The Psychiatric Cell Map Initiative: A Convergent Systems Biological Approach to Illuminating Key Molecular Pathways in Neuropsychiatric Disorders
2018; Cell Press; Volume: 174; Issue: 3 Linguagem: Inglês
10.1016/j.cell.2018.06.016
ISSN1097-4172
AutoresA. Jeremy Willsey, Montana T. Morris, Sheng Wang, Helen Rankin Willsey, Nawei Sun, Nia Teerikorpi, Tierney Baum, Gerard Cagney, Kevin J. Bender, Tejal A. Desai, Deepak Srivastava, Graeme W. Davis, Jennifer A. Doudna, Edward F. Chang, Vikaas S. Sohal, Daniel H. Lowenstein, Hao Li, David A. Agard, Michael J. Keiser, Brian K. Shoichet, Mark von Zastrow, Lennart Mucke, Steven Finkbeiner, Li Gan, Nenad Šestan, Michael E. Ward, Ruth Hüttenhain, Tomasz J. Nowakowski, Hugo J. Bellen, Loren M. Frank, Mustafa K. Khokha, Richard P. Lifton, Martin Kampmann, Trey Ideker, Matthew W. State, Nevan J. Krogan,
Tópico(s)Cell Image Analysis Techniques
ResumoAlthough gene discovery in neuropsychiatric disorders, including autism spectrum disorder, intellectual disability, epilepsy, schizophrenia, and Tourette disorder, has accelerated, resulting in a large number of molecular clues, it has proven difficult to generate specific hypotheses without the corresponding datasets at the protein complex and functional pathway level. Here, we describe one path forward—an initiative aimed at mapping the physical and genetic interaction networks of these conditions and then using these maps to connect the genomic data to neurobiology and, ultimately, the clinic. These efforts will include a team of geneticists, structural biologists, neurobiologists, systems biologists, and clinicians, leveraging a wide array of experimental approaches and creating a collaborative infrastructure necessary for long-term investigation. This initiative will ultimately intersect with parallel studies that focus on other diseases, as there is a significant overlap with genes implicated in cancer, infectious disease, and congenital heart defects. Although gene discovery in neuropsychiatric disorders, including autism spectrum disorder, intellectual disability, epilepsy, schizophrenia, and Tourette disorder, has accelerated, resulting in a large number of molecular clues, it has proven difficult to generate specific hypotheses without the corresponding datasets at the protein complex and functional pathway level. Here, we describe one path forward—an initiative aimed at mapping the physical and genetic interaction networks of these conditions and then using these maps to connect the genomic data to neurobiology and, ultimately, the clinic. These efforts will include a team of geneticists, structural biologists, neurobiologists, systems biologists, and clinicians, leveraging a wide array of experimental approaches and creating a collaborative infrastructure necessary for long-term investigation. This initiative will ultimately intersect with parallel studies that focus on other diseases, as there is a significant overlap with genes implicated in cancer, infectious disease, and congenital heart defects. The global burden of mental illness is enormous, whether measured in health care expenditures, lost productivity, or personal suffering. Worldwide, mental and substance use disorders rank number five among the top 10 categories contributing to overall disease burden as measured by global disability-adjusted life years (DALYs) and are the leading cause of non-fatal burden of disease (Whiteford et al., 2013Whiteford H.A. Degenhardt L. Rehm J. Baxter A.J. Ferrari A.J. Erskine H.E. Charlson F.J. Norman R.E. Flaxman A.D. Johns N. et al.Global burden of disease attributable to mental and substance use disorders: findings from the Global Burden of Disease Study 2010.Lancet. 2013; 382: 1575-1586Abstract Full Text Full Text PDF PubMed Scopus (2796) Google Scholar). In the United States, neuropsychiatric disorders (NPDs) as a group account for 6 of the top 30 leading contributors to DALYs, and total costs exceed those of any other area of medicine (Murray et al., 2013Murray C.J. Atkinson C. Bhalla K. Birbeck G. Burstein R. Chou D. Dellavalle R. Danaei G. Ezzati M. Fahimi A. et al.U.S. Burden of Disease CollaboratorsThe state of US health, 1990-2010: burden of diseases, injuries, and risk factors.JAMA. 2013; 310: 591-608Crossref PubMed Scopus (1434) Google Scholar, Whiteford et al., 2013Whiteford H.A. Degenhardt L. Rehm J. Baxter A.J. Ferrari A.J. Erskine H.E. Charlson F.J. Norman R.E. Flaxman A.D. Johns N. et al.Global burden of disease attributable to mental and substance use disorders: findings from the Global Burden of Disease Study 2010.Lancet. 2013; 382: 1575-1586Abstract Full Text Full Text PDF PubMed Scopus (2796) Google Scholar). This public health emergency is exacerbated by poor access to care, particularly in much of the developing world, persistent stigma that still plagues those suffering from these conditions, as well as their families, a striking lack of insight into the underlying pathobiology of these syndromes, and a limited armamentarium of efficacious treatments (Krystal and State, 2014Krystal J.H. State M.W. Psychiatric disorders: diagnosis to therapy.Cell. 2014; 157: 201-214Abstract Full Text Full Text PDF PubMed Scopus (74) Google Scholar). Recent advances in gene discovery have set the stage for a transformation in our understanding of NPDs. A confluence of high-throughput genomic technologies, team science, and very large patient cohorts has identified dozens of definitive risk alleles and genes for many NPDs (Lehner et al., 2015Lehner T. Senthil G. Addington A.M. Convergence of advances in genomics, team science, and repositories as drivers of progress in psychiatric genomics.Biol. Psychiatry. 2015; 77: 6-14Abstract Full Text Full Text PDF PubMed Google Scholar). The importance of this recent shift in neuropsychiatric genetics—away from unreliable candidate gene studies to highly reproducible exome-wide and genome-wide methodologies—cannot be overstated. For the first time, the scientific community has access to an expanding set of reliable molecular clues to the etiology of NPDs including autism spectrum disorders (ASD), intellectual disability (ID), epilepsy (EP) and epileptic encephalopathies (EE), Tourette disorder (TD), attention-deficit/hyperactivity disorder (ADHD), obsessive-compulsive disorder (OCD), schizophrenia (SCZ), bipolar disorder (BD), major depressive disorder (MDD), and developmental disorders (DDs) as a group. While there is justifiable excitement about the progress in gene discovery, translating these findings to an understanding of the underlying pathobiology of NPDs remains largely unrealized. This is due to multiple factors. First, risk-associated genetic variants likely affect brain development, an extraordinarily complex process wherein our understanding of molecular, cellular, and circuit level organization is strikingly limited (Figure 1). Furthermore, many of the causal genes likely have pleiotropic biological effects. Consequently, the pertinence of a phenotype downstream of a disease-associated perturbation in a model system is unclear. Second, the proximal cause of NPD is likely alterations in activity patterns in the neural circuits that support mental processes; linking genes to these alterations requires that we understand the relevant underlying biological pathways, the corresponding cell types and neural circuits in which these pathways are present, and the complex interactions between the pathways and the circuits underlying these conditions. Only then will we be able to predict the developmental consequences of risk-associated genetic variants, as well as understand if the resulting changes are actionable later in life. This is a difficult challenge given the functional diversity of genes, cells, and circuits associated with NPDs, and our relatively limited knowledge of pathobiology with which to make sense of this diversity. One particularly promising approach to addressing this challenge rests on the notion of convergence. A convergent framework posits that multiple diverse biological perturbations carrying risk for a given disorder are likely to converge mechanistically in the path from genome to clinical phenotype (Geschwind and State, 2015Geschwind D.H. State M.W. Gene hunting in autism spectrum disorder: on the path to precision medicine.Lancet Neurol. 2015; 14: 1109-1120Abstract Full Text Full Text PDF PubMed Scopus (231) Google Scholar, State and Šestan, 2012State M.W. Šestan N. Neuroscience. The emerging biology of autism spectrum disorders.Science. 2012; 337: 1301-1303Crossref PubMed Scopus (103) Google Scholar, Willsey and State, 2015Willsey A.J. State M.W. Autism spectrum disorders: from genes to neurobiology.Curr. Opin. Neurobiol. 2015; 30: 92-99Crossref PubMed Scopus (85) Google Scholar). Importantly, this common pathway can manifest at many levels, from gene and protein networks within a cell to common patterns of neuronal network dysfunction that manifest in the complex distributed networks of the brain. Indeed, it is now clear that across individuals, similar functional networks can be built out of cells that have widely varying patterns of gene and protein expression (Prinz et al., 2004Prinz A.A. Bucher D. Marder E. Similar network activity from disparate circuit parameters.Nat. Neurosci. 2004; 7: 1345-1352Crossref PubMed Scopus (529) Google Scholar). The converse is also likely to be true: dysfunctional networks may show common modes of dysfunction that arise from very different cellular-level pathways. Accordingly, parallel investigations of multiple genes and mutations are critical. Ideally, such studies would yield functional data for all NPD risk genes and alleles across multiple levels of investigation, including molecular, cell taxonomic, morphological, and neural circuit. Data would include both spatial and temporal dimensions, with a particular focus on function in human brain development. Such data would likely identify the strongest points of functional convergence, the most relevant pathobiology, and an understanding of the functional connections between risk-associated genes. The utility of this knowledge is exemplified in hypertension: large effect mutations converged on salt handling in the kidney, with vectoral effects predicting direction of blood pressure, greatly informing therapy (Lifton et al., 2001Lifton R.P. Gharavi A.G. Geller D.S. Molecular mechanisms of human hypertension.Cell. 2001; 104: 545-556Abstract Full Text Full Text PDF PubMed Scopus (1272) Google Scholar). To date, functional data of NPD risk genes remains strikingly limited across many levels, including the protein level. While emerging datasets exist that allow one to trace the expression of any gene transcribed in the developing and adult human brain and, consequently, to investigate convergence across risk genes (Tebbenkamp et al., 2014Tebbenkamp A.T.N. Willsey A.J. State M.W. Sestan N. The developmental transcriptome of the human brain: implications for neurodevelopmental disorders.Curr. Opin. Neurol. 2014; 27: 149-156Crossref PubMed Scopus (57) Google Scholar, Willsey and State, 2015Willsey A.J. State M.W. Autism spectrum disorders: from genes to neurobiology.Curr. Opin. Neurobiol. 2015; 30: 92-99Crossref PubMed Scopus (85) Google Scholar), we still lack foundational data regarding how the proteins encoded by risk-associated genes interact with other proteins, or DNA. Moreover, we do not understand how the vast majority of risk-associated mutations alter protein structure, function, and physical interactions. Because perturbations of the coding genome strongly contribute to NPD risk (Cappi et al., 2017Cappi C. Oliphant M.E. Peter Z. Zai G. Sullivan C.A.W. Gupta A.R. Hoffman E.J. Virdee M. Jeremy Willsey A. Shavitt R.G. et al.De novo damaging coding mutations are strongly associated with obsessive-compulsive disorder and overlap with autism.bioRxiv. 2017; https://doi.org/10.1101/127712Crossref Scopus (0) Google Scholar, Deciphering Developmental Disorders Study, 2017Deciphering Developmental Disorders StudyPrevalence and architecture of de novo mutations in developmental disorders.Nature. 2017; 542: 433-438Crossref PubMed Scopus (467) Google Scholar, EuroEPINOMICS-RES Consortium et al., 2014EuroEPINOMICS-RES ConsortiumEpilepsy Phenome/Genome ProjectEpi4K ConsortiumDe novo mutations in synaptic transmission genes including DNM1 cause epileptic encephalopathies.Am. J. Hum. Genet. 2014; 95: 360-370Abstract Full Text Full Text PDF PubMed Google Scholar, Fromer et al., 2014Fromer M. Pocklington A.J. Kavanagh D.H. Williams H.J. Dwyer S. Gormley P. Georgieva L. Rees E. Palta P. Ruderfer D.M. et al.De novo mutations in schizophrenia implicate synaptic networks.Nature. 2014; 506: 179-184Crossref PubMed Scopus (893) Google Scholar, Hamdan et al., 2014Hamdan F.F. Srour M. Capo-Chichi J.-M. Daoud H. Nassif C. Patry L. Massicotte C. Ambalavanan A. Spiegelman D. Diallo O. et al.De novo mutations in moderate or severe intellectual disability.PLoS Genet. 2014; 10: e1004772Crossref PubMed Scopus (198) Google Scholar, de Ligt et al., 2012de Ligt J. Willemsen M.H. van Bon B.W. Kleefstra T. Yntema H.G. Kroes T. Vulto-van Silfhout A.T. Koolen D.A. de Vries P. Gilissen C. et al.Diagnostic exome sequencing in persons with severe intellectual disability.N. Engl. J. Med. 2012; 367: 1921-1929Crossref PubMed Scopus (931) Google Scholar, Rauch et al., 2012Rauch A. Wieczorek D. Graf E. Wieland T. Endele S. Schwarzmayr T. Albrecht B. Bartholdi D. Beygo J. Di Donato N. et al.Range of genetic mutations associated with severe non-syndromic sporadic intellectual disability: an exome sequencing study.Lancet. 2012; 380: 1674-1682Abstract Full Text Full Text PDF PubMed Scopus (646) Google Scholar, Sanders et al., 2015Sanders S.J. He X. Willsey A.J. Ercan-Sencicek A.G. Samocha K.E. Cicek A.E. Murtha M.T. Bal V.H. Bishop S.L. Dong S. et al.Autism Sequencing ConsortiumInsights into autism spectrum disorder genomic architecture and biology from 71 risk loci.Neuron. 2015; 87: 1215-1233Abstract Full Text Full Text PDF PubMed Scopus (507) Google Scholar, Satterstrom et al., 2018Satterstrom F.K. Walters R.K. Singh T. Wigdor E.M. Lescai F. Demontis D. Kosmicki J.A. Grove J. Stevens C. Bybjerg-Grauholm J. et al.ASD and ADHD have a similar burden of rare protein-truncating variants.bioRxiv. 2018; https://doi.org/10.1101/277707Crossref Scopus (0) Google Scholar, Willsey et al., 2017Willsey A.J. Fernandez T.V. Yu D. King R.A. Dietrich A. Xing J. Sanders S.J. Mandell J.D. Huang A.Y. Richer P. et al.De novo coding variants are strongly associated with Tourette disorder.Neuron. 2017; 94: 486-499Abstract Full Text Full Text PDF PubMed Google Scholar), determining how genetic variations impact these domains should be a high priority. Fortunately, much of the technology needed to build such resources already exists, and therefore, it is time to establish NPD initiatives similar to the Cancer Cell Mapping Initiative (CCMI; http://www.ccmi.org) (Krogan et al., 2015Krogan N.J. Lippman S. Agard D.A. Ashworth A. Ideker T. The cancer cell map initiative: defining the hallmark networks of cancer.Mol. Cell. 2015; 58: 690-698Abstract Full Text Full Text PDF PubMed Google Scholar) and the Host Pathogen Mapping Initiative (HPMI; http://hpmi.ucsf.edu). For example, our group has recently formed the Psychiatric Cell Map Initiative (PCMI; http://pcmi.ucsf.edu), which is focused on a number of NPDs. Each of these initiatives aim to (1) comprehensively map the networks of physical interactions among relevant proteins; (2) map the genetic interactions between risk genes; and (3) establish computational tools to reveal higher order relationships (Figure 2). As described below, we propose starting with ASD and other early-onset NPDs, due to the substantial number of risk genes of large effect already identified. We argue that these efforts are a critical component of an even broader effort that would understand how these interactions alter neuronal circuit function and behavior and how eventual integration with other data sources (e.g., patient data) has the potential to lead to new and rationally designed treatments for NPD. Unprecedented progress has been made recently in the genetics and genomics of NPDs (Figure 3A). Multiple definitive risk-carrying copy number variations (CNVs), protein-altering mutations, and/or non-coding alleles have been identified in ASD, ID, EP, EE, TD, SCZ, MDD, BD and other disorders such as structural brain abnormalities (Bilgüvar et al., 2010Bilgüvar K. Oztürk A.K. Louvi A. Kwan K.Y. Choi M. Tatli B. Yalnizoğlu D. Tüysüz B. Cağlayan A.O. Gökben S. et al.Whole-exome sequencing identifies recessive WDR62 mutations in severe brain malformations.Nature. 2010; 467: 207-210Crossref PubMed Scopus (344) Google Scholar, Cross-Disorder Group of the Psychiatric Genomics Consortium, 2013Cross-Disorder Group of the Psychiatric Genomics ConsortiumIdentification of risk loci with shared effects on five major psychiatric disorders: a genome-wide analysis.Lancet. 2013; 381: 1371-1379Abstract Full Text Full Text PDF PubMed Scopus (1693) Google Scholar, Deciphering Developmental Disorders Study, 2017Deciphering Developmental Disorders StudyPrevalence and architecture of de novo mutations in developmental disorders.Nature. 2017; 542: 433-438Crossref PubMed Scopus (467) Google Scholar, Wray et al., 2018Wray N.R. Ripke S. Mattheisen M. Trzaskowski M. Byrne E.M. Abdellaoui A. Adams M.J. Agerbo E. Air T.M. Andlauer T.M.F. et al.Genome-wide association analyses identify 44 risk variants and refine the genetic architecture of major depression.Nat. Genet. 2018; 50: 668-681Crossref PubMed Scopus (581) Google Scholar, EuroEPINOMICS-RES Consortium et al., 2014EuroEPINOMICS-RES ConsortiumEpilepsy Phenome/Genome ProjectEpi4K ConsortiumDe novo mutations in synaptic transmission genes including DNM1 cause epileptic encephalopathies.Am. J. Hum. Genet. 2014; 95: 360-370Abstract Full Text Full Text PDF PubMed Google Scholar, Fromer et al., 2014Fromer M. Pocklington A.J. Kavanagh D.H. Williams H.J. Dwyer S. Gormley P. Georgieva L. Rees E. Palta P. Ruderfer D.M. et al.De novo mutations in schizophrenia implicate synaptic networks.Nature. 2014; 506: 179-184Crossref PubMed Scopus (893) Google Scholar, Hamdan et al., 2014Hamdan F.F. Srour M. Capo-Chichi J.-M. Daoud H. Nassif C. Patry L. Massicotte C. Ambalavanan A. Spiegelman D. Diallo O. et al.De novo mutations in moderate or severe intellectual disability.PLoS Genet. 2014; 10: e1004772Crossref PubMed Scopus (198) Google Scholar, Hou et al., 2016Hou L. Bergen S.E. Akula N. Song J. Hultman C.M. Landén M. Adli M. Alda M. Ardau R. Arias B. et al.Genome-wide association study of 40,000 individuals identifies two novel loci associated with bipolar disorder.Hum. Mol. Genet. 2016; 25: 3383-3394Crossref PubMed Scopus (72) Google Scholar, Huang et al., 2017Huang A.Y. Yu D. Davis L.K. Sul J.H. Tsetsos F. Ramensky V. Zelaya I. Ramos E.M. Osiecki L. Chen J.A. et al.Rare copy number variants in NRXN1 and CNTN6 increase risk for Tourette syndrome.Neuron. 2017; 94: 1101-1111Abstract Full Text Full Text PDF PubMed Scopus (56) Google Scholar, International League Against Epilepsy Consortium on Complex Epilepsies., 2014International League Against Epilepsy Consortium on Complex Epilepsies.Genetic determinants of common epilepsies: a meta-analysis of genome-wide association studies.Lancet Neurol. 2014; 13: 893-903Abstract Full Text Full Text PDF PubMed Scopus (143) Google Scholar, Kataoka et al., 2016Kataoka M. Matoba N. Sawada T. Kazuno A.-A. Ishiwata M. Fujii K. Matsuo K. Takata A. Kato T. Exome sequencing for bipolar disorder points to roles of de novo loss-of-function and protein-altering mutations.Mol. Psychiatry. 2016; 21: 885-893Crossref PubMed Google Scholar, de Ligt et al., 2012de Ligt J. Willemsen M.H. van Bon B.W. Kleefstra T. Yntema H.G. Kroes T. Vulto-van Silfhout A.T. Koolen D.A. de Vries P. Gilissen C. et al.Diagnostic exome sequencing in persons with severe intellectual disability.N. Engl. J. Med. 2012; 367: 1921-1929Crossref PubMed Scopus (931) Google Scholar, Power et al., 2017Power R.A. Tansey K.E. Buttenschøn H.N. Cohen-Woods S. Bigdeli T. Hall L.S. Kutalik Z. Lee S.H. Ripke S. Steinberg S. et al.CONVERGE Consortium, CARDIoGRAM Consortium, GERAD1 ConsortiumGenome-wide association for major depression through age at onset stratification: Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium.Biol. Psychiatry. 2017; 81: 325-335Abstract Full Text Full Text PDF PubMed Scopus (87) Google Scholar, Rauch et al., 2012Rauch A. Wieczorek D. Graf E. Wieland T. Endele S. Schwarzmayr T. Albrecht B. Bartholdi D. Beygo J. Di Donato N. et al.Range of genetic mutations associated with severe non-syndromic sporadic intellectual disability: an exome sequencing study.Lancet. 2012; 380: 1674-1682Abstract Full Text Full Text PDF PubMed Scopus (646) Google Scholar, Sanders et al., 2015Sanders S.J. He X. Willsey A.J. Ercan-Sencicek A.G. Samocha K.E. Cicek A.E. Murtha M.T. Bal V.H. Bishop S.L. Dong S. et al.Autism Sequencing ConsortiumInsights into autism spectrum disorder genomic architecture and biology from 71 risk loci.Neuron. 2015; 87: 1215-1233Abstract Full Text Full Text PDF PubMed Scopus (507) Google Scholar, Schizophrenia Working Group of the Psychiatric Genomics Consortium, 2014Schizophrenia Working Group of the Psychiatric Genomics ConsortiumBiological insights from 108 schizophrenia-associated genetic loci.Nature. 2014; 511: 421-427Crossref PubMed Scopus (3662) Google Scholar, Willsey et al., 2017Willsey A.J. Fernandez T.V. Yu D. King R.A. Dietrich A. Xing J. Sanders S.J. Mandell J.D. Huang A.Y. Richer P. et al.De novo coding variants are strongly associated with Tourette disorder.Neuron. 2017; 94: 486-499Abstract Full Text Full Text PDF PubMed Google Scholar). Additional progress is imminent in characterizing the underlying genetics of OCD (Cappi et al., 2017Cappi C. Oliphant M.E. Peter Z. Zai G. Sullivan C.A.W. Gupta A.R. Hoffman E.J. Virdee M. Jeremy Willsey A. Shavitt R.G. et al.De novo damaging coding mutations are strongly associated with obsessive-compulsive disorder and overlap with autism.bioRxiv. 2017; https://doi.org/10.1101/127712Crossref Scopus (0) Google Scholar, International Obsessive Compulsive Disorder Foundation Genetics Collaborative (IOCDF-GC) and OCD Collaborative Genetics Association Studies (OCGAS), 2017International Obsessive Compulsive Disorder Foundation Genetics Collaborative (IOCDF-GC) and OCD Collaborative Genetics Association Studies (OCGAS)Revealing the complex genetic architecture of obsessive-compulsive disorder using meta-analysis.Mol. Psychiatry. 2017; 23: 1181-1188PubMed Google Scholar), ADHD (Garcia-Martínez et al., 2017Garcia-Martínez I. Sánchez-Mora C. Soler Artigas M. Rovira P. Pagerols M. Corrales M. Calvo-Sánchez E. Richarte V. Bustamante M. Sunyer J. et al.Gene-wide association study reveals RNF122 ubiquitin ligase as a novel susceptibility gene for attention deficit hyperactivity disorder.Sci. Rep. 2017; 7: 5407Crossref PubMed Scopus (0) Google Scholar, Satterstrom et al., 2018Satterstrom F.K. Walters R.K. Singh T. Wigdor E.M. Lescai F. Demontis D. Kosmicki J.A. Grove J. Stevens C. Bybjerg-Grauholm J. et al.ASD and ADHD have a similar burden of rare protein-truncating variants.bioRxiv. 2018; https://doi.org/10.1101/277707Crossref Scopus (0) Google Scholar), and other NPDs. Much of this progress is due to technological and methodological advances, and parallel changes in the culture of science, such as team science and open data sharing (Lehner et al., 2015Lehner T. Senthil G. Addington A.M. Convergence of advances in genomics, team science, and repositories as drivers of progress in psychiatric genomics.Biol. Psychiatry. 2015; 77: 6-14Abstract Full Text Full Text PDF PubMed Google Scholar). The large-scale studies that have resulted, combined with high-throughput and cost-effective genomic assays, have been the key to reproducible and reliable gene discovery. Success in identifying specific genetic risk factors has emerged in two broad areas: (1) discovery of rare, large effect de novo variants affecting the coding regions of the genome (Figure 3A), and (2) identification of common variants of small effect, often mapping to the non-coding genome. Initial insights from successful genomic investigations suggest that while each disorder involves a wide variety of risk allele types, the specific architecture of different syndromes varies considerably. For example, for ASD, ID, TD, and EE, the lion’s share of progress in identifying specific loci has been via the identification of highly penetrant de novo protein-altering mutations and genic CNVs (Figure 3A) (EuroEPINOMICS-RES Consortium et al., 2014EuroEPINOMICS-RES ConsortiumEpilepsy Phenome/Genome ProjectEpi4K ConsortiumDe novo mutations in synaptic transmission genes including DNM1 cause epileptic encephalopathies.Am. J. Hum. Genet. 2014; 95: 360-370Abstract Full Text Full Text PDF PubMed Google Scholar, Hamdan et al., 2014Hamdan F.F. Srour M. Capo-Chichi J.-M. Daoud H. Nassif C. Patry L. Massicotte C. Ambalavanan A. Spiegelman D. Diallo O. et al.De novo mutations in moderate or severe intellectual disability.PLoS Genet. 2014; 10: e1004772Crossref PubMed Scopus (198) Google Scholar, Sanders et al., 2015Sanders S.J. He X. Willsey A.J. Ercan-Sencicek A.G. Samocha K.E. Cicek A.E. Murtha M.T. Bal V.H. Bishop S.L. Dong S. et al.Autism Sequencing ConsortiumInsights into autism spectrum disorder genomic architecture and biology from 71 risk loci.Neuron. 2015; 87: 1215-1233Abstract Full Text Full Text PDF PubMed Scopus (507) Google Scholar, Willsey et al., 2017Willsey A.J. Fernandez T.V. Yu D. King R.A. Dietrich A. Xing J. Sanders S.J. Mandell J.D. Huang A.Y. Richer P. et al.De novo coding variants are strongly associated with Tourette disorder.Neuron. 2017; 94: 486-499Abstract Full Text Full Text PDF PubMed Google Scholar). Conversely, for SCZ, MDD, EP, and BD, much of the progress has emerged from genome-wide association studies (GWAS) focusing on common alleles of small individual effect (Wray et al., 2018Wray N.R. Ripke S. Mattheisen M. Trzaskowski M. Byrne E.M. Abdellaoui A. Adams M.J. Agerbo E. Air T.M. Andlauer T.M.F. et al.Genome-wide association analyses identify 44 risk variants and refine the genetic architecture of major depression.Nat. Genet. 2018; 50: 668-681Crossref PubMed Scopus (581) Google Scholar, Hou et al., 2016Hou L. Bergen S.E. Akula N. Song J. Hultman C.M. Landén M. Adli M. Alda M. Ardau R. Arias B. et al.Genome-wide association study of 40,000 individuals identifies two novel loci associated with bipolar disorder.Hum. Mol. Genet. 2016; 25: 3383-3394Crossref PubMed Scopus (72) Google Scholar, International League Against Epilepsy Consortium on Complex Epilepsies., 2014International League Against Epilepsy Consortium on Complex Epilepsies.Genetic determinants of common epilepsies: a meta-analysis of genome-wide association studies.Lancet Neurol. 2014; 13: 893-903Abstract Full Text Full Text PDF PubMed Scopus (143) Google Scholar, Power et al., 2017Power R.A. Tansey K.E. Buttenschøn H.N. Cohen-Woods S. Bigdeli T. Hall L.S. Kutalik Z. Lee S.H. Ripke S. Steinberg S. et al.CONVERGE Consortium, CARDIoGRAM Consortium, GERAD1 ConsortiumGenome-wide association for major depression through age at onset stratification: Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium.Biol. Psychiatry. 2017; 81: 325-335Abstract Full Text Full Text PDF PubMed Scopus (87) Google Scholar, Schizophrenia Working Group of the Psychiatric Genomics Consortium, 2014Schizophrenia Working Group of the Psychiatric Genomics ConsortiumBiological insights from 108 schizophrenia-associated genetic loci.Nature. 2014; 511: 421-427Crossref PubMed Scopus (3662) Google Scholar). The trajectory of discovery for OCD, ADHD, post-traumatic stress disorder (PTSD), anxiety, and eating disorders is not yet clear. The enrichment of rare variants with large effect size within certain NPDs (ASD, TD, ID, EE) may be reflective of greater phenotypic severity and earlier onset of these disorders (i.e., in early childhood versus adulthood), the combination of which could contribute to a larger impairment of reproductive fitness. In this situation, common variants of relatively high frequency would be unlikely due to selection pressure. Nonetheless, there is striking overlap of genes with rare de novo damaging mutations (Cappi et al., 2017Cappi C. Oliphant M.E. Peter Z. Zai G. Sullivan C.A.W. Gupta A.R. Hoffman E.J. Virdee M. Jeremy Willsey A. Shavitt R.G. et al.De novo damaging coding mutations are strongly associated with obsessive-compulsive disorder and overlap with autism.bioRxiv. 2017; https://doi.org/10.1101/127712Crossref Scopus (0) Google Scholar, Fromer et al., 2014Fromer M. Pocklington A.J. Kavanagh D.H. Williams H.J. Dwyer S. Gormley P. Georgieva L. Rees E. Palta P. Ruderfer D.M. et al.De novo mutations in schizophrenia implicate synaptic networks.Nature. 2014; 506: 179-184Crossref PubMed Scopus (893) Google Scholar, Sanders et al., 2015Sanders S.J. He X. Willsey A.J. Ercan-Sencicek A.G. Samocha K.E. Cicek A.E. Murtha M.T. Bal V.H. Bishop S.L. Dong S. et al.Autism Sequencing ConsortiumInsights into autism spectrum disorder genomic architecture and biology from 71 risk loci.Neuron. 2015; 87: 1215-1233Abstract Full Text Full Text PDF PubMed Scopus (507) Google Scholar, Satterstrom et al., 2018Satterstrom F.K. Walters R.K. Singh T. Wigdor E.M. Lescai F. Demontis D. Kosmicki J.A. Grove J. Stevens C. Bybjerg-Grauholm J. et al.ASD and ADHD have a similar burden of rare protein-truncating variants.bioRxiv. 2018; https://doi.org/10.1101/277707Crossref Scopus (0) Google Scholar) (Figure 3; Tables S2 and S3), genes found in large multigenic CNVs (Sanders et al., 2015Sanders S.J. He X. Willsey A.J. Ercan-Sencicek A.G. Samocha K.E. Cicek A.E. Murtha M.T. Bal V.H. Bishop S.L. Dong S. et al.Autism Sequencing ConsortiumInsights into autism spectrum disorder genomic architecture and biology from 71 risk loci.Neuron. 2015; 87: 1215-1233Abstract Full Text Full Text PDF PubMed Scopus (507) Google Scholar), and common variants implicated by GWAS across these conditions (Autism Spectrum Disorders Working Group of The Psychiatric Genomics Consortium, 2017Autism Spectrum Disorders Working Group of The Psychiatric Genomics ConsortiumMeta-analysis of GWAS of over 16,000 individuals with autism spectrum disorder highlights a novel locus at 10q24.32 and a significant overlap with schizophrenia.Mol. Autism. 2017; 8: 21Crossref PubMed Scopus (120) Google Scholar, Cross-Disorder Group of the Psychiatric Genomics Consortium, 2013Cross-Disorder Group of the Psychiatric Genomics ConsortiumIdentification of risk
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