Breen, G.

Collier, D.A.

Gaspar, H.A.

Geschwind, D.H.

Lewis, C.M.

Li, Q.

Roth, B.L.

Sullivan, P.F.

Carolina Digital Repository

 Conference Report: Psychiatric Genomics Consortium Meeting: Pathways to Drugs, London, March 2017To the Editor:The Psychiatric Genomics Consortium (PGC) (www.med.unc. edu/pgc) is delivering an increasing flow of discoveries about the fundamental basis of psychiatric disorders. Moving from the discovery of genome-wide association study (GWAS) loci toward delivering new therapeutic approaches is a challenge that requires a new wave of multidisciplinary work and close liaison between academia and industry. The PGC has recently initiated a new research program to deliver “actionable” find-ings that 1) reveal the fundamental biology of psychiatric dis-orders, 2) inform clinical practice, and 3) deliver new therapeutic targets. Working with industry will be essential, but there is a lack of a forum to exchange ideas with academia. With the aim of filling this gap, the first PGC Pathways to Drugs industry–academia workshop was held at the Institute of Psychiatry, Psychology and Neuroscience, King’s College London on March 2 and 3, 2017. We review the main advances in the field (1).The PGC works on schizophrenia, bipolar disorder, major depressive disorder, autism spectrum disorder, eating disorders, posttraumatic stress disorder, attention-deficit/hyperactivity disorder, Alzheimer’s disease, obsessive-compulsive disorder, Tourette syndrome, and substance use disorders. The PGC has identified more than 300 genetic as-sociations in seven disorders and the aim of the next 5 years is to increase sample sizes to more than 100,000 cases for each psychiatric disorder and find new treatments (1). There is considerable potential for the knowledge derived from GWASs to revitalize industry drug discovery efforts (2). In addition, the complex nature of psychiatric disorders means that the study of biological pathways is also of paramount importance (3).Strong examples of translation are emerging, exemplified by the new anorexia GWAS results, which are inspiring a recon-ceptualization of anorexia nervosa as both a metabolic and psychiatric disorder (4). Major contributions to the PGC from the Lundbeck Foundation Initiative for Integrative Psychiatric Research and others are advancing the genetics of attention-deficit/hyperactivity disorder and autism spectrum disorder (1). Likewise, the UK Biobank (5) (www.ukbiobank.ac.uk) is anextensive resource of approximately 500,000 genotyped in-dividuals. UK Biobank mental health phenotyping on 157,000 patients is available and will reach more than 300,000 in-dividuals, meaning that the UK Biobank will become the largest cohort with mental health questionnaire data worldwide (1). Multiple psychiatric disorders are achieving successful GWASs, leading to the hope that new therapeutic leads can be identified. Finally, the PGC is developing a pipeline for the identification of drug candidates using GWAS results (6). However, these hypotheses are only a first step in the drug discovery process and need to be followed up by functionaland pharmacological studies, in collaboration with industry,and validated by clinical trials.Determining mechanistic hypotheses arising from a GWASassociation is a general problem across medicine. Some re-gions occasionally implicate a single gene with clarity; e.g.,genetic evidence for major depressive disorder has highlightedLRFN5, TCF4, PTPN1, and NEGR1. Other loci are intergenicand far from any known genes; still other loci can contain manygenes or lie within regulatory regions. Connecting GWASfindings to salient genes and mapping regulatory regions iscrucial to identifying targets.Discussions at the conference focused on the integration ofthree sets of methods. First, statistical methods to evaluategene sets, which have been used to demonstrate the salienceof major depressive disorder and schizophrenia GWAS find-ings to the targets of antidepressant and antipsychotic medi-cations (6,7). Second, bioinformatics approaches to leveragefunctional genomic data [gene expression (2), DNA–DNAlooping (8), and epigenomics (9)]. Data from the NationalInstitute of Mental Health PsychENCODE Consortium on brainsamples from people with severe psychiatric disorders willfurther enable this intent (9). Finally, large-scale genetic editingmay be needed (10). Together, the above steps can be used togenerate hypotheses, narrow an interval to include regulatoryregions, or identify key elements.After identifying potentially relevant genes, a key challengeis to determine which of the corresponding proteins are“druggable” to find drugs that could bind to these proteins,regulate their production, prevent protein–protein interactions,or in any way have an influence on their biological mecha-nism(s). These steps are enabled by chemoinformatics andbioinformatics approaches encompassing machine learning,molecular modelling, and data mining. There is an increasingquality of data available in databases collecting drug/targetaffinities (3) (ChEMBL, PHAROS, Ki DB, etc.). Open Targets(www.targetvalidation.org) is a relatively new free platform thatcollects target/phenotype associations from various sources(including UniProt, GWAS Catalog, European VariationArchive, and Gene2Phenotype). These public databases, manypartly funded by industry, are complemented by new open-source drug laboratory resources that can be used to allowscreening of the entire druggable G protein–coupled receptorreceptorome (1).Polygenic risk scores (PRSs) summarize an individual’sgenetic loading for a disorder in a single measure. Their poweris increasing, and it is now possible to calculate PRSs forcommon side effect profiles, such as hypertension and type 2diabetes. In designing clinical trials, the use of PRSs couldallow the recruitment of individuals at high genetic risk, or forstratifying response. Post hoc analysis of PRSs in completedclinical trials may improve the understanding of drug responseprofiles and encourage the pharmaceutical industry to movegenetics earlier within the trial pipeline, to ultimately developcompanion diagnostics with PRSs. Using the power of clinicaltrial samples will require interaction between the researchcommunity and industry to test the utility of PRSs for improvedprescribing and clinical trials.In conclusion, our discussions pointed out the need tointegrate multiple data sources to discover new treatments forpsychiatric disorders: gene expression in different tissues,drug/target affinities, GWAS results, bioinformatics, chemo-informatics, and pharmacogenomics. New drug developmentcould be further aided by the adoption of precision medicinefor psychiatric clinical trials, as exemplified by PRSs and“precision psychiatry.” Ultimately, however, new drug discov-ery in psychiatry will be best enabled if academia and industryjoin forces and if open data- and sample-sharing initiatives areencouraged. Joint industry–academia conferences will beessential to achieve these goals, identify main research ob-jectives, and find a shorter route for drug discovery pipelines.Héléna A. GasparDavid A. CollierDaniel H. GeschwindCathryn M. LewisQingqin LiBryan L. RothPatrick F. SullivanGerome BreenAcknowledgments and DisclosuresThis work was supported by the United Kingdom National Institute forHealth Research Biomedical Research Centre at South London andMaudsley National Health Service Foundation Trust and King’s CollegeLondon (to GB, HAG, CML). The views expressed are those of the authorsand not necessarily those of the National Health Service, the NationalInstitute for Health Research, or the Department of Health.DAC reports employment by Eli Lilly and Company, QL reports employ-ment by Janssen Research and Development, and GB acknowledges fundingfrom Eli Lilly and Illumina, Inc. HAG, DHG, CML, PFS, and BLR report nobiomedical financial interests or potential conflicts of interest.Article InformationFrom the Medical Research Council Social, Genetic and DevelopmentalPsychiatry Centre (HAG, DAC, CML, GB), Institute of Psychiatry, Psychologyand Neuroscience, King’s College London, London; United Kingdom Na-tional Institute for Health Research Biomedical Research Centre for MentalHealth (HAG, CML, GB), South London and Maudsley Hospital, London; andDiscovery Neuroscience Research (DAC), Eli Lilly and Company, Wind-lesham, Surrey, United Kingdom; Program in Neurogenetics (DHG),Department of Neurology and Center for Autism Research and Treatment,Department of Psychiatry, Semel Institute for Neuroscience and HumanBehavior, University of California, Los Angeles, Los Angeles, California;Neuroscience Therapeutic Area (QL), Janssen Research and Development,Titusville, New Jersey; Department of Pharmacology (BLR) and the NationalInstitute of Mental Health Psychoactive Drug Screening Program (BLR),School of Medicine, Department of Genetics (PFS), and Division of ChemicalBiology and Medicinal Chemistry (BLR), Eshelman School of Pharmacy,University of North Carolina at Chapel Hill, Chapel Hill, North Carolina; andthe Department of Medical Epidemiology and Biostatistics (PFS), KarolinskaInstitutet, Stockholm, Sweden.Address correspondence to Gerome Breen, Ph.D., Institute of Psychi-atry, Psychology and Neuroscience, Medical Research Council SocialGenetic and Developmental Psychiatry Research Centre, PO82, MRCSGDP, 16 De Crespgny Park Denmark Hill, London, SE5 8AF UnitedKingdom; E-mail: gerome.breen@gmail.com.Received Dec 1, 2017; revised Jan 17, 2018; accepted Jan 25, 2018.References1. PGC Meeting: Pathways to Drugs. Abstracts. Available at: https://sites.google.com/view/pgc-pharma-meeting/abstracts. AccessedJanuary 4, 2018.2. Fromer M, Roussos P, Sieberts SK, Johnson JS, Kavanagh DH,Perumal T, et al. (2016): Gene expression elucidates functionalimpact of polygenic risk for schizophrenia. Nat Neurosci 19:1442–1453.3. Breen G, Li Q, Roth BL, O’Donnell P, Didriksen M, Dolmetsch R, et al.(2016): Translating genome-wide association findings into new thera-peutics for psychiatry. Nat Neurosci 19:1392–1396.4. Duncan L, Yilmaz Z, Gaspar H, Walters R, Goldstein J, Anttila V, et al.(2017): Significant locus and metabolic genetic correlations revealed ingenome-wide association study of anorexia nervosa. Am J Psychiatry174:850–858.5. Sudlow C, Gallacher J, Allen N, Beral V, Burton P, Danesh J, et al.(2015): UK biobank: An open access resource for identifying thecauses of a wide range of complex diseases of middle and old age.PLoS Med 12:e1001779.6. Gaspar HA, Breen G (2017): Pathways analyses of schizophreniaGWAS focusing on known and novel drug targets [published onlineahead of print Aug 18]. bioRxiv.7. Major Depressive Disorder Working Group of the Psychiatric Geno-mics Consortium, Wray NR, Sullivan PF (2017): Genome-wide asso-ciation analyses identify 44 risk variants and refine the geneticarchitecture of major depressive disorder [published online ahead ofprint Jul 24]. bioRxiv.8. Won H, de la Torre-Ubieta L, Stein JL, Parikshak NN, Huang J,Opland CK, et al. (2016): Chromosome conformation elucidates reg-ulatory relationships in developing human brain. Nature 538:523–527.9. PsychENCODE Consortium, Akbarian S, Liu C, Knowles JA,Vaccarino FM, Farnham PJ, et al. (2015): The PsychENCODE project.Nat Neurosci 18:1707–1712.10. Cai L, Fisher AL, Huang H, Xie Z (2016): CRISPR-mediated genomeediting and human diseases. Genes Dis 3:244–251.

Conference Report: Psychiatric Genomics Consortium Meeting: Pathways to Drugs, London, March 2017

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Conference Report: Psychiatric Genomics Consortium Meeting: Pathways to Drugs, London, March 2017

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