Evidence map›Paper›PMID 42212514›Full record

ReviewDisease models & mechanisms2026

Modeling Fabry nephropathy: insights from experimental systems towards precision nephrology.

Hassan Elsaid, Jessica Furriol, Øystein Eikrem, Camilla Tøndel, Einar Svarstad

Abstract readReview
In one paragraph

Review in Disease models & mechanisms, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

5 authors.

Hassan ElsaidDepartment of Clinical Medicine, University of Bergen, 5020 Bergen, Norway.ORCID 0000-0002-4797-0245
Jessica FurriolDepartment of Clinical Medicine, University of Bergen, 5020 Bergen, Norway.
Øystein EikremDepartment of Clinical Medicine, University of Bergen, 5020 Bergen, Norway.
Camilla TøndelDepartment of Clinical Medicine, University of Bergen, 5020 Bergen, Norway.
Einar SvarstadDepartment of Clinical Medicine, University of Bergen, 5020 Bergen, Norway.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Fabry nephropathy is a major cause of kidney failure in Fabry disease, caused by pathogenic GLA variants that reduce α-galactosidase A activity and lead to globotriaosylceramide (Gb3) accumulation. In recent years, rapid advances in experimental modeling and emerging therapeutic strategies have dramatically reshaped understanding and treatment prospects for Fabry nephropathy. Experimental models - including cellular systems, patient-derived kidney organoids, and animal models such as zebrafish, Drosophila, mice and rats - have been pivotal in elucidating classic Gb3-dependent and novel Gb3-independent pathogenic mechanisms. These insights challenge the traditional Gb3-centric paradigm by highlighting other contributors, such as its metabolite lyso-Gb3, as well as α-synuclein accumulation and endothelial dysfunction. Despite established therapies for Fabry nephropathy, such as enzyme replacement and pharmacological chaperones, disease progression remains a clinical challenge, underscoring the urgent need for deeper mechanistic understanding and precision medicine approaches. This timely Review summarizes diverse model systems' unique strengths, limitations and translational potential to guide future research and therapeutic development for this complex disease.

Indexed as

Fabry DiseaseNephrologyPrecision Medicinealpha-GalactosidaseAnimalsDisease Models, AnimalHumansKidneyTrihexosylceramidesalpha-GalactosidaseglobotriaosylceramideTrihexosylceramidesExperimental disease modelsFabry nephropathyKidney organoidsPrecision nephrologyα-Galactosidase A deficiency

Identifiers

PMID42212514
PMCPMC13267772

What OpenQuestion holds

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Registered trials

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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.