SfN Day 3/Theme C: Altered structural and functional connectivity in schizophrenia and unaffected siblings – evidence for intermediate phenotypes?

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.


SfN Day 2: Change in stress across development and functional connectivity

Day 2 has already been jam packed with lots of exciting findings presented here at Neuroscience 2013. In some weird, unintentional effort to wear myself out (what is wrong with me?) I’ve been going up and down the escalators, bouncing between the poster hall and talks all morning.

In one of my forays upstairs, I sat in on a short talk by Alice Graham from the University of Oregon. Graham presented a novel way to look at a commonly studied topic: early life stress. Citing a study that discovered obesity in individuals who experienced famine in utero as opposed to postnatally, Graham emphasized that there is a mismatch between pre- and postnatal environments when it comes to risk for disease. Instead of looking at stress at a specific time point in development (e.g. only prenatal), Graham proposed looking at the change in stress that occurs as an infant transitions from the pre- to postnatal environment.

This change in stress might be particularly evident in a variable such as interparental conflict. This variable, tested via response to an angry-toned voice, has been previously shown in Graham’s work to influence functional connectivity between the medial prefrontal cortex (mPFC) and other brain regions in infants. In a new study, Graham used self-report measures to show that interparental conflict is higher in the postnatal environment, meaning after a baby is born, as compared to the prenatal environment, meaning during pregnancy. Perhaps this has something to do with sleep deprivation and the screaming, spitting up bundle of joy, I’m not sure.

Since there is a difference in the stress due to interparental conflict that an infant might experience prenatally versus postnally, there may be differential effects of this stress on development. Graham studied this difference within the context of resting-state functional connectivity in the default mode network (DMN), a functional network in the brain that is active when someone is not specifically engaged in a task. Graham chose this network because it seems to be impacted by early life stress and it exhibits rapid development from 0 to 2 years of life.

When subtracting prenatal interparental conflict from postnatal interparental conflict, Graham showed that functional connectivity was increased between the posterior cingulate cortex and the following regions: mPFC, medial temporal lobe, inferior temporal gyrus, and the right amygdala. Thus, the postnatal increase in the stress an infant might experience due to interparental conflict seems to increase functional connectivity between several regions of the DMN, effectively speeding up the development of this network.

Perhaps this is an adaptive response to stress. However, Graham noted that another study has reported increased DMN functional connectivity in full term infants as compared to premature infants, meaning the less stressed, full term infants actually displayed greater DMN connectivity. This finding is in contrast to the findings of Graham’s group. Accordingly, further study of the effects of change in stress across development is necessary. Perhaps different types of stress have different effects at different times. As with most questions in neuroscience, this idea is compelling, yet extremely complicated.

SfN Day 1/Theme C: Altered functional connectivity in autism, as confirmed by MEG

It’s only been Day 1 of Neuroscience 2013, I am already filling up with awesome findings to share (plus my feet are already mad at me). Since my themes are pretty disparate (C: Disorders of the Nervous System & H: History/Teaching/Public Awareness/Societal Impacts) I figured it would be helpful to post on each theme separately throughout the week. So here we go:

SfN Day 1/Theme C – Human Biomarkers of Autism

The first poster I visited turned out to be very relevant to my work as well as pretty interesting. Annette Ye of the University of Toronto took the time to discuss her poster (49.01) on the highly explored topic of altered functional connectivity in adolescents with autism spectrum disorder (ASD), only she looked at this idea using magnetoencephalography (MEG), as opposed to functional magnetic resonance imaging (fMRI). MEG data complements the information provided by fMRI, as it provides a picture of the synchrony of oscillations in neural activity. Using resting state MEG data, Ye and colleagues explored the synchrony between 90 brain regions using different frequency bands. When comparing individuals with ASD to those without ASD, they found several regions, most of which were in the frontal lobe, that exhibited increased inter-regional connectivity in the gamma frequency band. This frequency band is related to local as opposed to long range connections and may be predictive of cognition. Disruption in neural synchrony within this band has been associated with schizophrenia and depression.

When Ye used graph theoretical analysis, in which brain regions are treated as nodes in a connected functional network, the increased functional connectivity among the frontal lobe regions was confirmed by increased node strength and clustering coefficients, indicating stronger inter-regional connections and a greater likelihood of neighboring connections, respectively. These MEG findings replicate previous findings that functional connectivity may be higher in ASD in local areas of the brain, including those related to cognition. Whereas decreased long-range connectivity in ASD has been robustly demonstrated in current literature, the local hyper-connectivity argument has been less defined. However, the findings Ye presented show that this argument definitely warrants further consideration.

Ye’s next steps for this project include collecting more data so she can explore potential relationships between this increased frontal lobe connectivity and the severity of autism symptoms, such as impairments in social communication or restricted, repetitive behaviors. I would guess that this increased frontal lobe connectivity would be related to increased repetitive behaviors, such as resistance to change. I look forward to what Ye finds.