ArticleInternational journal of obesity (2005)2017
Pharmacological modulation of LMNA SRSF1-dependent splicing abrogates diet-induced obesity in mice.
Article in International journal of obesity (2005), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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.
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.
Who cites it
6 citing papers in PubMed, 9 citations in OpenAlex.
- Tissue-Specific Multi-Omics Integration Demonstrates Molecular Signatures Connecting Obesity to Immune Vulnerability.Metabolites · 2026Article
- Orchestrating Nutrient Homeostasis: RNA-Binding Proteins as Molecular Conductors in Metabolic Disease Pathogenesis.Nutrients · 2025Review
- Altered splicing factor and alternative splicing events in a mouse model of diet- and polychlorinated biphenyl-induced liver disease.Environmental toxicology and pharmacology · 2023Article
- RNA splicing is a key mediator of tumour cell plasticity and a therapeutic vulnerability in colorectal cancer.Nature communications · 2022Article
- Regulation of alternative splicing in obesity-induced hypertension.Diabetes, metabolic syndrome and obesity : targets and therapy · 2019Article
- Alternative mRNA Splicing in the Pathogenesis of Obesity.International journal of molecular sciences · 2018Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
17 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Bakground/Objectives:Intense drug discovery efforts in the metabolic field highlight the need for novel strategies for the treatment of obesity. Alternative splicing (AS) and/or polyadenylation enable the LMNA gene to express distinct protein isoforms that exert opposing effects on energy metabolism and lifespan. Here we aimed to use the splicing factor SRSF1 that contribute to the production of these different isoforms as a target to uncover new anti-obesity drug. SUBJECTS/
methodsSmall molecules modulating SR protein activity and splicing were tested for their abilities to interact with SRSF1 and to modulate LMNA (AS). Using an LMNA luciferase reporter we selected molecules that were tested in diet-induced obese (DIO) mice. Transcriptomic analyses were performed in the white adipose tissues from untreated and treated DIO mice and mice fed a chow diet.
resultsWe identified a small molecule that specifically interacted with the RS domain of SRSF1. ABX300 abolished DIO in mice, leading to restoration of adipose tissue homeostasis. In contrast, ABX300 had no effect on mice fed a standard chow diet. A global transcriptomic analysis revealed similar profiles of white adipose tissue from DIO mice treated with ABX300 and from untreated mice fed a chow diet. Mice treated with ABX300 exhibited an increase in O
conclusionsTargeting SRSF1 with ABX300 compensates for changes in RNA biogenesis induced by fat accumulation and consequently represents a novel unexplored approach for the treatment of obesity.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.