Evidence map›Paper›PMID 38430613›Full record

ReviewMolecular genetics and metabolism2024

A review of fatty acid oxidation disorder mouse models.

Shannon J Babcock, Sander M Houten, Melanie B Gillingham

Abstract readReview
In one paragraph

Review in Molecular genetics and metabolism, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. Article
  3. Acute arrhythmias in a long-chain 3-hydroxyacyl-CoA dehydrogenase deficiency mouse model.American journal of physiology. Heart and circulatory physiology · 2026
    Article
  4. 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.

Shannon J BabcockDepartment of Molecular and Medical Genetics, Oregon Health and Science University, Portland, OR, USA. Electronic address: babcocsh@ohsu.edu.
Sander M HoutenDeparment of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Melanie B GillinghamDepartment of Molecular and Medical Genetics, Oregon Health and Science University, Portland, OR, USA.

Funding

Exploring the pathophysiology and treatment of LCHADD retinopathyR01EY032889 · NEI · OREGON HEALTH & SCIENCE UNIVERSITY · PI GILLINGHAM, MELANIE B · 2021 to 2025
$1.9M
NEI NIH HHS R01 EY032889
6 · The paper itself

Abstract

Fatty acid oxidation disorders (FAODs) are a family of rare, genetic disorders that affect any part of the fatty acid oxidation pathway. Patients present with severe phenotypes, such as hypoketotic hypoglycemia, cardiomyopathy, and rhabdomyolysis, and currently manage these symptoms by the avoidance of fasting and maintaining a low-fat, high-carbohydrate diet. Because knowledge about FAODs is limited due to the small number of patients, rodent models have been crucial in learning more about these disorders, particularly in studying the molecular mechanisms involved in different phenotypes and in evaluating treatments for patients. The purpose of this review is to present the different FAOD mouse models and highlight the benefits and limitations of using these models. Specifically, we discuss the phenotypes of the available FAOD mouse models, the potential molecular causes of prominent FAOD phenotypes that have been studied using FAOD mouse models, and how FAOD mouse models have been used to evaluate treatments for patients.

Indexed as

Disease Models, AnimalFatty AcidsLipid Metabolism, Inborn ErrorsOxidation-ReductionAnimalsCardiomyopathiesHumansMicePhenotypeFatty AcidsCardiomyopathyExerciseFatty acid β-oxidationGene additionHypoglycemiaInborn errors of metabolismMouse models

Identifiers

PMID38430613
PMCPMC11073919

What OpenQuestion holds

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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.