Abstracts of the 4th Biennial Schizophrenia International Research Conference / Schizophrenia Research 153, Supplement 1 (2014) S1–S384 S73

DISC1 coding variants identified exclusively in patients were found in likely

functional protein domains and functional analyses haves confirmed effects

on protein-protein interactions and mitochondrial function. Sequence vali-

dation confirmed that the majority of single nucleotide polymorphisms had

a minor allele frequencies of <1% and have not been reported in the 1000

Genomes Project. Analysis suggests that many variants remain undiscov-

ered and are essentially private. Such high levels of rare variation requires

multi-marker analyses and better understanding of the putative function

of non-coding variants. We will present the results of analyses from both

sequencing of the DISC1 locus and the DISC1 interactome that consists of

over 260 genes implicated in downstream signalling of the DISC1 pathway.

The results identify association between DISC1 and recurrent major depres-

sion from both single marker and burden analyses, as well as evidence for

epistatic interactions between regions of DISC1, and nominal association

for burden of coding and non-coding variants with measures of mood and

cognition. These results indicate that variants that alter gene expression

will be as important as those that alter protein sequence. We will describe

our bioinformatic pipelines for prioritisation of both coding and non-coding

variants utilising the growing publically available genome annotation.

INTERPRETING GENE NETWORKS FOR SCHIZOPHRENIA RESEARCH:

BIASES, HEURISTICS, AND CONTROLS

Jesse Gillis

Cold Spring Harbor Laboratory, Cold Spring Harbor, USA

A central challenge to understanding neuropsychiatric disorders is de-

termining how candidate variants interact with one another and the

environment to produce a disease phenotype. In response to this challenge,

gene networks have become a common resource for integrating potentially

diffuse functional effects into a single common framework. Ideally, candi-

date variants not only converge on consistent pathways or interact within

a network, but also do so in a way that is perturbed in response to disease

or factors relevant to disease. The interpretation of gene networks related

to the brain is particularly important not just because the biology of the

brain is complex, but also because the number of genes involved appears to

be so high. This has the effect of making methods for interpreting systemic

properties of the brain particularly likely to rely on computational means,

and many of the problems that seem endemic to network analysis are

actually properties specific to the interpretation of brain related networks.

For example, how should we interpret a cluster of genes numbering in the

thousands that seems to be involved in disease? While network analyses

can be extremely opaque (even to their developers), they are grounded in

a few straightforward principles. Understanding those principles gives us a

basis for interpreting the results of network studies. The central top-down

principle in the interpretation of gene networks is “Guilt by Association”

(GBA) and it simply states that genes which share functions are more

likely to be associated. This principle generally finds application in two

uses within networks: first, in attempting to learn gene properties; and,

second, in validating the network as a whole. A good network is taken to

be one which exhibits this property strongly, and networks are frequently

optimized to ensure this property holds. Many, perhaps most, analyses

of “novel” sets of candidate disease genes rely on GBA to claim that the

genes have some known shared function determinable through their as-

sociations. In a recent series of papers, we laid out grounds for treating

previous gene network analyses related to function with scepticism. We

showed that gene networks (protein interactions, genetic interactions and

co-expression) tend to encode very generic information about gene func-

tion without learnable specificity, leading to highly multifunctional genes

dominating analyses to the point that details of network structure have a

surprisingly small impact. We suggest that this property plays a dominant

role in most previously reported network analyses. We focus on replicating

published reports on schizophrenia gene networks in demonstrating the

important role of this confound. We consider approaches for addressing this

problem using co-expression networks. Multifunctionality bias can creep

into co-expression analyses in subtle ways (e.g., gene representation across

microarray platforms). We will present our findings as to “best practises”

surveyed across a large collection of public microarray data sets and fo-

cusing on meta-analysis of matched schizophrenia/control data across 306

post-mortem samples from the pre-frontal cortex. Because co-expression

networks built in this way are not so generically swamped by enrichment of

multifunctional/prevalent/promiscuous/hub genes, they exhibit specificity

to the data from which they were constructed (e.g., disease state). We

provide concrete steps necessary to control for functional specificity when

attempting to characterize schizophrenia candidate genes in network data.

Workshop

RECENT ADVANCES IN COGNITIVE BEHAVIOUR THERAPY FOR

PSYCHOSIS (CBTP) FOR COMPLEX AND TREATMENT RESISTANT

GROUPS

Chairperson: Emmanuelle Peters

Discussant: Til Wykes

Tuesday, 8 April 2014 6:30 PM – 8:30 PM

Overall Abstract: CBTp is recommended by national UK (NICE 02; 09) and

US (PORT; 10) treatment guidelines. However, it is not without contro-

versy. Some have claimed that the CBTp movement has gone too far, with

claims for its efficacy being unfounded (McKenna, 03), while others have

claimed it has not gone far enough, and should be offered as an equal

choice to medication (Morrison, 12). Recent advances have focused on

theoretically-informed, targeted interventions, rather than branding CBTp

as a quasi-neuroleptic (Birchwood & Trower, 06). This symposium will

present the latest findings in CBTp trials for complex and treatment re-

sistant populations by the leaders in the field. The discussant, Til Wykes

(Institute of Psychiatry), who has published the most highly quoted CBTp

meta-analysis (Wykes et al, 08), will cast a critical eye on the findings and

lead a discussion on their clinical implications. Max Birchwood (Warwick

University) will present the results of a multicentre RCT comparing CBT

for Command Hallucinations with treatment-as-usual (TAU). In a sample of

197 individuals, CBT significantly reduced the perceived power of the voice

to do harm, which was linked to a halving of the rate of serious compliance

18 months post randomisation. This trial demonstrates one of the largest

effect size of CBTp to date, and marks a significant breakthrough in the

evidence base for this most severe group. Tom Craig (Institute of Psychiatry)

will describe the development of AVATAR therapy, an adaptation of “voices

dialogue” therapy in which patients enter into a dialogue with their voices.

Patients create a representation of their voice using computerised face

animation software, and select a speech sample matching the quality of

their voice. The therapist speaks either as the avatar or in their own voice.

The pilot study (Leff et al, 13) showed striking results, with patients who

received AVATAR therapy reporting significant reductions in hallucinations

compared to TAU; some patients stopped hearing voices entirely. The larger

RCT is underway, comparing 7 sessions of AVATAR therapy with a support-

ive counselling control condition for 142 patients with treatment-resistant

voices. Basic descriptive data and illustrative cases will be presented, and

the updated AVATAR system will be demonstrated. Traditionally therapists

have been wary of treating trauma in psychosis patients, for fear that it

may worsen the psychosis. Mark van der Gaag (Vrije Universiteit Amster-

dam) will report the findings from a group of 155 patients with psychosis

and post-traumatic stress disorder (PTSD) who were randomised to Eye

Movement Desensitisation and Reprocessing (EMDR); Prolonged Exposure

(PE), or TAU. Both therapies were effective with large effect sizes (EMDR:

0.76; PE: 0.83) on PTSD scale scores, with 66% of the treated patients no

longer fulfilling criteria for PTSD, and fewer adverse events than the TAU

group. This trial demonstrates that reducing trauma symptoms in psychosis

through exposure is a safe and effective psychological intervention. To date,

CBTp has mostly been implemented as an adjunct to medication. Tony

Morrison (University of Manchester), however, showed in a pilot trial that

CBTp could be effective in individuals who have chosen to not take med-

ication (Morrison et al, 12). These results have been replicated in a larger

RCT, which recruited 74 unmedicated patients who were followed up for a

minimum of 9 and a maximum of 18 months. Psychiatric symptoms were

significantly reduced in the CBTp group, compared to TAU, with an esti-

mated between-group effect size of −6.52 (95% CI −10.79 to −2.25, p=0.003).

The results have important implications for the provision of mental health

services for people with schizophrenia spectrum disorders.