The pathogenesis and phenotype of children with microcephaly - Retrospective analysis and development of a microcephaly database

Abstract

Aims: Microcephaly (MC) is usually defined as a head circumference more than 2 standard deviations (SD) below the mean for age and gender. The pathogenesis of MC is hetergenous and the phenotype variable. Aim of this study was to develop a (multi center) data bank comprising (i) the putative pathogenesis oft the MC, (ii) the prevalence of structural brain abnormalities and (iii) the phenotype of MC and associated disorders. Methods: In this pilot study the hospital charts of 197 children (54% (n=105) girls, 46% (n=92) boys) between 2005 and 2011 were reviewed and the data were stored anonymised. Results: 26% (n=51) had a primary, congenital MC, and 19% (n=37) had a secondary MC, this classification was not possible in 55% (n=109) of the children due to present data. Etiology of the MC was genetic in 21% (n=42), in 28% (n=56) perinatally – and in 2% (n=4) postnatally acquired and in 47% (n=92) the pathogenesis remains unclear. Genetic causes were chromosomal and genomic aberrations in 9% (n=11), monogenic disorders in 8% (n=10) and the phenotype is highly suspicious of a genetic disorder in 17% (n=21). 69% (n=137) of he children had a cMRI at a mean age of 45 months, in 60% (n=82) the results were abnormal and in 40% (n=55) MR revealed normal images of the brain. The most frequent structural brain lesions were: in 38% (n=31) hypo-/dysplasia of the corpus callosum, in 38% (n=31) a brain atrophy and in 14%(n=16) complex structural brain anomalies. 81% (n=159) of the children had a developmental disability (severity range: from learning disabilities to severe complex developmental disorders and disability), 40% (n=80) had epilepsy, furthermore craniofacial dysmorphism, ophthalmologic disorders and extra CNS organ involvement were documented. Conclusion: The pathogenesis, the variable phenotype of infantile MC and the high percentage of unknown etiology reveals further heterogeneity. On the basis of the empirical multi center data collection, the diagnostic algorythm especially for children with primary MC, should be optimised and prognostic factors for the psychomotor development identified.