Summaries of oral sessions at the XXI World Congress of Psychiatric Genetics, Boston, Massachusetts, 17-21 October 2013: state of the field.

Review article 125

Summaries of oral sessions at the XXI World Congress of Psychiatric Genetics, Boston, Massachusetts, 17–21 October 2013: state of the field Hilary Akpudoa, Branko Aleksicg, Anna Alkelaih, Christie Burtonf, Tania Carillo Roai, David T.W. Chenb, Min-Chih Chengl, Enrico Cocchin, Lea K. Davisc, Isabele G. Giorio, Leon M. Hubbardp, Alison Merikangass, Nagaraj S. Moilyt, Adeniran Okewoleu, Emily Olfsond, Irene Pappav,w,x, Markus Reittj, Ajeet B. Singhz, Julia Steinbergq,r, Jana Strohmaierk, Te-Tien Tingm, Kimm J.E. van Hulzeny, Anne O’Sheae and Lynn E. DeLisie The XXI World Congress of Psychiatric Genetics (WCPG), sponsored by the International Society of Psychiatric Genetics (ISPG), took place in Boston, Massachusetts, on 17–21 October 2013. Approximately 900 participants gathered to discuss the latest findings in this rapidly advancing field. The following report was written by student travel awardees. Each was assigned one or more sessions as a rapporteur. This manuscript represents topics covered in most, but not all of the oral presentations during the conference, and contains some of the major notable new findings reported. Psychiatr Genet 24:125–150 © 2014 Wolters Kluwer Health | Lippincott Williams & Wilkins. Psychiatric Genetics 2014, 24:125–150 Keywords: commercial DNA testing, DNA, International Society of Psychiatric Genetics, post-traumatic stress disorder, schizophrenia, sequencing, substance abuse, World Congress of Psychiatric Genetics a Meharry Medical College, Nashville, Tennessee, bHuman Genetics Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland, cSection of Genetic Medicine, Department of Medicine, University of Chicago, Chicago, Illinois, dWashington University School of Medicine at Washington University Medical Center, St Louis, Missouri, eHarvard Medical School, VA Boston Healthcare System, Brockton, Massachusetts, fHospital for Sick Children, Toronto, Ontario, USA, gDepartment of Psychiatry, Nagoya

Introduction The International Society of Psychiatric Genetics (ISPG) was first established as a nonprofit corporation in the USA in 1992 and is now a worldwide organization that strives for the highest standards in the application of genetic methodologies to the study of psychiatric disorders. It was formed to provide a stable structure for continual congresses in this field with the mission of overseeing an annual gathering at different international locations. The 2013 World Congress of Psychiatric Genetics (WCPG), sponsored by the ISPG, took place on 17–21 October

University Graduate School of Medicine, Nagoya, Japan, hThe Weizmann Institute of Science, Rehovot, Israel, iMax-Planck Institute of Psychiatry, Munich, jSection on Psychiatric Genetics, University Medical Center, University of Goettingen, Goettingen, kDepartment of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Heidelberg, Germany, lDepartment of Psychiatry, Yuli Mental Health Research Center, Yuli Branch, Taipei Veterans General Hospital, Yuli, mInstitute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei, Taiwan, nInstitute of Psychiatry, Department of Biomedical and Neuromotor Science – DIBINEM, University of Bologna, Bologna, Italy, oDepartment of General Biology, Fluminense Federal University, Rio de Janeiro, Brazil, pMRC Centre for Neuropsychiatric Genetics and Genomic, Institute of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, qMedical Research Council Functional Genomics Unit, Department of Physiology, Anatomy, and Genetics, rThe Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK, sDepartment of Psychiatry and Neuropsychiatric Genetics Research Group, Trinity College Dublin, Trinity Centre for Health Sciences, St James’s Hospital, Dublin, Ireland, tNeurosciences, Molecular Genetics Laboratory, Neurobiology Research Center, National Institute of Mental Health and Neurosciences, uNeuropsychiatric Hospital, Abeokuta, Nigeria, vSchool of Pedagogical and Educational Sciences, Erasmus University, wThe Generation R Study Group, Erasmus University Medical Center, xDepartment of Child and Adolescent Psychiatry/Psychology, Erasmus University Medical Center-Sophia Children’s Hospital, Rotterdam, yDepartment of Human Genetics, Radboud University Medical Centre, Nijmegen, The Netherlands and zSchool of Medicine, Deakin University, Victoria, Australia Correspondence to Lynn E. DeLisi, MD, Harvard Medical School, Brockton VA Boston Healthcare System, 940 Belmont Street, Brockton, MA 02301, USA Tel: + 1 774 826 3155; fax: + 1 774 826 1758; e-mail: [email protected] Received 13 February 2014 Accepted 20 April 2014

2013 in Boston. Over 900 researchers in psychiatry, psychology, and molecular genetics participated. The congress was co-chaired by Harvard professors, Drs Jordan Smoller and Lynn DeLisi. Rapporteurs for these sessions were student travel awardees. Their tasks were to summarize individual sessions as well as relevant discussions. Similar accounts of the 2007, 2008, 2009, 2010, 2011, and 2012 congresses held in New York City, Osaka, Japan, San Diego, California, Athens, Greece, and Washington, DC, and Hamburg, Germany, have been published previously (Alkelai et al., 2008; Bergen et al., 2009, 2011; Amstadter et al., 2010; Dai et al., 2012; Anderson-Schmidt et al., 2013).

Rapporteurs in alphabetical order, all performed equal work. Anne O’Shea and Lynn E. DeLisi are the coordinators of rapporteurs and this report and also the editors of this report. 0955-8829 © 2014 Wolters Kluwer Health | Lippincott Williams & Wilkins

The following report represents the topics and major findings of the year covered during most oral sessions and DOI: 10.1097/YPG.0000000000000043

Copyright © Lippincott Williams & Wilkins. Unauthorized reproduction of this article is prohibited.

126 Psychiatric Genetics 2014, Vol 24 No 4

they appear together under major topics, irrespective of the timing or the format of specific sessions. During this congress, the most obvious theme was the necessity for large international collaborations as the way forward to unravel the genetic architecture of mental illness and that the outcome may be the defining of a new diagnostic system.

Changing the DSM through genetics (reported by Ajeet B. Singh) The theme of this 2013 congress was ‘Defining Mental Illness through Genetics’ and was discussed in an opening plenary session chaired by Dr Steven Hyman (Harvard University and Broad Institute, former Director of NIMH, USA). Presentations from a panel of experts included Drs Kenneth Kendler (Virginia, USA), Myrna Weissman (Columbia, New York, USA), Jan Buitelaar (Nijmegen, the Netherlands), Michael Owens (Cardiff, UK), and Cuthbert (NIMH, USA). Tensions between dimensional and categorical nosologies, pleiotropy, and polygenetic inheritance, stochastic and deterministic mechanisms, and an environmental epigenetically mediated neurodevelopmental overlay yielded a thoughtprovoking session. Dr Hyman quoted Robins and Guze (1970) ‘Reliable and valid diagnosis would follow from – clinical description, laboratory studies, delineation of one disorder from another, follow-up studies, family studies’, but then reflected that ‘clinically diagnosis transgresses boundaries’ and the DSM (Diagnostic & Statistical Manual) was akin to an ‘automobile pile-up: several hundred disorders with arbitrary thresholds’. Comorbidity was common in part because of the ‘desire to achieve homogeneity so categories are over specified’ and conveniently ‘those that don’t fit in get the label, NOS (Not Otherwise Specified)’. He went on to state that the DSM is ‘easy to make fun of, hard to do better – there is no bright line to define categories’. He concluded that it is ‘not clear how much genetics itself will contribute to diagnosis’, but believed that ‘dimensions permit empirical data to influence diagnostic thresholds’. Dr Kendler postulated six phases of how psychiatric nosology and genetics have interacted historically. ‘Phase 1, an ancillary source of diagnostic information; Phase 2, family history as a formal validator of a proposed diagnosis (Robins and Guze, 1970); Phase 3, multivariate models; Phase 4, candidate genes; Phase 5, GWAS and patterns of SNPs; Phase 6, polygene scores’. He reflected on early work examining the influence of family history on the prognosis of schizophrenia (Fowler et al., 1972), and elegantly articulated the problems of multivariate models ‘If mood disorders are mammals and anxiety disorders are fish is GAD (Generalized Anxiety Disorder) a dolphin?’ He went on to lament the ‘nosological castles on sand from small variance findings’ stemming from candidate gene studies evolving into the ‘complex mix …

spectrum of genes’ identified in genome-wide association studies (GWAS). He concluded by positing that the next phase will be polygene scores that indicate diagnostic likelihood, citing the work of Naomi Wray and colleagues indicating overlapping genetics of psychiatric illnesses and stochastic heredity (Lee et al., 2013). He concluded ‘What do nosologists want from genetics? This, depends on the model of psychiatric diagnosis. If we want syndromal, descriptive diagnoses, such as with the DSM, then nosologists want aggregate data, the broad picture (heritability/polygene scores). But, if we move towards more etiologically based diagnoses, then the picture shifts considerably. The results obtained at single variants and aggregates of genetic variants, and probably associated network analysis, will ultimately prove more useful’. Dr Weissman provided an epidemiological perspective ‘large representative samples may generate new phenotypes, endophenotypes independent of disease. Hypotheses regarding environmental exposure can be generated’. ‘The hottest area is epigenetics’ and environmental factors (including in-utero exposure) could be important by modifying the epigenetic imprint. Dr Buitelaar suggested that ‘genetics will probably not deliver defining of diagnosis’. Increasing recognition of the role of de-novo mutations and data indicating ‘hundreds of common variants with very small effect size appear to play a role’, underscoring his view. He raised the importance of ‘reconceptualized psychiatry as disease of not just brain but also body’ with pleiotropy between somatic and mental illnesses. The promise of genetics is that it ‘can delineate underlying mechanisms and more homogeneous subgroups’, helping us ‘deconstruct disorders’, potentially yielding novel preventative and therapeutic approaches. Dr Owens emphasized a ‘gradient of neurodevelopmental pathology’, with damaging mutations more often seen in intellectual disability than autism spectrum disorders (ASDs) or schizophrenia, ‘supporting a gradient of neurodevelopmental impairment’ mediated by genetics. He drew an analogy to myocardial infarction (MI) involving genes, environment, risk biomarkers (e.g. blood pressure, blood sugar, lipids), pathology (atheroma), then symptoms, and finally MI. He wondered whether risk markers, ‘distal’ biomarkers (such as lipids in MI), proximal biomarkers (such as abnormal ECG in MI), preclinical syndrome, and clinical syndrome could also be developed for psychiatric conditions. He posited a ‘multilevel psychiatric diagnosis of the future’. Dr Cuthbert, as the final panel presenter, focused on the ‘NIMH Research Domain Criteria (RDoc) Project’ as a needed ‘framework for research’ separate from the DSM – ‘go back to ground zero … organize research in different ways from the DSM approach’, reflecting that ‘any nosology is imposing a structure on a much more complex


XXI World Congress of Psychiatric Genetics Akpudo et al. 127

reality’. Greater focus on ‘dimensions of observable behavior and neurobiological mechanisms’ with ‘a lot of interest in pathways, polygenes, functional gene groups’ and a need to ‘also try to focus research on developmental processes’ would be critical to advancing the understanding of psychiatric disorders. He highlighted the work of Lips et al. (2012) on functional synaptic gene groups as risk factors for schizophrenia as an example of polygene pathways.

Affective disorders and PTSD Genetics of mood disorders (reported by Nagaraj S. Moily)

Dr Emma Knowles (Yale University, USA) presented her work on identifying genes involved in major depression using whole-genome sequencing. This analysis was completed on 530 Mexican-American individuals from extended pedigrees and showed two novel variants on chromosome 3 that were associated significantly with depression. One was located at ∼ 188.0 Mb (χ2 = 40.15, P = 2.35 × 10− 10) and the other at ∼ 67.0 Mb (χ2 = 35.21, P = 2.96 × 10 − 9). Dr Alexander Charney (Icahn School of Medicine at Mount Sinai, USA) presented bipolar disorder (BPD) GWAS data of 13 741 cases and 19 762 controls. The meta-analysis combined four independent GWAS datasets after accounting for overlap: a Swedish national sample (2121 cases, 5894 controls), a UK sample (2595 cases, 5645 controls), a sample of mixed European ancestry (1512 cases, 1338 controls), and the previously published PGC BPD (Psychiatric GWAS Consortium Bipolar Disorder Working Group, 2011) sample (7481 cases, 9250 controls). Eight regions were identified that showed genome-wide significance. These included genes associated with the calcium channel and the fragile X mental retardation protein (FMRP). Copy number variant (CNV) burden analysis carried out on a subset of BPD samples did not reach significance and showed a limited contribution of CNVs toward the risk for BPD. Dr Pamela Sklar (Icahn School of Medicine at Mount Sinai, USA) spoke on the progress of the Psychiatric Genomics Consortium (PGC) for BPD. The wave 2 samples of PGC were updated with additional samples of ∼ 8643 cases and 13 949 controls from Germany, Sweden, Norway, and the USA, bringing the total to 47 719 samples: 19 631 cases and 28 088 controls. The analyses of the entire dataset yielded additional genome-wide significant findings as well as strong support for previous loci. Eight genome-wide significant loci were reported in the primary analysis and an additional 10 loci were reported in the replication analysis. She also presented her preliminary work on shared loci and shared pathways of BPD with schizophrenia. She emphasized the importance of continued efforts to increase the number of samples to uncover more associations with BPD and to

consider genetic analyses across current diagnostic boundaries. Dr Fernando Goes (Johns Hopkins University School of Medicine, USA) spoke about next-generation sequencing of synaptic genes in familial major depressive disorder (MDD). He elaborated the role of synaptic pathophysiology in the etiology of major depression and that the synapse is the primary target of most antidepressant drugs. Next-generation sequencing of all exons in 2011 genes that comprise the vast majority of genes expressed in the synapse was performed in 350 cases from the Genetics of Recurrent Early-Onset Depression family collection and equal numbers of controls to identify rare variants involved in major depression. Gene-based and pathway-based mutational burden analyses did yield some interesting hits, but they did not survive Bonferroni correction nor were they exome wide. Some of the suggestive findings involved intriguing genes involved in actin regulation and a moderately significant enrichment of rare damaging single-nucleotide polymorphisms (SNPs) in synaptic genes. Dr Catherine Schaefer (Kaiser Permanente Research Program on Genes, Environment and Health, USA) reported on the GWAS of MDD in the Kaiser Permanente Research Cohort. She highlighted the availability of comprehensive longitudinal electronic medical records and phenotypic clarity linked to genomewide genotype data in the present study. More than 9000 cases of MDD and 54 000 controls were screened for analysis. The GWAS analysis was carried out using Plink v1.07 (http://pngu.mgh.harvard.edu/ ~ purcell/plink/down load.shtml) using an additive logistic regression model that controlled for age, sex, and ancestry principal components. A single SNP, rs35350027, on the SHROOM3 gene on chromosome 4, reached a genome-wide level of statistical significance (odds ratio = 0.85; 95% confidence interval: 0.81, 0.90; P = 5.14 × 10 − 9). Eight other SNPs were associated with MDD with P-values less than 10 − 5. The study did not replicate or overlap the suggestive associations of the findings in the MDD Working Group of the Psychiatric GWAS Consortium other than a single SNP on chromosome 7 that is near a suggestive signal in a male-only analysis. The results reflect the heterogeneity and complexity that remain obstacles for understanding the underlying genetics of MDD. Dr Gerome Breen (Institute of Psychiatry, King’s College, London) cited the lack of significant findings in GWAS studies of MDD (Major Depressive Disorder Working Group of the Psychiatric GWAS Consortium et al., 2013) and spoke on the PGC2 for MDD. The present study samples involved almost doubling of the sample size of the cases (n = 18 000) and a large increase in the number of controls (n = 25 201), but did not yield any genome-wide significant hits, and provided few suggestive findings. The issue of increasing the power of



the study by increasing the sample size was discussed for MDD. The importance of phenotypic reliability and adjustment for heterogeneity in MDD were also highlighted. The BPD sequencing consortium (reported by Anna Alkelai)

Dr Jared Roach (Institute for Systems Biology) discussed high-throughput sequencing of pedigrees, ‘family genomics’, and presented a sequencing study that included 200 whole genomes from 43 BPD families and 158 from 34 non-BPD families. This study showed candidate variants in different genes. One of them is located in MTRNR2L1. Pathway analyses of the data implicated the involvement of gene networks, that is, in the voltagegated calcium channels and GABA pathways. Dr Guy Rouleau (McGill University) discussed the failure of linkage and GWAS to explain the high BPD heritability. He highlighted the importance of looking for multiple highly penetrant rare variants to fully explain the missing heritability in BPD. He presented a highthroughput sequencing family-based study that focused on a well-defined subphenotype of BPD (patients with a positive response to lithium therapy). Some promising BPD susceptibility variants (∼12 variants in each family) were found by prioritization of rare (< 1%) variants that fully or partially segregate with affected status within families. Some of these variants are located in genes such as OSBPL6, SH3BP5, and HTR3A. He also presented analyses still in progress from lymphoblastoid cell lines that explored the biological effect of the novel sequenced variants. Dr Francis McMahon (NIMH Intramural Research Program, National Institutes of Health) introduced the ‘AMBiGen: A Next-Generation Sequencing Study in the Plain People’ project. He presented a SNP chip and whole-exome sequencing study in an Amish and Mennonite homogeneous BPD sample. A total of 170 BPD individuals were studied, most of whom came from one large Amish kindred. The SNP genotyping was performed using the HumanOmniExpress BeadChip Kit (Illumina Inc., San Diego, California, USA) and the Genome-Wide Human SNP Array 6.0 (Affymetrix, Santa Clara, California, USA). Identity by descent and shared segment analyses were carried out using Beagle and Plink software. These analyses found suggestive candidate chromosomal regions such as 1p34.3, harboring many genes. Whole-exome sequencing was performed in 50 selected cases and candidate variants were found in genes such as EPHA10, SCRN3, and HEATR2. Dr Eli Stahl (Icahn School of Medicine at Mount Sinai) presented a large-scale whole-exome sequencing study in three different BPD cohorts (BLISS, Swedish BPD case–control cohort, and BRIDGES). No overall significant findings were found. However, one notable

variant was found in the GRIN2C gene. This session emphasized the importance of data sharing and it was made known that additional groups were needed to join the consortium. Genetics of PTSD (reported by Markus Reitt and Jana Strohmaier)

Although traumatic events are frequent and experienced by ∼ 50–85% of Americans, only about 8% develop posttraumatic stress disorder (PTSD). The rate is higher in individuals who experienced combat (18%) and twice as high in women than in men. The experience of stress activates the hypothalamic–pituitary–adrenocortical (HPA) axis, which also influences memory consolidation and retrieval. Chronic or extreme stress can cause longlasting alterations of the HPA axis. The contribution of epigenetic mechanisms toward stress and trauma include DNA methylation, chromatin remodeling, and RNA/miRNA. An example of how epigenetics and environment factors (particularly early life stress) may interact is the finding that childhood trauma deregulates the stress response through DNA demethylation in the FKBP5 gene (Klengel et al., 2013). Dr Kerry Ressler (Emory University) spoke about the intergenerational transmission of learned olfactory fear in rodents – a possible tractable animal model for the intergenerational transmission of PTSD in humans (Dias and Ressler, 2013). The olfactory system is associated closely with emotion. The receptors in the nose directly project through the olfactory bulb to the prefrontal cortex, amygdala, and hippocampus. The olfactory system has a high level of neural plasticity. Stem cells in the olfactory epithelium are constantly replacing new olfactory sensory neurons. Three days of olfactory fear conditioning in mice have already been shown to enhance the number of neurons in the nose and axons to the bulb and may model epigenetic alteration in primary brain regions critical for fear memory. These neuroanatomical and epigenetic alterations may also be inherited. In fact, two generations of naïve offspring of trained male mice (fathers and offspring never came in contact) showed enhanced behavioral sensitivity to the paternalconditioned odor and significantly enhanced numbers of odor receptors, which seem to result from methylation changes of the specific receptor gene that detects the conditioned odor. In a cross-fostering design, neuroanatomical and behavioral changes in the offspring were associated with their biological parent’s training. These findings as well as methylation-specific imprinted DNA of odor receptor genes after conditioning in sperm suggest that transgenerational effects can be inherited through changes in parental gametes. Professor Akira Sawa (Johns Hopkins School of Medicine) spoke about the disturbance of epigenetic control on stress response and dopaminergic neurotransmission in mental illness. Psychiatric disorders often



develop in late adolescence and young adulthood, a time of increased social stress that may disrupt normal brain maturation and influence behavioral patterns in adulthood. This process may be mediated by epigenetic mechanisms. In an animal model, social stress was operationalized through social isolation (Niwa et al., 2013). After 5–8 weeks of isolation, altered prepulse inhibition was observed, possibly mediated by the HPA axis, but only when combined with an appropriate genetic risk (in this case, dominant-negative DISC1 in the GXE mice). The application of a glucocorticoid receptor antagonist normalized the prepulse inhibition alteration and decreased extracellular dopamine levels. This influence of glucocorticoids on dopamine levels may be because of epigenetic alteration. In fact, increased DNA methylation of a specific projection of dopamine neurons (mesocortical projection) was observed. The increased DNA methylation continued for months and could be normalized by the glucocorticoid receptor antagonist. The results suggest that genetic interaction with adolescent stress drives long-lasting cortical changes. Dr Elisabeth Binder (Max-Planck Institute of Psychiatry) spoke about the identification of genetic variants for gene–environment interactions using early traumamoderated methylation and expression quantitative trait locus (eQTL) analysis. In a study within the Grandy Trauma Project, genome-wide gene expression and DNA methylation data in peripheral blood and SNP genotype data were investigated to identify expression and methylation quantitative trait loci (eQTLs and mQTLs) that were moderated by exposure to child abuse. Participants (N = 394) were from a poor AfricanAmerican population with a high rate of traumatization. Analyses were controlled for age, sex, BMI, substance abuse, and adult trauma as well as multiple testing. Almost 450 unique transcripts were identified. In the language delay blocks of SNP regions that moderate transcription, an enrichment of DNAse I hypersensitive sites was observed as well as an enrichment of glucocorticoid receptor-binding sites. Twenty-seven percent of the SNPs that altered transcription in interaction with child abuse also alter methylation patterns. A significant over-representation of eSNPs among SNPs showing a gene–environment interaction on psychiatric symptoms was observed in a larger (N > 3000), independent cohort. Dr Douglas E. Williamson (University of Texas Health Science Center at San Antonio) spoke about patterns of DNA methylation and gene expression in PTSD in postmortem tissue, preclinical, and clinical samples. In five PTSD cases and five controls, post-mortem tissue analyses, methylation patterns of the posterior cingulate cortex, and the medial olfactory cortex were analyzed. Changes in methylation were observed in the medial olfactory cortex. The two top genes hypermethylated in PTSD cases were GRIA2 and KDM6B. Then, the Illumina Human Methylation 450k array was run in DNA

samples from the medial olfactory cortex of eight PTSD cases and eight controls. Two novel genes ALOX5 and ATXN71 were hypomethylated in PTSD cases. The first GWAS of PTSD was published by Logue et al. (2013). In addition, Dr Guia Guffanti (Columbia University) reported the results of a GWAS on 413 women from Detroit. A novel RNA gene lincRNA AC068718.1 was identified and replicated as a risk factor for PTSD (Guffanti et al., 2013). As a next step, they identified an associated pathway of a cluster of nine genes associated with immune-related diseases. Dr Joel Gelernter (Yale University, USA) presented a study using the ‘SSADDA’ (Semi-Structured Assessment for Drug Dependence and Alcoholism). They could identify PTSD patients among a large drug and alcohol addiction sample and performed a GWAS on 6000 individuals. Using this and a replication sample of almost 3600 patients, TLL1 was found to be a risk locus (Xie et al., 2013). This association was significant for EuropeanAmericans, but not African-Americans. Kerry Ressler (Emory University, Georgia, USA), focusing on ‘inner city trauma’, studied ∼ 8000 individuals. They found an association with the gene FKBP5, which is a mediator of the HPA response. The risk allele was also associated with a decrease in hippocampus size. Murray Stein (UCSD, Departments of Psychiatry and Family & Preventive Medicine, San Diego, USA) presented the ‘Army Starrs’ project featuring 57 000 participants and 34 000 available blood samples and its subproject the ‘New soldier study’, for which a pre–post deployment design has been developed. However, no results are available as yet. The definition of PTSD is a major issue as there is much heterogeneity and comorbidity involved, and PTSD from military experiences may represent a select subgroup not comparable with other PTSD phenotypes studied globally.

Schizophrenia (reported by Julia Steinberg) Dr George Kirov (Cardiff University, Wales) discussed the penetrance of 70 CNVs implicated in schizophrenia, developmental delay (DD), autism (ASD), or congenital malformations (CMs) (Kirov et al., 2013). Almost all confer a much higher risk for DD/ASD/CM than for schizophrenia; for the remaining CNVs, the difference in the risk for DD/ASD/CM versus schizophrenia was small and not significant. Considering all schizophrenia and DD/ASD/CM together, the mean penetrance of the 70 CNVs varied between 10 and 100% (mean 41%). The selection coefficients of the CNVs were correlated strongly with the overall penetrance estimates (r2 = 0.6). It was noted that the inclusion of prenatal death as a phenotype could increase the penetrance estimates of some CNVs. Dr Karolina Aberg (Virginia Commonwealth University, USA) presented a methylome-wide association study (MWAS) from blood of 750 patients with schizophrenia



and 750 controls. A total of 141 differentially methylated regions were identified at a false-discovery rate of 0.01. Although 139 of these regions were located within or near genes, few overlapped promoter regions; some of the associations, including the top hit in FAM63B, were replicated in an independent sample. A network analysis linked a large number of the genes to immune response and hypoxia pathways. Dr Aberg argued that mouse studies support the use of blood tissue to study methylation, given the limited availability of post-mortem brain samples. Dr Stephan Ripke (The Broad Institute, Harvard and MIT, USA) reported the latest PGC schizophrenia GWAS results. He showed that as the sample number increased from just a few thousand to now 80 000 samples, significant numbers of risk loci also increased considerably so that currently there are over 100 that are significant for schizophrenia. He showed examples of GWAS hits that would be useful as drug targets and have also been implicated in the past, such as DRD2, glutamate receptors, and calcium channel genes. A gene set analysis by Dr Tune Pers, one of his collaborators, showed significant associations with 74 biological pathways, including gene sets related to dendritic and neuron spines, postsynaptic density, and synaptic transmission. Polygene scores from the PGC significantly predicted schizophrenia in an independent dataset [r2 = 0.14 compared with 0.05; (Ripke et al., 2013)]. Dr Danielle Posthuma (VU University) presented the association analysis of schizophrenia with gene sets characteristic for three glial cell lineages: astrocytes, oligodendrocytes, and microglia. For each of the three glial cell types, a set of genes associated with that cell type, but neither neurons nor the other two cell types was compiled from a literature search (Goudriaan et al., 2013). The gene sets for oligodendrocytes and astrocytes, but not for microglia, were associated significantly with the risk of schizophrenia; for astrocytes, this included subsets related to signal transduction, gene transcription, and cell processes, whereas the associated oligodendrocyte subsets related to cell metabolism. Dr Steven McCarroll (The Broad Institute) reported a whole-genome sequencing study of 759 schizophrenia cases and controls from the Genome Psychiatry Cohort. The variant calls showed a concordance of greater than 99.8% with array-based genotypes. The schizophrenia cases showed an excess of large CNVs; a new method called Genome STRiP (Handsaker et al., 2011) was used to identify additional deletions as small as 1 kb. In total, over 20 000 CNVs of size 1 kb to 1 Mb were detected, of which 15% were multiallelic. Moreover, on examining mobile elements, over 7800 novel ALU insertions were discovered. The use of admixture to map the sequence that did not align to the reference genome (Genovese et al., 2013) showed that the missing regions largely fall

around the centromere. This approach showed that CNVs at 1q21.1 considered to be identical varied at megabase scales. Dr Menachem Fromer (Mount Sinai, New York, USA) presented an RNA-sequencing study of post-mortem brains by the CommonMind Consortium. In the preliminary analysis, prefrontal cortex samples of individuals with schizophrenia (n = 228), BPD (n = 9), and healthy controls (n = 240) were included. Cases and controls were matched for age, and several other variables (including sex, RNA quality, and brain bank) were accounted for. The RNA-sequencing pipeline was optimized for transcript discovery. The genes expressed differentially between schizophrenia cases and controls in a previous study (Mistry et al., 2013) were found to mostly show changes in expression in the same direction in the current dataset; a detailed analysis for differential expression of genes and transcripts is ongoing. The data will be made available through Synapse (http://www.synapse.org) in 2014.

Autism and related neurodevelopmental disorders (reported by Branko Aleksic and Irene Pappa) Dr Christopher Walsh (Boston Children’s Hospital, USA) spoke on ASDs and neurodevelopmental disorders in which diagnosis is based on behavioral measures, typically at ages of 3–4 years. ASD are often associated with comorbidities, such as cognitive impairment and epilepsy. ASD are complex neuropsychiatric diseases, with significant heritability, and a genetic architecture that includes single genes, chromosomal abnormalities, CNVs, and de-novo mutations (Sanders et al., 2012). Rare recessive mutations are an important inherited mechanism for ASD (Lim et al., 2013) and can be identified more easily in consanguineous families. Consanguinity has been associated previously with high rates of neurodevelopmental disorders. Dr Walsh presented research performed in 200 consanguineous families in the Middle East and Pakistan. His research shows that diverse genomic regions are responsible for ASD, intellectual disability, and seizures and that there is significant overlap with other neurodevelopmental, metabolic, and synaptic disorders. He stressed the importance of missense alleles for the development of these disorders and the need to discover more efficient ways to detect them and access their functional impact. Whole-genome and exome sequencing in American ASD patients has identified partial loss of function (LoF) in some generegulatory regions. However, when compared with consanguineous families, nonconsanguineous American families show notable differences, including fewer denovo CNVs and a lower female : male ratio among probands. Nonconsanguineous families (e.g. from the USA, in which parents are rarely related) have a rate of de-novo CNVs as a cause of ASD of ∼ 5%, whereas normal



individuals have a rate of de-novo CNV of about 1%. In contrast, affected children with ASD, when the parents are first cousins, show a lower rate of causative de-novo CNV than do affected children of unrelated parents. It is likely that the overall rate of de novos is equal in all families, but consanguineous families have a higher risk of recessive mutations because of consanguinity; thus, de-novo mutations represent a smaller fraction of the overall disease-causing mutations. Dr Julia Steinberg (Wellcome Trust Center for Human Genetics, UK) presented data on the role of FMRP genes in autism. Specifically, FMRP target sets contribute toward ASD through different types of genetic variation and genes disrupted by deleterious de-novo mutations. Rare ASD-associated CNVs preferentially disrupt a subpopulation of FMRP targets with synaptic functions; this same subpopulation of FMRP targets is also associated with ASD diagnosis on the basis of SNP data. In addition, individuals carrying multiple disruptions of FMRP targets, particularly those with synaptic functions, by rare CNVs, are at a significantly higher risk for ASD. Furthermore, she explained that mutations in genes regulated by FMRP may contribute toward ASD through two distinct genetic etiologies: (a) single disruptions of embryonically upregulated FMRP targets that are likely to be highly penetrant and ultra-rare or (b) lesspenetrant, multiple disruptions of nonembryonic, synaptic FMRP targets, which act in combination to give rise to ASD. Dr Richard Anney (Trinity College Dublin, IE) carried out large high-density meta-analyses combining data from multiple studies including 6500 individuals with ASD using the Illumina Human Exome bead chip. He found a single, genome-wide significant, finding at the ASTN2 locus on chromosome 9. ASTN2 in a rare CNV has been implicated previously in ASD. He also carried out a supporting replication study, indicating that common variation also contributes toward ASD genetic liability. Dr Christopher Poultney (Seaver Autism Center, Icahn School of Medicine at Mount Sinai, USA) investigated CNV deletions of between 1 and 30 kb in ASD using whole-exome sequencing. The validation of 85% of these deletions by quantitative PCR showed that the CNV calling algorithm (XHMM) could accurately detect small variation. Dr Poultney showed a significant (P = 0.017) burden of these deletions in ASD cases, which may be associated in as many as 7% of cases. Dr Mark Daly (The Analytic and Translational Genetics Unit, Massachusetts General Hospital, USA) examined an etiologic role of low frequency [minor allele frequency (MAF) < 1%] in ASD using exome array data from 12 510 individuals. He identified nine low-frequency/rare single-nucleotide variants (SNVs) associated with ASD at a P-value of less than 10 − 3. Eight of the variants were located within protein-coding genes: ANO1, COLEC12,

GJA9, MYCBP, MYH13, RRP8, SRRM5, STX5, TET2, and ZNF428. Furthermore, Dr Daly showed significant inflation of test statistics for low-frequency variants (0.5% < MAF < 1%; λ = 1.038), which is highly unlikely to occur by chance. The inflation was not observed for rare variants (MAF ≤ 0.5%; λ = 0.704), which suggests a lack of power to detect the genetic effects. With increased power from larger sample sizes, a targeted exome genotyping strategy will provide a valuable approach to elucidate the genetic basis of this complex brain disorder. Ian Blumenthal and the Talkowski Lab (Center for Human Genetic Research, Massachusetts General Hospital, USA) investigated the global transcriptional consequences of reciprocal 16p11.2 CNVs using a customized strand-specific RNA-sequencing protocol on lymphoblasts from a unique cohort of 35 individuals from seven multiplex ASD families, each harboring a segregating 16p11.2 CNV, and showing heterogeneity of both genotype and phenotype. The team also sequenced RNA from the cortex of eight mice with the 16p11.2 syntenic region either deleted or duplicated and eight sex-matched wild-type littermates. The most robust expression alterations were observed within the 16p11.2 CNV region itself; however, interconnected networks of dysregulated genes provided evidence for the convergence of altered global gene expression on previously identified ASD pathways and loci, as well as insights into the importance of chromatin conformation on gene expression. Dr Harrison Brand (Center for Human Genetic Research, Massachusetts General Hospital, USA) identified complex chromosomal rearrangements (>3 breakpoints) in 15 individuals (26.8%), disrupting 45 genes, which is markedly higher than the 2.8% predicted by cytogenetic estimates. Of the 41 cases with canonical balanced chromosomal aberrations, he found disruption of 27 genes among 26 individuals, a finding that emphasizes the significance of cytologically visible chromosomal abnormalities as a source of mutations with a significant impact in human development and psychopathology. Furthermore, Dr Brand implicated several novel genes (e.g. CDK6, CTNND2) that may be associated with neurodevelopmental disorders. ADHD (reported by Christie Burton)

Dr Peter Holmans (Cardiff University, UK) shared findings from a pathway analysis of GWAS hits and CNVs from PGC attention-deficit/hyperactivity disorder (ADHD) samples. For the analysis of CNVs (>500 kb), the top pathway enriched for CNVs in ADHD was interleukin-6-mediated signaling (P = 9.59E − 08). These CNVs were primarily duplications. Ion channel pathways also showed enrichment for ADHD CNVs, specifically nicotinic acetylcholine receptors, metabotropic glutamate receptors, and GRM interactors, supporting Elia et al.



(2011). Other significant pathways included transforming growth factor-β signaling and the synaptic pathway (in particular the ARC complex). SNP data were analyzed using ALIGATOR, but fewer pathways were enriched in the GWAS than CNV data; only some pathways were identified in both analyses (e.g. nicotinic acetylcholine receptor). Dr Andreas Reif (University Clinic of Würzburg, Germany) described findings from the PGC crossdisorder GWAS focusing on BPD and ADHD samples. These disorders are comorbid, coheritable (Faraone et al., 2012), and may share some similar phenotypes (e.g. impulsivity). No genome-wide significant hits were identified in the previous GWAS of BPD and ADHD from the PGC, although there was an increased burden of BPD risk genes in ADHD samples. In an additional analysis of 5800 BPD cases and 6000 ADHD cases, more genes were concordant than discordant between the two disorders. Of note, two genome-wide significant markers were identified in a meta-analysis of ADHD and BPD (with age of onset < 21) GWASs. To further investigate the shared phenotype between BPD and ADHD, the performances of BPD participants with and without ADHD were compared on a combined stop-signal and go/no-go task measuring impulsivity. No group differences were observed when controlling for age. Thus, this form of impulsivity may not be a shared phenotype between bipolar and ADHD. Dr Barbara Franke (Radbound University Medical Centre, the Netherlands) spoke on methods to identify mechanisms of the ADHD genes identified using GWAS. One example is the Drosophila melanogaster (fruit fly) model; hyperactive flies were significantly enriched for ADHD genes. DAT1 knockdown flies were also more active and treatment with methylphenidate, a drug used to treat ADHD, rescued this phenotype. Dr Franke outlined a pipeline of methods to assess the function of identified GWAS genes that includes bioinformatics, model systems, and brain imaging (e.g. IMPACT project). For the bioinformatics phase, she cited work by Poelmans et al. (2011), which used pathway analyses and systematic literature reviews to characterize a gene landscape for ADHD related to neurite outgrowth. For the model systems phase, she reported that DAT1 knockdown flies showed altered number of neurites, branches, and branch length compared with controls. For the brain imaging phase, data from the IMPACT project using human tract-based spatial statistics that assesses brain connectivity through white matter tracts were discussed. In 200 ADHD cases and controls, the DRD5 genotype was associated with brain connectivity in various brain regions including the corpus callosum and the cerebellum. These methods will help characterize risk genes at multiple levels of analysis and our future challenge is to connect these levels of analysis.

Dr Ben Neale (Massachusetts General Hospital, USA) discussed the findings to date from the analysis of the PGC ADHD samples as well as the 23 and Me project. The current ADHD GWAS includes 5621 cases. No markers reached genome-wide significance, although the top hit was intergenic. The analysis of the exome chip for the PGC ADHD sample included 7000 samples (3065 ADHD, 3058 controls, and 783 unknown individuals who are parents without a diagnosis). For the case–control and family-based analyses, call rates were adequate for both common and rare variants. On the basis of the quantile–quantile-plots, no common variants were significant. For the rare variants, the quantile–quantile-plot showed some general deflation overall that may be because rare SNPs may not meet the assumptions of the asymptotic distribution. More samples are required for the analysis of rare variants in this sample. Findings from the meta-analysis of the 5800 self-identified ADHD cases and 70 393 self-identified controls from the 23 and Me project were presented. No markers reached genomewide significance; however, using the polygenetic risk score from the PGC some P-values were marginally significant. Dr Neale suggested that these findings were similar to those initially observed for schizophrenia, suggesting the possibility for more hits with more samples. Finally, the PsychChip that will be used for future PGC analyses was discussed. The array chip uses the HumanCoreExome chip as a backbone and will contain an additional 50 000 variants specifically related to psychiatric disorders. The PGC is targeting to run 30 000 ADHD cases on the PsychChip.

Other childhood-onset disorders (reported by Enrico Cocchi) Dr Irene Pappa (Universitair Medisch Centrum Rotterdam, the Netherlands) presented a GWAS metaanalysis for aggression (N: preschool = 15 670, school = 16 315) and showed no significant finding, but some suggestion of increases in schizophrenia (preschool) and autism (school) known risk loci. She concluded that future studies of complex behaviors should include known rare variants found in other disorders such as schizophrenia and autism, and suggested that phenotyping needs improvement (parents vs. self-reported vs. observed assessment) and the differentiation of situational aggression (Dodge and Coie, 1987) from other types of aggressive disorders. Dr Cynthia M. Bulik (University of North Carolina, Chapel Hill, USA) described a GWAS of anorexia nervosa (AN) from the Wellcome Trust Case Control Consortium 3 (WTCCC3) and Genetic Consortium for Anorexia Nervosa (GCAN). It is the largest GWAS for any eating disorder ever performed. Results indicated various genetic risk loci for eating disorders and showed that no highly associated MDD signal could explain AN case–control status.



Dr Philip Mitchell (University of New South Wales, Sydney, Australia) carried out a brain imaging study with genetic correlations in a youth cohort at high genetic risk for BPD. This was a prospective longitudinal study (N = 352, 158 at risk for BPD, 130 controls, and 64 BPD, age: 12–30 years). Dr Mitchell's study showed that in BPD, there are differences (fMRI) in emotional regulation and functional connectivity. The correlation between the polygenic risk score and fMRI functional connectivity showed interesting results only when ethnicity weighted, highlighting the necessity of further analysis. Dr Kimm van Hulzen (Radboud University Nijmegen, the Netherlands) reported on the sharing of genetic background between ADHD and BPD. Although the symptoms overlap [Cross-Disorder Group of the Psychiatric Genomics Consortium; Genetic Risk Outcome of Psychosis (GROUP) Consortium, 2013], this does not seem to be genetically supported [Cross-Disorder Group of the Psychiatric Genomics Consortium; Genetic Risk Outcome of Psychosis (GROUP) Consortium, 2013]. These investigators selected young bipolar patients (onset < 21 years) to further investigate this relationship. A meta-analysis of 14 GWAS studies of BPD patients and ADHD patients younger than 21 years old found two GWAS significant results in a cross-disorder analysis and 1515 suggestively loci, suggesting individual genes to be further investigated. However, a polygenic analysis with ADHD as the training set and BPD as the target set showed no significant overlaps. Dr Andrew E. Jaffe (Lieber Institute for Brain Development, Baltimore, Maryland, USA) reported on DNA methylation in development and neuropsychiatric disorders of the post-mortem human brain. The analysis (N = 351, lifespan-second trimester fetal) showed that DNA methylation markedly changes at birth (single CpG changes = 78.5% fetal vs. nonfetal). A total of 118 genes showed a different expression because of methylation. These differentially methylated regions were enriched with genomic loci of risk for schizophrenia and several other common diseases. Dr Matcheri Keshavan (Boston, Massachusetts, USA) reported on a longitudinal study of 168 adolescents at familial risk for schizophrenia, aged 10–22 years, who had no psychotic disorders at entry compared with schizophrenic patients. He concluded that at-risk patients show prodromal symptoms and clinical features that predicted psychosis. Genome and environmental data strengthened the predictive power. Dr Shane McCarthy (Cold Spring Harbor Laboratory, New York, USA) reported an analysis of de-novo variants that supported a genetic overlap of schizophrenia with autism and suggested that nonsense variants and chromatin remodeling play a role in the pathogenesis of

psychiatric disorders. He also reported that there was a higher than expected load of de-novo mutations in sporadic trios (P = 0.01), with some new potential candidates identified. He concluded that family designs are a very useful way to narrow heterogeneity and exome sequencing helps to prioritize the importance of pathogenetic mutations, combining it with GWAS approaches.

Substance abuse Role of methylation and chromatin modification (reported by Lea K. Davis)

Dr Jian Feng (Mount Sinai School of Medicine, New York, USA) began the session with a study of the epigenetic regulation of cocaine action in mouse nucleus accumbens. His group performed next-generation sequencing, RNA sequencing, and chromatin immunoprecipitation sequencing (ChIP-seq) on DNA and RNA extracted from mouse nucleus accumbens after 7 days of cocaine administration. They mapped histone modification (i.e. H3K4m1/3, H3K9m2/3, H3K36m3, and H3K27me3) and gene expression changes induced by cocaine and found ∼ 250 genes (1% of the total transcripts) and 4106 isoforms (5% of total transcripts) that were differentially expressed. They then mapped regions of coinciding chromatin and gene expression alterations, termed ‘chromatin signatures’. They identified 29 such signatures and highlighted A2BP1 (aka rbfox1) as a splicing factor that was enriched at the location of chromatin signatures, suggesting that A2BP1 may be a primary molecule involved in cocaine-mediated changes in gene expression. Dr Anne West (Duke University Medical Center, North Carolina, USA) presented findings on the roles for the methyl-DNA binding protein (MeCP2) in addiction. Previous work has shown that altered expression of MeCP2 can alter stimulant-induced addictive behaviors. Dr West and colleagues hypothesize that the phosphorylation of MeCP2 Ser41 can be induced by amphetamine and may modulate addiction. To test this hypothesis, they developed a mouse knock-in that selectively removed the Ser41 phosphorylation site. The mice developed normally, but showed increased rates of selfadministration of amphetamines, increased locomotor activity after two doses of investigator-administered amphetamines, and reduced excitability of medium spiny neurons compared with wild-type mice. They thus proposed that the phosphorylation of MeCP2 Ser41 functions to limit the circuit plasticity in the nucleus accumbens that underlies addictive behaviors. Dr Chris Pierce (University of Pennsylvania) presented evidence from a rat model showing that cocaine exposure resulted in epigenetic and behavioral changes detectable in the male offspring of sires that self-administered cocaine. He showed that BDNF mRNA levels, protein levels, and promoter acetylation were increased in the medial prefrontal cortex and that there was a



corresponding decrease in the self-administration of cocaine in the male offspring of cocaine-exposed sires. The administration of a BDNF receptor antagonist restored the self-administration of cocaine to wild-type levels in male offspring of cocaine-exposed sires. Dr Gustavo Turecki (McGill University, Montreal, Canada) presented an analysis of DNA methylation patterns of dopamine pathway genes in post-mortem brain tissue from individuals with a history of cocaine dependence and drug-naïve individuals. They used reduced representation bisulfite sequencing to detect DNA methylation at single-nucleotide resolution in the dorsal and ventral striatum. In the caudate, they detected 71 CpGs differentially methylated in cases compared with controls (61 hypomethylated and 10 hypermethylated). In the nucleus accumbens, they detected 20 CpGs differentially methylated between cases and controls (19 hypomethylated and one hypermethylated). Sixteen of these sites were common to the caudate. Differentially methylated sites clustered on chromosomes 20 and 21. Substance use disorders (reported by Te-Tien Ting, Christie Burton, and Enrico Cocchi)

Dr Brien Riley (Virginia Commonwealth University, USA) reported on findings from a GWAS in a homogeneous Irish sample of alcohol dependence (AD) cases and controls. SNPs in the collagen 6A3 (COL6A3) gene on chromosome 2 were genome-wide significant. Functional studies in multiple model organisms show consistent effects on ethanol response of changes in COL6A3 and three other genes (the Krueppel-like factor 12, KFL12 gene on chromosome 13, the Ryanodine receptor 3, RYR3, gene on chromosome 15, and the ProteinO-mannosyltransferase 2, POMT2, on chromosome 8) also significant in the GWAS. Dr Shaunna Clark (Virginia Commonwealth University, USA) presented findings from a MWAS. A combined analysis of the MWAS and GWAS was used to clarify the mechanism of alcohol exposure or inherited susceptibility toward alcohol use. Only CNTN4 showed a significantly consistent association with alcohol use on the basis of the combined MWAS and GWAS results and another replication study. Further examination showed significant evidence that methylation of CNTN4 mediated the relationship between rs1382875 and alcohol use. This inherited susceptibility can lead to reorganization of neural circuits and is considered to contribute toward addiction. Ms Emily Olfson (Washington University, St Louis, USA) described findings from the Collaborative Study on the Genetics of Alcoholism (COGA) on the interplay between genes and risk factors in the development of early drinking behaviors. Cox proportional hazards regression was used to model drinking milestones starting at age of first drink. Preliminary results supported an

interaction between an ADH1B variant and smoking in the development of first alcohol use among adolescents and young adults. The presence of the ADH1B protective allele was associated with a decreased risk for first symptom onset. This protective effect appeared to be reduced among individuals who had previously initiated smoking. Dr Georgy Bakalkin (Uppsala University, Sweden) reported findings on the epigenetic mechanism of prodynorphin (PDYN) on emotion regulation and reward in human post-mortem brain of individuals with alcoholism. DNA methylation of the PDYN promoter was examined in prefrontal cortices. CpG methylation in CpG islands (CGI) was found to be correlated with PDYN expression levels. In addition, an upstream regulatory factor-2 (USF2) was colocalized with PDYN protein in neurons and bound to the PDYN CGI in studies using ChIPqPRC. PDYN mRNA/peptides, CpG methylation in the CGI, and USF2 correlated with each other. CGI demethylation in alcoholics may promote USF2-mediated recruitment of histone modifiers to the promoter, resulting in PDYN activation. The challenge is that these measures change across the lifetime and cannot be seen in a post-mortem design. Dr Margit Burmeister (University of Michigan, USA) presented gene–environment interactions from the Michigan Longitudinal Study, a sample of 463 families. Two major haplotypes are formed by GABRA2 SNPs, one of which was previously significantly associated with alcoholism. The results showed that this haplotype was associated with female impulsivity and linked with insula activation during monetary reward anticipation. Impulsivity was a mediator for the GABRA2 effect on alcoholism. Patients with the risk haplotype of GABRA2 were more likely to engage in problem behaviors during adolescence when not monitored by parents. This shows that individuals carrying this haplotype are more susceptible to environmental influence. Dr Shirley Hill (University of Pittsburgh, Pennsylvania, USA) spoke on brain structural changes as important endophenotypes of AD familial risk. The findings on the basis of three-generational family data showed a greater risk for developing substance disorders and at an earlier age among the offspring of AD families than those of control families. To uncover morphological endophenotypes associated with familial risk for AD, three important variables (i.e. sex, developmental changes, and exposure to alcohol and drugs) were assessed. On the assumption that the occipit-frontal cortex (OFC) modulates the amygdala in regulating emotion, OFC/amygdala ratios were constructed and related to age of onset to develop substance use disorders. Using survival analysis, it was found that those with smaller OFC to amygdala ratios had an earlier onset of substance use disorders. This was found within the entire sample as well as within the high-



risk sample. These results suggest that even among offspring from multiplex families, brain morphology can assist in predicting the likelihood of developing substance use disorders in adolescence and young adulthood. Dr Yasmin Hurd (Icahn School of Medicine at Mount Sinai, New York, USA) spoke on her vast body of translational work on the genetic and neurobiological mechanisms underlying drug addiction that combines human genetics with animal models. For example, she showed the link between opioid-related genes and brain changes associated with opioid use in both humans and animals. Compared with controls, the post-mortem brains of a homogenous sample of European heroin users showed reduced μ-opioid receptor (MOR) expression as well as altered expression of several components of the mitogen-activated protein kinase intracellular signaling pathway induced by MOR activation, including extracellular signal-regulated kinase (ERK) 1. Downstream targets of the mitogen-activated protein kinase pathway such as the transcription factor ets-like kinase (ELK) 1 were also dysregulated in heroin users, particularly in the striatum, a region well known for its role in the effects of drugs of abuse. Notably, ELK1 expression in this brain region was associated with a risk allele in the OPRM1 gene that codes for MORs. Further, ELK1 expression was related to a history of heroin use in the human sample. In an animal model of heroin use, heroin intake through intravenous self-administration was also correlated with ELK1 protein levels in the striatum. These findings suggest a possible mechanism underlying the neurobiological changes associated with substance abuse disorders (Sillivan et al., 2013). One of her main findings is that the genetics of the opioid neuropeptide system relates to inhibitory control, negative affect, and reward choice. She also investigated the association between epigenetic modulation and the regulation of neuronal systems that relates to inhibitory control, affect, and reward. In addition, she developed an in-vivo imaging and molecular strategy to examine the neural network directly linked to cell-specific molecular disturbances. For example, remote inhibition of neurons in the periamygdala nucleus expressing the PDYN gene (disturbances of which were detected in heroin abusers and suicide victims) was found to lead to selective activation of the extended amygdala network linked to stress and anxiety. Finally, a striking finding of the effects of drug exposure detected in animals was the impact on affective and anxiety-like behavior across generations. Dr Joel Gelernter (Yale University School of Medicine, New Haven, USA) performed a GWAS of AD traits in three populations, two USA (N = 16 087), and a Chinese sample (N = 313). The USA populations replicated risk loci in alcohol dehydrogenase 1B (ADH1B) and alcohol dehydrogenase 1C (ADH1C) genes and identified novel risk loci mapping to the ADH gene cluster on chromosome 4. Combining the USA populations resulted in a

strong association on chromosome 2 (P < 10 − 17). It was related to an intergenic region (rs1437396) between coiled-coil domain containing 88A (CCDC88A) and mitochondrial translational initiation factor-2 (MTIF2). CCDC88A was differently expressed in alcoholics and its product interacts with both disrupted in schizophrenia 1 (DISC1) and vascular endothelial growth factor A (VEGFA), associated with AD (Heberlein et al., 2010). The Chinese sample showed a risk locus on alcohol dehydrogenase 2 (ALDH2) associated with AD (P = 4.73 × 10 − 8) and two AD-related phenotypes: flushing response and maximum drinks in a 24-h period. These results are of central importance because a GWAS analysis identified different variants but on the same gene for the USA populations and in the same pathway (hepatic metabolism) among all the populations under analysis. Dr Arpana Agrawall (Washington University, St Louis, USA) carried out a meta-analysis of genome-wide studies of AD. Twelve GWAS were analyzed. There was an absence of replication across studies. However, the most promising genes found were fukutin (FKTN)-fibronectin type III and FSD1L domain containing 1-like (FSD1L) and ectonucleotide pyrophosphatase-phosphodiesterase 3 (ENPP3). Consistent with Dr Gelernter’s results, the most interesting locus was found on chromosome 4, in the ADH cluster. Dr John Nurnberger Jr (Indiana University, USA) studied variation in the phenotype for single genes related to AD on the basis of developmental stage, sex, and ethnicity using the COGA sample (1164 families of AD and 233 families of controls). ADH1B variations were associated with AD in both groups (adolescent and young adults). New data show three SNPs in ADH4 with potential protective effects in homozygotes. The other relevant gene identified was γ-aminobutyric acid A receptor-α2 (GABRA2), where conduct disorder symptoms were associated with AD only in carriers of the high-risk rs279871 genotype, particularly in those with age of onset of conduct problems in early adolescence. Recent data from Perry et al. (2013) suggest that daily life events can predict the risk for AD, but only in males with the GABRA2 risk genotype. Predictive phenotypes for the ADH genes include drinking frequency and alcohol problems; predictive phenotypes for GABRA2 include conduct disorders. Dr Dayne Mayfield (University of Texas, Austin, Texas, USA) studied the integrated miRNA, mRNA, and protein coexpression networks in brains of ethanol-treated mice. The importance of miRNA is that they have huge network regulatory potential, ‘fine-tuning’ capabilities and they appear to be associated with psychiatric disorders (Kolshus et al., 2013) and addiction (Nunez et al., 2013). Fifty-two differently expressed miRNA families were found in mouse AD models and 32 in humans;



among these, 14 families’ results overlapped (P < 10 − 5). The Toll-like receptor 4 (TLR4) MyD88-dependent pathway seems to be the best associated and the most functionally plausible. Genetics of smoking behaviors (reported by Emily Olfson)

Dr Eric Johnson (RTI International, USA) described the first study reporting an association between nicotine dependence and variants in a region on chromosome 15, which includes the CHRNA5–CHRNA3–CHRNB4 cholinergic nicotine receptor subunit genes (Saccone et al., 2007). The nonsynonymous variant rs16969968 in CHRNA5 emerged as a consistent variant in GWAS and was shown to play a functional role (Bierut et al., 2008). To better understand whether there are additional distinct loci in this region on chromosome 15, haplotype analysis was carried out. Findings from this analysis indicate that the region harbors multiple loci associated with smoking behaviors, particularly in individuals of African descent. Dr Alison Goate (Washington University School of Medicine, St Louis, USA) presented data from functional studies that implicate additional variants in the same above region on chromosome 15 for risk of nicotine dependence. Wang et al. (2009) found that common noncoding variation upstream of CHRNA5 is associated with mRNA expression in brain tissue as well as risk for nicotine dependence and lung cancer. Recently, this region associated with mRNA expression has been narrowed by examining individuals of African descent. In the adjacent nicotinic receptor subunit gene, CHRNB4, Haller et al. (2012) found that rare missense variants at conserved residues were associated with a lower risk of nicotine dependence. In-vitro studies of these CHRNB4 rare variants indicate that they increase cellular response to nicotine. Taken together, these studies of both common and rare variation provide additional mechanisms beyond the well-established rs16969968 variant by which this region on chromosome 15 contributes toward smoking-related problems. Dr Jerry Stitzel (Institute for Behavioral Genetics, University of Colorado, USA) presented a mouse model of the well-established rs16969968 human variant that causes an Asp398Asn change in the CHRNA5 (nicotinic receptor α5 subunit gene). Mice with the Asn risk allele consumed more nicotine than wild-type mice and showed greater positive reinforcement from nicotine intake. With cocaine, the reverse effect was observed: the Asn risk variant was associated with a protective effect for self-administration of cocaine. Reversal of risk for two substances, nicotine and cocaine, has been reported previously in humans by Grucza et al. (2008). Beyond behavioral changes, this variant alters brain chemistry in mice. In the ventral tegmental area and the nucleus accumbens, the variant was associated with

neurotransmitter changes in response to nicotine intake, but did not considerably alter baseline neurotransmitter levels. In the habenula, where CHRNA5 is considered to be important, the baseline levels of several neurotransmitters were altered, possibly reflecting a difference in predisposition. Overall, these findings show that one SNP identified in humans can have marked effects on both behavioral responses to substances and brain chemistry in a controlled model system. Dr Nancy Saccone (Washington University School of Medicine, St Louis, USA) focused on the importance of translating knowledge of the genetics of nicotine dependence into smoking cessation. Chen et al. (2012) identified a significant interaction between pharmacologic cessation treatment and genetic variation in CHRNA5. Specifically, those at highest genetic risk for nicotine dependence were least likely to quit smoking, and these individuals benefited most from the addition of pharmacological treatment to counseling. This latter point is emphasized by examining the number needed to treat (NNT), defined as the average number of patients who must be treated for one to benefit. In the high-risk genetic group, adding pharmacotherapy to counseling resulted in an NNT of four compared with an NNT of over 1000 in the low-risk genetic group. More recently, Chen et al. (2013) examined how variation in the nicotine metabolizing gene CYP2A6 contributes toward cessation of treatment response. Among those with high-risk genotypes for both CHRNA5 and CYP2A6, the NNT is further reduced to 2.6. These findings show how specific genotypes can guide cessation treatment decisions.

Cross-disorder analyses (reported by Isabele G. Giori) Dr John Hettema (Virginia Commonwealth University, USA) discussed GWAS targeting in shared anxiety disorder susceptibility. His ongoing work has been a metaanalysis with pre-existing samples. He then carried out a replication analysis with different samples. He obtained no significant findings with the case–control studies. However, when using a quantitative phenotype, he had GWAS significant hits on chromosome 10, chromosome 2, and chromosome 4. Dr Elaine Green (Plymouth University, UK) discussed CNVs in a novel large BPD sample in comparison with schizophrenia. Large rare CNVs have been implicated in the etiology of schizophrenia; however, their role in BPD has been less well studied and remains unclear, with some studies reporting an increased incidence of CNVs and others not. The incidence of rare (< 1% in general population) CNVs (>100 kb in size) in BPD (n = 2591) (BDRN sample, http://www.BDRN.org) was compared with that in a large dataset of patients affected with schizophrenia from the UK. Significantly fewer deletions of greater than 1 Mb were observed in BPD (P = 0.0012). They also noted fewer duplications in BPD cases of



500 kb to 1 Mb in size (P = 0.012). These findings were driven to some extent by deletions at known schizophrenia loci, in particular deletions greater than 1 Mb at the following loci: NRXN1, 3q29, 15q13.3, 17p12, 17q12, and 22q11.2. The findings were consistent with the group’s previous findings (Grozeva et al., 2010) indicating that schizophrenia and BPD differ with respect to CNV burden in general, and in particular in the possession of large, rare deletions. Dr Douglas Ruderfer (Icahn School of Medicine at Mount Sinai, USA) presented findings from a preliminary analysis of exome sequencing in BPD, schizophrenia, and controls from a matched Swedish population. He discussed the careful attention required in comparing individuals from different sequencing runs and implemented a three-way matching scheme across all phenotypes on the basis of genetic information and sequencing metrics. After matching, he reported a significant enrichment of very rare disruptive mutations in calcium channel genes in BPD cases, similar to enrichment observed in schizophrenia in the same dataset. Dr Verneri Anttila (MGH/Broad Institute, USA) discussed the Brainstorm Project. He reviewed the genetic architecture of psychiatric disorders and highlighted the successes of recent GWAS consortia in both neurological and psychiatric diseases, as well as positing an approach to leverage of those results as a way to understand the comorbidity of diseases of the brain. The study builds on the previous work within the PGC in probing the genetic cross-phenotype links and expands on that work to include neurological diseases as well. The project was a collaboration between several different consortia, and represents an effort to understand the common genetic causes of neurological and psychiatric diseases. Initial results are from across-disease single marker and pathway analyses, which suggest an excess sharing of GWAS signals and increased pathway aggregation in the neurological and psychiatric diseases studied. Dr Giulio Genovese (Stanley Center/Broad Institute, USA) presented results from a new large cohort of USA individuals of African descent. He showed an increase in large deletions and duplications in both schizophrenia and bipolar patients compared with controls. The schizophrenia results in European samples were replicated in these samples with African ancestry. Dr Mark Reimers (Virginia Commonwealth University, USA) highlighted that SNPs in regions that are functional are more likely to have consequences for psychiatric or other phenotypes than SNPs in regions that have no apparent function. He described a novel empirical Bayes method for integrating genomic functional information with genetic association, which increased the power to detect risk SNPs. For the shared genetic risk of schizophrenia and BPD, this method found an enrichment for genes related to neuron differentiation, development of

dendrites, and postsynaptic density. The differential risk between the disorders was enriched in genes for nicotinic cholinergic signaling. Dr Chunyu Liu (University of Illinois, Chicago, USA) spoke on using brain molecular QTLs to identify novel risk genes shared by multiple psychiatric diseases. He used brain eQTL data to reanalyze GWAS signals of 11 diseases and traits. All psychiatric disease GWAS signals showed significant enrichment of brain eQTL SNPs. Moreover, some diseases shared brain eQTL SNPs in their GWAS signals more than by chance, indicating their shared genetics/genes. A novel region on chromosome 3 was identified as harboring shared risk genes for bipolar, schizophrenia, and obsessive–compulsive disorder (OCD).

Genetic testing and clinical care Personal and clinical genomics and returning results to the consumer (reported by Adeniran Okewole and Jana Strohmaier)

Dr Robert Green (Brigham and Women’s Hospital, USA) introduced the different types (e.g. array testing, sequencing, karyotyping), purposes (e.g. clinical testing, testing within a research environment, biobanking), and contexts (e.g. medical, consumer or research driven, prenatal, preconceptive, counseling available or information through internet, incidental findings) of genetic testing. The expectations of medical benefit to genetic testing are high. The company, 23 and Me, already has more than 400 000 customers and particularly individuals are very interested in finding genetic explanations for their diseases. The costs for whole-genome sequencing have decreased considerably. For these reasons, important issues need to be addressed, such as the potential harm and uncertainty of a result, the tremendous amount of data, and handling of incidental findings. Data from the REVEAL (the Risk Evaluation and Education for Alzheimer’s Disease) study were presented, suggesting that disclosure of APOE test results do not have a huge psychological impact on individuals (Ashida et al., 2010). Testing results do not cause significant degrees of anxiety and the testing profile is not correlated with the degree of anxiety. Anticipatory anxiety previous to result disclosure predicts stress levels after results have been disclosed. However, after testing, individuals seek healthcare examinations that are related to the results and not necessarily useful. Those with a positive test for APOE4 were more likely to modify lifestyle to reduce cardiovascular risk (Chao et al., 2008), follow better dietary controls (Vernarelli et al., 2010), and take out longterm care insurance (Zick et al., 2005). In the NIH program exploring the use of genomic sequencing in newborn healthcare (http://www.nih.gov/news/health/sep2013/ nhgri-04.htm), parents are surprisingly interested in the testing results even if they know what information they will receive.



Dr Greene also discussed a study of the motivations and impact of customers using personal genomics services. He reported findings from the Impact of Personal Genomics (PGen) study, addressing the question of whether access to genomic information shifts the client’s risk paradigm. Interest in genetic testing was found to be related to concerns about specific disease risk, risks for children, and drug response for those with health concerns. Patients with known diagnoses such as BPD and multiple sclerosis were particularly interested in their testing, implying that individuals were simply trying to understand themselves. A sizable proportion were planning to talk to their family and friends about their results. Although 28.4% had discussed their results with a primary care provider, 11% had had tests, examinations, and procedures attributable to the new genetic information. Predictors of anxiety after testing included poorer selfreported health and increased baseline anxiety. Dr Scott Roberts (University of Michigan, USA) presented genetic risk disclosure in Alzheimer’s disease, focusing on the ε4 allele of APOE, carriers of which were at an increased risk but that was neither necessary nor sufficient for Alzheimer’s disease. APOE disclosure was thus used as an illustrative paradigm of the risks and benefits of disclosure. He also discussed findings from the REVEAL study, in which it was found that women, Whites, middle aged individuals (vs. older adults), with higher socioeconomic status, and healthy ‘monitors’ (vs. blunters) all had a higher test uptake. Personal utility (increased awareness of disease/health risks, advance planning, the idea that ‘knowledge is power’), rather than clinical utility, informed the seeking of testing. Risk discordance was reported in 47%. A condensed protocol was found to be just as effective in communicating information as was a more elaborate protocol and telephone was just as effective as communicating in person. With respect to impact of information, no adverse psychological outcomes were experienced by participants. Behavioral changes prompted by the information included that ε4 carriers made long-term insurance changes and a significant change to dietary supplementations (P < 0.001). Dr Atul Butte (Stanford University, USA) spoke about the decrease in costs for sequencing and described a future in which healthcare insurance may someday offer discounts for individuals who provide their genetic information. When he started his work, there was no ‘master database’ that included all identified diseaseassociated SNPs and risk alleles, and using only internal funding his team constructed such a database, now numbering nearly 20 000 papers, identified from the literature nearly half a million SNPs for 7400 diseases. He further talked about the odds ratio, a measure of association that may not be applicable in medical settings. The likelihood ratio might be better as it is able to be combined across multiple tests and may be less

susceptible to spurious or incidental findings (Morgan et al., 2010). He stressed that physicians must be trained to understand, incorporate, and communicate genetic results (Ashley et al., 2010) and spoke about the value of risk prediction and knowing one’s own risk for medical and pharmacological prevention (Dewey et al., 2011). Individuals can be educated about their risks and how they can change environmental and behavioral factors to decrease their risk. Visualization tools may help physicians and the tested individual better understand the results. Dr Uta Francke (Stanford University; Senior Medical Director at 23 and Me, USA) spoke about the right of everyone to access and understand his/her genetic information. 23 and Me offers quick and easy access to one’s own genetic make-up. One can sign up online and a saliva sample is delivered by mail. Genotyping is performed using the Illumina OmniExpress Plus Genotyping BeadChip and thousands of custom designed variants for ∼ 1 000 000 SNPs are examined. Results include information on the carrier status for 50 Mendelian diseases, 121 health risks on the basis of GWAS and association study results (e.g. ANK3 for BPD, APOE for Alzheimer’s), and 24 drug responses. All this information can be important for family planning, planning for old age. The standard for 23 and Me is that risk loci must have been established in at least 1000 cases and controls and replicated in an independent study before they are reported to the customer. The customer receives links to up-to-date research literature [Cross-Disorder Group of the Psychiatric Genomics Consortium; Genetic Risk Outcome of Psychosis (GROUP) Consortium, 2013]. 23 and Me collects raw data and this database is growing rapidly. Over 80% of customers consent to the collection of phenotypes, which allows for new discoveries. 23 and Me also investigates how customers respond emotionally and behaviorally to the disclosure of results. Thirty-two carriers and 31 noncarriers who had decided to know their BRCA1 and BRCA2 carrier status were interviewed (Francke et al., 2013). None reported extreme anxiety and four carriers reported moderate, but transient anxiety. Female carriers sought medical advice and risk-reducing procedures. Some men felt a burden because of the fact that their carrier status implies genetic risk for female relatives. Except for one individual, all appreciated knowing their carrier status. Dr A. Cecile J.W. Janssens (Emory University, Georgia, USA) spoke about the high predictive power of DNA testing for monogenic diseases (e.g. Huntington disease) and the lower power for multifactorial diseases (e.g. diabetes, cardiovascular disease). For risk prediction, it is important to ask what is being predicted in which population. Genetic information is more reliable for matching individuals or diagnosing (e.g. paternity testing, rare congenital syndromes) than for prediction (e.g. pharmacogenetics, common/complex diseases,



nutrigenomics). In complex diseases, most traits are only partly heritable. She discussed the relationship between heritability and predictive ability of a test. A test cannot be very predictive if the heritability of the predicted disease is low (e.g. < 25%). Also, the complexity of a disease, that is, the variety of factors causing the disease, and with common alleles of small effect, all influence its predictability. However, risk testing despite nonperfect models has benefits on a population level in reducing morbidity and mortality (Janssens and van Duijn, 2010). Dr Paul Appelbaum (Columbia University, New York, USA) spoke on the issue of incidental findings. Research on incidental findings is a priority focus of the Ethical, Legal and Social Implications (ELSI) Research Program of NHGRI (http://www.genome.gov/10001618). The American College of Medical Genetics has now released recommendations for 24 conditions that should systematically be disclosed to the patient (Green et al., 2013). In all, 234 researchers of the US genetic research community completed an online questionnaire and 28 an extensive semistructured interview to understand their views of and experiences with incidental genetic research findings (Appelbaum et al., 2013). Ninety-five percent of respondents would disclose information about highly penetrant, actionable findings; over 60% would disclose information on high-penetrance alleles even if no intervention is available; 80% would disclose information on modest-penetrance alleles with available interventions; and 16% would prefer to disclose a list of variants from the entire genome. Although respondents endorsed a long list of information to be discussed with participants before obtaining informed consent for return of incidental findings, they would like to spend 30 min or less on the process. Dr Appelbaum suggested that alternative models of informed consent were needed in place of traditional consent, in which the decision about receiving results is made before onset of study participation. In a staged consent, the decision about receiving results is made close to the disclosure of results, thereby allowing consideration of current life circumstances. A mandatory list of results defines what must be disclosed and simplifies the consent process. The consent for and disclosure of results can also be outsourced. Dr Sarah Hartz (Washington University in St Louis School of Medicine, St Louis, USA) started with the observation that although information about genetic risk factors had improved, no system existed for reporting genetic results to study participants. There is nevertheless an ethical duty to report results. Her study reported ‘incidental genetic results’ (lung cancer, breast/ prostate cancer, colorectal cancer, heart attack, and diabetes type 2) to 50 heavy smoking individuals. Over 90% of the participants found the results worthwhile and discussed their results with a relative, doctor, or friend. Over 80% reported increased motivation to quit smoking and to change their diet or exercise. With respect to

psychological symptoms, 31% of the study participants had moderate to severe anxiety at baseline, whereas 71% had depression at baseline. No significant change from baseline was found after counseling. Isaac Kohane (Boston Children’s Hospital, USA) advanced the argument that ASD requires an ‘expansive integrative perspective’. This was in response to the question of what to do with unexpected ‘incidental’ genetic findings (Kohane et al., 2006). He observed that although ASD genetic research had produced considerable information on immune and synaptic mechanisms, there was a lack of overlap between communities, amounting to ‘academic blindness’. Analysis of data suggested that different comorbidities lead to different clusters of presentation. He therefore suggested that bioinformatics would help to overcome disciplinary blinders. Large population studies, improved sequencing, as well as systematic and comprehensive phenotyping would also be beneficial. What can we recommend to clinicians and the public? (reported by Ajeet B. Singh)

One session was aimed at ultimately writing a statement that would represent the ISPG containing recommendations about how to use commercial DNA testing in psychiatry. Themes for the session included the accelerating uptake of already commercialized genetic tests in psychiatry, marked progress in the field since the last ISPG guidelines were posted in 2009, the pressing need for updated guidelines to assist both the public and clinicians, and finally the consideration of potential harms arising from misapplication of test information. Dr Francis McMahon (President of ISPG) began by reflecting on the need to update the 2009 ISPG guidelines and articulated potential uses of testing as ‘differential diagnosis, prediction of treatment outcomes, identification of high risk individuals … preventative strategies’. However, there is a need to ensure that genetic biomarkers could be assayed reliably, are robustly evidence based, and have an effect size sufficient to enable clinical utility above current clinical practices. He reflected that ‘genetic testing is already here in psychiatry’, with companies actively marketing them. Thus, ‘should the psychiatric genetics community weigh in?’ He presented pros and cons, the ‘yes’ case being more resonate, articulated on a slide as ‘Yes – genetic testing is being marketed and used, we have the expertise, clinicians want/need help, patients are confused/misinformed, psychiatric disorders pose unique issues for genetic tests’. Dr Margit Burmeister (University of Michigan, USA) discussed how pharmacogenetics of warfarin has evolved to a clinically translatable stage over several years. ‘Variants of VKORC1 (vitamin K epoxide reductase complex subunit 1 gene) are estimated to explain 25% of



the variability of dose’. This clinically relevant genetic variant translates to an optimal dosage varying 20–30-fold between patients. She added that pharmacokinetics has shown some relevant effect sizes and ‘compared to GWAS nearly Mendelian effects’. Her impression was that pharmacodynamics had provided less clinically useful findings and that the path ahead was principally for pharmacokinetic pharmacogenetics. She reflected that CYP450 2D6 metabolizer variation status in some individuals leads to an overdose or ineffective treatment, and such information a priori could avert such unwanted outcomes. Dr Burmeister cited data suggesting atypical antipsychotic weight gain appears to be associated with polymorphisms of rs489693 (Malhotra et al., 2012). She speculated that pharmacogenetic information may help prescribers choose between typical and atypical antipsychotics on the basis of such information, as well as pharmacogenetic prediction of tardive dyskinesia risk (Zai et al., 2013). Finally, she highlighted that rare but dangerous side effects such as Stevens–Johnson syndrome from aromatic anticonvulsants such as carbamazepine could be predicted by the HLA-B*1502 genotype. She concluded that ‘clinicians need to be educated that time is ripe for genetic testing for some variants now’. Dr Elliot Gershon (University of Chicago, USA) highlighted that despite being rare, ‘the most potent genetic risks known in psychiatry are related to CNVs’. He cited the example of the deletion in 22q11.21 being associated with a 68.25% risk of schizophrenia (Malhotra and Sebat, 2012). He cautioned against adopting tests with an effect sizes too small for clinical utility, but added that ‘aggregate risk of a polygenetic component may become usable in counselling’. He concluded with the need to reflect on the possible ethical ramifications of such testing, in particular, the risk of stigma and issues of pregnancy planning and termination on the basis of parental and antenatal genetic risk profiling (Gershon and Alliey-Rodriguez, 2013). Dr Lynn DeLisi (VA Boston Healthcare System, USA) recalled attending the WCPG in 1998 in Bonn, Germany. During that meeting, an excursion was made to a psychiatric facility where thousands of schizophrenic patients were ‘euthanized’ in the mistaken belief that this could help end a cycle of heritable schizophrenia. Dr DeLisi emphasized that there is still a ‘gap in knowledge between we know as researchers and what the public thinks and wants’. She pointed out that the growth in commercial testing was occurring with a ‘lack of regulations’ and ‘lack of informed consent or understanding of what is being gotten’ by consumers. ‘Some companies offer expert medical advice, but they lack the legal capacity to do so’. Direct to consumer testing gives a sense of empowerment and being in control of healthcare decisions by consumers. She further emphasized that genetic testing is not at the level of providing diagnosis,

but only risk of illness, and consumers needed to be aware of this critically important fact when they bring information to providers and expect interpretation. Most providers do not believe that genetic information is useful and do not have a good understanding of genetics.

Functional genomics (reported by Min-Chih Cheng) Dr Joseph Dougherty (Washington University School of Medicine, USA) applied the translating ribosome affinity purification methodology to identify the comprehensive in-vivo suite of ribosome bound mRNA in serotonergic neurons in adult mice. He found genetic variants in CELF6 that may contribute toward the risk of autism and that the Celf6 mutant mice show partial autism-related phenotypes (Dougherty et al., 2013). Thus, he suggested that CELF6 is likely to be one gene that can influence risk for some autism. Dr Melanie Leussis (Emmanuel College, USA) showed that decreased ankyrin G levels (a putative BPD gene) were associated with altered dendritic synaptic spine density and synaptic functions, and the alterations in synaptic proteins were largely normalized by chronic treatment with the lithium (Leussis et al., 2013). Dr Melvin McInnis (University of Michigan, USA) generated induced pluripotent stem cell (iPSC) from four BPD patients and three controls using retroviral transduction with pluripotency factors, followed by differentiated into neurons. He observed that expressions of genes for membrane receptors, ion channels, and neuronal transcription factors were different in cells derived from BPD versus controls. Furthermore, exposure of BPD neurons to lithium significantly altered their calcium and glutamine metabolism compared with control neurons. Dr Panos Roussos (Icahn School of Medicine at Mount Sinai School, USA) carried out a multiscale integration of high dimensional datasets, combined with gene coexpression network analysis, to identify putative causal SNPs and genes related to neuronal function and synaptic neurotransmission in schizophrenia. Overall, their results support the existence of convergent genetic abnormalities in schizophrenia. Dr Sevilla DeteraWadleigh (HGB, NIMH) showed that mefloquine, a drug known to induce neuropsychiatric symptoms, induced phenotypes in iPSC-derived neural stem cells (NSCs). Pretreatment with lithium or valproate significantly protects NSCs from the adverse effect of mefloquine on viability, suggesting that cell viability is possible and high-throughput assays can be performed in the search for compounds that mimic the effect of mood stabilizers and other agents. Dr Alexander Urban (Center for Genomics and Personalized Medicine, Stanford University, USA) generated 25 iPSC lines derived from fibroblast biopsies



from seven patients with a 22q11 deletion and seven controls and characterized these iPSC lines using genomic and gene expression methods. Dr Urban summarized that the iPSCs showed stable genomes and good neuronal differentiation potential. Dr Olli Pietiläinen (Institute for Molecular Medicine, Finland) reported on a 240 kb ‘Finnish specific’ deletion on chr22q11.22 including the TOP3-β gene was associated with schizophrenia, and predisposed to schizophrenia and intellectual deficit (Stoll et al., 2013). Their results highlight the usefulness of population isolates in studying rare variation underlying complex disorders.

GWAS (reported by Alison Merikangas and Irene Pappa) The PGC

Dr Patrick Sullivan (University of North Carolina, USA) introduced the session by describing the highly successful collaborative network, the PGC, which includes work groups spanning all major classes of psychiatric disorders including attention-deficit hyperactivity, autism spectrum (ASD), bipolar, major depression (MDD), schizophrenia, cross-disorders, a liaison with the ENIGMA (Enhancing Neuro Imaging Genetics through Meta-Analysis) project, and new work groups on AN, OCDs, and PTSDs starting in the next year. This is the largest experiment in biological psychiatry (i.e. > 400 investigators, 80 institutions, 30 countries > 170 000 current cases, and 80 000 additional in the next year). The newly designed PsychChip, an Illumina chip tagging 250 000 common SNPs, 250 000 exome variants, and 50 000 custom SNPs, will be used for GWAS, CNV, and exome variation studies for $45 per chip plus processing fees. Dr Sullivan highlighted the success of the schizophrenia workgroup as an example of the progress that can be made, and his appreciation to the contributing investigators was noted. Dr Michael O’Donovan (Cardiff University, UK) presented a summary of the results and future plans for research on common variation in the PGC, citing findings of 128 genome-wide significant hits for schizophrenia, 10 for BPD, and findings from the cross-disorder analyses. In light of the polygenic nature of these conditions, he described the large number of cases that will be necessary, particularly for disorders such as MDD, which has a lower relative risk than those of schizophrenia and BPD. He described the next step involving eQTL dissection of loci, indicating that these studies could inform pathophysiology. Dr Shaun Purcell (Mount Sinai School of Medicine, New York, USA) spoke about the value of pursuing studies of rare variation in psychiatric disorders, particularly of highly penetrant single gene loci that can inform the mechanism of action of disease genes and delineate more homogeneous subgroups for analysis. He presented

examples of a trio-based Bulgarian sample and a Swedish case–control sample that showed excess burden of very rare gene-disruptive mutations across ∼ 2500 genes, without enrichment of de-novo LoF variants. Despite the technical challenges in harmonizing datasets, he noted the importance of consortia and me(t/g)a-analyses in rare variant discovery and potential models of collaboration. Dr Benjamin Neale (Massachusetts General Hospital and the Broad Institute, USA) spoke about the genomics of ASDs and the major goal of discovery of actionable biological pathways with rare variants providing particular promise of success. LoF mutations as well as de-novo or two-hit recessive markers may be particularly valuable in ASDs. Challenges in this work include the reduced power because of neutral rare variation, the very large sample sizes required (e.g. 88 000 cases would be required to obtain 80% power for a relative risk of 1.1), and the complex genetic architecture of ASDs. Naomi Wray, PhD (The University of Queensland), described the genetic architecture of psychiatric disorders that are characterized by genes with small effects. She also described the importance of considering the architecture of specific disorders that appear to be highly variable using the lower amount of variance explained by genes for MDD than for some other psychiatric disorders. She highlighted the need for collecting more information on phenotypes, environmental risk factors, and genetic information on the same sample to investigate their combined contribution toward psychiatric disorders. Dr Mark Daly (Massachusetts General Hospital and the Broad Institute, USA) closed the session by stating that genetics, big data, and statistics are delivering, with data sharing as a key factor in the success. The major topics of the discussion included the following: (a) the reliability and accuracy of sequencing technology; (b) the need for more active recruitment of additional samples, particularly those with environmental risk information and additional phenotypic information; and (c) the development of a database for rare variants including pathogenicity information with input from clinical geneticists, which would be particularly valuable for the future. In his ‘Young Investigator Award’ talk, Dr Stephan Ripke (Massachusetts General Hospital; Broad Institute, USA) highlighted research in genetics as a driving force to our understanding of biology. His presentation was mainly focused on the efforts of the PGC, the challenges, and the successes it yielded over the last few years. First, he gave the example of Crohn’s disease, where early GWAS research showed more than 70 genome-wide significant sites. Dr Ripke stressed the importance of genetics in drug development (Plenge et al., 2013) through the example of statins, where previous GWAS research in hyperlipidemia indicated genetic sites with small effects but huge clinical significance. Contrary to somatic diseases, the psychiatric field faces more challenges. He



gave a small historical tour of PGC, beginning in 2009 with relatively small samples of schizophrenic patients and ever growing. Vast efforts led to more than 100 distinct genetic regions being associated with schizophrenia (Ripke et al., 2013). Among the new genes was the dopamine receptor 2, DRD2, long implicated in schizophrenia. Moreover, calcium channels, glutamate receptors (GRM3), sex-linked genes, and the immune system have emerged as components of schizophrenia’s genetic architecture.

The use of novel statistical methods to understand genetic architecture (reported by David T.W. Chen) Dr Lea K. Davis (University of Chicago, USA) presented on the additive genetic risk (chip heritability) using Tourette syndrome (TS) and OCD as examples. Interestingly, the results showed that chip heritability were quite similar to twin estimates (h2 for TS = 0.58; OCD = 0.37). Polygenicity was observed, with some chromosomes contributing larger portions (chromosome 15 for OCD). Also, common and rare variations appeared to contribute equal portions to the heritability of TS (MAF < 0.05, h2 = 0.13), but rare variations made no contribution for OCD. Finally, h2 estimates by brain eQTL were 33 and 59% (TS, OCD, respectively). A shared genetic correlation was also found (r2 = 0.41; P = 0.002). Dr Gerhard Moser (University of Queensland, Australia) described a single model for GWAS (Erbe et al., 2012) that maps causal variants, estimates the genetic variance explained by all SNPs, and predicts phenotypes from SNP genotypes. The Swedish schizophrenia cohort (∼7000 case–controls) and the WTCCC (seven phenotypes) were used. The accuracy of risk prediction depends on the heritability and genetic architecture of the trait. Less than 10 000 SNPs explained all of the genetic variance for schizophrenia, with 98% each explaining 0.0001% of the genetic variance. Compared with other methods, this approach had higher prediction accuracy for traits with relatively strong associations. Dr Alexander Gusev (Harvard School of Public Health, USA) showed findings from coding variations in schizophrenia in the Swedish cohort (∼6400 case–control). Recent GWAS chip heritability for schizophrenia has not yet matched twin estimates. Using GCTA, common coding heritability was estimated at ∼ 0.4. On breaking down into noncoding regions [i.e. UTR, promoters, DNase 1 hypersensitivity site (DHS), intergenic], the DHS was found to be nominally significant for enrichment. Observing consistency between exome chip and GWAS data, this approach was applied to nine traits in the WTCCC data. Similar enrichments for coding and DHS regions were observed, especially with imputed SNPs (20-fold for coding; six-fold for DHS).

Dr Kaitlin Samocha (Massachusetts General Hospital; Broad Institute, USA) presented on the contribution of de-novo variation to ASD. Despite high heritability (70–90%), only 10–20% have known lesions (chromosomal abnormality or FMR1 gene silencing). Recent reports of sequencing ∼ 950 families showed approximately two-fold excess of de-novo ‘loss of function’ (LoF) variants, implicating neither pathways nor disease processes. To develop a clearer expectation, she developed a probability model of genome-wide de-novo rates using the 1000 Genomes data. With this method, a significant enrichment for LoF de-novo mutations in the low IQ ASD group only was observed. Furthermore, approximately two-fold enrichment for de-novo LoF mutations (P = 1.44E − 6) for FMRP gene targets for all ASD samples was observed. Subdivided by IQ, approximately three-fold enrichment (P = 1.48E − 7; odds ratio = ∼ 6) was observed only in the low IQ ASD group notable for an over-representation of individuals with atypical cognition and female sex. No excess was observed in cases with IQ of at least 100. Dr Eli Stahl (Icahn School of Medicine, Mt Sinai, New York, USA) discussed the genetic architecture of schizophrenia in the Swedish study (∼12 000 participants) using the polygenic risk score profiling approach. Results for schizophrenia showed a plateauing effect with increasing number of SNPs, suggesting a difference in genetic architecture from other diseases such as rheumatoid arthritis. To better understand these differences, a simulation (ABPA) of polygenic risk score profiling was utilized. The results showed that 50% of the variance was explained with ∼ 8000 SNPs. Compared with GCTA, a larger portion of the variance was explained. Dr Michael E. Talkowski (Massachusetts General Hospital, Harvard Medical School, Broad Institute, USA) discussed the role of structural variation in neuropsychiatric diseases. He sequenced all classes of structural variation, including small or ‘cryptic’ balanced chromosomal rearrangements (disrupting a single gene without net gains or losses from the genome) using large insert jumping libraries (3–4 kb fragments with 40–140 × coverage) in 34 individuals with comorbid developmental and psychiatric disorders. Structural variant calls were refined by machine learning, followed by validation by PCR/Sanger, which showed several potentially pathogenic cryptic rearrangements directly disrupting genes such as (CTNNA3, FAM155A, UBE2F) as well as the first example of cryptic chromothripsis.

Biomarkers and endophenotypes (reported by Tania Carrillo Roa) Sophie E. Legge (Cardiff University, UK) presented results from two GWAS of schizophrenic patients with clozapine-induced neutropenia (n = 64, < 1500 cells/ mm3) and severe clozapine-induced neutropenia (n = 18, < 1000 cells/mm3) versus treated controls (n = 5469). The



sample was obtained from two UK sources: the CLOZUK and the Cardiff COGS sample. Samples were genotyped on two different Illumina arrays and further imputed. Quality control and logistic regression were performed separately on each array and meta-analyzed using Plink (Purcell et al., 2007). She reported two genome-wide significant SNPs (rs116019360 and rs112478317 on chromosome 1p36.32 and 12q14.3, respectively) associated with clozapine-induced neutropenia and one genome-wide significant SNP (rs75062547) associated with severe clozapine-induced neutropenia. rs75062547 is located in an intron of SLX41P; mutations in this gene have been associated previously with Fanconi anemia (Kim et al., 2011). Dr Lina S.C. Martinsson (Karolinska Institutet, Sweden) investigated whether response to long-term lithium treatment for BPD is associated with telomere length (TL) (Martinsson et al., 2013). The study included 256 outpatients with BPD and 139 controls. TL was determined by quantitative real-time PCR in peripheral blood leukocytes. Cases had 35% longer telomeres compared with controls (P < 0.0005, partial η2 = 0.13); TL was positively correlated with lithium treatment duration (P = 0.031, r2 = 0.13, < 30 months) and negatively associated with increasing number of depressive episodes (P < 0.007). Lithium-responders had longer telomeres than nonresponders, suggesting that increased telomerase activity might be involved in response to lithium treatment in BPD patients. Dr Marco P.M. Boks (Rudolf Magnus Institute Neuroscience, the Netherlands) discussed results from an epigenome-wide association study (Illumina 450k) in a cohort of Dutch military individuals deployed to Afghanistan (n = 96). They hypothesized that DNA methylation changes because of trauma lead to an increase in PTSD. Blood samples and standardized measures PTSD were collected before and 6 months after deployment. This cohort was divided into subgroups on the basis of the level of combat trauma exposure and the presence of PTSD symptoms. Results showed two genome-wide associated CpG loci, with later development of PTSD. These loci are located in the PPP1R18 gene and the AMZ1 gene, which is proposed as a candidate biomarker for the development of PTSD. Dr Alexander B. Niculescu III (Indiana University School of Medicine, USA) sought to identify differentially expressed genes in blood in patients (n = 75) diagnosed with BPD during no suicidal ideation states and high suicidal ideation states, as well as between patients (Le-Niculescu et al., 2013). They used convergent functional genomics to identify and prioritize from the list of differentially expressed genes, biomarkers of relevance to suicidality. They also examined whether expression levels of these were altered in blood from agematched suicide completers. Thirteen of the 41 top

convergent functional genomics scoring biomarkers (32%) showed a step-wise significant change from no suicidal ideation to high suicidal ideation states and to the suicide completer. Their top identified biomarker could differentiate future hospitalizations because of suicidality in a cohort of bipolar patients. Dr Rakesh Karmacharya (Harvard Medical School, USA) reported on the opportunity to generate neuronal cells that contain genetic backgrounds from patients by reprogramming iPSCs and neuronal progenitor cells (NPCs) from fibroblasts. He reprogrammed iPSCs and NPCs from patients with schizophrenia and BPD as well as matched controls. Methodologies were developed to differentiate these along neuronal lineages and mature neuronal cultures, as well as assays to study image-based phenotypes, and gene expression to identify unique signals involved in these disorders. He hypothesized that the vulnerability for disease will be reflected at the cellular level when studying specific neuronal subtypes. Dr Stephen J. Glatt (SUNY Upstate Medical University, USA) spoke about a machine-learning algorithm that distinguished children with ASDs from those developing normally on the basis of gene expression levels in peripheral blood samples. Their goal was to identify differentially expressed genes between subsamples from normal development, ASD, DD, or language delay children as well as to replicate previous results in an independent sample of ∼ 200 individuals. Expression levels of differentially expressed genes were used to optimize support vector machines classifying patients into clinically derived diagnostic categories. The support vector machine that obtained ∼ 70–90% accuracy in distinguishing ASD patients from normally developing children in their initial results achieved an accuracy of 58% in the replication sample. Further cross-validation, reoptimization of classifier parameters, and more precise quantification of mRNA isoforms will aim to identify more accurate and stable classifiers of ASDs and other developmental disorders. Their results suggest that the continued pursuit of a blood-based biomarker of early autism is warranted. Neuroimaging: the ENIGMA consortium (reported by Kimm J.E. van Hulzen)

The ENIGMA consortium was presented as an international resource that brings together researchers in imaging genomics. It aims to explore the genetic architecture associated with human brain structure and function to find the genetic underpinnings of psychiatric and neuro-degenerative disease using structural and function MRI and diffusion tensor imaging (DTI) and genomewide association data. The ENIGMA consortium started in 2009 with three groups and now consists of 35 sites contributing to the analysis. Free and standardized imaging protocols, quality control guidelines, and genetic imputation and association testing protocols are made



available for the participating sites, but also for individuals outside the consortium through the website, to perform genome-wide association analysis. Meta-analysis of results obtained from participating sites is carried out by the support group of the ENIGMA consortium. This session provided an overview of the consortium’s work on structural MRI and DTI. ENIGMA1 is a pilot project in which the support group of ENIGMA carried out meta-analyses on hippocampal volume, intracranial volume, and total brain volume including over 16 000 individuals from 28 sites that span five continents. Dr Derek Hibar (University of California), member of the support group of the ENIGMA consortium, showed that several genome-wide significant variants were found to be associated with hippocampal and intracranial volume. ENIGMA1 was followed by ENIGMA2, an ongoing project that extends the scope of ENIGMA1 by including subcortical volumes (nucleus accumbens, amygdala, caudate, pallidum, putamen, thalamus, as well as hippocampal and intracranial volume). ENIGMA2 was initiated in 2012 and involves additional participating sites. ENIGMA2 is currently nearing completion and first results were presented in this session. The collaboration of sites in the ENIGMA consortium has led to the creation of working groups addressing a range of important topics, including genetic influences on white matter microarchitecture and integrity. This integrity is measured through DTI fractional anisotropy and is shown to be highly heritable. Variations in fractional anisotropy are also strongly linked to disorders such as schizophrenia and Alzheimer’s disease. The DTI Working Group was formed with the initial goal of developing a validated protocol to obtain reliable and consistently heritable measures from images. Dr Emma Sprooten (Yale University) showed that this protocol is now easily implementable at many ENIGMA sites that have DTI and genome-wide association data. In addition to the DTI Working Group, the focus on neuroimaging as an endophenotype for psychiatric and neurodegenerative disease has led to the formation of working groups carrying out phenotypic meta-analyses examining the association between brain measures and psychiatric disease and neurodegenerative disease. The Bipolar Disorder Working Group was represented by Dr Ole A. Andreassen (Oslo University Hospital). Their approach is to first determine patient versus control effect sizes for subcortical volume differences, and second, explore common genetic variants associated with the brain structure abnormalities. Asymmetry in left and right cortical structures will be taken into account in a later stage. The Schizophrenia Working Group was represented by Dr Jessica Turner. She presented preliminary results from a coordinated, large-scale meta-analysis applying the same quality assurance metrics and statistical models across independent datasets, with the goal of

identifying the strongest effect sizes across the various subcortical abnormalities in schizophrenia. Given the focus on neuroimaging as an endophenotype for psychiatric and neurodegenerative disease, a crossconsortium collaboration was established with the PGC (ENIGMA2-PGC2). The ENIGMA2-PGC2 collaboration aims to (a) find genetic variants that have both effect on brain and effect on disease, (b) lend biological relevance to findings of the ENIGMA consortium and the PGC, and (c) validate endophenotypes.

Networks and pathways (reported by Adeniran Okewole and Julia Steinberg) Dr Amitabh Sharma (Northeastern University, Boston, USA) discussed the application of protein interaction networks to disease genetics. For the majority of diseases, the associated genes were more tightly connected to a network than expected by chance, suggesting that the disease might result from localized perturbations in a network. The tighter the connection of the genes associated with the disease, the more similar the annotations of the genes were based on gene ontology. Moreover, the overlap or distance between modules for different diseases reflected the similarity of the diseases on the basis of overlap of symptoms, comorbidity, or similarity of the gene annotations for the disease genes. Starting with a set of associated disease genes, the network allows the detection of a network module extended to other candidate genes, the ranking of all other genes on the basis of the distance to the module, the identification of biological pathways overlapped by the module, and the identification of drugs that modify the expression of the module genes. During the discussion, tissue specificity of gene expression and protein interactions emerged as an important factor for future networks. Dr Kristen Brennand (Mount Sinai, New York, USA) presented results from modeling schizophrenia predisposition using human-iPSCs (Brennand et al., 2011). iPSCs derived from schizophrenic patients and controls were differentiated into neural tissue corresponding to the first trimester stage. A rabies transneuronal tracing assay showed reduced connectivity and outgrowth of neurons derived from iPSCs of schizophrenic patients. However, this did not affect basal electrophysiology or spontaneous Ca2 + transients. Gene expression differences between iPS-derived neurons from schizophrenia patients and controls pointed to gene ontology processes such as synaptic proteins, cell adhesion, and migration. Some expression changes in known schizophrenia candidate genes could be reversed when the cells were treated with loxapine. When NPCs were derived from iPSCs of schizophrenia patients and controls, gene expression and protein analyses showed some differences related to synaptic transmission. The NPCs derived from patients also showed higher oxidative stress and aberrant migration.



Dr Olaf Sporns (Indiana University, USA) presented a network analysis of the ‘human brain connectome’, a structural map of human brain regions from MRI data (Hagmann et al., 2008). The analysis showed features such as the existence of brain region modules linked by hub regions, unique regional connectivity fingerprints, short path lengths between brain regions, and a prominent structural core. Moreover, structural connectivity of regions was found to predict functional connectivity. The highly connected/central hub nodes were often connected to each other (‘rich-club’ organization). The ‘richclub’ enables short, efficient information transfer and the integration of information from diverse sources (Van den Heuvel and Sporns, 2011). As 89% of the shortest paths between brain regions were found to pass through a member of the ‘rich-club’, damage in the ‘rich-club’ was hypothesized to strongly affect the integrity and efficiency of the network. A similar ‘rich-club’ was also detected in the macaque brain (Harriger et al., 2012). The human ‘richclub’ members were found to be connector hubs, linking resting-state networks determined from functional connectivity. In schizophrenic patients, the density of ‘richclub’ connections was reduced; this correlated with a lower global efficiency (Van den Heuvel et al., 2013), whereas local connection density was unaffected. Dr Dennis Vitkup (Columbia, New York, USA) presented an analysis of gene networks underlying autism and schizophrenia. He cited earlier reported clustering of genes harboring inherited mutations (Feldman et al., 2008) and information on the similarity of genes on the basis of coevolution, coexpression, and colocalization, integrating these into a gene network (Gilman et al., 2011). He presented a study adopting a naïve Bayesian integration approach to create a model, which was investigated using NETBAG (Network Based Analysis of Genetic Associations). CNVs, SNVs, and SNPs were combined under one principled framework. Implicated gene networks in ASD involved chromosome modification/regulation, neuron signaling/cytoskeleton, postsynaptic density, and channel activity (primarily calcium channels). Schizophrenia clustered into a signaling/ cytoskeleton functional network and a chromosomal modification/regulation network. Network connections were found between genes implicated in ASD, intellectual disability, and schizophrenia. He concluded by forecasting 300–1000 causal genes in 20–40 pathways involved in 5–10 biological processes. The genes in the subnetwork showed high expression in the human brain, with higher brain expression of the genes mutated in females with autism compared with the genes mutated in males. An analysis of genome regions associated with schizophrenia showed a significant subnetwork with functions in cell signaling similar to autism. This work highlighted the need to adopt a computational approach to integrate the diversity of genetic data into a framework that would aid understanding of pathways and networks.

Dr Dick McCombie (Cold Spring Harbor Laboratory, New York, USA) discussed the potential overlap of genes involved in autism and schizophrenia, with a possible link to chromatin remodeling. He presented data on exome sequencing of 42 trios of unaffected parents and schizophrenia offspring. Findings included a higher than expected number of de-novo nonsense mutations that overlap with ASD and intellectual disability, and enrichment of genes involved in chromatin remodeling and epigenetic mechanisms (CHD8, MLL2, MEPCP2, HUWE1). Dr Daniel Howrigan (Massachusetts General Hospital, Boston, USA) discussed emerging evidence for the FMRP gene network enrichment among de-novo LoF alleles in ASD and schizophrenia. He presented findings from a Taiwanese trio schizophrenia sample. There were 1135 trios of sporadic cases, with 117 putative de-novo LoF mutations. Four overlapping genes were found, all four being in the FMRP network that is enriched in both autism and schizophrenia. Second, he introduced the PsychChip design, whose components include a GWAS 256k platform, an exome component (∼236k), and a Psych component (∼50k). The platform was designed to cheaply genotype large samples to identify robust associations. The custom content covers common and rare variants, CNVs, and community requests. Dr Daniel Geschwind (UCLA, USA) presented a study mapping SFARI and exome sequencing data of ASD to developmental and anatomical data (developmental dynamics and laminar specificity). Modules were found to reflect important processes in cortical development. Coexpression network showed clustering of genes affected by de-novo mutation, and networks helped stratify the more pathogenic variants. Transcriptional and translational regulation was found to be linked to the ASD modules. With respect to anatomical and circuit specificity of ASD genes, a difference was recorded in laminar enrichment of ASD-associated gene modules in fetal human cortex and adult cortex. Function, expression, protein interaction, and regulation were all implicated. Finally, ASD genes converged to disrupt neuronal development and cortical–cortical connectivity in superficial layers.

Stem cell science (reported by Hilary Akpudo) Dr Kevin Eggan (Harvard University, USA) highlighted that new and emerging developments in stem cell research have made it imperative that the architecture of disease is reconceptualized. The hierarchical ways of classifying disease fail to take into account new genetic variations that are now known to underlie many neurologic and psychiatric diseases. With the emergence of a myriad of variants found in psychiatric patients with autism and schizophrenia, two convergent models to consider are the idea that (a) different mutations act through distinct pathways with strong effects to cause



psychiatric disease and (b) that many small genetic variants add up through convergent pathways to place individuals into the psychiatric disease box. In either case, we have to deploy models that have the flexibility and capacity to take on board the study of many different genetic variants in parallel. Stem cell reprogramming approaches have presented new opportunities by allowing an unprecedented supply of neuronal subtypes with relevance to psychiatric disease and other conditions. If done reproducibly and well, this promises to be an important tool for dissecting the effects of these monogenic variants on human neurobiology. He reported that with advances in stem cell biology and reprogramming technology, it has become routine to use the cell-based model of psychiatric disorders: fibroblast cells obtained from patients can be used to generate live human neurons with a genetic background known to produce the disease state. First, fibroblasts can be reprogrammed to hiPSCs by transient expression of OCT4, SOX2, KLF4, and c-MYC and then subsequently differentiated into NPCs and mature neurons. Second, fibroblasts can be directly converted into iNPCs by transient expression of SOX2 and then subsequently differentiated to neurons. Third, fibroblasts can be directly converted into a neuronal fate by transient expression of ASCL1, BRN2, MYT1L, and NEUROD1. The real challenge for stem cell science is how to responsibly deploy these types of technologies to gain a durable understanding of the genetic underpinnings of these conditions. He addressed important questions about these technologies: (a) what can in-vitro-derived cell types offer and what are the liabilities of these systems? (b) Given that psychiatric diseases affect select cell types in the brain, can the correct cell types be produced rather than just generic neurons in culture? (c) How reproducible can we make the cell lines from patient to patient, from experiment to experiment? What are the influences of these reprogramming processes on the products made and studied? When progenitor cells or human embryonic stem cells are induced to differentiate into specific neural populations for the study of disease, one problem that every directed differentiation or lineage conversion approach has is that none of them is neatly efficient in making the type of cells we are interested in. The cell subtype is embedded in a milieu of diverse cell types from the nervous system. The relative proportion of the desired cell type in the mixture is variable. One approach to overcome this problem is to engineer stem cell lines to carry reporter genes that allow those cells of interest to be prospectively purified out of those more diverse and complicated populations of cells. Cell line variation in the study of psychiatric disease adds substantial ‘noise’ to phenotypic measures. This problem can be overcome with gene targeting approaches, which could also be useful in understanding the causal nature of variants.

New mutations (reported by Lea K. Davis) Dr James R. Lupski (Baylor College of Medicine, Texas, USA) spoke on the mechanisms for human genome rearrangements. He described two major classes of rearrangement including recurrent and nonrecurrent events, and highlighted the clinical importance of these mechanisms. He noted that the postzygotic mosaic mutation was 100–1000 times greater than the mutation rate for SNVs. He described the mechanisms of nonhomologous end joining as well as fork stalling and template switching, which is a replication-mediated mechanism and can result in multiple complex rearrangements. He noted that CNVs can cause disease by multiple mechanisms and that rare variants can contribute toward common disease phenotypes. Dr Jonathan Sebat (University of California, San Diego, USA) spoke on using whole-genome sequencing to identify hotspots for germline mutation in autism disorders (ASDs). He presented the results of a study of 10 monozygotic twin families with ASDs. Five of the genes discovered with germline mutations were also highlighted in recent autism exome studies. He then described a metric constructed to quantify the mutability of each base pair in the genome using genomic annotations and the finding that genes associated with dominant disorders have a higher mutability index. Dr Steven A. McCarroll (Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, USA) spoke on mutational hotspots and genetic analysis of psychiatric illness. He described a study designed to understand the relationship between replication timing and mutational events. The first step of the study was to grow cells asynchronously and then sort the mid S-phase cells and compare genome-wide DNA dosage levels to G1 cells (single diploid), thus constructing a map across the genome to determine which regions replicate early and which replicate late. They found that the timing of replication events is synchronous across cells from a single individual, but polymorphic across individuals. The genetic variants controlling the timing events were then mapped by GWAS. In addition, they then found that transitions, transversions, and polymorphisms in general were more common in late replicating regions of the genome. Dr Christopher A. Walsh (Boston Children’s Hospital) spoke on somatic mutation and genomic diversity in the developing human cerebral cortex. He presented results from a study in which 300 single neurons from three normal individuals were analyzed with multiple displacement amplification and assessed for aneuploidy. They found significant clonal mosaicism of retrotransposon-mediated aneuploidy in the brain, which can be mapped to a single neuronal source. These events are unlikely to be a major source of neuronal diversity, but in some cases, may be responsible for disease.



The future of psychiatric genetics: where do we go from here? (reported by Alison Merikangas) Drs Lynn DeLisi and Jordan Smoller (Harvard Medical School, Boston, USA) introduced the session and the key issues on the next steps for biological follow-up and clinical translation of recent genetic discoveries. Dr Patrick Sullivan (University of North Carolina, USA) described that the primary goal of psychiatric genetics is to discover underlying genetic and biologic pathways rather than explaining heritability. He anticipated that gaining understanding of the types and numbers of variants, their mutual interactions, and the combined influence of environmental factors will be possible within the next 3–10 years through both continued collaborative efforts and application of multiple approaches in tandem, such as examining common variation, structural variation, exome sequencing, and whole-genome sequencing to facilitate discovery. Dr Peter Donnelly (Wellcome Trust Centre for Human Genetics, Oxford, UK) explained the goals of studying genetics including: (a) to learn key biology in an accessible tissue; (b) to improve risk prediction; and (c) to stratify the patient population, thereby refining the diagnosis and improving treatments. He contrasted the rate of discovery of common variants for schizophrenia with those for Crohn’s disease, which required much smaller samples, and how the latter led to the identification of its key biologic pathways. Future research on gene regulation and developmental timing, discovery of relevant tissues, and their clinical relevance in terms of drug targets on the basis of the direction of gene/pathway modulation will be other important future directions. There appears to be no relationship between GWAS effect size and the potential as a drug target (e.g. statins). Because there do not appear to be low-frequency variants of large effect, and their lack of power, he questioned the value of sequence-based discovery as it has not yet yielded much information, especially in light of the high cost. He supported efforts to mine large prospective cohorts, such as the UK Biobank, in the future. Dr Mark Daly (Massachusetts General Hospital and the Broad Institute, USA) described the changing contributions of genetic findings to our understanding of the underpinnings of disease, that they may deliver biological insight that will be useful in therapeutic development. As GWAS do not directly identify these pathways, advances in high-throughput genomics, neurobiology, and identification of supportable models (human cells, fish, and mice) to reverse the molecular change are needed. He suggested that genome sequencing will provide an opportunity to explore the genetic underpinnings of psychiatric disorders and redirect efforts away from noninformative findings. Genomics may also lead to identification of distinct therapeutic subgroups as well as in adverse drug reactions.

Dr Thomas Insel (Director of The National Institute of Mental Health, USA) described multiple ongoing and future directions for genomics research including: (a) the continued use of large samples; (b) studies of gene expression (e.g. the Genetic Tissue Expression project of > 900 individuals with 32 tissue types exploring variation in tissue expression); (c) developments in iPSC technology and model animal studies; (d) identification of environmental effects on gene expression; (e) studies that identify phenotypes on the basis of genotypes, particularly rare variants; (f) studies of resilient populations; and (g) studies examining developmental patterns of gene expression (e.g. the BrainSpan project). He emphasized that all of these directions will rely on sharing, standardizing, and integrating data. Issues addressed in discussion: (a) the need to expand studies to other (non-European) ancestries; (b) disagreement on whether identification of a large number of genetic markers of small effect can be considered a success; (c) the importance of replication before moving forward with labor-intensive biologic studies; and (d) the importance of identifying environmental risk factors. The difficulties in consortia models were discussed in terms of consent and attribution of scientific contributions. The 2013 Snow and Ming Tsuang lifetime achievement award winner: John I. Nurnberger Jr (Indiana University School of Medicine, USA) (reported by Leon M. Hubbard)

Dr Nurnberger’s work has contributed considerably toward the genetics and neurobiology of BPD, AD, and autism/autistic spectrum disorders (ASDs). He presented a fascinating journey through 20th-century and 21stcentury psychiatric genetics, with an emphasis on the advances in BPD. He spoke about his psychiatric residency at the New York State Psychiatric Institute in the 1970s, where his interest in BPD developed through working with Professor David Dunner (University of Washington), who defined bipolar II and rapid cycling subtypes. His mentor, Elliot Gershon (University of Chicago), introduced him to methodological design of family, linkage, and association studies that would become pivotal in his career. Reflecting on research performed with Gershon and colleagues on the neurobiology of BPD in the 1980s, Professor Nurnberger spoke about the novel paradigms used to study cholinergic rapid eye movement sleep in euthymic bipolar patients (Sitaram et al., 1980) and super sensitivity to light being a potential trait of BPD (Lewy et al., 1985), among others. These studies investigated interesting hypotheses, but he reflected that they had problems of scalability, and could not overcome problems of disease heterogeneity and other confounding factors such as medication effects. The development of consortia has helped to overcome some of the limitations observed in smaller scale studies in the 1980s. Professor Nurnberger is a member of



COGA, the Autism Genome Project, the Bipolar Genome Study, and Bipolar High Risk Consortium. Furthermore, he discussed his involvement with the PGC Bipolar Working Group that found genome-wide association for rs1006737 in CACNA1C. Enrichment was observed for the gene ontology category ‘voltage gated calcium channel activity’ including calcium channel genes CACNA1D and CACNB3 (Psychiatric GWAS Consortium Bipolar Disorder Working Group, 2011). A recent meta-analysis of individuals with schizophrenia, BPD, major depression, autism, and ADHD showed enrichment for calcium channel genes across these disorders [Cross-Disorder Group of the Psychiatric Genomics Consortium; Genetic Risk Outcome of Psychosis (GROUP) Consortium, 2013]. Calcium channel antagonist flunarizine has shown antipsychotic properties in schizophrenia (Bisol et al., 2008); however, single studies lack consistency, with further work required to translate the observed enrichment of calcium channel genes into efficacious treatments (Casamassima et al., 2010). In conclusion, Professor Nurnberger compared the myriad of new genetic findings across psychiatric diseases with a good harvest after the summer rains. He instilled the importance of utilizing technological innovation and collaboration to further understand the genetic etiology and neurobiology of psychiatric disorders.

Acknowledgements This report was made possible by grants from NIMH and NIDA: R13MH060596 and R13DA022792. Each summary is the subjective understanding of the rapporteur for each session. The data reported are as heard during the presentation and where possible; all statements have been checked with the speaker for accuracy. However, the speakers are not responsible for any of the information contained in this report. Conflicts of interest

There are no conflicts of interest.

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Summaries of plenary, symposia, and oral sessions at the XXII World Congress of Psychiatric Genetics, Copenhagen, Denmark, 12-16 October 2014.

Rapporteur summaries of plenary, symposia, and oral sessions from the XXIIIrd World Congress of Psychiatric Genetics Meeting in Toronto, Canada, 16-20 October 2015.

Abstracts of the International Academy of Cardiology Annual Scientific Sessions 2014 19th World Congress on Heart Disease, July 25-28, 2014, Boston, Massachusetts., USA, july 25-28, 2014.

Abstracts of the 5th World Congress on Sleep Medicine, 28 September-2 October 2013, Valencia, Spain.

The 2013 EAPC World Congress.

WORLD BRAIN MEETING The XXII World Congress of Neurology, Santiago, Chile: October 31 - November 5, 2015.

Selected personal highlights of the 8th Interdisciplinary World Congress on Low Back and Pelvic Pain, Dubai, October 2013.

The International Diabetes Federation’s 2013 World Diabetes Congress, Melbourne, Australia.

9th world stroke congress, 22-25 october 2014, istanbul, Turkey.

WFC'S 13th Biennial Congress Proceedings Athens, Greece, 10-13, 2013: Abstracts of the Scientific Sessions.

Report on the VIII World Congress of Physchiatry, Athens: October 1989.

Genetics of Parkinson's disease--state of the art, 2013.

Declaration of Hawaii. Declaration adopted unanimously by the General Assembly of the World Psychiatric Association at the Sixth World Congress of Psychiatry, 1977.

World Congress on Osteoporosis, Osteoarthritis and Musculoskeletal Diseases (WCO-IOF-ESCEO 2015): Meet-the-Expert Sessions.

At the crossroads of oral facial genetics.

Abstracts of the Scientific Sessions from the WFC'S 12th Biennial Congress Proceedings, Durban, South Africa, April 10-13, 2013.

Twenty-seventh annual meeting of the Congress of Neurological Surgeons, San Francisco, California (open scientific sessions, October 13, 1977) and Carmel-by-the-Sea, California (supplementary scientific sessions, October 15 and 16, 1977). Abstracts.

Evaluating the Impact of the Healthy Beverage Executive Order for City Agencies in Boston, Massachusetts, 2011-2013.

Report on the 2013 European Multidisciplinary Cancer Congress-ECC 17, Amsterdam, 27 September-1 October 2013: nursing highlights.

The 6th World Congress of Paediatric Cardiology and Cardiac Surgery, Cape Town 2013.

Proceedings of the EPMA World Congress.

Completing the results of the 2013 Boston marathon.

5th World Congress of the International Academy of Oral Oncology (IAOO).

The nurses group oral sessions.