Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder
Authors: Gandal Michael J. , Zhang Pan , Hadjimichael Evi , Walker Rebecca L. , Chen Chao , Liu Shuang , Won Hyejung , van Bakel Harm , Varghese Merina , Wang Yongjun , Shieh Annie W. , Haney Jillian , Parhami Sepideh , Belmont Judson , Kim Minsoo , Moran Losada Patricia , Khan Zenab , Mleczko Justyna , Xia Yan , Dai Rujia , Wang Daifeng , Yang Yucheng T. , Xu Min , Fish Kenneth , Hof Patrick R. , Warrell Jonathan , Fitzgerald Dominic , White Kevin , Jaffe Andrew E. ,   PsychENCODE Consortium, Peters Mette A. , Gerstein Mark , Liu Chunyu , Iakoucheva Lilia M. , Pinto Dalila , Geschwind Daniel H. , Ashley-Koch Allison E. , Crawford Gregory E. , Garrett Melanie E. , Song Lingyun , Safi Alexias , Johnson Graham D. , Wray Gregory A. , Reddy Timothy E , Goes Fernando S. , Zandi Peter , Bryois Julien , Jaffe Andrew E. , Price Amanda J. , Ivanov Nikolay A. , Collado-Torres Leonardo , Hyde Thomas M. , Burke Emily E. , Kleiman Joel E. , Tao Ran , Shin Joo Heon , Akbarian Schahram , Girdhar Kiran , Jiang Yan , Kundakovic Marija , Brown Leanne , Kassim Bibi S. , Park Royce B. , Wiseman Jennifer R , Zharovsky Elizabeth , Jacobov Rivka , Devillers Olivia , Flatow Elie , Hoffman Gabriel E. , Lipska Barbara K. , Lewis David A. , Haroutunian Vahram , Hahn Chang-Gyu , Charney Alexander W. , Dracheva Stella , Kozlenkov Alexey , Belmont Judson , DelValle Diane , Francoeur Nancy , Hadjimichael Evi , Pinto Dalila , van Bakel Harm , Roussos Panos , Fullard John F. , Bendl Jaroslav , Hauberg Mads E. , Mangravite Lara M , Peters Mette A. , Chae Yooree , Peng Junmin , Niu Mingming , Wang Xusheng , Webster Maree J. , Beach Thomas G. , Chen Chao , Jiang Yi , Dai Rujia , Shieh Annie W. , Liu Chunyu , Grennan Kay S. , Xia Yan , Vadukapuram Ramu , Wang Yongjun , Fitzgerald Dominic , Cheng Lijun , Brown Miguel , Brown Mimi , Brunetti Tonya , Goodman Thomas , Alsayed Majd , Gandal Michael J. , Geschwind Daniel H. , Won Hyejung , Polioudakis Damon , Wamsley Brie , Yin Jiani , Hadzic Tarik , De La Torre Ubieta Luis , Swarup Vivek , Sanders Stephan J. , State Matthew W. , Werling Donna M. , An Joon-Yong , Sheppard Brooke , Willsey A. Jeremy , White Kevin P. , Ray Mohana , Giase Gina , Kefi Amira , Mattei Eugenio , Purcaro Michael , Weng Zhiping , Moore Jill , Pratt Henry , Huey Jack , Borrman Tyler , Sullivan Patrick F. , Giusti-Rodriguez Paola , Kim Yunjung , Sullivan Patrick , Szatkiewicz Jin , Rhie Suhn Kyong , Armoskus Christoper , Camarena Adrian , Farnham Peggy J. , Spitsyna Valeria N. , Witt Heather , Schreiner Shannon , Evgrafov Oleg V. , Knowles James A. , Gerstein Mark , Liu Shuang , Wang Daifeng , Navarro Fabio C. P. , Warrell Jonathan , Clarke Declan , Emani Prashant S. , Gu Mengting , Shi Xu , Xu Min , Yang Yucheng T. , Kitchen Robert R. , Gürsoy Gamze , Zhang Jing , Carlyle Becky C. , Nairn Angus C. , Li Mingfeng , Pochareddy Sirisha , Sestan Nenad , Skarica Mario , Li Zhen , Sousa Andre M. M. , Santpere Gabriel , Choi Jinmyung , Zhu Ying , Gao Tianliuyun , Miller Daniel J. , Cherskov Adriana , Yang Mo , Amiri Anahita , Coppola Gianfilippo , Mariani Jessica , Scuderi Soraya , Szekely Anna , Vaccarino Flora M. , Wu Feinan , Weissman Sherman , Roychowdhury Tanmoy , Abyzov Alexej 
Published: December 2018

INTRODUCTION
Our understanding of the pathophysiology of psychiatric disorders, including autism spectrum disorder (ASD), schizophrenia (SCZ), and bipolar disorder (BD), lags behind other fields of medicine. The diagnosis and study of these disorders currently depend on behavioral, symptomatic characterization. Defining genetic contributions to disease risk allows for biological, mechanistic understanding but is challenged by genetic complexity, polygenicity, and the lack of a cohesive neurobiological model to interpret findings.

RATIONALE
The transcriptome represents a quantitative phenotype that provides biological context for understanding the molecular pathways disrupted in major psychiatric disorders. RNA sequencing (RNA-seq) in a large cohort of cases and controls can advance our knowledge of the biology disrupted in each disorder and provide a foundational resource for integration with genomic and genetic data.

RESULTS
Analysis across multiple levels of transcriptomic organization—gene expression, local splicing, transcript isoform expression, and coexpression networks for both protein-coding and noncoding genes—provides an in-depth view of ASD, SCZ, and BD molecular pathology. More than 25% of the transcriptome exhibits differential splicing or expression in at least one disorder, including hundreds of noncoding RNAs (ncRNAs), most of which have unexplored functions but collectively exhibit patterns of selective constraint. Changes at the isoform level, as opposed to the gene level, show the largest effect sizes and genetic enrichment and the greatest disease specificity. We identified coexpression modules associated with each disorder, many with enrichment for cell type–specific markers, and several modules significantly dysregulated across all three disorders. These enabled parsing of down-regulated neuronal and synaptic components into a variety of cell type– and disease-specific signals, including multiple excitatory neuron and distinct interneuron modules with differential patterns of disease association, as well as common and rare genetic risk variant enrichment. The glial-immune signal demonstrates shared disruption of the blood-brain barrier and up-regulation of NFkB-associated genes, as well as disease-specific alterations in microglial-, astrocyte-, and interferon-response modules. A coexpression module associated with psychiatric medication exposure in SCZ and BD was enriched for activity-dependent immediate early gene pathways. To identify causal drivers, we integrated polygenic risk scores and performed a transcriptome-wide association study and summary-data–based Mendelian randomization. Candidate risk genes—5 in ASD, 11 in BD, and 64 in SCZ, including shared genes between SCZ and BD—are supported by multiple methods. These analyses begin to define a mechanistic basis for the composite activity of genetic risk variants.

CONCLUSION
Integration of RNA-seq and genetic data from ASD, SCZ, and BD provides a quantitative, genome-wide resource for mechanistic insight and therapeutic development at Resource.PsychENCODE.org. These data inform the molecular pathways and cell types involved, emphasizing the importance of splicing and isoform-level gene regulatory mechanisms in defining cell type and disease specificity, and, when integrated with genome-wide association studies, permit the discovery of candidate risk genes.

The PsychENCODE cross-disorder transcriptomic resource.
Human brain RNA-seq was integrated with genotypes across individuals with ASD, SCZ, BD, and controls, identifying pervasive dysregulation, including protein-coding, noncoding, splicing, and isoform-level changes. Systems-level and integrative genomic analyses prioritize previously unknown neurogenetic mechanisms and provide insight into the molecular neuropathology of these disorders.