Evidence map›Paper›PMID 29849043›Full record

ArticleScientific reports2018

Combining micro-RNA and protein sequencing to detect robust biomarkers for Graves' disease and orbitopathy.

Lei Zhang, Giulia Masetti, Giuseppe Colucci, Mario Salvi, Danila Covelli, Anja Eckstein, Ulrike Kaiser, Mohd Shazli Draman, Ilaria Muller, Marian Ludgate and 2 more

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed, 5 pooled it
1.7field-weighted citation impact, top 12% 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

30 citing papers in PubMed, 5 syntheses or guidelines pooled it, 49 citations in OpenAlex.

  1. Pooled it
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  6. Article
  7. Article
  8. Article
  9. Review
  10. Applications of artificial intelligence and bioinformatics methodologies in the analysis of ocular biofluid markers: a scoping review.Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie · 2024
    Article
  11. Review
  12. Article
  13. Molecular Biomarkers in Thyroid Eye Disease: A Literature Review.Ophthalmic plastic and reconstructive surgery · 2023
    Review
  14. Article
  15. Article
  16. Article
  17. Article
  18. Novel inflammatory biomarkers in thyroid eye disease.European journal of endocrinology · 2022
    Article
  19. Review
  20. 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

12 authors at 6 institutions in 3 countries.

Lei ZhangCardiff University, School of Medicine, Division of Infection & Immunity, Cardiff, UK.
Giulia MasettiCardiff University, School of Medicine, Division of Infection & Immunity, Cardiff, UK.
Giuseppe ColucciUniversità degli Studi di Milano, Fondazione Ca' Granda IRCCS, Department of Clinical Sciences and Community Health, Milan, Italy.
Mario SalviUniversità degli Studi di Milano, Fondazione Ca' Granda IRCCS, Department of Clinical Sciences and Community Health, Milan, Italy.ORCID 0000-0002-0276-0367
Danila CovelliUniversità degli Studi di Milano, Fondazione Ca' Granda IRCCS, Department of Clinical Sciences and Community Health, Milan, Italy.
Anja EcksteinUniversity Hospital Essen/University of Duisburg-Essen, Department of Ophthalmology, Essen, Germany.
Ulrike KaiserUniversity Hospital Essen/University of Duisburg-Essen, Department of Ophthalmology, Essen, Germany.
Mohd Shazli DramanCardiff University, School of Medicine, Division of Infection & Immunity, Cardiff, UK.ORCID 0000-0003-0144-8467
Ilaria MullerCardiff University, School of Medicine, Division of Infection & Immunity, Cardiff, UK.ORCID 0000-0003-2926-0722
Marian LudgateCardiff University, School of Medicine, Division of Infection & Immunity, Cardiff, UK.
Luigi LuciniUniversità Cattolica del Sacro Cuore, Department for Sustainable food process, Piacenza, Italy.ORCID 0000-0002-5133-9464
Filippo BiscariniCardiff University, School of Medicine, Division of Infection & Immunity, Cardiff, UK. biscarinif@cardiff.ac.uk.ORCID 0000-0002-3901-2354
Cardiff University · GBUniversity of Milan · ITUniversity of Duisburg-Essen · DEInstitute of Agricultural Biology and Biotechnology · ITParco Tecnologico Padano · ITUniversità Cattolica del Sacro Cuore · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Graves' Disease (GD) is an autoimmune condition in which thyroid-stimulating antibodies (TRAB) mimic thyroid-stimulating hormone function causing hyperthyroidism. 5% of GD patients develop inflammatory Graves' orbitopathy (GO) characterized by proptosis and attendant sight problems. A major challenge is to identify which GD patients are most likely to develop GO and has relied on TRAB measurement. We screened sera/plasma from 14 GD, 19 GO and 13 healthy controls using high-throughput proteomics and miRNA sequencing (Illumina's HiSeq2000 and Agilent-6550 Funnel quadrupole-time-of-flight mass spectrometry) to identify potential biomarkers for diagnosis or prognosis evaluation. Euclidean distances and differential expression (DE) based on miRNA and protein quantification were analysed by multidimensional scaling (MDS) and multinomial regression respectively. We detected 3025 miRNAs and 1886 proteins and MDS revealed good separation of the 3 groups. Biomarkers were identified by combined DE and Lasso-penalized predictive models; accuracy of predictions was 0.86 (±0:18), and 5 miRNA and 20 proteins were found including Zonulin, Alpha-2 macroglobulin, Beta-2 glycoprotein 1 and Fibronectin. Functional analysis identified relevant metabolic pathways, including hippo signaling, bacterial invasion of epithelial cells and mRNA surveillance. Proteomic and miRNA analyses, combined with robust bioinformatics, identified circulating biomarkers applicable to diagnose GD, predict GO disease status and optimize patient management.

Indexed as

ProteomicsSequence Analysis, RNAAdultBiomarkersCluster AnalysisFemaleGraves OphthalmopathyHumansMaleMicroRNAsMiddle AgedBiomarkersMicroRNAs

Identifiers

PMID29849043
PMCPMC5976672
OpenAlexW2806495656

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.