On Monday, I sat in on part of a nanosymposim entitled “Biomarkers and Imaging in Schizophrenia.” Again, I was drawn to these talks because of their relevance to my work, but their content is worth sharing with the broader SfN 2013 audience.
In the first talk I heard, Guusje Collin from the Rudolf Magnus Institute of Neuroscience presented data on the structural organization of networks in unaffected siblings of schizophrenia patients. Using diffusion tensor imaging (DTI), Collin and colleagues were able to look at the white matter tracts of the brains of these siblings in the form of a network. They were then able examine the connectivity within what’s called the “rich club” of these networks, meaning a group of densely interconnected hubs (pictured in red in the image) that serve as centers of integration of information in the brain. The connectivity of these rich club regions has been previously demonstrated to be reduced in patients with schizophrenia.
In their current study, Collin have found that when looking at siblings of these individuals (who don’t have schizophrenia themselves), there is reduced rich club connectivity as compared to unrelated control participants. In fact, the unaffected siblings appear to have intermediate rich club connectivity that falls between the schizophrenia patients and the control participants. This finding indicates that there appears to be a familial or perhaps genetic influence on rich club connectivity as it relates to schizophrenia. Thus, this phenotype of impaired connectivity could indicate a predisposition to this disorder.
In future work, Collin plans to explore rich club connectivity in additional disorders, such as bipolar disorder, and compare the connectivity to that of schizophrenia.
In another talk, Hengyi Cao from Heidelberg University discussed an additional intermediate phenotype that can be found in unaffected siblings of schizophrenia patients. It is well documented that emotional dysfunction is a common symptom of schizophrenia. Previous studies involving functional connectivity analyses of unaffected siblings of schizophrenia patients have found no changes in connectivity in the amygdala, a region known to play a role in the processing of emotions such as fear. However, Cao argued that these null-findings may have been due to the analysis techniques that were used.
Using graph theoretical analyses, in which regions of the brain are treated as nodes in a functional network, Cao and colleagues explored the functional connectivity of unaffected siblings of schizophrenia patients and unrelated control participants while they completed a matching task involving faces showing different emotions. Interestingly, there were no differences between these groups in terms of global network organization; however, Cao was able to identify a subnetwork of limbic system and visual cortex areas in which connectivity was lower in the siblings of schizophrenia patients.
Cao was then able to to collapse this network into a single variable by averaging the strength of each connection in the network. This variable correlated with neuroticism and anxiety, in that those with lower connectivity in this subnetwork demonstrated higher levels of these schizophrenia-associated symptoms.
Similar to the findings of Collin’s group, these findings indicate a potential intermediate phenotype of limbic system connectivity, which relates to genetic risk for schizophrenia. Interestingly, Cao’s future plans include exploring the connectivity of this limbic/visual system subnetwork in patients with schizophrenia, which I actually think should have been done before looking at unaffected siblings.
[This post was originally published at my previous blog, Neurolore.]
In the first talk I heard, Guusje Collin from the Rudolf Magnus Institute of Neuroscience presented data on the structural organization of networks in unaffected siblings of schizophrenia patients. Using diffusion tensor imaging (DTI), Collin and colleagues were able to look at the white matter tracts of the brains of these siblings in the form of a network. They were then able examine the connectivity within what’s called the “rich club” of these networks, meaning a group of densely interconnected hubs (pictured in red in the image) that serve as centers of integration of information in the brain. The connectivity of these rich club regions has been previously demonstrated to be reduced in patients with schizophrenia.
In their current study, Collin have found that when looking at siblings of these individuals (who don’t have schizophrenia themselves), there is reduced rich club connectivity as compared to unrelated control participants. In fact, the unaffected siblings appear to have intermediate rich club connectivity that falls between the schizophrenia patients and the control participants. This finding indicates that there appears to be a familial or perhaps genetic influence on rich club connectivity as it relates to schizophrenia. Thus, this phenotype of impaired connectivity could indicate a predisposition to this disorder.
In future work, Collin plans to explore rich club connectivity in additional disorders, such as bipolar disorder, and compare the connectivity to that of schizophrenia.
In another talk, Hengyi Cao from Heidelberg University discussed an additional intermediate phenotype that can be found in unaffected siblings of schizophrenia patients. It is well documented that emotional dysfunction is a common symptom of schizophrenia. Previous studies involving functional connectivity analyses of unaffected siblings of schizophrenia patients have found no changes in connectivity in the amygdala, a region known to play a role in the processing of emotions such as fear. However, Cao argued that these null-findings may have been due to the analysis techniques that were used.
Using graph theoretical analyses, in which regions of the brain are treated as nodes in a functional network, Cao and colleagues explored the functional connectivity of unaffected siblings of schizophrenia patients and unrelated control participants while they completed a matching task involving faces showing different emotions. Interestingly, there were no differences between these groups in terms of global network organization; however, Cao was able to identify a subnetwork of limbic system and visual cortex areas in which connectivity was lower in the siblings of schizophrenia patients.
Cao was then able to to collapse this network into a single variable by averaging the strength of each connection in the network. This variable correlated with neuroticism and anxiety, in that those with lower connectivity in this subnetwork demonstrated higher levels of these schizophrenia-associated symptoms.
Similar to the findings of Collin’s group, these findings indicate a potential intermediate phenotype of limbic system connectivity, which relates to genetic risk for schizophrenia. Interestingly, Cao’s future plans include exploring the connectivity of this limbic/visual system subnetwork in patients with schizophrenia, which I actually think should have been done before looking at unaffected siblings.
[This post was originally published at my previous blog, Neurolore.]
