A simple and robust reporter-based framework for deep functional characterization of PPARγ mutants.

Area of Science:

• Molecular Biology
• Genetics
• Biochemistry

Background:

• Nuclear receptor (NR) transcription factors (TF) play critical roles in cellular processes.
• Missense mutations in NRs, such as PPARG, are linked to genetic disorders like familial partial lipodystrophy type 3 (FPLD3).
• In silico prediction of mutation effects is challenging due to the complex nature of these proteins.

Purpose of the Study:

• To develop and validate a simple, robust experimental framework for assessing the functional impact of PPARγ variants.
• To provide a first-line approach for mechanistic resolution of PPARγ mutations.
• To establish a scalable method for variant interpretation in research and clinical settings.

Main Methods:

• Development of a four-complementary reporter assay system.
• Independent assessment of transcriptional activation, ligand-binding domain integrity, heterodimerization, and DNA binding.
• Analysis of uncharacterized FPLD3-associated loss-of-function (LOF) and bladder cancer-associated gain-of-function (GOF) variants.

Main Results:

• The framework successfully identified unique functional phenotypes for all five tested PPARγ mutants.
• Results were further supported by co-regulator profiling.
• Demonstrated proof-of-concept for assessing both LOF and GOF variants.

Conclusions:

• The established framework is a simple, robust, and mechanistically informative tool for initial assessment of PPARγ variants.
• This approach is broadly applicable to other nuclear receptors.
• Facilitates systematic variant interpretation in genetic research and clinical diagnostics.