Congenital Generalized Lipodystrophy (CGL) Panel

Congenital generalized lipodystrophies (CGL) are a group of heterogeneous disorders characterized by a near complete loss of adipose tissue at or soon-after birth (Patni and Garg. 2015. PubMed ID: 26239609; Akinci et al. 2018. PubMed ID: 30406415). These disorders are typically accompanied by severe metabolic dysregulation. The exact prevalence of CGL is unknown, but is estimated to be approximately 0.2 to 1 cases per million individuals (Chiquette et al. 2017. PubMed ID: 29066925).

CGL has four main subtypes, CGL1, CGL2, CGL3, and CGL4, which are associated with biallelic pathogenic variants in the AGPAT2, BSCL2, CAV1, and CAVIN1 (also known as PTRF) genes, respectively (Patni and Garg. 2015. PubMed ID: 26239609). CGL1 and CGL2 are also referred to as Berardinelli-Seip congenital lipodystrophy (BSCL; Van Maldergem. 2016. PubMed ID: 20301391). In addition to these four main subtypes, several genes are also known to present congenitally with generalized lipodystrophy as a primary clinical feature. These include the PPARG, PCYT1A, FBN1, LMNA, and KCNJ6 genes. Pathogenic variants in the PPARG and PCYT1A genes are associated with CGL-like presentations, pathogenic variants in the FBN1 and LMNA genes are associated with progeroid syndromes, and pathogenic variants in the KCNJ6 gene are associated with Keppen–Lubinsky syndrome (Akinci et al. 2018. PubMed ID: 30406415).

Clinical features associated with these disorders may include generalized lipodytrophy, a muscular appearance, prominent veins, accelerated growth, voracious appetite, umbilical hernias, hepatomegaly, splenomegaly, acanthosis nigricans, advanced bone age, and metabolic complications (insulin resistance, hypertriglyceridaemia, hepatic steatosis; Patni et al. 2015. PubMed ID: 26239609; Akinci et al. 2018. PubMed ID: 30406415). Female patients may also exhibit mild hirsutism, clitoromegaly, irregular menstrual periods, and polycystic ovaries. Clinical features associated with pathogenic variants in FBN1, KCNJ6, and LMNA may also include a marfanoid or progeroid appearance, as well as skeletal, cardiovascular and/or neurologic anomalies (Akinci et al. 2018. PubMed ID: 30406415). Medical management may include surveillance, psychological support, restriction of total fat intake, caloric restriction, increased physical activity, therapy for diabetes mellitus and hyperlipidemia, and possibly cosmetic surgery (Akinci et al. 2018. PubMed ID: 30370487). Genetic testing may aide in establishing a differential diagnosis and may assist reproductive planning.

Pathogenic variants in one or more of these genes included as part of this panel are reported to be associated with additional phenotypes including (but not limited to) familial partial lipodystrophy, encephalopathy, insulin resistance, severe obesity, skeletal dysplasia, neuropathy, muscular dystrophy, pulmonary hypertension, and Weill-Marchesani syndrome.

CGL is primarily inherited in an autosomal recessive manner, however dominant inheritance is reported for the FBN1, KCNJ6, LMNA, and PPARG genes. Pathogenic variants may be inherited from a carrier parent, an affected parent, or arise de novo (Lightbourne and Brown. 2017. PubMed ID: 28476236). CGL is associated with small deletions, nonsense, splice site, frameshift, missense, and regulatory pathogenic variants. Structural variants, predominantly in the form of gross deletions, have been reported in isolated and familial cases of CGL (Agarwal et al. 2002. PubMed ID: 11967537; Purizaca-Rosillo et al. 2017. PubMed ID: 27868354).

The AGPAT2, BSCL2, CAV1 and CAVIN1 genes encode proteins that are involved in phospholipid and triglyceride synthesis, the fusion of lipid droplets, and the biogenesis of caveolae within adipocytes (Patni and Garg. 2015. PubMed ID: 26239609). The LMNA and PPARG genes encode proteins that are involved in adipocyte differentiation pathways (Evans et al. 2004. PubMed ID: 15057233; Capanni et al. 2005. PubMed ID: 15843404). The FBN1 gene encodes a glycoprotein that contributes to the strength and elasticity of tissues, regulates the bioavailability of transforming growth factor beta, and may be important in determining adipose tissue levels (Davis et al. 2016. PubMed ID: 27386756). The KCNJ6 gene encodes an inwardly rectifying potassium channel, which may be involved in the control of cellular processes such as adipogenic differentiation (Masotti et al. 2015. PubMed ID: 25620207; Van Maldergem. 2016. PubMed ID: 20301391).The PCYT1A gene encodes a rate-limiting enzyme in the in the CDP-choline or Kennedy pathway for de novo phosphatidylcholine biosynthesis (Wang et al. 2005. PubMed ID: 15798219).

See individual gene summaries for more information about molecular biology of gene products and spectra of pathogenic variants.

Due to the genetic heterogeneity of the disorders tested in this panel, the clinical sensitivity of this specific grouping of genes is difficult to estimate. However, it is estimated that up to 80% of individuals with CGL have an identifiable genetic cause (Akinci et al. 2018. PubMed ID: 30406415).

This test is performed using Next-Gen sequencing with additional Sanger sequencing as necessary.

This panel provides 100% coverage of all coding exons of the genes plus 10 bases of flanking noncoding DNA in all available transcripts along with other non-coding regions in which pathogenic variants have been identified at PreventionGenetics or reported elsewhere. We define coverage as ≥20X NGS reads or Sanger sequencing. PGnome panels typically provide slightly increased coverage over the PGxome equivalent. PGnome sequencing panels have the added benefit of additional analysis and reporting of deep intronic regions (where applicable).

Dependent on the sequencing backbone selected for this testing, discounted reflex testing to any other similar backbone-based test is available (i.e., PGxome panel to whole PGxome; PGnome panel to whole PGnome).