Evidence map›Paper›PMID 31201317›Full record

ArticleScientific data2019

Multi omics analysis of fibrotic kidneys in two mouse models.

Mira Pavkovic, Lorena Pantano, Cory V Gerlach, Sergine Brutus, Sarah A Boswell, Robert A Everley, Jagesh V Shah, Shannan H Sui, Vishal S Vaidya

Open access · goldAbstract readDataset
In one paragraph

Article in Scientific data, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed, 1 pooled it
3.6field-weighted citation impact, top 7% 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

21 citing papers in PubMed, 1 synthesis or guideline pooled it, 37 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Matrix metalloproteinases in kidney homeostasis and diseases: an update.American journal of physiology. Renal physiology · 2024
    Review
  10. Article
  11. Review
  12. Article
  13. Article
  14. Article
  15. Article
  16. The NaCellular and molecular life sciences : CMLS · 2021
    Review
  17. Article
  18. Review
  19. Article
  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

9 authors at 3 institutions in 1 country.

Mira PavkovicLaboratory of Systems Pharmacology, Harvard Medical School, Boston, MA, USA.
Lorena PantanoBioinformatics Core, Harvard T. H. Chan School of Public Health, Boston, MA, USA.
Cory V GerlachLaboratory of Systems Pharmacology, Harvard Medical School, Boston, MA, USA.
Sergine BrutusLaboratory of Systems Pharmacology, Harvard Medical School, Boston, MA, USA.
Sarah A BoswellLaboratory of Systems Pharmacology, Harvard Medical School, Boston, MA, USA.
Robert A EverleyLaboratory of Systems Pharmacology, Harvard Medical School, Boston, MA, USA.
Jagesh V ShahLaboratory of Systems Pharmacology, Harvard Medical School, Boston, MA, USA.
Shannan H SuiBioinformatics Core, Harvard T. H. Chan School of Public Health, Boston, MA, USA.
Vishal S VaidyaLaboratory of Systems Pharmacology, Harvard Medical School, Boston, MA, USA. vvaidya@bwh.harvard.edu.
Center for Systems Biology · USHarvard University · USBrigham and Women's Hospital · US

Funding

Harvard Clinical and Translational Science CenterUL1TR001102 · NCATS · HARVARD MEDICAL SCHOOL · PI NADLER, LEE MARSHALL · 2013 to 2017
$106.2M
Pharmaco Response Signatures and Disease MechanismU54HL127365 · NHLBI · HARVARD MEDICAL SCHOOL · PI SORGER, PETER KARL · 2014 to 2019
$13.1M
TRANSLATIONAL PHARMACOLOGY COREP50GM107618 · NIGMS · HARVARD MEDICAL SCHOOL · PI GOLAN, DAVID E. · 2014 to 2018
$10.8M
Role of SMOC2 in Kidney FibrosisR01ES017543 · NIEHS · BRIGHAM AND WOMEN'S HOSPITAL · PI VAIDYA, VISHAL S. · 2011 to 2021
$3.9M
Role of SMOC2 in Kidney FibrosisR56ES017543 · NIEHS · BRIGHAM AND WOMEN'S HOSPITAL · PI VAIDYA, VISHAL S. · 2016 to 2016
$213k
Deutsche Forschungsgemeinschaft (German Research Foundation) PA 2577/2-1NCATS NIH HHS UL1 TR001102NHLBI NIH HHS U54 HL127365NIEHS NIH HHS R01 ES017543NIEHS NIH HHS R56 ES017543NIGMS NIH HHS P50 GM107618U.S. Department of Health & Human Services | NIH | National Center for Advancing Translational Sciences (NCATS) UL1 TR001102
6 · The paper itself

Abstract

Kidney fibrosis represents an urgent unmet clinical need due to the lack of effective therapies and an inadequate understanding of the molecular pathogenesis. We have generated a comprehensive and combined multi-omics dataset (proteomics, mRNA and small RNA transcriptomics) of fibrotic kidneys that is searchable through a user-friendly web application: http://hbcreports.med.harvard.edu/fmm/ . Two commonly used mouse models were utilized: a reversible chemical-induced injury model (folic acid (FA) induced nephropathy) and an irreversible surgically-induced fibrosis model (unilateral ureteral obstruction (UUO)). mRNA and small RNA sequencing, as well as 10-plex tandem mass tag (TMT) proteomics were performed with kidney samples from different time points over the course of fibrosis development. The bioinformatics workflow used to process, technically validate, and combine the single omics data will be described. In summary, we present temporal multi-omics data from fibrotic mouse kidneys that are accessible through an interrogation tool (Mouse Kidney Fibromics browser) to provide a searchable transcriptome and proteome for kidney fibrosis researchers.

Indexed as

Disease Models, AnimalProteomeAnimalsFibrosisKidney DiseasesMiceMicroRNAsProteomicsRNA, MessengerUreteral ObstructionMicroRNAsProteomeRNA, Messenger

Identifiers

PMID31201317
PMCPMC6570759
OpenAlexW2952904999

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.