Abstract
Apparent mineralocorticoid excess, a rare autosomal recessive disorder characterized by low renin hypertension, may display a severe or mild phenotype in patients. The variability in clinical presentation stems from different extents of impairment of the 11β-hydroxysteroid dehydrogenase type 2 (HSD11B2) enzyme arising from distinct mutations in the encoding gene. The computational model of the HSD11B2 protein that we constructed here will be useful in predicting disease severity for newly reported missense mutations in this gene.
Mutations in 11β-hydroxysteroid dehydrogenase type 2 gene (
HSD11B2
) cause an extraordinarily rare autosomal recessive disorder, apparent mineralocorticoid excess (AME). AME is a form of low renin hypertension that is potentially fatal if untreated. Mutations in the
HSD11B2
gene result either in severe AME or a milder phenotype (type 2 AME). To date, ∼40 causative mutations have been identified. As part of the International Consortium for Rare Steroid Disorders, we have diagnosed and followed the largest single worldwide cohort of 36 AME patients. Here, we present the genotype and clinical phenotype of these patients, prominently from consanguineous marriages in the Middle East, who display profound hypertension and hypokalemic alkalosis. To correlate mutations with phenotypic severity, we constructed a computational model of the HSD11B2 protein. Having used a similar strategy for the in silico evaluation of 150 mutations of
CYP21A2
, the disease-causing gene in congenital adrenal hyperplasia, we now provide a full structural explanation for the clinical severity of AME resulting from each known
HSD11B2
missense mutation. We find that mutations that allow the formation of an inactive dimer, alter substrate/coenzyme binding, or impair structural stability of HSD11B2 yield severe AME. In contrast, mutations that cause an indirect disruption of substrate binding or mildly alter intramolecular interactions result in type 2 AME. A simple in silico evaluation of novel missense mutations could help predict the often-diverse phenotypes of an extremely rare monogenic disorder.