Information from Lay-Language Summaries is Embargoed Until the Conclusion of the Scientific Presentation
308—Biomarkers and Imaging in Schizophrenia
Monday, November 11, 2013, 8:00 am - 11:15 am
308.11: Altered connectivity in limbic subnetworks during emotion processing: A graph-based intermediate phenotype linked to the genetic risk for schizophrenia
*H. CAO1, A. SCHAEFER1, O. GRIMM1, H. WALTER2, A. HEINZ2, L. HADDAD1, H. TOST1, A. MEYER-LINDENBERG1; 1Central Inst. of Mental Hlth., Mannheim, Germany; 2Dept. of Psychiatry and Psychotherapy, CharitÈ Universitaetsmedizin Berlin, Berlin, Germany
Abstract Body: Amygdala dysfunction during emotion processing has been reported in schizophrenia, but the question whether this deficit represents a valid intermediate phenotype for illness remains disputed. Specifically, a prior fMRI study (Rasetti et al., 2009) failed to observe deficits in amygdala activity and connectivity in healthy first-degree relatives of schizophrenia patients during emotional face-matching task, an observation that does not support the notion these deficits relate to the genetic risk for the illness. To explore the potential impact of the analysis method on this null finding, we applied the same face-matching task to 60 unaffected first-degree relatives of schizophrenia and 100 controls without a family history of mental illness that were matched for age, sex, task performance, and site. Activation analysis followed established procedures including random-effects group analysis of individual contrast estimates (face-matching > form-matching). Brain graphs were constructed from 90 anatomical nodes defined by the AAL atlas. Network-based statistics (NBS) were performed as previously described (Zalesky et al., 2010) by computing initial t-test statistics for all pairwise associations and generating a set of suprathreshold links. Link-clusters were identified using breadth first search, and permutation testing was used to derive the corrected p value for the identified link-clusters. Consistent with the earlier report, we failed to detect a significant group difference in amygdala activity in the standard activation analysis (pFWE = 0.18, small-volume corrected). However, NBS provided evidence for a disconnected limbic subnetwork in relatives. Specifically, a cluster of totally 37 altered links between pairs of nodes including the amygdala, fusiform gyrus, parahippocampal gyrus, insula, and orbitofrontal cortex was identified. The functional connectivity were significantly decreased in the healthy first-degree relatives compared to the matched controls (pcorr = 0.01). These data provide evidence for a potential novel graph-based functional intermediate phenotype for schizophrenia manifesting as decreased connectivity in limbic subnetworks, and draws attention to the choice and differential sensitivity of fMRI-based outcome measures in imaging genetics. Further work in patients is necessary to show the presence of this systems-level phenotype in subjects with manifest illness.
Lay Language Summary: Our research identifies a diminished functional dynamic of the brain emotion processing network (or “limbic system”) in healthy first-degree relatives of schizophrenia patients. These individuals share, by definition, half of the genes conferring risk for the illness, suggesting that the observed deficits reflect a “neural signature” of the genetic vulnerability for schizophrenia. Schizophrenia is a highly heritable illness. Many affected patients show difficulties in emotion expression and recognition, which is linked to the alterations in limbic brain function, but the link between these deficits and the genetic risk for the illness is disputed. Specifically, prior research in healthy first-degree relatives of schizophrenia patients suggested that the impairments in the limbic processing of emotions do not relate to the genetic vulnerability for the illness, a research outcome that may be affected by the choice of the analysis methods that characterize the functional interplay of limbic brain regions. To test this hypothesis, we used a newly-developed method called ‘network-based statistics’ for the characterization of the interaction of brain networks. This method surveys neural areas (or ‘nodes’) across the whole brain and quantifies the “functional connectivity” between each of the areas, i.e., their interregional cooperation and communication. To achieve this, we recruited 60 healthy first-degree relatives of schizophrenia patients and 100 healthy volunteers without a family history of mental illness. All participants performed a face-matching task during a functional magnetic resonance imaging (fMRI) experiment, which involves the processing of pictures with fearful or angry facial expressions. We carefully matched the groups for task performance during the experiment, i.e., both groups accomplished the task with equal accuracy and speed. This was important for the interpretation of our findings, as any differences in overt behavior during the experiment would complicate the understanding of the brain functional results. We found that in the relatives group, the participants showed decreased functional connectivity during emotion processing. This decreased network consisted of functional interactions between brain regions in the limbic system, and between the limbic system and nodes in the visual system (where the input emotional pictures are initially processed). As both groups were healthy, but only the relatives group had an enriched set of schizophrenia risk genes, this may indicate that schizophrenia risk genes disturb the well-organized functional communications of brain regions relevant for the understanding and expression of emotions. Moreover, as we only observed group differences in the functional interplay of limbic regions, but not in their own activity, this further suggests that the involved risk genes disturb the coordinated communication rather than the response of individual regions in the emotion processing network of the brain. The limbic system is a complex set of brain structures that includes, among others, the amygdala, cingulate cortex, insula, and orbitofrontal cortex. This system plays a critical role in the neural processing of emotions in humans and has been previously identified to be associated with the emotional symptoms of schizophrenia patients. Schizophrenia is a common mental disorder that affects about 1% of the population lifetime and involves severe impairments in perception, cognition, emotion, and behavior. The neural mechanisms of schizophrenia are incompletely understood, yet genetic factor is a well-known risk for the illness. Our research extends prior research in the field, highlights the value of high-dimensional methods for the characterization of functional brain networks, and provides novel insights into the neural mechanisms related to the genetic risk of schizophrenia. Further work is necessary to show the presence of these alterations in patients with manifest illness and in healthy risk gene carriers.
Neuroscience 2013 (43rd annual meeting of the Society for Neuroscience)Exit