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WCPG 2013—Substantial Genetic Leads Emerge for Schizophrenia

October 23, 2013. Over 900 researchers gathered in Boston, Massachusetts, to attend the 21st World Congress of Psychiatric Genetics. Organizers Jordan Smoller and Lynn DeLisi, both of Harvard Medical School, welcomed people from all over the world to the city, which offered up bright autumn days to offset dimly lit conference rooms. On Friday, October 18, a schizophrenia genetics symposium emphasized that the way forward lies in collaborations among researchers from all over the world.

The PGC takes Manhattan
On behalf of the Psychiatric Genomics Consortium (PGC), Stephan Ripke of the Broad Institute in Cambridge, Massachusetts, gave an update on their efforts to find common variants contributing to schizophrenia through genomewide association studies (GWAS) (see SRF related news story). Since 2009, the PGC has been amassing ever larger sample sizes with increasing returns, and this year was no different: Comparing single nucleotide polymorphisms (SNPs) between 35,476 cases of schizophrenia and 46,839 controls revealed a whopping 97 genomewide-significant hits. “This is one of the most thrilling analyses of psychiatric genetics ever,” Ripke said.

These hits replicated in an independent sample and together implicated 108 distinct regions, including three on the X chromosome. Plotted across the genome, these signals crossed the very high bar for genomewide significance (p < 5 x 10-8), reaching the skyscraper-like heights looked for in these so-called Manhattan plots. Together these signals accounted for 13 percent of liability for schizophrenia. These hits shine spotlights on a daunting 672 genes, and Ripke highlighted a selection that neuroscientists will recognize: DRD2, which encodes the D2 dopamine receptor, the common target of antipsychotic drugs; various genes encoding glutamate receptors (e.g., GRM3, GRIN2A); and genes for voltage-gated calcium channels (CACNAC1C, CACNB2, CACNA1L). These results mesh with current ideas about overactive dopamine and underactive glutamate signaling in schizophrenia (see SRF hypotheses by Anissa Abi-Dargham and Bita Moghaddam).

Ripke was also this year’s winner of the Theodore Reich Young Investigator Award, and in his celebratory talk on Sunday morning, he described some of the genes that harbored GWA-significant variants in more detail. One was NLGN4, an autism-related gene that encodes a protein involved in synaptic wiring. Another was KCTD13, which lies within the large region at 16p11.2 that, when duplicated, increases risk for schizophrenia. Here, the GWAS signals narrowed in on KCTD13, which controls head size in zebrafish (see SRF related news story). Further analyses showed that the signals are reassuringly enriched in brain-related genes as well as immune system genes (even when signals in the major histocompatibility region were excluded). Ripke argued that even things with very small effect sizes give a clearer picture of biological mechanisms, and he emphasized that finding all of them will require further collaboration.

Consortiums (and acronyms) prevail
Steven McCarroll of the Broad Institute described a newly developing resource called the Genomic Psychiatry Cohort (GPC; Pato et al., 2013), which aims to sequence the entire genome in over 30,000 people, including a subset with schizophrenia. So far, 759 whole genomes are done, including 500 schizophrenia cases. This has picked up 28 million variants with high resolution. For example, McCarroll highlighted the crisp boundaries of the well-known 22q11 deletions found in schizophrenia, which give more accurate measures of the size and locations of these deletions. In addition, whole-genome sequencing detected other types of gene-disrupting variations: smaller deletions that interrupted single exons within a gene; extreme instances of CNVs in which a person carried two to 12 copies of a DNA segment; and insertions of short, mobile pieces of DNA known as Alu elements that can move throughout the genome.

McCarroll also made the point that sequencing turns up many stretches of DNA that don’t align to the human reference sequence. That’s because this venerable reference is, in fact, incomplete, particularly around the centromeres. Studying people of mixed ethnicity has helped map these regions (Genovese et al., 2013), which include one—1q21—hit by deletions in schizophrenia. McCarroll mentioned that things that looked like fairly identical 1q21 deletions are, with sequencing, turning out to be different in size and relative location—something that may help explain the variable expressivity and penetrance associated with such deletions.

Looking for clues among the subset of genes expressed by the brain, Menachem Fromer of the Mount Sinai School of Medicine in New York City outlined the CommonMind Consortium (CMC), a new, collaborative effort to sequence the RNA from large numbers of brain samples. Consisting of five academic groups, two pharmaceutical companies, and one nonprofit, the consortium has already sequenced the RNA from postmortem samples of dorsolateral prefrontal cortex from 228 people with schizophrenia and 240 controls. Unlike microarrays that probe expression of select transcripts, RNA sequencing can pick up a more comprehensive collection of transcripts, including rare or unknown splice variants. Preliminary results point to 27 genes upregulated and 63 genes downregulated in schizophrenia compared to controls. Finally, the CMC plans to eventually make its data available to other researchers to promote further analysis by using the Synapse platform.

Other penetrating results
In the same session, George Kirov of Cardiff University in the United Kingdom evaluated just how harmful deletions or duplications of segments of DNA—called copy number variants (CNVs)—are. Though rare, many CNVs scattered across the genome increase risk for schizophrenia (see SRF related news story) as well as for other neural disorders. According to Kirov’s newly published analysis (Kirov et al., 2013), a given CNV is not equally potent across disorders, however. For 70 specific CNVs, a lower frequency was found in cases of schizophrenia than in cases of autism, developmental delay, or congenital malformations lumped together. Based on these frequencies, plus the occurrence of these CNVs in controls, Kirov estimated the penetrance for each CNV, which was the probability of developing schizophrenia for people carrying a particular CNV. For schizophrenia, this revealed a high penetrance, ranging between 10 to 100 percent for each CNV. But their penetrance was even higher for the developmental delay category. This indicates that these CNVs are highly pathogenic, but more likely to produce an early-onset disorder than schizophrenia, and suggests that some other factors interact with CNVs to buffer, or worsen, their effects.

Karolina Aberg of Virginia Commonwealth University in Richmond reminded the audience of yet another kind of genetic variation, found within the complicated patterns of DNA methylation across the genome (the “methylome”). Methyl groups added to stretches of DNA suppress the expression of the genes underneath, and Aberg asked whether these patterns differed in schizophrenia. Starting with blood cells from 750 people with schizophrenia and 750 controls, Aberg extracted the methylated parts of the genome and then sequenced it. This revealed 141 differently methylated regions, implicating 139 regions within or near genes. Several of these were replicated in a second dataset, including those pointing to FAM63B—a gene linked to neuronal differentiation—and CREB1, SMAD3, and ARNT—genes with roles in hypoxia and which suggest lasting marks of environmental mishaps. Preliminary results in postmortem brain tissue suggested a similar, disease-specific pattern of overmethylation in gene pathways related to hypoxia and the immune system. Still, one audience member worried that studying the methylome derived from blood rather than brain may not be optimal. Aberg countered that blood-based information may offer a reliable biomarker for, if not causal insight into, schizophrenia.—Michele Solis.

Comments on Related News

Related News: Schizophrenia Genetics 2: The Rise of GWAS

Comment by:  Chris Carter
Submitted 7 April 2010
Posted 8 April 2010

I wonder whether the relative lack of success in schizophrenia GWAS may be because the origin of schizophrenia may lie not so much in the genetic make-up of people with schizophrenia themselves, but in their prenatal experience, and possibly with the genes of the mother rather than with those of the offspring. Famine, rubella, influenza, herpes (HSV1 and HSV2), and poliovirus infection as well as high fever during pregnancy have all been listed as risk factors for the offspring developing schizophrenia in later life, as have maternal preeclampsia and obstetric complications. (See page at Polygenic Pathways for the many references.)

Maternal resistance to these effects is likely to be gene-dependent. Is it worth considering GWAS in the mothers rather than in the offspring?

View all comments by Chris Carter

Related News: SfN 2013—New Tools for Rational Drug Design

Comment by:  Hugo Geerts
Submitted 29 January 2014
Posted 5 February 2014

Multi-target drug discovery has typically been neglected in the world of genetics and high-throughput screening because of the difficulty of rationally defining a pharmacological profile, but it has major advantages for treating complex disorders such as schizophrenia. It is no wonder that the currently approved antipsychotics do have a rich pharmacology and substantially improve the clinical phenotype. With so many different genotypes defining individual patients, focusing on only one target is likely to have small effects that might disappear in clinical trials with larger patient populations. Even over all indications (not only CNS), more than half of the first-in-class medicines approved in the last decade have been found by using phenotypic assays and have typically multi-target pharmacology (Swinney and Anthony, 2011).

The approach presented here suggests a rational way to identify 1) a set of targets and 2) chemical structures that might serve as hits for further medical chemistry development. It might therefore alleviate the concerns of many medical chemistry departments in pharmaceutical companies.

Changing the mindset from developing the next extremely specific and potent inhibitor to pursuing multi-target pharmacology is urgently needed to break the deadlock of unsuccessful new drug development in schizophrenia.


Swinney DC, Anthony J. How were new medicines discovered? Nat Rev Drug Discov . 2011 Jul ; 10(7):507-19. Abstract

View all comments by Hugo Geerts

Related News: Channels of Working Memory

Comment by:  David C. Glahn
Submitted 11 March 2014
Posted 11 March 2014

The article by Heck and colleagues provides additional support for the notion that common genetic factors influence risk for schizophrenia and working memory performance. While evidence that working memory performance is sensitive to genetic liability for schizophrenia was well established by twin and family studies (e.g., Cannon et al., 2000; Glahn et al., 2007), the current article extends these findings by suggesting that at least a portion of this joint effect is conferred by common variants in the voltage-gated cation channel activity (see QuickGO page) gene network. The paper provides a potential biological mechanism through which a set of genes could influence both traits. Such testable biological hypotheses are critical both for unraveling the genetic architecture of schizophrenia and other psychotic illnesses and for helping to characterize how these genes aid in manifesting the behavioral disorders. Thus, although the paper does not provide a single pleiotropic gene as would be required in classical human genetics, I believe the findings represent a true advancement in our understanding of schizophrenia genetics.

A major strength of the paper is the large number of independent samples with similar, but not identical, working memory measures that provided data for the discovery or replication samples. Papassotiropoulos and his group have applied this powerful approach to provide insight into the genetic make-up of cognitive processes, particularly memory.

Recently, there has been a good deal of debate concerning the utility of endophenotypes in the search for mental illness genes. As described by Gottesman and Gould (Gottesman and Gould, 2003), endophenotypes are measurable components unseen by the unaided eye along the pathway between disease and distal genotype. John Blangero and I pointed out that joint genetic determination (pleiotropy) of endophenotype and disease risk is fundamental to the endophenotype concept (Glahn et al., 2012). The current paper clearly demonstrates pleiotropy between schizophrenia risk and working memory performance, reinforcing working memory as a schizophrenia endophenotype and demonstrating how such traits can be used to provide testable biological hypotheses.

Finally, I would like to point out that this work was primarily conducted in healthy individuals not selected for mental illness. The endophenotype and normal variation strategy (e.g., using unselected samples to learn about the genetic factors influencing an endophenotype and then confirming these results in a sample selected for the illness) has worked in other areas of medicine, and I believe it will work in psychiatric genetics as well. Indeed, I think this paper demonstrated exactly that.


Cannon TD, Huttunen MO, Lonnqvist J, Tuulio-Henriksson A, Pirkola T, Glahn D, Finkelstein J, Hietanen M, Kaprio J, Koskenvuo M. The inheritance of neuropsychological dysfunction in twins discordant for schizophrenia. Am J Hum Genet. 2000 Aug;67(2):369-82. Epub 2000 Jul 3. Abstract

Glahn DC, Almasy L, Blangero J, Burk GM, Estrada J, Peralta JM, Meyenberg N, Castro MP, Barrett J, Nicolini H, Raventós H, Escamilla MA. Adjudicating neurocognitive endophenotypes for schizophrenia. Am J Med Genet B Neuropsychiatr Genet. 2007 Mar 5;144B(2):242-9. Abstract

Glahn DC, Curran JE, Winkler AM, Carless MA, Kent JW Jr, Charlesworth JC, Johnson MP, Göring HH, Cole SA, Dyer TD, Moses EK, Olvera RL, Kochunov P, Duggirala R, Fox PT, Almasy L, Blangero J. High dimensional endophenotype ranking in the search for major depression risk genes. Biol Psychiatry. 2012 Jan 1;71(1):6-14. Abstract

Gottesman II, Gould TD. The endophenotype concept in psychiatry: etymology and strategic intentions. Am J Psychiatry. 2003 Apr;160(4):636-45. Review. Abstract

View all comments by David C. Glahn