The molecular networks of living cells have been studied extensively, and some systems like metabolism have been well characterized (Lewis, Nat Biotech, 2010). However, other biological processes remain poorly characterized, and so the molecular etiology of complex pathologies, such as neurological disorders like autism spectrum disorders (ASD), remains unclear. This is in part because these disorders stem from alterations in brain development, which is immensely complex and guided by a strictly regulated network of molecular circuits in different interacting cell types. ASD, in particular, is a neurodevelopmental disorder that involves deregulation of this intricate and intertwined system through potentially a wide range of heterogeneous insults including genetic, epigenetic, or environmental factors.

While much research remains to unravel this complex disorder, current evidence points to deregulation of molecular circuits with multi-scale consequences on the brain development, including cell proliferation, neuron maturation, abnormal brain growth, and deficits in social, language and behavioral traits (Pramparo, Mol Syst Bio, 2015, Lombardo, Mol Autism, 2017. Given the staggering complexity and heterogeneity associated with autism, we are using top-down statistical and network analysis approaches to elucidate the pathways involved in ASD and to guide the development of novel early-age diagnostics. Specifically, systems biology models will help us to: 1) understand the diversity of phenotypic presentation across ASD subjects, 2) identify the molecular perturbations and their impact on brain development, 3) discover biomarkers for early diagnosis, thus enabling earlier therapeutic intervention while the brain is more flexible for repair. The developed models will be experimentally validated with stem cell biology (Busskamp*, Lewis*, Mol Syst Bio, 2014) and genome editing techniques to gain a mechanistic understanding of processes underlying neurological diseases.