Evidence map›Paper›PMID 28977551›Full record

ArticleNucleic acids research2018

AAgMarker 1.0: a resource of serological autoantigen biomarkers for clinical diagnosis and prognosis of various human diseases.

Jianbo Pan, Sheng Liu, Heng Zhu, Jiang Qian

Abstract readComparative Study
In one paragraph

Article in Nucleic acids research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

4 authors.

Jianbo PanDepartment of Ophthalmology, Johns Hopkins School of Medicine, Baltimore, MD 21205, USA.
Sheng LiuDepartment of Ophthalmology, Johns Hopkins School of Medicine, Baltimore, MD 21205, USA.
Heng ZhuDepartment of Pharmacology and Molecular Sciences, Johns Hopkins School of Medicine, Baltimore, MD 21205, USA.
Jiang QianDepartment of Ophthalmology, Johns Hopkins School of Medicine, Baltimore, MD 21205, USA.

Funding

Differential Regulatory Networks in Disease: Application to Macular DegenerationR01EY024580 · NEI · JOHNS HOPKINS UNIVERSITY · PI QIAN, JIANG · 2014 to 2017
$1.6M
Epigenetics-mediated transcription regulation in mammalsR01GM111514 · NIGMS · JOHNS HOPKINS UNIVERSITY · PI QIAN, JIANG, ZHOU, FENGQUAN · 2014 to 2017
$1.4M
NEI NIH HHS R01 EY024580NIGMS NIH HHS R01 GM111514
6 · The paper itself

Abstract

Autoantibodies are produced to target an individual's own antigens (e.g. proteins). They can trigger autoimmune responses and inflammation, and thus, cause many types of diseases. Many high-throughput autoantibody profiling projects have been reported for unbiased identification of serological autoantigen-based biomarkers. However, a lack of centralized data portal for these published assays has been a major obstacle to further data mining and cross-evaluate the quality of these datasets generated from different diseases. Here, we introduce a user-friendly database, AAgMarker 1.0, which collects many published raw datasets obtained from serum profiling assays on the proteome microarrays, and provides a toolbox for mining these data. The current version of AAgMarker 1.0 contains 854 serum samples, involving 136 092 proteins. A total of 7803 (4470 non-redundant) candidate autoantigen biomarkers were identified and collected for 12 diseases, such as Alzheimer's disease, Bechet's disease and Parkinson's disease. Seven statistical parameters are introduced to quantitatively assess these biomarkers. Users can retrieve, analyse and compare the datasets through basic search, advanced search and browse. These biomarkers are also downloadable by disease terms. The AAgMarker 1.0 is now freely accessible at http://bioinfo.wilmer.jhu.edu/AAgMarker/. We believe this database will be a valuable resource for the community of both biomedical and clinical research.

Indexed as

Databases, FactualAutoantibodiesAutoantigensBiomarkersBlood ProteinsData MiningDatasets as TopicHumansPrognosisProtein Array AnalysisProteomeSensitivity and SpecificityUser-Computer InterfaceAutoantibodiesAutoantigensBiomarkersBlood ProteinsProteome

Identifiers

PMID28977551
PMCPMC5753245

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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.