Evidence map›Paper›PMID 26110394›Full record

ArticleInternational journal of molecular sciences2015

Biomarkers for Refractory Lupus Nephritis: A Microarray Study of Kidney Tissue.

Thitima Benjachat, Pumipat Tongyoo, Pornpen Tantivitayakul, Poorichaya Somparn, Nattiya Hirankarn, Santitham Prom-On, Prapaporn Pisitkun, Asada Leelahavanichkul, Yingyos Avihingsanon, Natavudh Townamchai

Open access · goldAbstract read
In one paragraph

Article in International journal of molecular sciences, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
1.6field-weighted citation impact, top 18% 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

15 citing papers in PubMed, 21 citations in OpenAlex.

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  11. Terminal nucleotidyl transferases (TENTs) in mammalian RNA metabolism.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2018
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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

10 authors at 4 institutions in 1 country.

Thitima BenjachatBiomedical Science, Interdisciplinary Program, Graduate School, Chulalongkorn University, Bangkok 10330, Thailand. tbenjachat@gmail.com.
Pumipat TongyooBiomedical Science, Interdisciplinary Program, Graduate School, Chulalongkorn University, Bangkok 10330, Thailand. ptongyoo@gmail.com.
Pornpen TantivitayakulDepartment of Oral Microbiology, Faculty of Dentistry, Mahidol University, Bangkok 10400, Thailand. phornpen_071@hotmail.com.
Poorichaya SomparnResearch Affairs, Faculty of Medicine, Chulalongkorn University, Bangkok 10330, Thailand. pook_bio@yahoo.com.
Nattiya HirankarnCenter of Excellence in Immunology and Immune-mediated Diseases, Faculty of Medicine, Chulalongkorn University, Bangkok 10330, Thailand. nattiyap@gmail.com.
Santitham Prom-OnDepartment of Computer Engineering, Faculty of Engineering, King Mongkut's University of Technology Thonburi, Bangkok 10140, Thailand. san.promon@gmail.com.
Prapaporn PisitkunDivision of Allergy, Immunology, and Rheumatology, Department of Medicine, Faculty of Medicine, Ramathibodi Hospital, Mahidol University, Bangkok 10400, Thailand. beepisitkun@gmail.com.
Asada LeelahavanichkulCenter of Excellence in Immunology and Immune-mediated Diseases, Faculty of Medicine, Chulalongkorn University, Bangkok 10330, Thailand. a_leelahavanit@yahoo.com.
Yingyos AvihingsanonCenter of Excellence in Immunology and Immune-mediated Diseases, Faculty of Medicine, Chulalongkorn University, Bangkok 10330, Thailand. yingyos.a@gmail.com.
Natavudh TownamchaiDivision of Nephrology, Department of Medicine, Faculty of Medicine, Chulalongkorn University and King Chulalongkorn Memorial Hospital, Bangkok 10330, Thailand. ntownamchai@gmail.com.
Chulalongkorn University · THKing Mongkut's University of Technology Thonburi · THMahidol University · THRamathibodi Hospital · TH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The prognosis of severe lupus nephritis (LN) is very different among individual patients. None of the current biomarkers can be used to predict the development of refractory LN. Because kidney histology is the gold standard for diagnosing LN, the authors hypothesize that molecular signatures detected in kidney biopsy tissue may have predictive value in determining the therapeutic response. Sixty-seven patients with biopsy-proven severely active LN by International Society of Nephrology/Renal Pathology Society (ISN/RPS) classification III/IV were recruited. Twenty-three kidney tissue samples were used for RNA microarray analysis, while the remaining 44 samples were used for validation by real-time polymerase chain reaction (PCR) gene expression analysis. From hundreds of differential gene expressions in refractory LN, 12 candidates were selected for validation based on gene expression levels as well as relevant functions. The candidate biomarkers were members of the innate immune response molecules, adhesion molecules, calcium-binding receptors, and paracellular tight junction proteins. S100A8, ANXA13, CLDN19 and FAM46B were identified as the best kidney biomarkers for refractory LN, and COL8A1 was identified as the best marker for early loss of kidney function. These new molecular markers can be used to predict refractory LN and may eventually lead to novel molecular targets for therapy.

Indexed as

AdultBiomarkersBiopsyDrug ResistanceFemaleHigh-Throughput Nucleotide SequencingHumansKidneyKidney Function TestsLupus NephritisMaleMicroarray AnalysisReal-Time Polymerase Chain ReactionReverse Transcriptase Polymerase Chain ReactionRNA, MessengerBiomarkersRNA, Messengerbiomarkerchronic kidney diseasegene expressionlupus nephritismicroarrays

Identifiers

PMID26110394
PMCPMC4490552
OpenAlexW1551852646

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.