Modeling Complex Developmental Disease: The Case of Polycystic Kidney Disease.

Jay DeLoriea, Cody Casey, Lexee Shearer, Victoria Chen, Angelica Bryant, Chiara Gamberi

Abstract readReview

In one paragraph

Review in Journal of developmental biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

0cells of the map it votes in

0citing papers in PubMed

–field-weighted citation impact

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Jay DeLorieaBiology Department, Coastal Carolina University, Conway, SC 29526, USA.

Cody CaseyBiology Department, Coastal Carolina University, Conway, SC 29526, USA.ORCID 0009-0006-4076-7646

Lexee ShearerBiology Department, Coastal Carolina University, Conway, SC 29526, USA.

Victoria ChenBiology Department, Coastal Carolina University, Conway, SC 29526, USA.

Angelica BryantBiology Department, Coastal Carolina University, Conway, SC 29526, USA.

Chiara GamberiBiology Department, Coastal Carolina University, Conway, SC 29526, USA.ORCID 0000-0002-7122-6491

Funding

South Carolina IDeA Networks of Biomedical Research (SC INBRE V)P20GM103499 · NIGMS · UNIVERSITY OF SOUTH CAROLINA AT COLUMBIA · PI EDIE C GOLDSMITH · 2012 to 2026

$61.0M

NIGMS NIH HHS P20 GM103499South Carolina IDEA Network for Research Excellence NIH 5P20GM103499

6 · The paper itself

Abstract

Both genetics and the environment affect the phenotypes of polycystic kidney diseases (PKD), such as autosomal dominant (AD) PKD, autosomal recessive (AR) PKD and nephronophthisis (NPH). Variable phenotypes, pleiotropy, divergent severity and progression, even in family members who inherited the same disease-causing mutation(s), signal the involvement of networked genes and modifiers. Several PKD-linked genes function in development and renal tubule morphogenesis. Cystic renal tissues feature metabolic remodeling, functional reprogramming and dysregulation of several shared factors and pathways. ADPKD, ARPKD and NPH partially phenocopy each other. Understanding the developmental arc of cystic kidney disease and its complex phenotypes would improve diagnostics and help develop effective personalized treatments. However, this is challenging to study in vertebrate systems due to genetic redundancy, functional overlap, and a dearth of genetic tools. Underused in this context,

Indexed as

developmentdisease modelsDrosophiladrug discoverygenetic modelsgenetic networkspolycystic kidney disease

Identifiers

PMID42647230

DOI10.3390/jdb14030036

PMCPMC13510785

What Socratic holds

Textmetadata

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 Socratic graph.