CoreP60AA006420 · NIAAA · SCRIPPS RESEARCH INSTITUTE, THE · PI AMANDA J ROBERTS · 2003 to 2026
$46.3M
Electrophysiology of alcohol in extended amygdelaU01AA013498 · NIAAA · SCRIPPS RESEARCH INSTITUTE, THE · PI MARISA ROBERTO · 2001 to 2026
$12.6M
GENE EXPRESSION IN THE HUMAN ALCOHOLIC BRAINR01AA012404 · NIAAA · UNIVERSITY OF TEXAS AUSTIN · PI MAYFIELD, ROY DAYNE · 2000 to 2025
$10.7M
Next Generation Sequencing of Human Alcoholic BrainU01AA020926 · NIAAA · UNIVERSITY OF TEXAS AT AUSTIN · PI Roy DAYNE MAYFIELD · 2011 to 2026
$6.7M
Gene-environment interaction: the brain CRF system in alcohol preferring msP ratsR37AA017447 · NIAAA · SCRIPPS RESEARCH INSTITUTE, THE · PI ROBERTO, MARISA · 2016 to 2025
$3.7M
Synaptic Mechanisms underlying sex-differences in alcohol use disorderR01AA029841 · NIAAA · SCRIPPS RESEARCH INSTITUTE, THE · PI MARISA ROBERTO · 2022 to 2026
$2.0M
Gene-environment interaction: the brain CRF system in alcohol preferring msP ratsR01AA017447 · NIAAA · SCRIPPS RESEARCH INSTITUTE, THE · PI ROBERTO, MARISA · 2009 to 2013
$1.8M
From FASD to AUDs: Strategies for Preventing Alcohol AddictionsK00AA029955 · NIAAA · UNIVERSITY OF TEXAS AT AUSTIN · PI SALEM, NIHAL A · 2021 to 2024
$350k
Dysregulated cell-type specific gene regulatory networks underlying alcohol dependenceK99AA032053 · NIAAA · UNIVERSITY OF TEXAS AT AUSTIN · PI Nihal A Salem · 2025 to 2026
$300k
NIAAA NIH HHS K00 AA029955NIAAA NIH HHS K99 AA032053NIAAA NIH HHS P60 AA006420NIAAA NIH HHS R01 AA012404NIAAA NIH HHS R01 AA017447NIAAA NIH HHS R01 AA029841NIAAA NIH HHS R37 AA017447NIAAA NIH HHS U01 AA013498NIAAA NIH HHS U01 AA020926
6 · The paper itself

Abstract

Alcohol use disorder (AUD) is a complex polygenic disease. Rodent models of alcohol dependence have been instrumental in modeling various aspects of dependence. Single-nucleus transcriptomics has enabled the profiling of cell-type-specific changes in gene expression in both human AUD and animal models. In this study, we identified shared dysregulated transcriptomic networks (TN), comprising gene co-expression modules and gene regulatory networks (GRNs) in a mouse model of alcohol dependence and individuals with AUD. Through cell-type-specific TN analysis, we identified translationally relevant, conserved dependence dysregulated molecular signatures. We identified conserved dependence-upregulated gene co-expression modules in astrocytes and oligodendrocytes, with hub genes Slc1a3 and Pde4b, respectively. These genes are linked to alcohol dependence mechanisms, such as glutamate signaling, a well-established target of alcohol's effects, and PDE4, whose inhibition has been shown to reduce alcohol intake in preclinical and clinical studies. We then integrated publicly available human and mouse GRN data to identify upstream regulators of alcohol-dysregulated gene signatures in each cell type. This approach revealed a set of transcription factors (TFs), including Mef2a, Mef2c, Jund, Nr3c1, and Zeb1, that were upstream of most dysregulated genes in both the mouse and human datasets and have established relevance to addiction biology, representing promising targets for translational research. Collectively, these findings demonstrate the utility of cross-species, cell-type-specific network analysis for uncovering conserved molecular mechanisms in alcohol dependence. The identification of shared dysregulated networks, cell type homology, and upstream regulators provides a foundation for developing translationally relevant targeting strategies that can be tested in animal models.

Identifiers

PMID42078895
PMCPMC13131876

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.