Evidence map›Paper›PMID 34945719›Full record

ArticleJournal of personalized medicine2021

A Comprehensive Evaluation of Cross-Omics Blood-Based Biomarkers for Neuropsychiatric Disorders.

Weichen Song, Weidi Wang, Zhe Liu, Wenxiang Cai, Shunying Yu, Min Zhao, Guan Ning Lin

Open access · goldAbstract read
In one paragraph

Article in Journal of personalized medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.3field-weighted citation impact, top 55% 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

5 citing papers in PubMed, 7 citations in OpenAlex.

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  5. 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 at 2 institutions in 1 country.

Weichen SongSchool of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200030, China.ORCID 0000-0003-3197-6236
Weidi WangSchool of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200030, China.ORCID 0000-0002-6312-0689
Zhe LiuSchool of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200030, China.
Wenxiang CaiSchool of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200030, China.
Shunying YuShanghai Key Laboratory of Psychotic Disorders, Shanghai 200030, China.ORCID 0000-0001-7929-204X
Min ZhaoShanghai Key Laboratory of Psychotic Disorders, Shanghai 200030, China.
Guan Ning LinSchool of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200030, China.ORCID 0000-0001-9496-0149
Shanghai Jiao Tong University · CNShanghai Mental Health Center · CN

Funding

National Natural Science Foundation of China 81971257National Natural Science Foundation of China 81971292
6 · The paper itself

Abstract

The identification of peripheral multi-omics biomarkers of brain disorders has long been hindered by insufficient sample size and confounder influence. This study aimed to compare biomarker potential for different molecules and diseases. We leveraged summary statistics of five blood quantitative trait loci studies (N = 1980 to 22,609) and genome-wide association studies (N = 9725 to 500,199) from 14 different brain disorders, such as Schizophrenia (SCZ) and Alzheimer's Disease (AD). We applied summary-based and two-sample Mendelian Randomization to estimate the associations between blood molecules and brain disorders. We identified 524 RNA, 807 methylation sites, 29 proteins, seven cytokines, and 22 metabolites having a significant association with at least one of 14 brain disorders. Simulation analyses indicated that a cross-omics combination of biomarkers had better performance for most disorders, and different disorders could associate with different omics. We identified an 11-methylation-site model for SCZ diagnosis (Area Under Curve, AUC = 0.74) by analyzing selected candidate markers in published datasets (total N = 6098). Moreover, we constructed an 18-methylation-sites model that could predict the prognosis of elders with mild cognitive impairment (hazard ratio = 2.32). We provided an association landscape between blood cross-omic biomarkers and 14 brain disorders as well as a suggestion guide for future clinical discovery and application.

Indexed as

diagnostic modelmendelian randomizationneuropsychiatric disorderperipheral biomarkerprognosis

Identifiers

PMID34945719
PMCPMC8703948
OpenAlexW3216525813

What OpenQuestion holds

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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.