Genotype/phenotype correlations in type 2 neurofibromatosis (NF2): evidence for more severe disease associated with truncating mutations.

TLDR

The study examined blood samples from 125 unrelated families with classical type 2 neurofibromatosis and an additional 17 families meeting modified criteria, screening for NF2 gene mutations. Causative NF2 mutations were identified in 43 % of classical families and 35 % of modified‑criteria families, and truncating mutations were linked to earlier symptom onset, more severe disease, and a higher likelihood of multiple CNS tumors before age 30, although mosaic truncating mutations showed milder phenotypes and mutation type alone should not be used to predict disease course.

Abstract

Blood samples from 125 unrelated families with classical type 2 neurofibromatosis (NF2) with bilateral vestibular schwannomas have been analysed for mutations in the NF2 gene. A further 17 families fulfilling modified criteria for NF2 have also been analysed. Causative mutations have been identified in 54 (43%) classical families and six (35%) of those fulfilling modified criteria. Forty-two cases from 38 families with truncating mutations had an average age at onset of symptoms of 19 years and diagnosis at 22.4 years. Fifty-one cases from 16 families with splice site mutations (15 from six), missense mutations (18 from six), and large deletions (18 from five) had an average age of onset of 27.8 years and at diagnosis of 33.4 years. Subjects with truncating mutations were significantly more likely to have symptoms before 20 years of age (p<0.001) and to develop at least two symptomatic CNS tumours in addition to vestibular schwannoma before 30 years (p<0.001). There were also significantly fewer multigenerational families with truncating mutations. Four further truncating mutations were in mosaic form and were associated with milder disease than other similar mutations. This large study has confirmed the previous impression that truncating mutations are associated with severe disease, but caution has to be exercised in using mutation type to predict disease course.