PPARG-related familial partial lipodystrophy: genes and variants

PPARG-related familial partial lipodystrophy is linked to 1 analyzed protein (PPARG). 7 DNA variants are known to cause it; 4 more are uncertain, and 0 of those already look disease-causing on computable evidence.

Last updated 2026-09-30. Research information, not medical advice.

Genes linked to PPARG-related familial partial lipodystrophy

Known disease-causing variants in PPARG-related familial partial lipodystrophy

VariantPositionProtein partClinical label
PPARG R164Q164Nuclear receptorDisease-causing (★★)
PPARG P495L495NR LBDDisease-causing (★★)
PPARG R425H425NR LBDDisease-causing (★★)
PPARG R164W164Nuclear receptorDisease-causing
PPARG P214L214Interaction with FAM120BDisease-causing
PPARG V318M318NR LBDDisease-causing
PPARG F388L388NR LBDDisease-causing

Diseases related to PPARG-related familial partial lipodystrophy

Frequently asked questions

Which genes are linked to PPARG-related familial partial lipodystrophy?

In CATVariant, PPARG-related familial partial lipodystrophy is linked to 1 analyzed protein: PPARG (Peroxisome proliferator-activated receptor gamma).

How many genetic variants are linked to PPARG-related familial partial lipodystrophy?

15 variants: 7 are classified as disease-causing (pathogenic or likely pathogenic) in ClinVar and 4 are of uncertain significance or have conflicting reports.

Which uncertain variants in PPARG-related familial partial lipodystrophy look disease-causing?

None of the uncertain variants currently reaches the likely-pathogenic range on computable evidence alone.

About this data

Variant–disease links come from ClinVar, Open Targets and UniProt, pooled from the latest public CATVariant analysis of each human protein. Evidence scores use the ACMG/AMP Bayesian points scale with computable criteria only (position among known disease variants, rarity in gnomAD, calibrated predictors, deep mutational scanning); there is no family or patient data, so they prioritise variants for expert review and never classify them.

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