Neuropsychiatric disorders such as autism, schizophrenia, bipolar disorder and intellectual disability are major burden to society. Our current knowledge of their underlying pathophysiology remains limited. However, a contribution of genetic factors has been clearly demonstrated. The goal of this study is to discover shared biological mechanisms between autism, schizophrenia and related disorders through investigation of the networks of interactions between proteins encoded by the high risk genetic factors implicated in these disorders. It is now firmly established that rare Copy Number Variants (CNVs): (1) play significant role in the risk of psychiatric disorders;(2) many high-risk CNVs cross disorder boundaries and are implicated in several psychiatric disorders. CNVs generally involve multiple genes, and how this large number of functionally heterogeneous genes contributes to the pathology is not completely understood. To advance our understanding of CNV contribution to psychiatric diseases, we propose to investigate how the genes from high risk rare CNVs interact on a protein level. The knowledge of the networks connecting CNV genes will help to better understand their pathological impact in different disorders. Using the constructed networks, we will test the hypotheses that: (1) cross-disorder CNVs share interacting protein partners that may explain shared etiology of different disorders;(2) cross-disorder CNVs have a unique set of interacting partners that may explain the differences between disorders. We have selected 11 high risk CNVs (containing 169 genes) that are firmly implicated in two or more psychiatric disorders for this study. Literature search fr binary protein-protein interactions (PPIs) for these 169 genes demonstrated that 33% of them have no PPIs annotated in the public databases, and only 3.5% of them interact with each other. However, it has been repeatedly demonstrated that literature PPIs are biased toward highly studied proteins, incomplete, and often are not as reliable as commonly assumed. Here, we are proposing to perform an unbiased protein interaction screen for 169 genes from high risk cross-disorder CNVs.
Our Specific Aims are as follows: (1) Assemble a library of 169 open reading frame (ORF) clones corresponding to genes from 11 CNVs that confer high risk to psychiatric disorders;(2) Build and validate the cross-disorder CNV interactome;(3) Identify and perform follow-up functional studies of the interacting partners that are shared by or are unique to cross-disorder CNVs.
Our proposed study will gain insights into shared molecular mechanisms of four psychiatric disorders. We will identify protein partners that connect genes from the high-risk copy number variants implicated in these disorders. These proteins may represent potential new drug targets for autism, schizophrenia, bipolar disorder and intellectual disability.
|Brandler, William M; Antaki, Danny; Gujral, Madhusudan et al. (2018) Paternally inherited cis-regulatory structural variants are associated with autism. Science 360:327-331|
|Gandal, Michael J; Zhang, Pan; Hadjimichael, Evi et al. (2018) Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder. Science 362:|
|Pagel, Kymberleigh A; Pejaver, Vikas; Lin, Guan Ning et al. (2017) When loss-of-function is loss of function: assessing mutational signatures and impact of loss-of-function genetic variants. Bioinformatics 33:i389-i398|
|Lin, Guan Ning; Corominas, Roser; Nam, Hyun-Jun et al. (2017) Comprehensive Analyses of Tissue-Specific Networks with Implications to Psychiatric Diseases. Methods Mol Biol 1613:371-402|
|Brandler, William M; Antaki, Danny; Gujral, Madhusudan et al. (2016) Frequency and Complexity of De Novo Structural Mutation in Autism. Am J Hum Genet 98:667-79|
|Yang, Xinping; Coulombe-Huntington, Jasmin; Kang, Shuli et al. (2016) Widespread Expansion of Protein Interaction Capabilities by Alternative Splicing. Cell 164:805-17|
|Lin, Guan Ning; Corominas, Roser; Lemmens, Irma et al. (2015) Spatiotemporal 16p11.2 protein network implicates cortical late mid-fetal brain development and KCTD13-Cul3-RhoA pathway in psychiatric diseases. Neuron 85:742-54|
|Rolland, Thomas; Ta?an, Murat; Charloteaux, Benoit et al. (2014) A proteome-scale map of the human interactome network. Cell 159:1212-1226|