Evidence map›Paper›PMID 38182777›Full record

ArticleNeuropsychopharmacology : official publication of the American College of Neuropsychopharmacology2024

Comparative rhythmic transcriptome profiling of human and mouse striatal subregions.

Kaitlyn A Petersen, Wei Zong, Lauren M Depoy, Madeline R Scott, Vaishnavi G Shankar, Jennifer N Burns, Allison J Cerwensky, Sam-Moon Kim, Kyle D Ketchesin, George C Tseng and 1 more

Open access · greenAbstract read
In one paragraph

Article in Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.8field-weighted citation impact, top 34% 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

5 citing papers in PubMed, 3 citations in OpenAlex.

  1. Review
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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

11 authors at 1 institution in 1 country.

Kaitlyn A PetersenDepartment of Psychiatry, Translational Neuroscience Program, Center for Neuroscience, University of Pittsburgh, Pittsburgh, PA, USA.
Wei ZongDepartment of Biostatistics, University of Pittsburgh, Pittsburgh, PA, USA.
Lauren M DepoyDepartment of Psychiatry, Translational Neuroscience Program, Center for Neuroscience, University of Pittsburgh, Pittsburgh, PA, USA.
Madeline R ScottDepartment of Psychiatry, Translational Neuroscience Program, Center for Neuroscience, University of Pittsburgh, Pittsburgh, PA, USA.ORCID http://orcid.org/0000-0002-2059-2256
Vaishnavi G ShankarDepartment of Psychiatry, Translational Neuroscience Program, Center for Neuroscience, University of Pittsburgh, Pittsburgh, PA, USA.
Jennifer N BurnsDepartment of Psychiatry, Translational Neuroscience Program, Center for Neuroscience, University of Pittsburgh, Pittsburgh, PA, USA.
Allison J CerwenskyDepartment of Psychiatry, Translational Neuroscience Program, Center for Neuroscience, University of Pittsburgh, Pittsburgh, PA, USA.
Sam-Moon KimDepartment of Psychiatry, Translational Neuroscience Program, Center for Neuroscience, University of Pittsburgh, Pittsburgh, PA, USA.
Kyle D KetchesinDepartment of Psychiatry, Translational Neuroscience Program, Center for Neuroscience, University of Pittsburgh, Pittsburgh, PA, USA.
George C TsengDepartment of Biostatistics, University of Pittsburgh, Pittsburgh, PA, USA.ORCID http://orcid.org/0000-0002-5447-1014
Colleen A McClungDepartment of Psychiatry, Translational Neuroscience Program, Center for Neuroscience, University of Pittsburgh, Pittsburgh, PA, USA. mcclungca@upmc.edu.ORCID http://orcid.org/0000-0003-4719-6197
University of Pittsburgh · US

Funding

Subject Management and BiobankingP50DA046346 · NIDA · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI Daniel J. Buysse, Colleen A McClung · 2020 to 2026
$23.4M
Predoctorial Training in Basic NeuroscienceT32NS007433 · NINDS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI MERINEY, STEPHEN D · 1998 to 2022
$8.0M
Identification of molecular rhythm changes in postmortem tissue from individuals with psychiatric illness. R01MH111601 · NIMH · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI Colleen A McClung, Marianne L Seney · 2018 to 2026
$5.5M
Role of NPAS2 in the nucleus accumbens in drug addictionR01DA039865 · NIDA · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI MCCLUNG, COLLEEN A · 2015 to 2024
$3.9M
Selective HDAC inhibition and therapeutic target genes: Identification of novel treatments for Bipolar DisorderR01MH106460 · NIMH · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI MCCLUNG, COLLEEN A · 2016 to 2024
$3.6M
Addiction-like behavior in models of mood disorders: role of CLOCK and NPAS2R01DA023988 · NIDA · UT SOUTHWESTERN MEDICAL CENTER · PI MCCLUNG, COLLEEN A · 2009 to 2013
$1.9M
Consequences of HDAC2 inhibition in VTA-NAc circuitryRF1MH106460 · NIMH · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI MCCLUNG, COLLEEN A · 2025 to 2025
$1.0M
Role of DNA methylation in regulating striatal molecular rhythm alterations in depressionK01MH128763 · NIMH · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI KETCHESIN, KYLE · 2021 to 2024
$680k
Circadian analysis of peripheral and brain samples in epilepsy patientsR21NS127064 · NINDS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI ABEL, TAYLOR JOHN, MCCLUNG, COLLEEN A · 2022 to 2023
$418k
NIDA NIH HHS P50 DA046346NIDA NIH HHS R01 DA023988NIDA NIH HHS R01 DA039865NIMH NIH HHS K01 MH128763NIMH NIH HHS R01 MH106460NIMH NIH HHS R01 MH111601NIMH NIH HHS RF1 MH106460NINDS NIH HHS R21 NS127064NINDS NIH HHS T32 NS007433
6 · The paper itself

Abstract

The human striatum can be subdivided into the caudate, putamen, and nucleus accumbens (NAc). In mice, this roughly corresponds to the dorsal medial striatum (DMS), dorsal lateral striatum (DLS), and ventral striatum (NAc). Each of these structures have some overlapping and distinct functions related to motor control, cognitive processing, motivation, and reward. Previously, we used a "time-of-death" approach to identify diurnal rhythms in RNA transcripts in these three human striatal subregions. Here, we identify molecular rhythms across similar striatal subregions collected from C57BL/6J mice across 6 times of day and compare results to the human striatum. Pathway analysis indicates a large degree of overlap between species in rhythmic transcripts involved in processes like cellular stress, energy metabolism, and translation. Notably, a striking finding in humans is that small nucleolar RNAs (snoRNAs) and long non-coding RNAs (lncRNAs) are among the most highly rhythmic transcripts in the NAc and this is not conserved in mice, suggesting the rhythmicity of RNA processing in this region could be uniquely human. Furthermore, the peak timing of overlapping rhythmic genes is altered between species, but not consistently in one direction. Taken together, these studies reveal conserved as well as distinct transcriptome rhythms across the human and mouse striatum and are an important step in understanding the normal function of diurnal rhythms in humans and model organisms in these regions and how disruption could lead to pathology.

Indexed as

Corpus StriatumVentral StriatumAnimalsGene Expression ProfilingHumansMiceMice, Inbred C57BLNucleus AccumbensTranscriptome

Identifiers

PMID38182777
PMCPMC10948754
OpenAlexW4390619156

What OpenQuestion holds

Textmetadata
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Registered trials

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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.