Evidence map›Paper›PMID 33987257›Full record

ArticleAnnals of translational medicine2021

Comprehensive serum metabolic and proteomic characterization on cognitive dysfunction in Parkinson's disease.

Na Zhang, Chuanxi Tang, Qiong Ma, Wei Wang, Mingyu Shi, Xiaoyu Zhou, Fangfang Chen, Chengcheng Ma, Xue Li, Gang Chen and 1 more

Open access · diamondAbstract read
In one paragraph

Article in Annals of translational medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 1 pooled it
1.1field-weighted citation impact, top 25% 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

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

  1. Pooled it
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  3. Longitudinal untargeted metabolomics of cognitive impairment in Parkinson's disease.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026
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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 2 institutions in 1 country.

Na ZhangDepartment of Neurobiology, Xuzhou Key Laboratory of Neurobiology, Xuzhou Medical University, Xuzhou, China.
Chuanxi TangDepartment of Neurobiology, Xuzhou Key Laboratory of Neurobiology, Xuzhou Medical University, Xuzhou, China.
Qiong MaSchool of Nursing, Xuzhou Medical University, Xuzhou, China.
Wei WangDepartment of Neurobiology, Xuzhou Key Laboratory of Neurobiology, Xuzhou Medical University, Xuzhou, China.
Mingyu ShiDepartment of Neurobiology, Xuzhou Key Laboratory of Neurobiology, Xuzhou Medical University, Xuzhou, China.
Xiaoyu ZhouDepartment of Neurobiology, Xuzhou Key Laboratory of Neurobiology, Xuzhou Medical University, Xuzhou, China.
Fangfang ChenDepartment of Neurology, Shuyang Hospital Affiliated to Xuzhou Medical University, Shuyang, China.
Chengcheng MaDepartment of Neurobiology, Xuzhou Key Laboratory of Neurobiology, Xuzhou Medical University, Xuzhou, China.
Xue LiSchool of Nursing, Xuzhou Medical University, Xuzhou, China.
Gang ChenDepartment of Neurobiology, Xuzhou Key Laboratory of Neurobiology, Xuzhou Medical University, Xuzhou, China.
Dianshuai GaoDepartment of Neurobiology, Xuzhou Key Laboratory of Neurobiology, Xuzhou Medical University, Xuzhou, China.
Xuzhou Medical College · CNXuzhou University of Technology · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGiven the increased incidence of Parkinson's disease (PD) and the lack of accurate early diagnosis of PD with cognitive impairment (PD-CI), we compared the serum metabolomes and proteomes of 26 patients with PD without cognitive impairment (PD-N) and 31 patients with PD-CI by combining grade-dependent proteomics and metabolomics analyses.

methodsLogistic and linear regression analyses were performed for differential metabolic indicators, cognition, and clinical diagnosis. Ingenuity pathway analysis (IPA) was used to identify metabolites linked to different pathways. Bioinformatics revealed 16 differentially expressed proteins and 32 metabolites.

resultsThe positive metabolic indicators related to the differential proteins were one sphingolipid, five phosphatidylcholines, and five long-chain fatty acids. The obtained metabolic and proteomics IPA network highlighted the central term of this network was inflammation and abnormal lipid metabolism which are prominent in PD-CI. There was a strong negative correlation between the Mini-Mental State Examination (MMSE)score and LPC (18:1). The receiver operating characteristic (ROC) of LPC (18:1) for PD-N and PD-CI showed that the area under the curve (AUC) value was 0.660 (P=0.039).

conclusionsIn conclusion, serum LPC (18:1) is inversely linked to cognition in PD and presented its potential clinical value in distinguishing the presence or absence of cognitive impairment in PD. The deeper implication of our discovery indicates abnormal lipid metabolism is associated with changes of cognitive status and suggests the potential for possibility of immune system- inflammatory involvement.

Indexed as

cognitive functionlong chain fatty acid metabolismmetabolomicsParkinson’s disease (PD)proteomics

Identifiers

PMID33987257
PMCPMC8105844
OpenAlexW3135395873

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.