Task-based functional connectivity as an indicator of genetic liability to schizophrenia

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Abstract

Impaired functional connectivity has been hypothesized as a potential source of the cognitive deficits routinely observed in patients with schizophrenia. Additionally, these deficits may be manifestations of the genetic liability to schizophrenia and present in the non-psychotic first-degree relatives of that group. However, no study has examined task-based functional connectivity in schizophrenia relatives using independent component analysis (ICA). We employed group ICA to test the hypothesis that the unexpressed genetic liability to schizophrenia is reflected in the functional connectivity between brain regions during a task measuring context processing. We compared 20 schizophrenia patients and 32 patients' first-degree relatives to 22 controls demographically matched to the patients and 28 controls' relatives, respectively. The group ICA showed differential connectivity between patients and controls in a task-related network constituting right middle frontal gyrus (MFG) and right posterior parietal lobe. A network constituting left MFG and left posterior parietal, which was also related to the context processing task, did not differ between groups. These findings demonstrate that connectivity abnormalities associated with the genetic liability to schizophrenia are most strongly expressed in a right lateralized executive fronto-parietal network, and that these abnormalities are linked to context processing impairments.

Introduction

The liability to schizophrenia is highly heritable, and genetic epidemiology implicates complex, polygenic causes for this predisposition (Gottesman and Shields, 1972, Harrison and Weinberger, 2005). A growing literature suggests that this genetic liability may affect neural connectivity (see Tost et al., 2012 for review). To test this possibility, the current study examined task-based functional connectivity in schizophrenia patients and their non-psychotic first-degree relatives using group independent component analyses (ICA).

Functional connectivity measures may be particularly useful for understanding disorders that arise from dysconnectivity. Schizophrenia may be one such disorder, however studies report a great diversity of findings in functional connectivity at rest (Pettersson-Yeo et al., 2011). One possibility for such divergent findings in these studies is that resting state scans do not constrain the activities of subjects and thereby introduce state-related noise. Task-based functional connectivity may provide an advantage in measuring certain functional connectivity differences, because subjects are engaged in tasks requiring functions that are disrupted in schizophrenia patients and their relatives.

One function that has been shown to be disrupted in schizophrenia patients and their non-psychotic relatives is context processing (Cohen and Servan-Schreiber, 1992), which is a putative endophenotype of schizophrenia (Gottesman and Gould, 2003). Context processing refers to the ability to represent and maintain goal-relevant information during the execution of a task, especially when the task requires inhibiting an automatic or over-learned response (Cohen and Servan-Schreiber). While a number of candidate endophenotypes are difficult to distinguish from generalized deficits (Dickinson et al., 2004, Snitz et al., 2006), the construct of context processing is specific and mechanistic (MacDonald et al., 2003). It has been shown that both schizophrenia patients (Servan-Schreiber et al., 1996, Jones et al., 2010) and their non-psychotic first-degree relatives (MacDonald et al., 2003) demonstrate deficits in their ability to perform tasks that require context processing abilities. Deficits in context processing ability as measured by AX continuous performance tasks demonstrated the highest effect sizes in studies of cognitive task performance between control subjects and the non-psychotic relatives of schizophrenia patients in a meta-analysis of putative endophenotypes of schizophrenia (Snitz et al., 2006). Furthermore, dysfunctional activation patterns have been observed in schizophrenia patients (Perlstein et al., 2003, MacDonald et al., 2005), and their non-psychotic relatives (MacDonald et al., 2006, Delawalla et al., 2008) during the performance of context processing tasks. The task used in the present study was the expectancy AX task, which will be discussed below.

One region of interest for studying the genetic liability to schizophrenia is the middle frontal gyrus (MFG). Functional connectivity between MFG and other brain regions is altered in schizophrenia patients (Yoon et al., 2008, Pettersson-Yeo et al., 2011). Degraded connectivity within functional networks that include MFG also has been demonstrated in the non-psychotic relatives of schizophrenia patients (Woodward et al., 2009), and evidence has shown this reduced MFG functional connectivity is present independent of differential activation (Rasetti et al., 2011). Despite this evidence, it remains to be seen what role impaired functional connectivity plays in the context processing deficits exhibited by schizophrenia patients and their non-psychotic relatives.

Group ICA was chosen as the analysis method in this study because it affords two primary benefits when compared with psychophysiological interaction analysis. First, it identifies a small number of components that can then be examined further, which reduces the number of comparisons and increases the power to detect subtle group differences. Second, because ICA extracts components without a model or spatial parameters, those components represent networks as they exist in the sample. This makes an improper characterization of a network less likely than if we were to define the network explicitly a priori.

Therefore, the first aim of the present study was to determine if functional connectivity networks that include MFG displayed differential task-relatedness in schizophrenia patients compared with healthy controls in response to demands on context processing. The second aim involved whether such connectivity differences fulfilled the familiality criterion of an endophenotype (Gottesman and Gould, 2003) by examining these measures in the non-psychotic first-degree relatives of schizophrenia patients. Additionally, to our knowledge, no one has explored task-based functional connectivity using group ICA in the non-psychotic relatives of schizophrenia patients.

Section snippets

Participants

Schizophrenia patients were identified who had a DSM-IV chart diagnosis of schizophrenia or schizoaffective disorder with siblings living nearby. When at least one first-degree relative (biological parent, child, or full sibling) between the ages of 21 and 40 contacted the researchers or agreed to be contacted, the patient was interviewed using the SCID IV (First et al., 2002). Patients' relatives, control subjects, and relatives' controls were screened for psychiatric disorders and substance

Behavioral Results

To determine if participant groups differed with regard to context processing ability, d′ context scores were computed for each participant, and independent sample t-tests were performed to examine group differences. The results of behavioral analyses are illustrated in Fig. 1. Schizophrenia patients (M = 2.34, SD = 1.00) had significantly lower d′ context scores (Fig. 1A) compared to controls (M = 3.13, SD = 0.64), t(40) = 3.01, p = .0025, one-tailed. Likewise, patients' relatives (M = 2.75, SD = 0.88) had

Discussion

This represents the first study to our knowledge to employ group ICA to examine task-based functional connectivity across the whole brain and the genetic liability to schizophrenia. The right and left fronto-parietal components were both task-related, yet only the right component showed differences between groups. In fact, the pattern of AX task-relatedness of this network was consistent with the idea of different levels of genetic loading in that schizophrenia patients showed the lowest

Funding source

This work was supported by NIH grant MH066629 awarded to Dr. Carter and grant MH079262 awarded to Dr. MacDonald.

Contributors

Study protocol and conceptualization by Angus MacDonald and Cameron Carter. Data analysis was completed by Andrew Poppe and Angus MacDonald. All authors participated in the interpretation of results and preparation and edition of the manuscript.

Conflict of interest

Dr. MacDonald has consulted for Astellas Pharma. All authors reported no biomedical financial interests or other potential conflicts of interest.

Acknowledgements

This work was supported by NIH grant MH066629 awarded to Dr. Carter and grants MH079262 and MH084861a warded to Dr. MacDonald. The authors are grateful to the participants and to Emily Olsen and Shaun Rafael for their assistance in completing the study. The authors would also like to thank Vince Calhoun for providing the GIFT software. Dr. MacDonald has consulted for Astellas Pharma. All authors reported no biomedical financial interests or potential conflicts of interest.

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