Evidence map›Paper›PMID 31022588›Full record

ArticleJournal of psychiatric research2019

Analyzing DNA methylation patterns in subjects diagnosed with schizophrenia using machine learning methods.

Behrooz Torabi Moghadam, Mitra Etemadikhah, Grazyna Rajkowska, Craig Stockmeier, Manfred Grabherr, Jan Komorowski, Lars Feuk, Eva Lindholm Carlström

Open access · greenAbstract read
In one paragraph

Article in Journal of psychiatric research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
1.0field-weighted citation impact, top 24% 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

8 citing papers in PubMed, 1 synthesis or guideline pooled it, 17 citations in OpenAlex.

  1. Pooled it
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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

8 authors at 2 institutions in 3 countries.

Behrooz Torabi MoghadamDepartment of Cell and Molecular Biology, Computational and Systems Biology, Uppsala University, Uppsala, Sweden.
Mitra EtemadikhahDepartment of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala University, Uppsala, Sweden.
Grazyna RajkowskaDepartment of Psychiatry and Human Behavior, University of Mississippi Medical Center, Jackson, MS, USA.
Craig StockmeierDepartment of Psychiatry and Human Behavior, University of Mississippi Medical Center, Jackson, MS, USA.
Manfred GrabherrDepartment of Medical Biochemistry and Microbiology/BILS, Genomics, Uppsala University, Uppsala, Sweden.
Jan KomorowskiDepartment of Cell and Molecular Biology, Computational and Systems Biology, Uppsala University, Uppsala, Sweden; Institute of Computer Science, Polish Academy of Sciences, Warsaw, 01248, Poland.
Lars FeukDepartment of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala University, Uppsala, Sweden. Electronic address: lars.feuk@igp.uu.se.
Eva Lindholm CarlströmDepartment of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala University, Uppsala, Sweden. Electronic address: eva.lindholm@igp.uu.se.
Uppsala University · SEJackson Memorial Hospital · US

Funding

A Natonal Resource for Postmortem Brain ResearchR24MH068855 · NIMH · MC LEAN HOSPITAL (BELMONT, MA) · PI BENES, FRANCINE M. · 2003 to 2012
$14.8M
Center for Psychiatric NeuroscienceP30GM103328 · NIGMS · UNIVERSITY OF MISSISSIPPI MED CTR · PI STOCKMEIER, CRAIG ALLEN · 2013 to 2017
$5.5M
NIGMS NIH HHS P30 GM103328NIMH NIH HHS R24 MH068855
6 · The paper itself

Abstract

Schizophrenia is a common mental disorder with high heritability. It is genetically complex and to date more than a hundred risk loci have been identified. Association of environmental factors and schizophrenia has also been reported, while epigenetic analyses have yielded ambiguous and sometimes conflicting results. Here, we analyzed fresh frozen post-mortem brain tissue from a cohort of 73 subjects diagnosed with schizophrenia and 52 control samples, using the Illumina Infinium HumanMethylation450 Bead Chip, to investigate genome-wide DNA methylation patterns in the two groups. Analysis of differential methylation was performed with the Bioconductor Minfi package and modern machine-learning and visualization techniques, which were shown previously to be successful in detecting and highlighting differentially methylated patterns in case-control studies. In this dataset, however, these methods did not uncover any significant signals discerning the patient group and healthy controls, suggesting that if there are methylation changes associated with schizophrenia, they are heterogeneous and complex with small effect.

Indexed as

Machine LearningBrainCase-Control StudiesDNA MethylationFemaleGene Expression RegulationHumansMaleMiddle AgedSchizophreniaClassificationClusteringDNA methylationMachine learningSchizophrenia

Identifiers

PMID31022588
PMCPMC7416578
OpenAlexW2935463731

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.