There have been extensive analyses of the ability of cells to generate

Complex disorders and diseases, such as cancer and heart disease, have multifactorial etiologies with genetic, physiological, and environmental factors. Understanding their interactions enables effective research, diagnosis, and treatment. Pathway analysis searches for sets of genes differentially expressed in certain phenotypes, and this genetic context provides a foothold for further work. This study extended the network-based algorithm HotNet2 to find gene clusters involved in neuropsychiatric diseases. Autism gene expression data from the Morrow Lab at Brown University revealed pathways involved in neurotransmitter release by soluble N-ethylmaleimide sensitive factor attachment protein receptors (SNARE) and regulation of the inhibitory neurotransmitter γ-aminobutyic acid (GABA). Analysis of a bipolar disorder genome-wide association study from the Wellcome Trust Case Control Consortium verified association of cell adhesion genes involved in synaptic development. The extension of HotNet to gene expression and single-nucleotide polymorphism data opens the door to a wide range of future computational studies and meta-analyses based on complementary biological experiments. This study’s approach offers mechanistic understanding and logical treatment targets for complex disorders.