Evidence map›Paper›PMID 36033628›Full record

ArticleFrontiers in neuroscience2022

Serum metabolomic characterization of PLA2G6-associated dystonia-parkinsonism: A case-control biomarker study.

Chen Chen, Min-Min Lou, Yi-Min Sun, Fang Luo, Feng-Tao Liu, Su-Shan Luo, Wen-Yuan Wang, Jian Wang

Open access · goldAbstract read
In one paragraph

Article in Frontiers in neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.4field-weighted citation impact, top 40% 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

3 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. Common genetic risk for Parkinson's disease and dysfunction of the endo-lysosomal system.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2024
    Review
  3. Case Report: A case ofFrontiers in neuroscience · 2022
    Article
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 4 institutions in 1 country.

Chen ChenState Key Laboratory of Medical Neurobiology, Department of Neurology and National Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, China.
Min-Min LouInterdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences - University of Chinese Academy of Sciences, Shanghai, China.
Yi-Min SunState Key Laboratory of Medical Neurobiology, Department of Neurology and National Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, China.
Fang LuoInterdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences - University of Chinese Academy of Sciences, Shanghai, China.
Feng-Tao LiuState Key Laboratory of Medical Neurobiology, Department of Neurology and National Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, China.
Su-Shan LuoState Key Laboratory of Medical Neurobiology, Department of Neurology and National Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, China.
Wen-Yuan WangInterdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences - University of Chinese Academy of Sciences, Shanghai, China.
Jian WangState Key Laboratory of Medical Neurobiology, Department of Neurology and National Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, China.
Huashan Hospital · CNShanghai Institute of Organic Chemistry · CNFudan University · CNUniversity of Chinese Academy of Sciences · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Phospholipase A2 Group VI (PLA2G6), encoding calcium-independent phospholipase A Design: This case-control biomarker study tested nine patients diagnosed with PARK14. Eight age and sex-matched healthy subjects were recruited as controls. To evaluate the influence of single heterozygous mutation, we enrolled eight healthy one-degree family members of patients with PARK14, two patients diagnosed with early-onset Parkinson's disease (EOPD) who had only a single heterozygous PLA2G6 mutation, and one patient with EOPD without any known pathogenic mutation. Methods: The diagnosis of PARK14 was made according to the diagnostic criteria for Parkinson's disease (PD) and confirmed by genetic testing. To study the serum metabolic features, we analyzed participants' serum using UHPLC-QTOF/MS analysis, a well-established technology. Results: We quantified 50 compounds of metabolites from the serum of all the study subjects. Metabolites alterations in serum had good predictive accuracy for PARK14 diagnosis (AUC 0.903) and advanced stage in PARK14 (AUC 0.944). Of the 24 metabolites that changed significantly in patients' serum, eight related to lipid metabolism. Oleic acid and xanthine were associated with MMSE scores. Xanthine, L-histidine, and phenol correlated with UPDRS-III scores. Oleic acid and 1-oleoyl-L-alpha-lysophosphatidic acid could also predict the subclass of the more advanced stage in the PLA2G6 Group in ROC models. Conclusion: The significantly altered metabolites can be used to differentiate PLA2G6 pathogenic mutations and predict disease severity. Patients with PLA2G6 mutations had elevated lipid compounds in C18:1 and C16:0 groups. The alteration of lipid metabolism might be the key intermediate process in PLA2G6-related disease that needs further investigation.

Indexed as

early-onset parkinsonismlong chain fatty acidsmetabolomicsPLA2G6serum biomarkers

Identifiers

PMID36033628
PMCPMC9406281
OpenAlexW4290802467

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.