Evidence map›Paper›PMID 34462306›Full record

ArticleThe Journal of neuroscience : the official journal of the Society for Neuroscience2021

Addiction-Associated Genetic Variants Implicate Brain Cell Type- and Region-Specific Cis-Regulatory Elements in Addiction Neurobiology.

Chaitanya Srinivasan, BaDoi N Phan, Alyssa J Lawler, Easwaran Ramamurthy, Michael Kleyman, Ashley R Brown, Irene M Kaplow, Morgan E Wirthlin, Andreas R Pfenning

Open access · bronzeAbstract read
In one paragraph

Article in The Journal of neuroscience : the official journal of the Society for Neuroscience, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
5.5field-weighted citation impact, top 4% of its field
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

21 citing papers in PubMed, 36 citations in OpenAlex.

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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

9 authors at 2 institutions in 1 country.

Chaitanya SrinivasanComputational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213.ORCID 0000-0002-1487-541X
BaDoi N PhanComputational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213.ORCID 0000-0001-6331-5980
Alyssa J LawlerDepartment of Biological Sciences, Mellon College of Science, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213.ORCID 0000-0002-2151-5164
Easwaran RamamurthyComputational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213.ORCID 0000-0002-2439-0600
Michael KleymanComputational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213.
Ashley R BrownComputational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213.
Irene M KaplowComputational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213.
Morgan E WirthlinComputational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213.
Andreas R PfenningComputational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213 apfenning@cmu.edu.
Carnegie Mellon University · USUniversity of Pittsburgh · US

Funding

TRAINING PROGRAM FOR MD/PHD STUDENTST32GM008208 · NIGMS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI STEINMAN, RICHARD A · 1987 to 2021
$15.4M
Interpreting the regulatory mechanisms underlying the predisposition to substance use disordersDP1DA046585 · NIDA · CARNEGIE-MELLON UNIVERSITY · PI PFENNING, ANDREAS ROBERT · 2018 to 2022
$2.4M
Integrating primate-rodent cell types and epigenomics to identify conservation in substance addictionF30DA053020 · NIDA · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI PHAN, BADOI NGUYEN · 2021 to 2024
$204k
NIDA NIH HHS DP1 DA046585NIDA NIH HHS F30 DA053020NIGMS NIH HHS T32 GM008208
6 · The paper itself

Abstract

Recent large genome-wide association studies have identified multiple confident risk loci linked to addiction-associated behavioral traits. Most genetic variants linked to addiction-associated traits lie in noncoding regions of the genome, likely disrupting

Indexed as

AnimalsBehavior, AddictiveBrainDatabases, GeneticFemaleGenetic Predisposition to DiseaseGenetic VariationHumansMaleMiceMice, Inbred C57BLMice, TransgenicNeuronsQuantitative Trait LociRegulatory Elements, Transcriptionaladdictiondeep learningepigeneticsgenomicsmachine learningneural circuits

Identifiers

PMID34462306
PMCPMC8549541
OpenAlexW3197410022

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.