Evidence map›Paper›PMID 31396499›Full record

ReviewFrontiers in pediatrics2019

Evolving Clinical Applications of Tissue Transcriptomics in Kidney Disease.

Andrea L Oliverio, Tiffany Bellomo, Laura H Mariani

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in pediatrics, 2019. 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
0.6field-weighted citation impact, top 33% 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, 9 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Article
  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

3 authors at 1 institution in 1 country.

Andrea L OliverioDivision of Nephrology, Department of Internal Medicine, University of Michigan, Ann Arbor, MI, United States.
Tiffany BellomoUniversity of Michigan Medical School, Ann Arbor, MI, United States.
Laura H MarianiDivision of Nephrology, Department of Internal Medicine, University of Michigan, Ann Arbor, MI, United States.
University of Michigan–Ann Arbor · US

Funding

University of Michigan O'Brien Kidney Translational Core CenterP30DK081943 · NIDDK · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI BROSIUS, FRANK C · 2008 to 2022
$12.9M
RESEARCH TRAINING IN NEPHROLOGYT32DK007378 · NIDDK · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI PENNATHUR, SUBRAMANIAM · 1986 to 2019
$5.9M
Integrative Molecular Epidemiology Approach to Identify Nephrotic Syndrome SubgroupsK08DK115891 · NIDDK · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI MARIANI, LAURA H · 2018 to 2021
$678k
NIDDK NIH HHS K08 DK115891NIDDK NIH HHS P30 DK081943NIDDK NIH HHS T32 DK007378
6 · The paper itself

Abstract

Nephrotic syndrome is classically categorized by the histopathology with examples including focal segmental glomerulosclerosis (FSGS) and minimal change disease. Pediatric patients are also classified by whether their nephrotic syndrome is sensitive to, dependent on, or resistant to steroids. However, this traditional classification system overlooks the frequent clinical conundrum when, for example, one patient with FSGS responds briskly to steroids, and another quickly progresses to end stage kidney disease despite therapy. Two patients may have similar histopathologic appearances on kidney biopsy but entirely different clinical characteristics, rates of progression, and treatment responses. Transcriptional regulation of gene activation and posttranscriptional processing of mRNA may drive the unique and heterogeneous phenotypes which are incompletely understood in kidney disease and are a recent focus of research. Gene expression profiles provide insight on active transcriptional programs in tissues, are being used to understand biologic mechanisms of progressive chronic kidney disease, and may help to identify patients with shared mechanisms of kidney damage. This mini-review discusses clinically relevant techniques of bulk tissue and single cell transcriptomics, as well as strengths and limitations of each methodology. Further, we summarize recent examples in kidney research achieved through transcriptomics. This review offers an outlook on the role of transcriptomics in an integrative systems biology model with the goal of defining unique disease subgroups, finding targets for drug development, and aligning the right drug with the right patient.

Indexed as

chronic kidney diseaseglomerular diseasenephrotic syndromesingle cell transcriptomicstranscriptomics

Identifiers

PMID31396499
PMCPMC6664065
OpenAlexW2961890918

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.