Evidence map›Paper›PMID 26314700›Full record

ArticleClinical and translational science2015

An Untargeted Metabolomics Analysis of Antipsychotic Use in Bipolar Disorder.

Kyle J Burghardt, Simon J Evans, Kristen M Wiese, Vicki L Ellingrod

Open access · bronzeAbstract readComparative Study
In one paragraph

Article in Clinical and translational science, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed, 1 pooled it
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

24 citing papers in PubMed, 1 synthesis or guideline pooled it, 31 citations in OpenAlex.

  1. Pooled it
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  19. Skeletal muscle DNA methylation modifications and psychopharmacologic treatment in bipolar disorder.European neuropsychopharmacology : the journal of the European College of Neuropsychopharmacology · 2019
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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

4 authors at 2 institutions in 1 country.

Kyle J BurghardtEugene Applebaum College of Pharmacy and Health Sciences, Wayne State University, Detroit, Michigan, USA.
Simon J EvansDepartment of Psychiatry, University of Michigan, Ann Arbor, Michigan, USA.
Kristen M WieseCollege of Pharmacy, University of Michigan, Ann Arbor, Michigan, USA.
Vicki L EllingrodDepartment of Psychiatry, University of Michigan, Ann Arbor, Michigan, USA.
University of Michigan · USEugene Applebaum College of Pharmacy and Health Sciences · US

Funding

MICHIGAN INSTITUTE FOR CLINICAL AND HEALTH RESEARCH (MICHR) (UL1): (BPCA)UL1RR024986 · NCRR · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI SHANLEY, THOMAS P. · 2007 to 2011
$51.2M
Michigan Institute for Clinical and Health Research (MCHR)UL1TR000433 · NCATS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI MASHOUR, GEORGE ALEXANDER · 2012 to 2016
$49.9M
PUBLIC HEALTH DEMONSTRATIONP60DK020572 · NIDDK · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI MYERS, MARTIN G · 1985 to 2012
$26.5M
Regional Pilot And Feasibility Study Grants ProgramP30DK020572 · NIDDK · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Mehboob A Hussain · 2013 to 2026
$24.3M
Pilot and Feasibility (P and F) ProgramP30DK089503 · NIDDK · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Joyce Lee · 2010 to 2026
$20.3M
Research BaseP30DK092926 · NIDDK · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI MARY ELLEN MICHELE HEISLER, ADESUWA B OLOMU · 2011 to 2026
$10.0M
Folate Pharmacogenomics and Risk of Atypical Antipsychtoic Metabolic Side EffectsR01MH082784 · NIMH · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI ELLINGROD, VICKI L · 2008 to 2017
$4.0M
NCATS NIH HHS UL1 TR000433NCATS NIH HHS UL1TR000433NCRR NIH HHS UL1 RR024986NCRR NIH HHS UL1RR024986NIDDK NIH HHS P30 DK020572NIDDK NIH HHS P30DK020572NIDDK NIH HHS P30 DK089503NIDDK NIH HHS P30 DK092926NIDDK NIH HHS P30DK092926NIDDK NIH HHS P60 DK020572NIMH NIH HHS R01 MH082784
6 · The paper itself

Abstract

backgroundSecond generation antipsychotic (SGA) use in bipolar disorder is common and has proven effective in short-term trials. There continues to be a lack of understanding of the mechanisms underlying many of their positive and negative effects in bipolar disorder. This study aimed to describe the metabolite profiles of bipolar subjects treated with SGAs by comparing to metabolite profiles of bipolar subjects treated with lithium, and schizophrenia subjects treated with SGAs.

methodsCross-sectional, fasting untargeted serum metabolomic profiling was conducted in 82 subjects diagnosed with bipolar I disorder (n = 30 on SGAs and n = 32 on lithium) or schizophrenia (n = 20). Metabolomic profiles of bipolar subjects treated with SGAs were compared to bipolar subjects treated with lithium and schizophrenia subjects treated with SGAs using multivariate methods.

resultsPartial lease square discriminant analysis (PLS-DA) plots showed separation between bipolar subjects treated with SGAs, bipolar subjects treated with lithium, or schizophrenia subjects treated with SGAs. Top influential metabolite features were associated with several pathways including that of polyunsaturated fatty acids, pyruvate, glucose, and branched chain amino acids.

conclusionsThe findings from this study require further validation in pre- and posttreated bipolar and schizophrenia subjects, but suggest that the pharmacometabolome may be diagnosis specific.

Indexed as

MetabolomicsAdultAntipsychotic AgentsBiomarkersBipolar DisorderChi-Square DistributionCross-Sectional StudiesDiscriminant AnalysisFemaleHumansLeast-Squares AnalysisLithium CompoundsMaleMiddle AgedMultivariate AnalysisSchizophreniaAntipsychotic AgentsBiomarkersLithium Compoundsantipsychoticatypicalbipolarmetabolomicsuntargeted

Identifiers

PMID26314700
PMCPMC4626284
OpenAlexW1918296210

What OpenQuestion holds

Textmetadata
LicenceTDM
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.