Lissencephaly (“smooth brain”, LIS) is a malformation of cortical development associated with deficient neuronal migration and abnormal formation of cerebral convolutions or gyri. The LIS spectrum includes agyria, pachygyria, and subcortical band heterotopia. Our first classification of LIS and subcortical band heterotopia (SBH) was developed to distinguish between the first two genetic causes of LIS – LIS1 (PAFAH1B1) and DCX. However, progress in molecular genetics has led to identification of 19 LIS-associated genes, leaving the existing classification system insufficient to distinguish the increasingly diverse patterns of LIS. To address this challenge, we reviewed clinical, imaging and molecular data on 188 patients with LIS-SBH ascertained during the last five years, and reviewed selected archival data on another ~1,400 patients. Using these data plus published reports, we constructed a new imaging based classification system with 21 recognizable patterns that reliably predict the most likely causative genes. These patterns do not correlate consistently with the clinical outcome, leading us to also develop a new scale useful for predicting clinical severity and outcome. Taken together, our work provides new tools that should prove useful for clinical management and genetic counselling of patients with LIS-SBH (imaging and severity based classifications), and guidance for prioritizing and interpreting genetic testing results (imaging based classification).

Purpose To estimate diagnostic yield and genotype-phenotype correlations in a cohort of 811 patients with lissencephaly or subcortical band heterotopia. Methods We collected DNA from 756 children with lissencephaly over 30 years. Many were tested for deletion 17p13.3 and mutations of LIS1, DCX and ARX, but few other genes. Among those tested, 216 remained unsolved and were tested by a targeted panel of 17 genes (ACTB, ACTG1, ARX, CRADD, DCX, LIS1, TUBA1A, TUBA8, TUBB2B, TUBB, TUBB3, TUBG1, KIF2A, KIF5C, DYNC1H1, RELN and VLDLR) or by whole exome sequencing. 55 patients studied in another institution were added as a validation cohort. Results The overall mutation frequency in the entire cohort was 81%. LIS1 accounted for 40% of patients, followed by DCX (23%), TUBA1A (5%), and DYNC1H1 (3%). Other genes accounted for 1% or less of patients. 19% remained unsolved, which suggests that several additional genes remain to be discovered. The majority of unsolved patients had posterior pachygyria, subcortical band heterotopia or mild frontal pachygyria. Conclusions The brain-imaging pattern correlates with mutations in single lissencephaly-associated genes, as well as in biological pathways. We propose the first LIS classification system based on the underlying molecular mechanisms.

In individuals with mutations, age at seizure onset appears to predict outcome better than mutation type. Because outcome is not predetermined by genetic factors only, early recognition and treatment that mitigates prolonged/repeated seizures in the first year of life might also limit the progression to epileptic encephalopathy.