Project Details
Projekt Print View

Establishing Interhemispheric Interaction assessed by resting state fMRI as an Intermediate Phenotype of Schizophrenia Risk Genes

Subject Area Biological Psychiatry
Term Funded in 2012
Project identifier Deutsche Forschungsgemeinschaft (DFG) - Project number 212170118
 
Final Report Year 2013

Final Report Abstract

Schizophrenia is a heritable disorder with genetic factors accounting for more than 80% of the variance in schizophrenia susceptibility. A new line of research, referred to as imaging genetics, has emerged in recent years, which uses brain activity patterns as intermediate phenotypes to investigate the impact of genetic polymorphisms on brain function. These intermediate phenotypes based on direct observation of brain activity are supposed to be closer to the genetic substrate than clinically diagnosed disorders. We proposed to establish an imaging biomarker for schizophrenia risk genes based on the intrinsic hemispheric interaction of the brain, which is completely independent of task paradigms and therefore avoids the confounding factors inherent in all task-based imaging paradigms. However, before embarking on the development of an imaging biomarker based on the lateralization of brain connectivity it is essential to have a clear understanding of the intra-subject reliability and range of inter-subject variability of intrinsic functional connectivity estimates. Therefore, before exploring functional alterations in schizophrenia, we made use of a previously acquired data set of twenty-three healthy subjects each scanned five times over six months. This unique dataset allowed us to assess the spatial distribution of inter-subject variability while controlling for measurement instability based on intra-subject variance. The resulting map of inter-subject variability showed a remarkable distribution with significantly higher inter-individual variability in heteromodal association cortex and lower variability in unimodal cortices. Inter-subject variability in connectivity was significantly correlated with the degree of evolutionary cortical expansion, suggesting a potential evolutionary root of functional variability. The connectivity variability was also related to variability in sulcal depth and positively correlated with the degree of long-range connectivity. A meta-analysis further revealed that regions predicting individual differences in cognitive domains are predominantly located in regions of high connectivity variability. Our work also received media interest in Germany. "Spektrum der Wissenschaft" will report on our findings in its upcoming issue of Gerhirn und Geist and the Bayerische Rundfunk broadcasted an interview about our study. In a second step, after having explored the reliability and variability of intrinsic functional connectivity, we aimed to establish a robust estimate of hemispheric specialization based on intrinsic functional connectivity. Hemispheric specialization of the human brain is a marker of successful neurodevelopment and may reflect the pathological connectivity changes in schizophrenia. Altered brain asymmetry has been repeatedly reported in schizophrenia including striatal presynaptic dopamine function as well as cortical neural activation. However, a complete picture of functional specialization in the schizophrenic brain and its connectional substrates are yet to be unveiled. Here we quantified the intrinsic hemispheric specialization at the whole brain level based on resting-state functional connectivity MRI. The caudate nucleus and cortical regions linked to the caudate showed markedly abnormal hemispheric specialization in schizophrenia. Compared to healthy controls, patients exhibited increased intrinsic specialization in the left caudate but decreased specialization in the right caudate. Schizophrenia patients also displayed a loss of the normal reverse correlation between the left and right caudate specialization, indicating the disruption of the coordination between two hemispheres. A linear classifier based on the specialization of the caudate nucleus distinguished the patients from controls with a classification accuracy of 72%, which is significantly better than traditional biomarkers based on anatomical features. These data suggest that hemispheric functional specialization could serve as a potential imaging biomarker for schizophrenia, and may be related to the asymmetric dopamine metabolism in the striatum.

Publications

  • Individual Variability in Functional Connectivity Architecture of the Human Brain. Neuron. 2013 Feb 6; 77(3): 586-95
    Mueller S, Wang D, Fox MD, Yeo BT, Sepulcre J, Sabuncu MR, Shafee R, Lu J, Liu H
    (See online at https://doi.org/10.1016/j.neuron.2012.12.028)
 
 

Additional Information

Textvergrößerung und Kontrastanpassung