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For example, in the US, total costs exceed those of any other area of medicine. This public health emergency is exacerbated by a striking lack of insight into the underlying biology, and the limited armamentarium of highly efficacious treatments. However, recent advances in gene discovery are setting the stage for a transformation in the understanding of psychiatric disorders. The confluence of high throughput genomic technologies, team science, and very large patient cohorts has led to the identification of dozens of definitive risk genes. For the first time, the community has access to an expanding set of reliable molecular clues to the etiology of common psychiatric disorders including autism spectrum disorders, Tourette disorder, intellectual disability, epilepsy, schizophrenia, and bipolar disorder. Yet while there is justifiable excitement about the progress in gene discovery, the promise of characterizing the underlying biology of psychiatric disorders remains largely unrealized. This is in part due to the large number of genes associated with these disorders and the complicated nature of the human brain. One particularly promising approach to addressing this challenge rests on the notion of convergence鈥攖he idea that the diverse set of genes carrying risk for a given disorder are likely to converge at some point in the path from genome to behavior to confer risk. Accordingly, parallel investigation of multiple genes and mutations at scale are a critical part of the experimental repertoire. Because we are starting with limited information about the underlying biology, it is critical to focus these investigations on first elucidating the specific molecular pathways that are impacted, so that we can build upwards into understanding more and more complicated aspects of these disorders. For example, the cell types and developmental processes that go awry in these disorders. Ideally, these data would capture both spatial, temporal, and cell-type dimensions, with a particular focus on roles in human brain development. This scope of data allows us to pinpoint the strongest points of convergence, and thus, the most relevant biology. Unfortunately, these types of resources remain extraordinarily limited. This is particularly true for protein-level data. While there are emerging datasets that allow one to trace, for example, the expression of any gene in the human brain, there is a paucity of foundational data on the dynamic physical (protein-protein and protein-DNA) interactome of risk genes. These data are critical for understanding molecular pathways. Fortunately however, the technology to begin to build such resources already exists. Consequently, we are proposing the establishment of the Psychiatric Cell Map Initiative (PCMI). This will be a collaborative effort that will be patterned primarily after the Cancer Cell Map Initiative (CCMI) and the Host Pathogen Map Initiative (HPMI). Broadly, the PCMI seeks to begin the generation of the necessary data and insights to bridge the knowledge gap between the genome and the clinic, as well as establish the infrastructure for efficient and sustained investigation well into the future. We have two areas of focus: (1) Generation of data and insights. This includes generation of physical interaction (protein-protein and protein-DNA), co-expression, genetic interaction, and small-molecule interaction networks from multiple cell types. We will integrate these data to produce critical insights into the underlying biology of psychiatric disorders. (2) Building of infrastructure. Our scope includes creating public databases and integrative analytic tools, establishing interfaces with clinical efforts, generating an extensive network of collaborators with diverse expertise, and training the next generation of scientists to tackle these critical challenges. - Matt State, Nevan Krogan </p> </div> </div> </div> </div> </div> <div class="col-md-4 no-padding middle-two" id="middle_top_associate11"> <div class="directortxt associate-directors-contain" id="associate_top_slide_211"> <h2>PCMI DIRECTORS STATEMENT</h2> <div class="dynamic-height-wrap"> <p id="associate_top_slide_text11" class="">The global burden of mental illness is enormous, whether measured in health care expenditures, lost productivity, or personal suffering. For example, in the US, total costs exceed those of any other area of medicine. This public health emergency is exacerbated by a striking lack of insight into the underlying biology, and the limited armamentarium of highly efficacious treatments. However, recent advances in gene discover...</p> </div>  <span><a class="hvr-icon-float-away-left slide-toggle" id="associate_top_action11" onclick="$(this).toggleClass('hvr-icon-float-away')">Read More</a></span> </div> </div> <div class="col-md-8 no-padding"> <div class=" box-inner slider2-image-class large-block-strict" > <div class="overlay"></div> <img src="https://pcmi.ucsf.edu/site-assets/images/1493655619_About us_Director StatementPCMI-2.jpg" alt="" class="header-image associate-top-image" /> </div> </div> </div> <script> $(document).ready(function() { /* Animation time taken for text to appear */ var animation_time11=500; /* Delay time for two texts to appear */ var delay_time11=125; /* Mission statement animation time */ var mission_statement_animation_time11=1500; /* Slide Animation Time */ var slide_animation_time11=250; /* Text appearing animation timer */ var text_li_ani_timer11=750; /* Text Appearing delay */ var text_li_ani_delay11=250; var original_content11 = $("#associate_top_slide_text11").html(); 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This will be conducted in neurons and other relevant cell types derived from human induced pluripotent stem cells (iPSCs) using affinity purification mass spectrometry, CRISPR-based genetics techniques, RNA-Seq, and ChIP-Seq....</p> </div> <span class='read'><a class="hvr-icon-float-away slide-toggle action" onclick="$(this).toggleClass('hvr-icon-float-away')" style="line-height:1px !important">Read More</a></span> <div class="list light hover" style="display:none;"> <div class="listin hvr-fade"> <p> <img src="images/ccmi.png" alt="" class="header-small-icon"> <span class="header_icon_text">Cancer Cell<br> Map Initiatives</span> </p> <div class="clearfix"></div> </div> <div class="listin hvr-fade"> <p> <img src="images/hpmi.png" alt="" class="header-small-icon"> <span class="header_icon_text">Host Pathogen<br> Map Initiatives</span> </p> <div class="clearfix"></div> </div> <div class="listin hvr-fade hvrfade-last"> <p> <img src="images/pcmi.png" alt="" class="header-small-icon"> <span class="header_icon_text">Psychiatric Cell<br> Map Initiatives</span> </p> <div class="clearfix"></div> </div> <div class="clearfix"></div> </div> </div> </div> <div class="item col-xs-12 col-sm-12 col-md-8 no-padding box2 dark hover last-header"> <div class="con-text box-inner"> <p class="text_to_iterate"> PCMI seeks to map the physical, co-expression, and genetic interaction networks associated with the ever-growing list of psychiatric disorder-associated genes. 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