MRI diffusion tractography study in individuals with schizotypal features: A pilot study

Psychiatry Research: Neuroimaging 221 (2014) 49–57

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Psychiatry Research: Neuroimaging journal homepage: www.elsevier.com/locate/psychresns

MRI diffusion tractography study in individuals with schizotypal features: A pilot study Richard P. Smallman a,b,n, Emma Barkus c, Hojjatollah Azadbakht d, Karl V. Embleton b,d, Hamied A. Haroon d, Shôn W. Lewis e, David M. Morris d, Geoffrey J. Parker d, Teresa M. Rushe f a

Neuroscience and Psychiatry Unit, University of Manchester, Manchester M13 9PT, UK School of Psychological Sciences, University of Manchester, Manchester, UK c School of Psychology, University of Wollongong, Wollongong, NSW, Australia d Centre for Imaging Sciences, University of Manchester, Manchester, UK e Institute of Brain, Behaviour and Mental Health, University of Manchester, Manchester, UK f School of Psychology, Queen’s University Belfast, Belfast, UK b

art ic l e i nf o

a b s t r a c t

Article history: Received 17 December 2012 Received in revised form 30 September 2013 Accepted 25 October 2013 Available online 31 October 2013

Diffusion tensor imaging (DTI) studies have identified changes in white matter tracts in schizophrenia patients and those at high risk of transition. Schizotypal samples represent a group on the schizophrenia continuum that share some aetiological risk factors but without the confounds of illness. The aim of the current study was to compare tract microstructural coherence as measured by fractional anisotropy (FA) between 12 psychometrically defined schizotypes and controls. We investigated bilaterally the uncinate and arcuate fasciculi (UF and AF) via a probabilistic tractography algorithm (PICo), with FA values compared between groups. Partial correlations were also examined between measures of subclinical hallucinatory/delusional experiences and FA values. Participants with schizotypal features were found to have increased FA values in the left hemisphere UF only. In the whole sample there was a positive correlation between FA values and measures of hallucinatory experience in the right AF. These findings suggest subtle changes in microstructural coherence are found in individuals with schizotypal features, but are not similar to changes predominantly observed in clinical samples. Correlations between mild hallucinatory experience and FA values could indicate increasing tract coherence could be associated with symptom formation. & 2013 Elsevier Ireland Ltd. All rights reserved.

Keywords: DTI Arcuate fasciculus Uncinate fasciculus SPQ Launay–Slade

1. Introduction Schizophrenia is characterised by aberrant connections and can be considered a disorder of dysconnectivity (Friston, 1998; Stephan et al., 2009). Research has identified structural and functional correlates of dysconnectivity, with one such example being altered white matter connectivity (Kanaan et al., 2005; Walterfang et al., 2006; Kubicki et al., 2007; Ellison-Wright and Bullmore, 2009; Peters et al., 2010a; Bora et al., 2011). Diffusion tensor imaging (DTI) enables the visualisation and quantification of white matter tracts (Basser et al., 1994) via encoding the diffusivity of water molecules. The widely used scalar measure, fractional anisotropy (FA—Basser and Pierpaoli, 1996), gives an indication of tract microstructural orientation coherence. Higher values of FA (0–1 n Corresponding author at: University of Manchester, Neuroscience and Psychiatry Unit, G.700 Stopford Building, Oxford Road, M13 9PT Manchester, UK. Tel.: þ44 161 2751725. E-mail address: [email protected] (R.P. Smallman).

0925-4927/$ - see front matter & 2013 Elsevier Ireland Ltd. All rights reserved. http://dx.doi.org/10.1016/j.pscychresns.2013.10.006

scale) are considered as having greater tract coherence since these represent increased directionality of water diffusion and likely to be influenced by factors such as integrity of the fibres, the extent of myelination, and geometric factors including crossing, splaying and curving fibres (Beaulieu, 2002). Alterations in frontotemporal connections are proposed as key regions in schizophrenia (Friston and Frith, 1995; Lawrie and Abukmeil, 1998), with DTI studies demonstrating changes in tracts such as the arcuate fasciculus (AF) and uncinate fasciculus (UF) (e.g. Mori et al., 2007; Phillips et al., 2009). The changes in tracts are likely due to abnormalities in oligodendrocytes as demonstrated in post-mortem studies examining prefrontal brain regions (Uranova et al., 2007). Clinical symptoms, particularly hallucinations, have been associated with abnormal tracts (e.g. Hubl et al., 2004; Rotarska-Jagiela et al., 2009; de Weijer et al., 2011). The AF connects temporoparietal regions with the frontal cortex and is a key tract between the Broca’s and Wernicke’s language areas. Consistent with its proposed role in language, there is asymmetry in the AF with greater fibre density

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and FA values in the left hemisphere (Nucifora et al., 2005; Parker and Alexander, 2005; Powell et al., 2006). The UF connects orbitofrontal cortex and temporal lobe and is thought to be involved in episodic memory (Levine et al., 1998). Again, asymmetries in this tract have been reported in tract width (Azadbakht et al., 2010) and FA values (Vernooij et al., 2007; Iturria-Medina et al., 2011). A reduction in normal asymmetry in brain function and structure is the central tenet of Crow’s aetiological theory on the failure of dominance in schizophrenia (Crow, 1990, 1997). The theory proposes that schizophrenia is associated with a failure in establishing cortical asymmetry, particularly the normal left hemisphere dominance for language. Crow argues that the dysfunctional development of language dominance could result in a predisposition to psychotic symptoms and problems in communication. DTI studies have shown a reduction in asymmetry, for example in the UF of patient groups compared to controls (Kubicki et al., 2002). It is uncertain whether changes in white matter occur pre- or post-psychosis onset. To understand the potential progression of change in white matter, groups along the schizophrenia continuum that have been investigated include first-episode (FE) patients (Szeszko et al., 2005; Federspiel et al., 2006; Hao et al., 2006; Price et al., 2007, 2008; Cheung et al., 2008; Luck et al., 2010; Perez-Iglesias et al., 2010) those with genetic proximity (Hoptman et al., 2008; Munoz Maniega et al., 2008) and those with ‘at-risk mental states’ (Peters et al., 2008, 2010a; Karlsgodt et al., 2009; Carletti et al., 2012). Studies examining individuals with at-risk mental states (ARMS) are particularly informative in understanding aetiological mechanisms. This group are considered at-risk due to presence of intermittent or mild subthreshold psychotic experiences (i.e. ARMS or clinical ‘ultra-high risk’ UHR; e.g. Yung et al., 1996). Reduced FA values in tracts have been observed in UHR groups, for instance in the superior longitudinal fasciculus (SLF) (Karlsgodt et al., 2009), with such reductions intermediary between FE patients and controls (Carletti et al., 2012). Others have not found regional differences between UHR and controls (Peters et al., 2008) or differences in baseline FA values in those UHR who later go through transition compared to those UHR that do not (Peters et al., 2010b). However in longitudinal studies, UHR patients that go through transition do subsequently present FA reductions compared to non-transition UHR (Carletti et al., 2012). Such studies are critical in determining whether changes in white matter are a risk factor for transition or epiphenomenon of illness. There is a degree of heterogeneity within the literature on white matter abnormalities and psychosis due to, at least in part, methodological factors including those related to the collection of data (e.g. image acquisition and method of analysis) and those associated with the samples being investigated. Studies have investigated various sources of sample variance including illness duration (Mori et al., 2007), age of onset (Kyriakopoulos and Frangou, 2009), and medication status on FA values (Kanaan et al., 2009). In high risk studies, individuals who meet the ARMS criteria are clinically undifferentiated, so there is potential for lack of diagnostic specificity. In the current study we propose to overcome some of the problems related to using clinical samples by investigating white matter in another sample along the extended phenotype of schizophrenia: individuals with schizotypal features. Schizotypy is a trait psychosis liability comprising attenuated psychotic symptoms, unusual beliefs, as well as negative-like symptoms such as social withdrawal (e.g. Esterberg and Compton, 2009). Individuals with schizotypal features can be identified in the general population via psychometric measures such as the Schizotypal Personality Questionnaire (SPQ: Raine, 1991). These individuals are at higher risk than the general population for clinical disorders such as schizotypal personality

disorder (SPD; see Raine, 2006) and schizophrenia-spectrum disorders (e.g. Gooding et al., 2005). The schizotypal trait provides a means of exploring the mechanisms underpinning risk factors for schizophrenia and psychotic symptoms (Cadenhead and Braff, 2002; Lenzenweger, 2006). Additionally some of the previously mentioned confounds are not present. One study has examined white matter structures in a related group (those experiencing heightened psychotic-like experiences; Volpe et al., 2008). Higher FA values were found in the left AF in the high psychotic-experience group, whereas the low psychoticlike experience group had higher FA values in the right AF, corpus callosum and fronto-parietal tracts. In a more recent study, various fronto-temporal and other tracts were examined in healthy volunteers (Nelson et al., 2011). Associations between diffusion metrics and the SPQ were examined, with reduced FA values being predictive of higher scores on the Cognitive–Perceptual factor of the SPQ (measure of psychotic-like schizotypal features). Both studies demonstrated that white matter changes commonly found in patients with a diagnosis of schizophrenia are associated with “symptoms” not in need of clinical treatment in healthy individuals. Further studies sampling individuals with increased presence of schizotypal features would be beneficial. In the current study white matter structures were identified via tractography methods. Two main white matter tracts that have been studied extensively in clinical samples are the AF and UF. Differences in the coherence have been observed in schizophrenia patients (e.g. Burns et al., 2003), as well as being associated with psychotic experiences (e.g. Rotarska-Jagiela et al., 2009). We compared these two tracts bilaterally between individuals with heightened schizotypal features (i.e. those scoring high on the SPQ: High SPQ Group) and Controls. The main hypothesis of this study was that individuals with schizotypal features represent part of the extended phenotype of schizophrenia and would show qualitatively similar white matter abnormalities. Therefore, it was predicted that reduced tract coherence (lower FA) would be found in the High SPQ group compared to Controls. A subsidiary hypothesis was that High SPQ Group would have reduced asymmetries in white matter tracts, most notably in the AF where there is usually a pronounced hemispheric difference (left4 right FA values). Finally, in exploratory analyses, schizotypal features and measures of psychosis-proneness were correlated with FA values in the AF and UF.

2. Methods 2.1. Participants and procedure The sample for the current study was selected from a series of earlier studies (PhD: Schizotypy and the association with brain function and structure: Smallman, 2011). Initially 994 participants completed an online SPQ from universities and colleges in North-West England. From this sample 109 participants were selected for neuropsychological testing, from which 24 participants were selected based on SPQ score for the current study. Controls (n¼ 12) were defined as scoring þ0.5SD or below the mean on total SPQ score from the online sample and individuals with heightened schizotypal features (High SPQ Group, n ¼12) were defined as scoring þ1SD above the mean. The choice of þ 1SD was sufficient to differentiate from the Controls, but also was determined by availability of high SPQ scoring individuals who fitted inclusion/exclusion criteria (see below), and were willing to undergo brain imaging. At þ 1SD the high scoring group had comparable scores to other studies selecting individuals on the SPQ (e.g. Raine, 1991). Exclusion criteria were current or past history of self-reported psychiatric disorder as assessed by the Mini International Neuropsychiatric Interview (MINI: Lecrubier et al., 1997), history of head trauma with loss of consciousness, non-right motor dominance, and exclusion criteria for magnetic resonance imaging (MRI). Groups were matched on age, sex and IQ. On the day of testing, in addition to scanning, participants completed two further questionnaires: the Peters et al. Delusions Inventory and Launay-Slade Hallucinatory Scale (see below). Measures of motor dominance and IQ were obtained in an earlier study (Smallman, 2011). Participants were debriefed after

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scanning and paid d20 for travel expenses. Ethical approval was received from the NHS (National Health Service) Stockport Research Ethics Committee.

correction step has been shown to improve tractography results (Embleton et al., 2010).

2.2. Measures

2.4. Diffusion data processing

2.2.1. Schizotypal Personality Questionnaire (SPQ: Raine, 1991) The SPQ is a 74-item questionnaire based on the DSM-III-R criteria for SPD. Participants respond either ‘Yes’ or ‘No’ to each of the items. The SPQ consists of 9 subscales representing the core features of SPD, which can be grouped via factor analyses into three dimensions: Cognitive–Perceptual (CogPer), Interpersonal (IntPer) and Disorganised (Dis) (Raine et al., 1994). The SPQ has good psychometric properties (internal reliability 0.9–0.91, test–retest reliability 0.82, and convergent validity 0.81; Raine, 1991) and correlates highly with clinical schizotypy (Raine, 1991).

Tractography was conducted with the in-house probabilistic index of connectivity (PICo) algorithm (Parker and Alexander, 2003, 2005; Parker et al., 2003; Morris et al., 2008). The algorithm quantifies the confidence in tractography measurements of connection via the diffusion MRI data. The first step involves estimating the uncertainty in the principal orientations of diffusion by producing a probability density function (PDF) which contains information from the diffusion data about the distribution of the underlying fibre structures. The PDF is created using an implementation of modelbased residual bootstrapping applied to the q-ball analysis of diffusion data (Tuch, 2004; Haroon et al., 2009). Constrained tracking was carried out from seed regions of interest (ROI: see below) at sub voxel resolution (0.5 mm) using trilinear interpolation of the PDFs. One thousand streamlines were propagated from each voxel in the seed ROI. Streamlines were terminated on leaving the brain volume, when doubling back, if they reached an unrealistic length (450 cm), or when they reached the second target ROI. The process was then reversed from the second to first ROI. The result was two maps of voxels between the two ROIs with values from 0 to 1000 assigned to each voxel depending on the number of streamlines passing through the voxel. The map of voxels with the highest streamline values was retained as the tract. Seed regions of interest (ROI) were individually drawn by a researcher who was unblinded to group membership. ROIs were drawn in the white matter of the tracts in the coronal plane bilaterally for each tract. For the AF, an ROI was placed in the posterior parietal region of the superior longitudinal fasciculus, and in the white matter in the posterior temporal lobe. This produced a partial, posterior section for the AF. For the UF, ROIs were placed in coronal slices of the inferior frontal gyrus and anterior temporal lobe (Wakana et al., 2007). ROI sizes were compared between groups with no significant difference found in all ROIs except for one ROI used for seeding the right AF (Controls (Mean¼ 62 voxels, SD ¼18) and High SPQ Group (Mean¼ 45, SD ¼ 8); (t(22)¼ 2.90, p ¼0.008). Once tracts of interest had been extracted via PICo and visually inspected to ensure successful tracking, connectivity maps were thresholded to remove low probability pathways likely to represent false positives. Group averaged thresholding was calculated so as to reduce inter-individual bias (Azadbakht et al., 2010). The suggested thresholding values for the AF and UF tracts were 50 and 100 streamlines, respectively. These values were in agreement with the suggested values for thresholding of probabilistic connection of greater than 5% (Ciccarelli et al., 2006; Price et al., 2008). See Figs. 1 and 2 for group thresholded tracts for the AF and UF, respectively. Each individual probabilistic connectivity map (tract) was then thresholded and binarised accordingly. ImageJ (Rasband, 1997–2009) was used to multiply together the resultant tract with the individuals’ FA maps created in DTIstudio (Jiang et al., 2006) to provide FA values for each voxel in the tract. Average FA values were then extracted for both tracts bilaterally for each individual and used in subsequent analyses.

2.2.2. Peters et al. Delusions Inventory (PDI-21; Peters et al., 2004) The PDI-21 is a self-report measure of delusional thought. There are 21 probe items. If an item is answered affirmatively, there are three subsidiary items which measure the complexity of the belief expression (distress, preoccupation and conviction) (Peters et al., 1999). The measure has adequate internal consistency (0.82) and test–retest reliability (scores for each belief expression 0.78–0.81) (Peters et al., 2004). The total score was the sum of the 21 probe items and subsidiary measures.

2.2.3. Launay–Slade Hallucinatory scale (LSHS-R) (Launay and Slade, 1981; Bentall and Slade, 1985) The LSHS-R is a 12-item self report instrument designed to measure predisposition to hallucinatory experiences. The 12-items are scored on a 5-point Likert scale, and are grouped into 5 subscales (vivid thoughts, intrusive thoughts, auditory hallucinations, vivid daydreams and visual hallucinations), The measure has adequate internal consistency (0.79) and test–retest reliability (0.84) (Bentall and Slade, 1985). The outcome measure was total score. Since visual hallucinations are unlikely to be associated with similar brain structures to the other subscales, we also used total score without visual hallucinations subscale.

2.2.4. Motor Dominance Demonstration Test (MDDT: Seisdedos et al., 1999) The MDDT is a measure of motor dominance. The participant demonstrated their preference for right or left side for hand actions (e.g. writing), vision (e.g. looking through telescope), and foot actions (e.g. kicking a ball). There were 10 actions in total: 5 hand, 3 ocular and 2 foot. Those with a right sided preference scored þ1, left  1 and no preference 0. This produced a range of scores from þ 10 to  10, from purely right sided to purely left sided. 2.2.5. IQ IQ was assessed via the Weschler Abbreviated Scale of Intelligence (WASI— Wechsler, 1999). The two subtest version was used: matrix reasoning and vocabulary.

2.3. Diffusion weighted imaging acquisition and pre-processing Images were acquired on a 3-T Philips Achieva scanner (Philips Medical Systems, Best, Netherlands) using an 8-element SENSE head coil. A pulsed gradient spin echo (PGSE) echo planar imaging (EPI) sequence was used to acquire diffusionweighted data, implemented with TE¼ 59 ms, Gmax ¼62 mT/m, half scan factor¼ 0.679, 112  112 image matrix reconstructed to 128  128 using zero filling, reconstructed resolution 1.875  1.875 mm, slice thickness 2.1 mm, 60 contiguous slices, 61 non-collinear diffusion sensitization directions at b¼ 1200 s/mm2 (Δ ¼29.8 ms, δ ¼ 13.1 ms), 1 at b¼ 0, SENSE acceleration factor¼ 2.5. Each diffusion weighted volume was acquired entirely before starting the next diffusion weighting, resulting in 62 temporally spaced volumes with different direction diffusion gradients. For each diffusion gradient direction, phase encoding was performed in right–left and left–right directions, giving two sets of images with the same diffusion gradient directions but opposite polarity k-space traversal. Diffusion weighted acquisitions were cardiac-gated using a peripheral pulse unit on the participant’s index finger, aimed at reducing artefacts associated with pulsatile brain movements (Jones and Pierpaoli, 2005). Due to the use of cardiac gating the duration of the diffusion weighted scan was dependent on participants’ heart rates, but was approximately 2  18 min (18 min per polarity acquisition, R–L/L–R). A colocalised T2 weighted turbo spin echo scan (TR¼4.075, TE¼ 70 ms) with 0.94  0.94 mm in-plane resolution and 2.1 mm slice thickness was also obtained as a structural reference scan for use in the distortion correction procedure. Pre-processing included the distortion correction of the diffusion datasets with described methods (Chang and Fitzpatrick, 1992; Bowtel, 1994) using the implementation of Embleton et al. (2010). This step corrects distortion due to magnetic susceptibility artefacts associated with the narrow bandwidth in the phase encode direction of EPI, and eddy current-induced distortion caused by rapid switching of diffusion sensitisation gradients by the scanner hardware (Jezzard et al., 1998). This

2.5. Statistical analysis Data was analysed with SPSS (version 15). Age, IQ, MDDT, and questionnaire scores were compared across groups using independent 2-sample t-tests. Additionally, three analyses were done in order to answer aforementioned aims of the study. First, for group comparisons of FA value-differences in the AF and UF, ANCOVAs were conducted. Each tract was examined bilaterally in separate analyses, with age and whole brain FA values as covariates—age was added due

Fig. 1. The posterior arcuate fasciculus tract at group level in the left hemisphere displaying tracts greater than 5% (i.e. greater than 50 streamlines, see Section 2.4). Greater intensity (brighter) represents higher number of streamlines passing through the voxel.

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to known ongoing developmental increases in FA during adolescence and early adulthood (Peters et al., 2012). For the right hemisphere AF, ROI sizes were also added as covariates due to the significant larger size in the control group. Second, repeated measures ANCOVAs with hemisphere as within subjects effect and group membership as between subjects effect were conducted to determine whether differences in extent of asymmetry in AF and UF occurred across groups. Additionally, to examine asymmetry of tracts in the whole sample, paired sample t-tests were run. Third, to examine relationships between FA values and attenuated psychotic experience, Pearson partial correlations were conducted between each tract and SPQ (and factor scores), LSHS total, LSHS total without visual hallucinations, and PDI-21 total scores, with age, whole brain FA values, and ROI sizes added as covariates. To compensate for multiple correlations, significance was taken at p o0.01 and trend level association at p o0.05.

3. Results 3.1. Sample characteristics and presence of schizotypal and psychosis proneness features Table 1 presents the sample characteristics for Controls and High SPQ Group. There were no significant differences in age, IQ,

MDDT, or sex ratio between groups. Table 2 presents the questionnaire scores for Controls and High SPQ Group along with test statistics for group differences. The High SPQ Group had significantly higher scores on total SPQ and all factor scores, and higher scores on LSHS and LSHS total without visual hallucinations, and PDI-21 totals.

3.2. Controls vs. High SPQ Group To compare differences in FA values in the tracts (AF and UF) between the High SPQ Group and Controls, ANCOVAs were carried out with age and whole brain FA values added as covariates in both left and right hemispheres. For the right hemisphere AF, ROI sizes were also added as covariates. Table 3 presents means (SD) for all tracts. There was no significant difference in FA values in the AF in either the left (F(1,23)¼0.29, p¼0.59) or right hemispheres (F(1,23)¼0.08, p¼0.79). In the UF, the High SPQ Group had higher FA values compared to Controls at a trend level in the left hemisphere UF (F(1,23)¼3.70, p¼ 0.069), but no significant/trend difference was found in the right hemisphere right UF (F(1,23)¼ 2.94, p¼ 0.102).

3.3. Lateralisation

Fig. 2. The uncinate fasciculus UF tract at group level in the right hemisphere displaying tracts greater than 10% (i.e. greater than 100 streamlines).

Table 1 Sample characteristic mean (SD) values/ratios for Control and High SPQ Group, along with test statistics.

Age Age range Sex (m/f) IQ MDDT

Controls (n ¼12)

High SPQ Group (n¼ 12)

Test statistic

p

21.37 (3.33) (16.8–26.7) 6/6 119.83 (9.58) 8.08 (2.35)

21.05 (2.11) (17.2–23.9) 5/7 118.08 (13.14) 8.33 (2.06)

t¼ 0.28

0.78

χ2 ¼ 0.17 t¼ 0.37 t¼  0.27

0.68 0.71 0.78

To test whether presence of schizotypal features was associated with asymmetry in tract coherence, repeated measure ANCOVAs were carried out for both AF and UF. Age, whole brain FA values, and for the right hemispheres AF ROI sizes, were added as covariates. The interaction effect of hemisphere  group was non-significant in both AF (F(1,20)¼ 0.09, p ¼0.77) and UF (F(1,20)¼ 0.22, p ¼ 0.64), indicating that group membership did not alter the extent of FA asymmetry in either tract. In the combined sample asymmetry of the AF was found with greater FA values in the left hemisphere (Mean ¼0.365, SD ¼0.061) compared to right (Mean ¼0.332, SD¼0.060); (t(23) ¼4.83, p o0.001, d¼ 0.55). There was no significant difference in FA values in the UF in the combined sample between the left (Mean ¼0.312, SD ¼0.049) and right hemispheres (Mean ¼0.311, SD ¼ 0.051); (t (23) ¼0.18, p ¼0.86, d ¼0.02). Table 3 FA values in the arcuate/uncinate fasciculi in both hemispheres for Control and High SPQ Group. Tract

Hemisphere

Controls mean (SD) FA

High SPQ Group mean (SD) FA

AF

Left Right Left Right

0.370 0.332 0.307 0.309

0.359 0.331 0.317 0.314

UF

(0.056) (0.064) (0.043) (0.048)

(0.067) (0.059) (0.055) (0.057)

Abbreviations: AF; arcuate fasciculus; FA: fractional anisotropy; UF: uncinate fasciculus.

Abbreviations: MDDT: Motor Dominance Demonstration Test.

Table 2 Questionnaire mean (SD) scores for Controls and High SPQ Group, along with test statistics.

SPQ total SPQ CogPer SPQ IntPer SPQ Dis LSHS—total LSHS—total without visual hallucinations PDI-21—dimensions total

Controls (n¼ 12)

High SPQ Group (n ¼12)

t

p

17.00 5.42 6.50 6.25 24.17 22.17 24.33

46.25 17.33 21.92 13.58 32.25 29.25 71.75

 9.70  5.87  7.46  6.09  2.61  2.53  3.93

.000 .000 .000 .000 .019 .021 .002

(8.46) (4.20) (5.09) (3.47) (4.95) (4.95) (13.79)

(6.12) (5.63) (5.03) (2.31) (9.52) (8.32) (39.49)

Abbreviations: LSHS: Launay–Slade Hallucinatory scale; PDI-21: Peters et al. Delusions Inventory; SPQ CogPer: Schizotypal Personality Questionnaire—cognitive perceptual factor; SPQ Dis: Schizotypal Personality Questionnaire—disorganised factor; SPQ IntPer: Schizotypal Personality Questionnaire—interpersonal factor; SPQ total: Schizotypal Personality Questionnaire—total.

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Table 4 Partial correlations r (p values) between FA values in arcuate/uncinate fasciculi and questionnaire scores.

SPQ CogPer SPQ IntPer SPQ Dis LSHS—total LSHS total without visual hallucinations PDI-21—dimensions total

Left arcuate

Right arcuate

Left uncinate

Right uncinate

 0.008  0.136  0.100 0.075 0.102  0.026

0.165 0.218 0.085 0.549 0.605 0.423

0.096 0.251 0.264  0.108  0.118 0.110

0.199 0.210 0.245 0.408 0.375 0.198

(0.97) (0.59) (0.68) (0.76) (0.67) (0.91)

(0.49) (0.36) (0.72) (0.01) (0.00) (0.06)

(0.69) (0.29) (0.26) (0.65) (0.62) (0.64)

(0.40) (0.37) (0.30) (0.07) (0.10) (0.40)

Abbreviations: LSHS: Launay–Slade Hallucinatory scale; PDI-21: Peters et al., Delusions Inventory; SPQ CogPer: Schizotypal Personality Questionnaire—cognitive perceptual factor; SPQ Dis: Schizotypal Personality Questionnaire—disorganised factor; SPQ IntPer: Schizotypal Personality Questionnaire—interpersonal factor.

3.4. Correlations between FA values and schizotypal features Partial correlations between FA values and schizotypy measures (controlling for age, whole brain FA values and ROI sizes) are reported in Table 4. There were significant (p o0.01) positive correlations between the LSHS total score/LSHS total score without visual hallucinations and FA values in the right AF. The right AF FA value was positively correlated with PDI-21 total score at a trend level (po0.05), and the right UF FA value positively correlated with the LSHS total (p o0.05), but this was no longer found when examining LSHS total score without visual hallucinations (p¼ 0.10).

4. Discussion 4.1. Overview White matter tract coherence of bilateral arcuate (AF) and uncinate fasciculi (UF), as measured by FA values, was compared between a sample of individuals with heightened schizotypal features and controls. A High SPQ Group had increased FA values at a trend level in the left UF compared to controls. Presence of schizotypal features did not alter the extent of asymmetry of FA values across hemispheres in either the AF or UF. In the whole sample, normal asymmetry in FA values was observed in the AF (i.e. left greater than right FA values), whereas no significant hemispheric differences were found in the UF. In the whole sample FA values were positively correlated with attenuated hallucinatory symptoms in the right hemisphere AF. 4.2. Increased FA in High SPQ Group The prediction that the High SPQ Group would have reduced FA in the AF and UF was not supported. In fact the High SPQ Group had increased FA values in the left UF, although only at a trend level. The higher FA values represent increased tract coherence, which could be related to differences in axonal number, diameter, and packing density; the integrity of the tracts; extent of myelination; and/or extent of crossing fibres (Beaulieu, 2002; Kubicki et al., 2005). In a sample of genetic high risk participants there was a similar difference in FA in deep left frontal regions: the subgenual anterior cingulate (Hoptman et al., 2008). Hoptman et al. suggested the higher FA values could be a result of differences in the presence of crossing fibres (commissural, association, and projection fibres) within the frontal lobes leading to a macroscopic differences in the degree of diffuse connectivity in this region and hence subsequent changes in overall FA values due to affecting the degree of microscopic orientational coherence of axonal bodies. Although requiring further investigation with other imaging techniques, it is possible increased FA values could represent an abnormal state related to reduced local diffuse connectivity.

Tract coherence in the UF has been examined extensively across the schizophrenia continuum. Patients with chronic schizophrenia have decreased FA values in the UF compared to controls (Mori et al., 2007). Reduced FA values in the UF (amongst other regions) are also present in FE patients when compared to controls using VBA methods (Szeszko et al., 2008), along with subtle localised changes observed via tractography methods (Price et al., 2008). Also, in a comparison of FE patients, those patients with a poorer clinical outcome had greater FA reduction in the UF (Luck et al., 2010). In related samples, the picture is less clear. For example whereas schizophrenia patients show frontotemporal volume loss, neuroleptic-naïve patients with SPD were relatively spared (Hazlett et al., 2008). Other SPD samples, have however, been shown to have reduced FA values bilaterally in the UF (Nakamura et al., 2005; Gurrera et al., 2007). In studies examining both the AF and UF the findings are mixed. In those at genetic risk for schizophrenia, areas within the anterior limb of the internal capsule only were associated with reduced FA values, with relative sparing of the AF and UF (Munoz Maniega et al., 2008). Similarly via tractography methods no differences in FA values were found between a high-risk group, FE patients and controls in the AF or UF (Peters et al., 2008), or even in high-risk groups that went through transition (Peters et al., 2010b). Other studies in UHR groups utilising VBA methods have found a decrease in the AF but not UF (Karlsgodt et al., 2009), whereas others have found those UHR who later go through transition have regions that have either decreased FA levels (e.g. left superior temporal lobe), as well as regions with increased levels (e.g. left medial temporal lobe) compared to non-transition patients (Bloemen et al., 2010). In the first study to examine longitudinal changes in UHR groups (Carletti et al., 2012), FA reductions were found in left frontal white matter regions in transition patients compared to those that did not. These collections of studies demonstrate less robust differences are observed in FE patients and UHR samples compared to chronic schizophrenia patients, whereas in the current study an actual increase in FA values was observed in the left UF of individuals with heightened schizotypal features. The evidence from various samples placed along the psychosis/schizophrenia continuum suggests there are gradations of extent of white matter ‘pathology’ particularly in regions such as the UF. It has been suggested that transitional periods and those immediately following onset are the most toxic in terms of white matter pathology (Pantelis et al., 2005). In the current study those with schizotypal features did not show deterioration in tract coherence as seen in clinical samples. Therefore individuals that present with schizotypal features, but are otherwise healthy, may have qualitatively different white matter structures to clinical cases. Whereas there are similarities between individuals with schizotypal features and patients within the schizophrenia spectrum of disorders, the evidence from the current study suggests that white matter pathology in the form of reduced tract coherence is unlikely to be one of them. To our knowledge this is the first study to use

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tractography in this sample, so further research with larger sample sizes would be beneficial. 4.3. Lateralisation There was no group by hemisphere interaction effect for either the AF or UF suggesting schizotypal features are not associated with a change in asymmetry of FA values across hemispheres. Thus the hypothesis that the High SPQ Group would display reduced asymmetry could not be confirmed. Asymmetry in FA values was observed in the AF with left hemisphere values greater than right in the whole sample. In contrast, there was no evidence of asymmetry in the UF in the whole sample or either group. Asymmetries in white matter tracts of healthy volunteers are often reported (Vernooij et al., 2007; Iturria-Medina et al., 2011), whilst schizophrenia patients tend to have reduced asymmetry (Park et al., 2004) including the UF (Kubicki et al., 2002). Regarding the UF, the extent to which asymmetry exists in healthy controls is debated (Rodrigo et al., 2007; Lebel et al., 2008; Hasan et al., 2009). There appears to be no consensus on either the extent of asymmetry of the UF in healthy volunteers or clinical groups to date, with the current study suggesting a lack of asymmetry and no association with schizotypal features. The right hemisphere tends to have a greater degree of interconnectivity compared to the left hemisphere (Iturria-Medina et al., 2011). Even so, the left AF has increased FA values (Buchel et al., 2004; Powell et al., 2006) and fibre density (Nucifora et al., 2005). This adds weight to the notion that the left hemisphere contains large specific pathways for specialised function such as language, whereas the right hemisphere may integrate multiple systems (Iturria-Medina et al., 2011). The current study supports these findings with greater FA values in the left hemisphere AF. In the schizophrenia literature, loss of asymmetry in the AF is debated (Voineskos et al., 2010), although reductions have been observed (Burns et al., 2003; Munoz Maniega et al., 2008; Phillips et al., 2009). In the current study no group by hemisphere effect was found in the AF, again suggesting departures from this normal degree of hemispheric differences in tract coherence could be clinically significant. For instance, a recent study found more severe symptoms in schizophrenia patients with an exaggerated left greater than right FA levels in the AF in temporal regions (Abdul-Rahman et al., 2012). 4.4. Correlations with schizotypal features In the current study significant positive correlations were found between FA values in the right AF and measures of hallucinatory experience, whereas an association was also found between delusional ideation and right AF at a corrected trend level. In contrast, Nelson et al. (2011) found that higher scores on the SPQ dimension measuring positive type schizotypal features were associated with reduced FA values in bilateral UF, right temporal regions of superior longitudinal fasciculus (possibly containing the AF), as well as left cingulum and some nonfronto-temporal tracts. The opposite direction of this relationship in these studies is difficult to rationalise but could be due to a number of reasons. First, there were differences in samples between studies: the current study had younger participants who expressed higher levels of schizotypal features compared to Nelson et al. (2011). Second, were methodological differences, for instance the current study data was collected at 3-T and used tractography derived tracts which can account for crossing fibres opposed to ROI based analyses. Since both studies had small sample sizes, it would be worthwhile replicating these with a larger number of participants. Within the schizophrenia literature, increased FA values have been implicated in symptom presentation. For example, patients

with auditory hallucinations have been shown to have increased FA values in the AF compared to patients without hallucinations (Hubl et al., 2004). Others have similarly shown increased FA values to be correlated with severity of hallucinations (RotarskaJagiela et al., 2009), whilst VBA studies have demonstrated associations between auditory hallucinations and primary/secondary auditory regions in bilateral temporal lobes (Nenadic et al., 2010) and lateral regions of the superior longitudinal fasciculus bilaterally (Shergill et al., 2007). Increases in white matter volume in deep temporal sagittal regions (predominantly left hemisphere) are also positively correlated with delusions and hallucinations (Makris et al., 2010). These studies suggest links between positive type symptoms and FA values, which could indicate the importance of increased tract coherence in regions associated with language function. It must be noted, however, that decreases in FA values in specific regions have also been linked to symptoms. Decreased tract coherence and clinical correlates has been documented in adolescent early-onset schizophrenia, with hallucinations associated with FA reductions in the inferior longitudinal fasciculus (IFL) (Ashtari et al., 2007), positive symptoms with FA reductions in anterior cingulum regions (Tang et al., 2010), and negative symptoms with FA values in right UF (Szeszko et al., 2008). In summary associations have been found between symptoms and both increase and decreased tract coherence across a number of brain regions. In the current study the positive correlation between LSHS score (with and without visual hallucinations subscale score) and FA values in the right hemisphere AF were the most robust and retained statistical significance at the corrected level (p o0.01). The right hemisphere is thought to be involved in higher order processing of language, with communicative and social functions lateralised to this hemisphere (Mitchell and Crow, 2005). The association between hallucinatory experience and FA values in the current sample could be representative of normal healthy connections. The LSHS has items measuring vivid daydreams and thoughts etc, which are not far removed from psychological constructs such as creativity which are known to be increased in individuals expressing schizotypal features (Nettle, 2006). These structural/behavioural correlates may underpin this beneficial relationship associated with schizotypy. Unlike hallucinations associated with illness, the experiences measured by the LSHS may be more representative of stable trait like features. It is considered that such traits are a pre-requisite for more transient hallucinatory experiences (Slade, 1976; Launay and Slade, 1981). The presence of these sub-clinical schizotypal features may be causally related to hyperconnectivity in language related areas. When these systems are impacted upon by stressors/ risk factors, the underlying structures could, along with other functional/structural changes, give rise to florid psychosis. In clinical samples, a more global pathology, particularly affecting prefrontal regions could result in the destabilising of the appraisal of perceptual experiences as has been theorised (see Hugdahl, 2009; Whitford et al., 2012). The current study could be demonstrating an association between symptoms and tract coherence, which in this situation is not detrimental to the individual, but with further stressors could become pathological. 4.5. Limitations and conclusions Since this was a pilot study, future research would benefit from increased number of participants. Furthermore, it may be appropriate to focus on specific schizotypal dimensions for group selection such as those with predominantly positive features. The sample was also not entirely representative of the general population. For instance IQ of both the control and the High SPQ Group were higher than would be expected, although unsurprising given the sampling pool of university

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and college students. Future studies would benefit from more representative sampling. Despite the limited nature of the sample, there was a strong imaging protocol including: (1) field strength of magnetic (3-T); (2) distortion correction to overcome artefacts found in regions such as the temporal lobe; (3) a large number of diffusion gradient directions; and (4) use of probabilistic tractography methods to identify tracts. Furthermore the study was conducted in a sample free from the confounds associated with serious mental illness, that was closely matched on age, sex and IQ which is imperative given the association between these variables and degree of coherence in white matter structures (Yu et al., 2008; Choi et al., 2010; Lenroot and Giedd, 2010; Peters et al., 2012). In future studies individuals with schizotypal features could be compared to high-risk candidates and first-episode patients in addition to controls. This would provide informative data on the relationship between white matter structure and increasing ‘severity’ of symptoms/features, complementing studies examining the progressive nature of white matter changes following first episode. Individuals with heightened schizotypal features were not found to have reduced tract coherence compared to controls. Instead there was a small increase in FA values in the left UF in a group with high schizotypal features. FA values in the right AF, thought to be related to language function, were found to be positively correlated with attenuated hallucinatory experiences. This lends support to proposals that hyperconnectivity in language associated regions may have some role in symptom formation and may occur in otherwise healthy individuals.

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