Knowledge of genetic cause in neurodevelopmental disorders can highlight molecular and cellular processes critical for typical development. Furthermore, the relative homogeneity of neurodevelopmental disorders of known genetic origin allows the researcher to establish the subsequent neurobiological processes that mediate cognitive and behavioural outcomes. The current study investigated white matter structural connectivity in a group of individuals with intellectual disability due to mutations in ZDHHC9. In addition to shared cause of cognitive impairment, these individuals have a shared cognitive profile, involving oro-motor control difficulties and expressive language impairment. Analysis of structural network properties using graph theory measures showed global reductions in mean clustering coefficient and efficiency in the ZDHHC9 group, with maximal differences in frontal and parietal areas. Regional variation in clustering coefficient across cortical regions in ZDHHC9 mutation cases was significantly associated with known pattern of expression of ZDHHC9 in the normal adult human brain. The results demonstrate that a mutation in a single gene impacts upon white matter organisation across the whole-brain, but also shows regionally specific effects, according to variation in gene expression. Furthermore, these regionally specific patterns may link to specific developmental mechanisms, and correspond to specific cognitive deficits.
Many cognitive and psychiatric disorders are highly heritable (Lee 2015, Haworth 2009). In some cases, genetic risk factors have been identified, but understanding the neural mechanisms linking altered gene transcripts to cognitive or behavioural outcomes remains challenging. One reason for this is the heterogenous nature of the vast majority of these disorders, which presents a major challenge to establishing the neural endophenotypes that mediate any gene-cognition relationships; any group defined on the basis of a cognitive impairment or behavioural difficulty will likely contain individuals with different genetic and neural causes, making it difficult to identify mechanisms at the group level. One promising approach has been to study neuroanatomical differences in groups of individuals that have rare but clearly defined genetic causes of those impairments (Meyer-Lindenberg 2009, Griffa 2013). These groups, whilst necessarily small in size, have an homogenous aetiology. Studying these groups can therefore provide a powerful means for identifying the neurobiological pathways that potentially mediate cognitive and behavioural phenotypes in the wider population. For instance, the study of a rare familial speech disorder (KE family, FOXP2 mutation) highlighted the importance of striatal networks for emergent higher-order language skills (Watkins 2011, Liegeois 2011).
However, studies of brain differences have mainly focussed on focal differences in brain areas or white matter tracts that show the most pronounced group differences. This is true of both genetically defined group comparisons and case-control designs more generally. However, genetic differences are likely to have wide-ranging effects on the organisation of neural ensembles across many areas. To explore this fully requires a more advanced network science approach, cable of establishing how o