Biallelic NLRP7 variants in patients with recurrent hydatidiform mole: A review and expert consensus.
Rima SlimRosemary FisherFlorian MilhavetReda HemidaSamantha K RojasCécile RittoreRashmi BaggaMonica AguinagaIsabelle TouitouPublished in: Human mutation (2022)
Hydatidiform mole (HM) is an abnormal human pregnancy characterized by excessive growth of placental trophoblasts and abnormal early embryonic development. Following a first such abnormal pregnancy, the risk for women of successive molar pregnancies significantly increases. To date variants in seven maternal-effect genes have been shown to cause recurrent HMs (RHM). NLRP7 is the major causative gene for RHM and codes for NOD-like receptor (NLR) family pyrin domain containing 7, which belongs to a family of proteins involved in inflammatory disorders. Since its identification, all NLRP7 variants have been recorded in Infevers, an online registry dedicated to autoinflammatory diseases (https://infevers.umai-montpellier.fr/web/). Here, we reviewed published and unpublished recessive NLRP7 variants associated with RHM, scored their pathogenicity according to the American College of Medical Genetics classification, and recapitulated all functional studies at the level of both the patients and the conceptions. We also provided data on further variant analyses of 32 patients and genotypes of 36 additional molar pregnancies. This comprehensive review integrates published and unpublished data on NLRP7 and aims at guiding geneticists and clinicians in variant interpretation, genetic counseling, and management of patients with this rare condition.
Keyphrases
- copy number
- pregnancy outcomes
- end stage renal disease
- preterm birth
- newly diagnosed
- chronic kidney disease
- ejection fraction
- genome wide
- prognostic factors
- nlrp inflammasome
- peritoneal dialysis
- escherichia coli
- pregnant women
- electronic health record
- palliative care
- oxidative stress
- randomized controlled trial
- metabolic syndrome
- type diabetes
- body mass index
- physical activity
- antiretroviral therapy
- hepatitis c virus
- deep learning
- artificial intelligence
- cystic fibrosis
- muscular dystrophy
- smoking cessation
- weight gain
- data analysis
- hiv testing
- genome wide identification
- candida albicans
- insulin resistance