Evidence map›Paper›PMID 37143779›Full record

ArticleFrontiers in psychiatry2023

Associations between prefrontal PI (16:0/20:4) lipid,

Fumito Sano, Kenji Kikushima, Seico Benner, Lili Xu, Tomoaki Kahyo, Hidenori Yamasue, Mitsutoshi Setou

Abstract read
In one paragraph

Article in Frontiers in psychiatry, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

7 authors.

Fumito SanoDepartment of Cellular and Molecular Anatomy, Hamamatsu University School of Medicine, Hamamatsu, Japan.
Kenji KikushimaDepartment of Cellular and Molecular Anatomy, Hamamatsu University School of Medicine, Hamamatsu, Japan.
Seico BennerDepartment of Psychiatry, Hamamatsu University School of Medicine, Hamamatsu, Japan.
Lili XuDepartment of Cellular and Molecular Anatomy, Hamamatsu University School of Medicine, Hamamatsu, Japan.
Tomoaki KahyoDepartment of Cellular and Molecular Anatomy, Hamamatsu University School of Medicine, Hamamatsu, Japan.
Hidenori YamasueDepartment of Psychiatry, Hamamatsu University School of Medicine, Hamamatsu, Japan.
Mitsutoshi SetouDepartment of Cellular and Molecular Anatomy, Hamamatsu University School of Medicine, Hamamatsu, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Though various mechanisms have been proposed for the pathophysiology of schizophrenia, the full extent of these mechanisms remains unclear, and little is known about the relationships among them. We carried out trans-omics analyses by comparing the results of the previously reported lipidomics, transcriptomics, and proteomics analyses; all of these studies used common post-mortem brain samples. Methods: We collected the data from three aforementioned omics studies on 6 common post-mortem samples (3 schizophrenia patients and 3 controls), and analyzed them as a whole group sample. Three correlation analyses were performed for each of the two of three omics studies in these samples. In order to discuss the strength of the correlations in a limited sample size, the Results: The following three factors were strongly correlated with each other: the lipid level of phosphatidylinositol (PI) (16:0/20:4), the amount of Conclusion: The current results suggest that these three factors may provide new clues to elucidate the relationships among the candidate mechanisms of schizophrenia, and support the potential of trans-omics analyses as a new analytical method.

Indexed as

lipidomicspostmortem brainproteomicsschizophreniatranscriptomicstrans-omics

Identifiers

PMID37143779
PMCPMC10151580

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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.