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25th European Congress of Psychiatry / European Psychiatry 41S (2017) S8–S52

the considerable variability in these neurobiological correlates

between patients can be translated into the clinical setting.


We aimed to identify neuroimaging predictors of clin-

ical course in patients with schizophrenia. Combined with the

identification of genetically determined markers of schizophrenia

risk, our studies aimed to elucidate the biological basis and the

clinical relevance of inter-individual variability between patients.


We included over 150 patients with schizophrenia and

279 healthy volunteers across five neuroimaging centers in the

framework of the IMAGEMEND project

[1] . W

e performed multiple

studies on MRI scans using random forests and ROC curves to pre-

dict clinical course. Data from healthy controls served to normalize

the data from the clinical population and to provide a benchmark

for the findings.


We identified ensembles of neuroimagingmarkers and of

genetic variants predictive of clinical course. Results highlight that

(i) brain imaging carries significant clinical information, (ii) clin-

ical information at baseline can considerably increase prediction



The methodological challenges and the results will

be discussed in the context of recent findings from other multi-site

studies. We conclude that brain imaging data on their own right are

relevant to stratify patients in terms of clinical course; however,

complementing these data with other modalities such as genetics

and clinical information is necessary to further develop the field

towards clinical application of the predictions.

Disclosure of interest

Giulio Pergola is the academic supervisor of

a Hoffmann-La Roche Collaboration grant that partially funds his



[1] Frangou S, Schwarz E, et al. World Psychiatry 2016, doi:



Neuroimaging findings in ADHD and

the role of genetics

B. Franke

Radboud University Medical Center, Departments of Human Genetics

and Psychiatry, Nijmegen, The Netherlands

ADHD is frequently diagnosed in children and adults. The disorder

is highly heritable. However, the genetic architecture of ADHD is

complex, with multiple genetic variants of individually small effect

size contributing to disease in most patients.

In our own studies as well as in the large mega-analyses of

the ENIGMA ADHD Working Group, we have investigated the

brain substrates of ADHD. We find the disorder to be char-

acterized by delayed sub–cortical and cortical growth of gray

matter in childhood, which gradually normalizes in adulthood:

sub–cortical volumes as well as cortical thickness and surface

area are smaller in children with ADHD, but become indistin-

guishable from healthy individuals in adulthood. The situation

looks different for white matter connectivity: both in childhood

and adulthood, widespread differences in the major white matter

tracts are found. The pattern of findings suggests that alterations

in myelination might lie at the basis of such case-control dif-

ferences. Since the disorder and many brain structural measures

affected in ADHD are highly heritable, we investigated the overlap

of genetic risk factors for ADHD with genetic factors involved in

brain volume. This resulted in the identification of several genetic

variants contributing to disease risk as well as ADHD-related brain


In conclusion, we find ADHD to be a disorder of delayed brain mat-

uration in terms of gray matter, but of persistently altered white

matter connectivity across the lifespan. Genetic factors influencing

both disease risk and brain measures might improve our under-

standing of disease etiology and persistence.

Disclosure of interest

The author declares that he has no compet-

ing interest.


Cortical and Sub–cortical volumetric

abnormalities in bipolar disorder

O. Andreassen

University of Oslo, NORMENT Centre- Dept of Mental Illness and

Addiction, Oslo, Norway

Previous MRI studies of bipolar disorder (BD) are often limited

by small sample sizes and heterogeneity exists with regard to

neuroimaging markers. To address these limitations, the ENIGMA

Bipolar Disorder Working Group collected the largest BD neu-

roimaging data set ever studied (


= 6,500). Here, we review

findings from sub–cortical volume and cortical thickness and area


ENIGMA harmonized analysis methods were applied to 28 interna-

tional pooled study samples of MRI data and involved sub–cortical

and cortical imaging analyses. We assessed differences between

BD and healthy controls (HC) using both mega and meta–analytic

multiple linear regressionmodels, adjusting for standard covariates

(age, sex, etc.), and correcting for multiple comparisons.

Sub–cortical volume analysis revealed we found consistent volu-

metric reductions in BD patients for hippocampus and thalamus

and enlarged lateral ventricles in patients. In BD, cortical gray mat-

ter was thinner in frontal, temporal and parietal regions of both

brain hemispheres. BD had large general effects on mean gray mat-

ter thickness in both left and right brain hemispheres. Further we

found that psychopharmacological treatment showed significant

associations with cortical thickness and surface area.

The ENIGMA pipeline allows for identification of brain MRI abnor-

malities in BD in the largest analysis ever conducted. The results

suggest a pattern of brain structure abnormalities, which provide

novel insight in pathophysiology of BD, and potential effects of

mood stabilizing agents.

Disclosure of interest

Received speaker’s honorarium from Lund-

beck, Lilly, Otsuka

Symposium: Schizophrenia and clinical

psychopathology: From research to clinical



Are deficits in social cognition

differentiating between

schizophrenia and affective disorders

G. Sachs

1 ,

, E . M


2 , A.




Medical University of Vienna, Department of Psychiatry and

Psychotherapy, Vienna, Austria


Otto Wagner Spital, 6th Psychiatric Department, Vienna, Austria

Corresponding author.

Over the last decades, in matters of the assessment of psy-

chopathology and its clinical consequences, there has been an

increased interest in neurocognitive function including non-social

and social cognition.

Classic psychopathology -as represented e.g. by the standardized

AMDP system- focuses on pathognomonic signs for the catego-

rization of syndromes

[1] a

nd differentiates between disturbances