Genomic and Bioinformatics Analysis of Familial Partial Lipodystrophy Type 3 Identified in a Patient with Novel PPARγ Mutation and Robust Response to Pioglitazone

Familial partial lipodystrophies (FPLDs) are very rare inherited disorders characterized by partial loss of adipose tissue from the upper and lower extremities. At least seven subtypes of FPLD have been identified and are mostly dominantly inherited. FPLD type 3 is caused by mutations in the PPARγ gene, which encodes for the protein peroxisome proliferator-activated receptor gamma (PPARγ). We identified a Saudi female with PFLD3 presented with partial lipoatrophy, uncontrolled diabetes, severe hypertriglyceridemia, and recurrent pancreatitis. The clinical and biochemical findings in this proband were described before and after treatment with Pioglitazone in addition to the conventional treatment. DNA extraction and whole exome sequencing (WES) were performed to detect the variant. The mutant gene was subjected to Sanger analysis to confirm the results. We applied five specific computational prediction tools to assess the pathogenicity of variation, namely the MT, DANN, CADD, BayesDel, and fitCons tools. We assessed protein modeling and stability with the AlphaFold-generated structures for both wild-type and mutant proteins. Finally, we conducted molecular docking using the AutoDock Vina virtual docking. Upon whole exome sequencing, a <i>c.1024C>T p.(Gln342Ter)</i> missense mutation was detected in the PPARγ gene associated with FPLD3. This variant is a novel mutation that has not been described in all genome databases. Sanger analysis confirmed the heterogenicity and pathogenicity of this variant. All five computational prediction tools indicate that this variant is considered highly pathogenic. Our patient showed a dramatic response to Pioglitazone, a synthetic PPARγ agonist. From structural modeling, we found that the enhanced binding affinity of the mutant PPARγ protein to Pioglitazone likely improves the activation of PPARγ, enhancing its transcriptional activity and resulting in better clinical outcomes. These findings extend the spectrum of PPARγ mutations responsible for FPLD3 and highlight the potential for personalized treatment strategies based on genetic mutations.