Evidence map›Paper›PMID 34786702›Full record

ArticleHepatology (Baltimore, Md.)2022

Aquaporin 9 induction in human iPSC-derived hepatocytes facilitates modeling of ornithine transcarbamylase deficiency.

Alexander Laemmle, Martin Poms, Bernadette Hsu, Mariia Borsuk, Véronique Rüfenacht, Joshua Robinson, Martin C Sadowski, Jean-Marc Nuoffer, Johannes Häberle, Holger Willenbring

Open access · hybridAbstract read
In one paragraph

Article in Hepatology (Baltimore, Md.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
2.4field-weighted citation impact, top 11% 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

14 citing papers in PubMed, 24 citations in OpenAlex.

  1. Review
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  8. Review
  9. Modelling urea cycle disorders using iPSCs.NPJ Regenerative medicine · 2022
    Review
  10. Review
  11. Article
  12. Review
  13. Review
  14. [Clinical research in cell therapy of liver diseases: progress and challenges].Zhonghua gan zang bing za zhi = Zhonghua ganzangbing zazhi = Chinese journal of hepatology · 2022
    Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors at 7 institutions in 2 countries.

Alexander LaemmleEli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California San Francisco, San Francisco, California, USA.
Martin PomsDivision of Clinical Chemistry and Biochemistry, University Children's Hospital Zurich, Zurich, Switzerland.
Bernadette HsuEli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California San Francisco, San Francisco, California, USA.
Mariia BorsukUniversity Institute of Clinical Chemistry, University of Bern, Bern, Switzerland.
Véronique RüfenachtDivision of Metabolism and Children`s Research Center, University Children's Hospital, Zurich, Switzerland.
Joshua RobinsonEli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California San Francisco, San Francisco, California, USA.
Martin C SadowskiInstitute of Pathology, University of Bern, Bern, Switzerland.
Jean-Marc NuofferDepartment of Pediatrics, University Children's Hospital, Bern, Switzerland.
Johannes HäberleDivision of Metabolism and Children`s Research Center, University Children's Hospital, Zurich, Switzerland.
Holger WillenbringEli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California San Francisco, San Francisco, California, USA.
University of Bern · CHUniversity Children's Hospital Zurich · CHBroad Center · USSwiss Integrative Center for Human Health · CHUniversity Children’s Hospital Bern · CHUniversity of California, San Francisco · USUniversity of San Francisco · US

Funding

UCSF Liver Core CenterP30DK026743 · NIDDK · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Jennifer Y. Chen · 1986 to 2026
$30.7M
Modeling metabolic interactions of liver and fat with integrated microphysiological systemsUH3TR000487 · NCATS · UNIVERSITY OF CALIFORNIA BERKELEY · PI HEALY, KEVIN EDWARD · 2014 to 2016
$2.9M
NCATS NIH HHS UH3 TR000487NIDDK NIH HHS P30 DK026743
6 · The paper itself

Abstract

BACKGROUND AND

aimsPatient-derived human-induced pluripotent stem cells (hiPSCs) differentiated into hepatocytes (hiPSC-Heps) have facilitated the study of rare genetic liver diseases. Here, we aimed to establish an in vitro liver disease model of the urea cycle disorder ornithine transcarbamylase deficiency (OTCD) using patient-derived hiPSC-Heps. APPROACH AND

resultsBefore modeling OTCD, we addressed the question of why hiPSC-Heps generally secrete less urea than adult primary human hepatocytes (PHHs). Because hiPSC-Heps are not completely differentiated and maintain some characteristics of fetal PHHs, we compared gene-expression levels in human fetal and adult liver tissue to identify genes responsible for reduced urea secretion in hiPSC-Heps. We found lack of aquaporin 9 (AQP9) expression in fetal liver tissue as well as in hiPSC-Heps, and showed that forced expression of AQP9 in hiPSC-Heps restores urea secretion and normalizes the response to ammonia challenge by increasing ureagenesis. Furthermore, we proved functional ureagenesis by challenging AQP9-expressing hiPSC-Heps with ammonium chloride labeled with the stable isotope [

conclusionOur results identify a critical role for AQP9 in functional urea metabolism and establish the feasibility of in vitro modeling of OTCD with hiPSC-Heps. By facilitating studies of OTCD genotype/phenotype correlation and drug screens, our model has potential for improving the therapy of OTCD.

Indexed as

Induced Pluripotent Stem CellsLiver DiseasesOrnithine Carbamoyltransferase Deficiency DiseaseAdultAquaporinsHepatocytesHumansUreaAQP9 protein, humanAquaporinsUrea

Identifiers

PMID34786702
PMCPMC9295321
OpenAlexW3214641467

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.