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. 2014 Nov 21;138(1):110–119. doi: 10.1093/brain/awu331

Increased PK11195-PET binding in normal-appearing white matter in clinically isolated syndrome

Paolo Giannetti 1,✉, Marios Politis 1,2, Paul Su 1, Federico E Turkheimer 3, Omar Malik 1, Shiva Keihaninejad 1, Kit Wu 1, Adam Waldman 1, Richard Reynolds 1, Richard Nicholas 1,*, Paola Piccini 1,*
PMCID: PMC4383265  PMID: 25416179

Giannetti et al. use the PET ligand [11C]-(R)-PK11195 to explore microglial activation in normal-appearing white matter of subjects with clinically isolated syndrome. Microglial activation is increased in patients compared to healthy controls, and increased in subjects who develop multiple sclerosis within two years compared to those who do not.

Keywords: multiple sclerosis, clinically isolated syndrome, microglia, normal-appearing white matter, PK11195-PET

Abstract

The most accurate predictor of the subsequent development of multiple sclerosis in clinically isolated syndrome is the presence of lesions at magnetic resonance imaging. We used in vivo positron emission tomography with 11C-(R)-PK11195, a biomarker of activated microglia, to investigate the normal-appearing white matter and grey matter of subjects with clinically isolated syndrome to explore its role in the development of multiple sclerosis. Eighteen clinically isolated syndrome and eight healthy control subjects were recruited. Baseline assessment included: history, neurological examination, expanded disability status scale, magnetic resonance imaging and PK11195-positron emission tomography scans. All assessments except the PK11195-positron emission tomography scan were repeated over 2 years. SUPERPK methodology was used to measure the binding potential relative to the non-specific volume, BPND. We show a global increase of normal-appearing white matter PK11195 BPND in clinically isolated syndrome subjects compared with healthy controls (P = 0.014). Clinically isolated syndrome subjects with T2 magnetic resonance imaging lesions had higher PK11195 BPND in normal-appearing white matter (P = 0.009) and their normal-appearing white matter PK11195 BPND correlated with the Expanded Disability Status Scale (P = 0.007; r = 0.672). At 2 years those who developed dissemination in space or multiple sclerosis, had higher PK11195 BPND in normal-appearing white matter at baseline (P = 0.007 and P = 0.048, respectively). Central grey matter PK11195 BPND was increased in subjects with clinically isolated syndrome compared to healthy controls but no difference was found in cortical grey matter PK11195 BPND. Microglial activation in clinically isolated syndrome normal-appearing white matter is diffusely increased compared with healthy control subjects and is further increased in those who have magnetic resonance imaging lesions. Furthermore microglial activation in clinically isolated syndrome normal-appearing white matter is also higher in those subjects who developed multiple sclerosis at 2 years. Our finding, if replicated in a larger study, could be of prognostic value and aid early treatment decisions in clinically isolated syndrome.

Introduction

Clinically isolated syndrome (CIS) is a single episode of CNS dysfunction suggestive of focal demyelination (Miller et al., 2008). In those diagnosed with multiple sclerosis CIS represents the disease onset in ∼80% (Richards et al., 2002). However, only 61% of CIS subjects developed clinical symptoms consistent with multiple sclerosis after 20 years, but those that do develop multiple sclerosis by 5 years will already have a higher disability (Chard et al., 2011). This outcome indicates that there are likely underlying factors in those who will get further symptoms consistent with multiple sclerosis and subsequently develop disability.

The most accurate predictor of multiple sclerosis development in CIS is the presence of brain lesions in the white matter on MRI (Brex et al., 2002). In 107 patients with CIS followed up for ∼20 years, 82% with an abnormal baseline MRI scan versus 21% with a ‘normal’ baseline MRI developed multiple sclerosis (Fisniku et al., 2008). This suggests that a more general effect is active in areas without lesions—the normal-appearing white matter—which might act as a trigger to the development of lesions (Linker et al., 2009). In CIS grey matter, atrophy is also reported (Dalton et al., 2004; Calabrese et al., 2011) both in cortical regions and deep grey matter. Neuropathological, biochemical and imaging studies have shown abnormalities within the normal-appearing white matter in multiple sclerosis (Bjartmar et al., 2001; Graumann et al., 2003; Wheeler et al., 2008; Aboul-Enein et al., 2010), the most prominent of which is the occurrence of microglial clusters around microvessels associated with increased expression of immune markers (De Groot et al., 2001) and axonal changes (Howell et al., 2010), not visible on conventional MRI scans. Significantly lower total N-acetyl-aspartate concentrations have been demonstrated in the normal-appearing white matter and were predictive of conversion to multiple sclerosis (Wattjes et al., 2008; Stromillo et al., 2013), whereas other MRI measures thus far have not been consistently abnormal or independently predictive of the development of multiple sclerosis (Brex et al., 1999; Fernando et al., 2005).

11C-(R)-PK11195 (PK11195) PET scanning offers a method to visualize in vivo tissue changes, predominantly microglial and macrophage activation (Banati et al., 2000), derived either from increased cell number or activation level, in the brain. PK11195-PET has been used in multiple sclerosis to show inflammation within lesions (Banati et al., 2000; Debruyne et al., 2003; Versijpt et al., 2005; Vas et al., 2008) and cortical grey matter PK11195-PET activity correlates with disability (Politis et al., 2012). Given the possibility of generalized normal-appearing white matter dysfunction and the potential importance of microglial clusters in multiple sclerosis, we used PK11195-PET scanning to identify whether there were any abnormalities within the normal-appearing white matter in CIS and, given the prior evidence of grey matter PK11195-PET in multiple sclerosis, whether there was any activity in the grey matter. Furthermore, if present, we were interested to understand whether any changes could potentially help refine the identification of subjects presenting with CIS who are at high risk of multiple sclerosis and future disability.

Materials and methods

Study population and assessment

The study received Hammersmith and Queen Charlotte’s Research Ethics Committee ethical approval and Administration of Radioactive Substances Advisory Committee permission to administer PK11195. On receiving fully informed consent according to the Declaration of Helsinki, subjects with a diagnosis of CIS, defined as a subject presenting with a single clinical episode suggestive of CNS demyelination, as well as healthy controls were recruited. All participants attended for a PK11195-PET scan and a co-localizing gadolinium enhancing MRI scan within 7 days of each other. Patients were followed up yearly for 2 years. At each visit subjects were interviewed and the Expanded Disability Status Scale (EDSS) (Kurtzke, 1983) was performed, and conversion to McDonald defined multiple sclerosis was assessed (Polman et al., 2011).

MRI and PK11195-PET imaging

A clinical 1.5 T MRI system (Siemens MAGNETOM Avanto) was used. Volumetric T1-weighted sequences (coronal and axial T1-spin echo: repetition time = 635 ms, echo time = 17 ms, 5 mm slice thickness); T1 volumetric magnetization-prepared rapid acquisition with gradient echo (MPRAGE, repetition time = 1900 ms, echo time = 3.53 ms, inversion time = 1100 ms, flip angle 15°, 1 mm isotropic voxels) pre- and post-intravenous administration of gadobutrol (7.5 mmol) and T2-weighted sequences [axial T2-spin echo: repetition time = 4540 ms, echo time = 97 ms, 5 mm slice thickness; axial fluid-attenuated inversion recovery (FLAIR): repetition time = 9000 ms, echo time = 114 ms, inversion time = 2500 ms, 5 mm slice thickness] were acquired for image registration and to define regions of interest. MRI images were reorientated with the horizontal line defined by the anterior–posterior commissure line and the sagittal planes parallel to the midline.

For the PET scanning a Discovery RX PET/CT scanner was used. Images were reconstructed with the ramp filter using the reprojection algorithm, acquiring a spatial resolution at 1 cm for 2D and 3D, respectively, of 4.8 mm and 5.8 mm full-width at half-maximum, at 10 cm from the centre of 6.3 mm and 6.5 mm, respectively (Kemp et al., 2006). The CT images were used for attenuation correction.

PK11195 was administered as an intravenous bolus; the tracer was injected over 10 s then flushed with saline solution over 20 s. Emission data generated 18 time frames of tissue data over 60 min (30 s background frame, 1 × 15 s frame, 1 × 5 s frame, 1 × 10 s frame, 1 × 30 s frame, 4 × 60 s frames, 7 × 300 s frames, and 2 × 600 s frames). PK11195 tracer was supplied by Hammersmith Imanet plc, London.

PK11195-PET analyses

Quantification of PK11195-PET data was carried out adopting the simplified reference region model (Gunn et al., 1997) that uses a reference tissue input function and applies a simplified one tissue compartment model to each pixel of the dynamic volume to generate a parametric map of binding potential relative to the non-specific volume (BPND) (Innis et al., 2007). The tissue reference input was extracted from the emission dynamic using the SUPERPK software (Imperial Innovations) (Turkheimer et al., 2007; Yaqub et al., 2012). The reference region is selected by modelling each pixel kinetic as the weighted sum of four tissue classes, normal grey and white matter, vascular and microglia binding, the latter identified from the striatum and globus pallidum of patients with clinically manifest Huntington’s disease. The reference region is then calculated as the weighted average of the pixel grey matter indexes across the whole brain. The method has been extensively validated against the gold-standard plasma input function and across centres (Turkheimer et al., 2007; Yaqub et al., 2012). PK11195-PET and MRI images were then automatically co-registered using the SPM2 software package (Functional Imaging Laboratory, Wellcome Department of Imaging Neuroscience, UCL).

Regions of interest analyses

Regions of interest were manually drawn within lesional white matter and normal-appearing white matter using the ANALYZE software (version 8.1, Mayo Foundation) to generate maps for each subject. White matter lesions were MRI-defined as T2-FLAIR hyperintensity identified by an experienced neuroradiologist (A.W.) and a neurologist (P.G.). Normal-appearing white matter was defined as non-lesional white matter, regions of interest were drawn as far as possible from white matter lesions (>1 cm). Normal-appearing white matter regions of interest were sampled in all subjects with a mean [±standard deviation (SD)] volume of 1.75 (±0.88) cm3. Grey matter was automatically segmented (SPM2 software) and regions of interest maps generated using the multi-atlas propagation with enhanced registration (MAPER) approach (Heckemann et al., 2010). Manually drawn and MAPER generated maps were then used to calculate the volume and the BPND of PK11195 for each region of interest.

Statistical analyses

Statistical analyses were performed using SPSS (Version 17.0) and PRISM (GraphPad Software, Inc. Version 6.01 for Windows). For all the variables, the normality of the distribution was tested with the Kolmogorov-Smirnov test, whereas the Shapiro-Wilk test was used for small samples (n < 5). If normality was satisfied, bivariate correlation was tested using Pearson correlation coefficient. If normality was not satisfied, the Spearman’s rho correlation coefficient was used. Differences between two groups were tested using the independent samples t-test, corrected when equal variance was not assumed (Welch’s correction), according to the Levene’s test for the equality of variance. When the assumption of normality was not satisfied, the difference between two groups was tested using the independent samples Mann-Whitney U Test. The Kolmogorov-Smirnov test was also used to compare population distributions. The general linear model for repeated measures was used to analyse the variance of within-subjects variables and between-subjects factors. The Greenhouse-Geisser correction was then used to test the Region of interest × Group interaction (given the significant Mauchly’s test of sphericity).

Results

Clinical onset, MRI T2 white matter lesions and outcome in CIS at 2 years

Eighteen subjects with CIS (Table 1) and eight healthy controls [mean (SD) age of 30.2 (±5.5) years, five female] were recruited. The CIS clinical presentation was a spinal cord syndrome in eight, brainstem syndrome in seven, optic neuritis in two and one had a hemispheric lesion. Sixteen subjects completed the 2-year follow-up, two patients withdrew because they felt they had no problems. At 2 years, 13 patients presented with the radiological criteria for dissemination in space, 13 for dissemination in time and 12 had multiple sclerosis, as defined in the 2010 McDonald criteria (Polman et al., 2011). Five patients had a second relapse satisfying the criteria for clinically-defined multiple sclerosis. As with previous reports (Fisniku et al., 2008; Chard et al., 2011) baseline MRI T2 lesion number and volume in subjects who developed multiple sclerosis at 2 years was increased compared to those subjects who had no further symptoms (Table 2). This was significant for both the number of MRI T2 lesions (P = 0.016) and the MRI T2 volume in our study population (P = 0.012). As expected, in T2 lesions the PK11195 BPND was higher than in normal-appearing white matter, 0.153 (±0.095) and 0.078 (±0.027) (P = 0.0096).

Table 1.

CIS population demographic and clinical characteristics

Subject Age (years) Gender EDSS Time from onset (months) Type Number of lesions at baseline DIS at baseline McDonald criteria at 2 years
1 CIS 36.5 F 1.5 5 ON 0 No N
2 CIS 37.5 M 3.5 10 ON 0 No N
3 CIS 36.6 F 1.0 4 BS 38 Yes Y
4 CIS 45.8 M 1.0 4 BS 3 Yes Withdrawn*
5 CIS 31.2 F 1.5 7 HP 11 Yes Y
6 CIS 53.7 M 2.0 7 SC 6 No Y
7 CIS 23.4 F 2.5 8 SC 0 No N
8 CIS 48.5 M 1.0 3 BS 4 Yes N
9 CIS 49.3 F 1.0 3 BS 14 No Y
10 CIS 41.5 F 1.0 2 BS 4 Yes Y
11 CIS 36.1 M 2.5 4 SC 19 Yes Y
12 CIS 34.2 F 4.0 6 BS 54 Yes Y
13 CIS 29.6 F 0.0 4 SC 1 No Y
14 CIS 31.3 F 1.5 4 SC 68 Yes Y
15 CIS 37.4 F 1.5 10 SC 31 Yes Y
16 CIS 38.3 F 2.0 8 SC 8 No Y
17 CIS 34.9 F 2.0 1 SC 1 No Withdrawn*
18 CIS 47.4 M 1.5 5 BS 13 Yes Y
Mean 38.5 (7.8) 12 F; 6M 1.7(1.0) 5.3(2.6) 15.3(19.9) 8N; 10Y 4n; 12Y
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DIS = dissemination in space; ON = optic neuritis; BS = brainstem; SC = spinal cord; HP = hemispheric; F = Female; M = male; Y = yes; N = no.

Patients are ordered by consent submission date.

*Two patients withdrew, they did not have any relapses and felt well at 2 years.

Table 2.

MRI data at baseline and 2-year follow-up

T2 lesion load median volume (cm3) range/P T2 lesion number median range/P T1 enhancinglesion number median range/P
Baseline (18 subjects) 1.19 7 0
0–19.64 0–68 0–15
Baseline of CIS who completed the follow-up (16 subjects) 1.76 9.5 0
0–19.64 0–68 0–15
2-year follow-up (16 subjects) 3.47 15.5 0.5
0–16.31 0–84 0–7
Baseline MRI CIS (four subjects) versus MS (12 subjects) 0 versus 2.87 0 versus 13.50 0 versus 0
P = 0.004 P = 0.003 P = 0.444
2-year follow-up MRI change CIS (four subjects) versus MS (12 subjects) 0 versus 1.35 0 versus 5.50 0 versus 0.50
P = 0.098 P = 0.016 P = 0.218
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MS = multiple sclerosis.

The BPND of PK11195 is globally increased within the normal-appearing white matter of subjects with CIS

To assess whether there were any differences in the normal-appearing white matter PK11195 BPND between CIS subjects and healthy controls (Fig. 1), we initially considered the mean normal-appearing white matter PK11195 BPND for each subject, and found PK11195 BPND was significantly increased in CIS subjects compared to healthy controls (P = 0.024, Fig. 2A). Given that the PK11195 BPND is measured in multiple regions of interest we compared the normal-appearing white matter PK11195 BPND distribution over all the regions of interest studied and found that in CIS the normal-appearing white matter PK11195 BPND was significantly different compared to healthy controls (P < 0.0001, Fig. 2B). Using repeated measures with Region of interest as the repeated factor and Group as a between-subject factor we found a significant increase in normal-appearing white matter PK11195 BPND in the CIS group compared to the healthy control group (P = 0.014, Fig. 2C). The increased PK11195 BPND in normal-appearing white matter did not show any significant region of interest effect (P = 0.414), implying a diffuse global change. There was no region of interest effect evident when the clinical symptom onset was considered.

Figure 1.

Figure 1

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Normal appearing white matter on PK11195-PET images co-registered and fused with MRI of three subjects of the study population. The first subject is a healthy control (A) with PK11195 BPND in normal-appearing white matter of 0.028; the second is a CIS subject without T2 MRI lesions (B), an EDSS score of 3.5 and PK11195 BPND in normal-appearing white matter of 0.037; the third is a CIS subject with T2 MRI lesions (C), EDSS = 2.0 and PK11195 BPND in normal-appearing white matter of 0.136. The colour scale bar represents the BPND of PK11195.

Figure 2.

Figure 2

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Global changes in normal-appearing white matter in subjects with CIS compared to healthy controls. (A) The average of PK11195 BPND for each subject represented by a black dot (healthy control PK11195 BPND average in normal-appearing white matter is 0.042, whereas it is 0.071 in CIS subjects). (B) Significant difference in normal-appearing white matter (NAWM) regions frequency distribution (y-axis, percentage) according to their PK11195 BPND (x-axis) between healthy control and CIS. There is a higher percentage of normal-appearing white matter regions with low PK11195 BPND in healthy control (left) than CIS (right). (C) Significant group effect studied using repeated measures with normal-appearing white matter Regions of interest as the repeated factor and Group (left, healthy control; right CIS) as a between subject factor.

MRI T2 lesions in CIS is associated with increased global PK11195 BPND change in normal-appearing white matter

Giving the known importance of T2 MRI lesions in prognosis of CIS, both in terms of developing multiple sclerosis and disability, we explored whether the presence of white matter lesions was associated with higher PK11195 BPND in the normal-appearing white matter. We found that mean normal-appearing white matter PK11195 BPND per subject was significantly increased in those CIS subjects with lesions compared to those without lesions (P = 0.017, Fig. 3A). To exclude any effect from the multiple regions of interest measured, we again used repeated measure testing between two groups (Group 1: CIS with lesions versus Group 2: CIS without lesions) and found a significant increase in the CIS group with lesions compared to those without lesions (P = 0.009, Fig. 3B), independent of the region of interest repeated factor (P = 0.414) implying a diffuse global change. The relevance of T2 lesions is further supported by the finding that in CIS subjects with lesions there was a significant correlation (P = 0.007; r = 0.673) between the BPND of PK11195 in normal-appearing white matter and disability score (EDSS, Fig. 3C).

Figure 3.

Figure 3

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Global changes in normal-appearing white matter in subjects with CIS without T2 white matter lesions at MRI scan compared to CIS subjects with T2 white matter lesions. (A) The average of PK11195 BPND for each subject represented by a black dot (CIS without white matter lesions PK11195 BPND average in normal-appearing white matter is 0.032, whereas it is 0.078 in CIS subjects with white matter lesions). (B) The significant group effect studied using repeated measures with normal-appearing white matter regions of interest as the repeated factor and Group (left, CIS without white matter lesions; right, CIS with white matter lesions) as a between subject factor. Inset C shows the significant correlation between PK11195 BPND (y-axis) and EDSS (x-axis) in CIS with white matter lesions (r = 0.673); dotted lines represent error bars. NAWM = normal-appearing white matter.

CIS subjects who develop multiple sclerosis at 2 years have increased normal-appearing white matter BPND of PK11195 at baseline

Given that those with CIS have an increased risk of developing multiple sclerosis, we tested the difference in mean normal-appearing white matter PK11195 BPND in each subject between those who developed multiple sclerosis at 2 years and those who did not. Mean normal-appearing white matter PK11195 BPND per subject was increased in those who developed multiple sclerosis at 2 years (P = 0.04), whereas those who did not develop multiple sclerosis had PK11195 BPND signal levels similar to healthy controls (Fig. 4A). Further analysis found that this significant increase in mean PK11195 BPND was evident in the group who fulfilled the criteria for dissemination in space (P = 0.014) but not for the group who fulfilled the criteria for dissemination in time (P = 0.207). Again we confirmed that these findings were a diffuse global change by using repeated measures with Region of interest as the repeated factor and Group as a between-subject factor in the normal-appearing white matter PK11195 BPND in CIS who developed multiple sclerosis at the 2-year follow-up. We found that normal-appearing white matter PK11195 BPND was increased in the CIS group who developed multiple sclerosis (P = 0.048, region of interest effect P = 0.612) and that this was related to the group who satisfied the dissemination in space criteria (dissemination in space-positive versus dissemination in space-negative P = 0.007, region of interest effect P = 0.369) and not the dissemination in time criteria (P = 0.308). Thus, the baseline PK11195 BPND activity in normal-appearing white matter was significantly higher in CIS subjects who subsequently developed multiple sclerosis and who satisfied the dissemination in space, but not dissemination in time criteria (Fig. 4B).

Figure 4.

Figure 4

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Baseline PK11195 BPND in normal-appearing white matter (NAWM) of healthy controls and CIS who remained CIS or were diagnosed with multiple sclerosis (MS) at the 2-year follow-up (FU). (A) The average of PK11195 BPND for each subject represented by a black dot (healthy control PK11195 BPND average in normal-appearing white matter is 0.042, CIS PK11195 BPND average in normal-appearing white matter is 0.045, whereas it is 0.080 in subjects with CIS who developed multiple sclerosis at 2-year follow-up). On the y-axis of the graph in B are listed the 16 subjects who completed the 2-year follow-up ordered according to their normal-appearing white matter PK11195 BPND value (x-axis) at the baseline PK11195-PET scan. The filled bars represent the dissemination in space (DIS, present in 13 subjects); in hatched, the dissemination in time (DIT, present in 13 subjects). Patients who developed both dissemination in space and dissemination in time, hence diagnosed with multiple sclerosis (12 subjects) according to the 2010 revision of McDonald criteria for multiple sclerosis diagnosis, are therefore multiple sclerosis labelled on the y-axis. The light grey bars represent the subjects who remained at the CIS stage and did not develop both dissemination in space and dissemination in time.

Grey matter central structures show a higher PK11195 BPND in CIS

In contrast to the findings in the white matter, there were no differences in the grey matter PK11195 BPND between CIS subjects and healthy controls in the mean grey matter PK11195 BPND (CIS 0.112 ± 0.080 and healthy controls 0.121 ± 0.079), its distribution within the regions of interest studied and in the cortical grey matter. However, in the central grey matter structures (Fig. 5) PK11195 BPND was significantly higher in CIS than healthy controls, both using repeated measures for Group effect (P = 0.028, with no region of interest effect P = 0.136) than the subjects’ average (P = 0.006, Fig. 6).

Figure 5.

Figure 5

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Coronal section of central structures on PK11195-PET images coregistered and fused with MRI of two subjects of the study population. The first subject is a healthy volunteer (A) with PK11195 BPND in grey matter central structures of 0.163; the second is a subject with CIS (B), EDSS = 4.0 and PK11195 BPND in grey matter central structures of 0.248. The colour scale bar represents the BPND of PK11195.

Figure 6.

Figure 6

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Baseline PK11195 BPND in central structure of healthy controls and CIS subjects. Each data point represents the average of PK11195 BPND for each subject (healthy control PK11195 BPND average in central structures is 0.167, whereas it is 0.197 in CIS subjects). Horizontal bars represent mean ± SD.

The presence of MRI T2 lesions was not associated with any differences in cortical grey matter PK11195 BPND [with MRI T2 lesions 0.092 (±0.064); without MRI T2 lesions 0.100 (±0.062); P = 0.588] but MRI T2 lesions were associated with increased central grey matter structure PK11195 BPND [with MRI T2 lesions 0.208 (±0.059); without MRI T2 lesions 0.173 (±0.051); group effect P = 0.049, with no region of interest effect P = 0.635]. However, there was no associated grey matter PK11195 BPND difference in those who were diagnosed with multiple sclerosis at 2 years compared to those who were not.

Discussion

In this study PK11195-PET has been used to investigate a surrogate marker of microglia activation, TSPO expression, in the normal-appearing white matter and the grey matter of CIS subjects. Normal-appearing white matter PK11195 BPND is globally increased in CIS compared to healthy controls at baseline and interestingly this increase was concentrated in those who had MRI T2 lesions at baseline imaging. Consistent with the known association of T2 lesions and the increased subsequent risk of multiple sclerosis, those who went on to develop McDonald defined multiple sclerosis at 2 years had higher global normal-appearing white matter PK11195 BPND at baseline. In the cortical grey matter there was no difference in PK11195 BPND between CIS and healthy controls. However, the central grey matter PK11195 BPND was increased in CIS compared to healthy controls.

PK11195 has proved particularly useful as a PET tracer because of its favourable dynamics and kinetics; it is a high affinity TSPO ligand and has the ability to cross the blood–brain barrier (Schweitzer et al., 2010) with a well-established methodology for quantification (Turkheimer et al., 2007; Yaqub et al., 2012) and its binding is not affected by the known polymorphism in the TSPO gene that affects other ligands (Owen et al., 2011). In both multiple sclerosis and experimental autoimmune encephalomyelitis (EAE) tissues PK11195 binding was found to be consistently and strongly coupled with microglial activation (Shah et al., 1994; Vowinckel et al., 1997; Banati et al., 2000; Venneti et al., 2008). Given the potential role of areas of activated microglial clustering (van Horssen et al., 2012) that are not visible to MRI, we used PK11195-PET as a biomarker to determine if there was any evidence of microglial activation in the normal-appearing white matter of CIS subjects.

This group, followed-up clinically and with MRI for 2 years, had a high rate of conversion to McDonald confirmed multiple sclerosis (12 converted versus four who did not convert). However, because two were lost to follow-up as they felt well, this would make them a typical CIS population (Chard et al., 2011). The finding that in CIS there is a global increase in normal-appearing white matter microglial activation, would be consistent with the presence of underlying areas of the normal-appearing white matter that might be predisposed to lesion formation in which clusters of activated microglia are present (van Horssen et al., 2012) together with diffuse changes to axons and nodes of Ranvier (Howell et al., 2010). The increase is more prominent in those who had MRI T2 lesions at baseline and this group is known to have a higher risk of developing multiple sclerosis than those with no MRI T2 lesions (Fisniku et al., 2008; Chard et al., 2011). Consistent with this, in our population higher levels of normal-appearing white matter PK11195 BPND were associated with a higher risk of developing multiple sclerosis at 2 years predominantly through subsequent dissemination in space. This could suggest, if confirmed in further studies, that the underlying change in the normal-appearing white matter increases the risk of a white matter lesion developing.

Alterations in brain homeostasis can cause microglial activation in normal-appearing brain tissue (van Horssen et al., 2012) and does not necessarily indicate irreversible damage or even impaired function of underlying brain tissue. In addition, it is possible that microglial activation in the normal-appearing white matter is a protective response to inflammation (Graumann et al., 2003; Heppner et al., 2005). However, the increase in normal-appearing white matter PK11195 BPND seen in subjects with MRI T2 white matter lesions was correlated with the EDSS, which might suggest, in our limited population that in subjects with white matter lesions the normal-appearing white matter is already affected and associated with an impaired neuronal function. The association of higher microglia activity in normal-appearing white matter and clinical disability was not present at 2 years. This could indicate that any impaired neuronal function was temporary; however, because of the exploratory nature of the study, PK11195-PET was not repeated at this point, thus this interpretation represents only one possible explanation. It is well known that microglial activation in the white matter is associated with more aggressive multiple sclerosis (Kutzelnigg et al., 2005) and it is possible to inhibit microglial activation at the early stages of EAE, and this has a beneficial effect on the final clinical outcome (Heppner et al., 2005; Bhasin et al., 2007).

In the CIS patients studied here, the grey matter in the central structures showed higher PK11195 BPND compared to healthy controls. Thalamic atrophy is known to be present in CIS and early multiple sclerosis (Cifelli et al., 2002; Calabrese et al., 2011; Langkammer et al., 2013) and increased PK11195-PET activity in the thalamus has been reported (Banati et al., 2000). However, the increased PK11195-PET activity in the thalamus has not been reported in CIS before, but would be consistent with the MRI thalamic atrophy seen in CIS. Cortical grey matter PK11195 BPND was not increased in CIS compared to healthy controls. We have previously shown using the same methods that there was increased cortical grey matter PK11195 BPND in multiple sclerosis, and that this correlated with disability (Politis et al., 2012). The lack of any elevation in cortical grey matter PK11195 BPND in CIS could be because PK11195-PET is not sensitive enough to detect any changes despite our detection of changes in deep grey matter PK11195 BPND. Cortical grey matter atrophy has been found on MRI (Dalton et al., 2004) in CIS and this could indicate that cortical grey matter atrophy might precede microglial activation and with microglial activation becoming more prominent in the cortex as the condition progresses.

In conclusion, we report widespread microglial activation in the normal-appearing white matter in CIS. Higher levels of microglial activation were seen in those CIS subjects with white matter lesions on MRI at baseline and in those who subsequently who developed multiple sclerosis. However, the relatively small population and the lack of a follow-up PK11195-PET scan represent limitations and further work is required to understand the persistence of the abnormal normal-appearing white matter activation and how normal-appearing white matter activation compares to MRI in predicting future development of multiple sclerosis.

Funding

P.G. thanks the EFNS (European federation of neurological Societies) for a Scientific Fellowship in 2009, the FISM (Fondazione Italiana Sclerosi Multipla) for a training (research) fellowship, (Cod. 2010/B/7) and MSTC (Multiple Sclerosis Trials Collaboration). F.T. received a Medical Research Council (MRC) PET Methodology Grant G1100809/1. R.N. was supported by the National Institute for Health Research (NIHR) Imperial Biomedical Research Centre. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health.

Glossary

Abbreviations

CIS

clinically isolated syndrome

BPND

binding potential of the specifically bound radioligand relative to the non-displaceable radioligand in tissue

EDSS

Expanded Disability Status Scale

PK11195

11C-(R)-PK11195

References

  1. Aboul-Enein F, Krssák M, Höftberger R, Prayer D, Kristoferitsch W. Reduced NAA-levels in the NAWM of patients with MS is a feature of progression. A study with quantitative magnetic resonance spectroscopy at 3 Tesla. PLoS One. 2010;5:e11625. doi: 10.1371/journal.pone.0011625. [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Banati RB, Newcombe J, Gunn RN, Cagnin A, Turkheimer F, Heppner F, et al. The peripheral benzodiazepine binding site in the brain in multiple sclerosis: quantitative in vivo imaging of microglia as a measure of disease activity. Brain. 2000;123:2321–37. doi: 10.1093/brain/123.11.2321. [DOI] [PubMed] [Google Scholar]
  3. Bhasin M, Wu M, Tsirka SE. Modulation of microglial/macrophage activation by macrophage inhibitory factor (TKP) or tuftsin (TKPR) attenuates the disease course of experimental autoimmune encephalomyelitis. BMC Immunol. 2007;8:10. doi: 10.1186/1471-2172-8-10. [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Bjartmar C, Kinkel RP, Kidd G, Rudick RA, Trapp BD. Axonal loss in normal-appearing white matter in a patient with acute MS. Neurology. 2001;57:1248–52. doi: 10.1212/wnl.57.7.1248. [DOI] [PubMed] [Google Scholar]
  5. Brex PA, Ciccarelli O, O'Riordan JI, Sailer M, Thompson AJ, Miller DH. A longitudinal study of abnormalities on MRI and disability from multiple sclerosis. N Engl J Med. 2002;346:158–64. doi: 10.1056/NEJMoa011341. [DOI] [PubMed] [Google Scholar]
  6. Brex PA, Gomez-Anson B, Parker GJ, Molyneux PD, Miszkiel KA, Barker GJ, et al. Proton MR spectroscopy in clinically isolated syndromes suggestive of multiple sclerosis. J Neurol Sci. 1999;166:16–22. doi: 10.1016/s0022-510x(99)00105-7. [DOI] [PubMed] [Google Scholar]
  7. Calabrese M, Rinaldi F, Mattisi I, Bernardi V, Favaretto A, Perini P, et al. The predictive value of gray matter atrophy in clinically isolated syndromes. Neurology. 2011;77:257–63. doi: 10.1212/WNL.0b013e318220abd4. [DOI] [PubMed] [Google Scholar]
  8. Chard DT, Dalton CM, Swanton J, Fisniku LK, Miszkiel KA, Thompson AJ, et al. MRI only conversion to multiple sclerosis following a clinically isolated syndrome. J Neurol Neurosurg Psychiatr. 2011;82:176–9. doi: 10.1136/jnnp.2010.208660. [DOI] [PubMed] [Google Scholar]
  9. Cifelli A, Arridge M, Jezzard P, Esiri MM, Palace J, Matthews PM. Thalamic neurodegeneration in multiple sclerosis. Ann Neurol. 2002;52:650–3. doi: 10.1002/ana.10326. [DOI] [PubMed] [Google Scholar]
  10. Dalton CM, Chard DT, Davies GR, Miszkiel KA, Altmann DR, Fernando K, et al. Early development of multiple sclerosis is associated with progressive grey matter atrophy in patients presenting with clinically isolated syndromes. Brain. 2004;127:1101–7. doi: 10.1093/brain/awh126. [DOI] [PubMed] [Google Scholar]
  11. De Groot CJ, Bergers E, Kamphorst W, Ravid R, Polman CH, Barkhof F, et al. Post-mortem MRI-guided sampling of multiple sclerosis brain lesions: increased yield of active demyelinating and (p)reactive lesions. Brain. 2001;124:1635–45. doi: 10.1093/brain/124.8.1635. [DOI] [PubMed] [Google Scholar]
  12. Debruyne JC, Versijpt J, Van Laere KJ, De Vos F, Keppens J, Strijckmans K, et al. PET visualization of microglia in multiple sclerosis patients using [11C]PK11195. Eur J Neurol. 2003;10:257–64. doi: 10.1046/j.1468-1331.2003.00571.x. [DOI] [PubMed] [Google Scholar]
  13. Fernando KTM, Tozer DJ, Miszkiel KA, Gordon RM, Swanton JK, Dalton CM, et al. Magnetization transfer histograms in clinically isolated syndromes suggestive of multiple sclerosis. Brain. 2005;128:2911–25. doi: 10.1093/brain/awh654. [DOI] [PubMed] [Google Scholar]
  14. Fisniku LK, Brex PA, Altmann DR, Miszkiel KA, Benton CE, Lanyon R, et al. Disability and T2 MRI lesions: a 20-year follow-up of patients with relapse onset of multiple sclerosis. Brain. 2008;131:808–17. doi: 10.1093/brain/awm329. [DOI] [PubMed] [Google Scholar]
  15. Graumann U, Reynolds R, Steck AJ, Schaeren-Wiemers N. Molecular changes in normal appearing white matter in multiple sclerosis are characteristic of neuroprotective mechanisms against hypoxic insult. Brain Pathol. 2003;13:554–73. doi: 10.1111/j.1750-3639.2003.tb00485.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Gunn RN, Lammertsma AA, Hume SP, Cunningham VJ. Parametric imaging of ligand-receptor binding in PET using a simplified reference region model. Neuroimage. 1997;6:279–87. doi: 10.1006/nimg.1997.0303. [DOI] [PubMed] [Google Scholar]
  17. Heckemann RA, Keihaninejad S, Aljabar P, Rueckert D, Hajnal JV, Hammers A. Improving intersubject image registration using tissue-class information benefits robustness and accuracy of multi-atlas based anatomical segmentation. Neuroimage. 2010;51:221–7. doi: 10.1016/j.neuroimage.2010.01.072. [DOI] [PubMed] [Google Scholar]
  18. Heppner FL, Greter M, Marino D, Falsig J, Raivich G, Hövelmeyer N, et al. Experimental autoimmune encephalomyelitis repressed by microglial paralysis. Nat Med. 2005;11:146–52. doi: 10.1038/nm1177. [DOI] [PubMed] [Google Scholar]
  19. Howell OW, Rundle JL, Garg A, Komada M, Brophy PJ, Reynolds R. Activated microglia mediate axoglial disruption that contributes to axonal injury in multiple sclerosis. J Neuropathol Exp Neurol. 2010;69:1017–33. doi: 10.1097/NEN.0b013e3181f3a5b1. [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Innis RB, Cunningham VJ, Delforge J, Fujita M, Gjedde A, Gunn RN, et al. Consensus nomenclature for in vivo imaging of reversibly binding radioligands. J Cereb Blood Flow Metab. 2007;27:1533–9. doi: 10.1038/sj.jcbfm.9600493. [DOI] [PubMed] [Google Scholar]
  21. Kemp BJ, Kim C, Williams JJ, Ganin A, Lowe VJ. NEMA NU 2-2001 performance measurements of an LYSO-based PET/CT system in 2D and 3D acquisition modes. J Nucl Med. 2006;47:1960–7. [PubMed] [Google Scholar]
  22. Kurtzke JF. Rating neurologic impairment in multiple sclerosis: an expanded disability status scale (EDSS) Neurology. 1983;33:1444–52. doi: 10.1212/wnl.33.11.1444. [DOI] [PubMed] [Google Scholar]
  23. Kutzelnigg A, Lucchinetti CF, Stadelmann C, Brück W, Rauschka H, Bergmann M, et al. Cortical demyelination and diffuse white matter injury in multiple sclerosis. Brain. 2005;128:2705–12. doi: 10.1093/brain/awh641. [DOI] [PubMed] [Google Scholar]
  24. Langkammer C, Liu T, Khalil M, Enzinger C, Jehna M, Fuchs S, et al. Quantitative susceptibility mapping in multiple sclerosis. Radiology. 2013;267:551–9. doi: 10.1148/radiol.12120707. [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Linker R, Gold R, Luhder F. Function of neurotrophic factors beyond the nervous system: inflammation and autoimmune demyelination. Crit Rev Immunol. 2009;29:43–68. doi: 10.1615/critrevimmunol.v29.i1.20. [DOI] [PubMed] [Google Scholar]
  26. Miller DH, Weinshenker BG, Filippi M, Banwell BL, Cohen JA, Freedman MS, et al. Differential diagnosis of suspected multiple sclerosis: a consensus approach. Mult Scler. 2008;14:1157–74. doi: 10.1177/1352458508096878. [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Owen DRJ, Gunn RN, Rabiner EA, Bennacef I, Fujita M, Kreisl WC, et al. Mixed-affinity binding in humans with 18-kDa translocator protein ligands. J Nucl Med. 2011;52:24–32. doi: 10.2967/jnumed.110.079459. [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Politis M, Giannetti P, Su P, Turkheimer F, Keihaninejad S, Wu K, et al. Increased PK11195 PET binding in the cortex of patients with MS correlates with disability. Neurology. 2012;79:523–30. doi: 10.1212/WNL.0b013e3182635645. [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Polman CH, Reingold SC, Banwell B, Clanet M, Cohen JA, Filippi M, et al. Diagnostic criteria for multiple sclerosis: 2010 revisions to the McDonald criteria. Ann Neurol. 2011;69:292–302. doi: 10.1002/ana.22366. [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Richards RG, Sampson FC, Beard SM, Tappenden P. A review of the natural history and epidemiology of multiple sclerosis: implications for resource allocation and health economic models. Health Technol Assess. 2002;6:1–73. doi: 10.3310/hta6100. [DOI] [PubMed] [Google Scholar]
  31. Schweitzer PJ, Fallon BA, Mann JJ, Kumar JSD. PET tracers for the peripheral benzodiazepine receptor and uses thereof. Drug Discov Today. 2010;15:933–42. doi: 10.1016/j.drudis.2010.08.012. [DOI] [PubMed] [Google Scholar]
  32. Shah F, Hume SP, Pike VW, Ashworth S, McDermott J. Synthesis of the enantiomers of [N-methyl-11C]PK 11195 and comparison of their behaviours as radioligands for PK binding sites in rats. Nucl Med Biol. 1994;21:573–81. doi: 10.1016/0969-8051(94)90022-1. [DOI] [PubMed] [Google Scholar]
  33. Stromillo ML, Giorgio A, Rossi F, Battaglini M, Hakiki B, Malentacchi G, et al. Brain metabolic changes suggestive of axonal damage in radiologically isolated syndrome. Neurology. 2013;80:2090–4. doi: 10.1212/WNL.0b013e318295d707. [DOI] [PubMed] [Google Scholar]
  34. Turkheimer FE, Edison P, Pavese N, Roncaroli F, Anderson AN, Hammers A, et al. Reference and target region modeling of [11C]-(R)-PK11195 brain studies. J Nucl Med. 2007;48:158–67. [PubMed] [Google Scholar]
  35. van Horssen J, Singh S, van der Pol S, Kipp M, Lim JL, Peferoen L, et al. Clusters of activated microglia in normal-appearing white matter show signs of innate immune activation. J Neuroinflammation. 2012;9:156. doi: 10.1186/1742-2094-9-156. [DOI] [PMC free article] [PubMed] [Google Scholar]
  36. Vas A, Shchukin Y, Karrenbauer VD, Cselényi Z, Kostulas K, Hillert J, et al. Functional neuroimaging in multiple sclerosis with radiolabelled glia markers: preliminary comparative PET studies with [11C]vinpocetine and [11C]PK11195 in patients. J Neurol Sci. 2008;264:9–17. doi: 10.1016/j.jns.2007.07.018. [DOI] [PubMed] [Google Scholar]
  37. Venneti S, Wang G, Nguyen J, Wiley CA. The positron emission tomography ligand DAA1106 binds with high affinity to activated microglia in human neurological disorders. J Neuropathol Exp Neurol. 2008;67:1001–10. doi: 10.1097/NEN.0b013e318188b204. [DOI] [PMC free article] [PubMed] [Google Scholar]
  38. Versijpt J, Debruyne JC, Van Laere KJ, De Vos F, Keppens J, Strijckmans K, et al. Microglial imaging with positron emission tomography and atrophy measurements with magnetic resonance imaging in multiple sclerosis: a correlative study. Mult Scler. 2005;11:127–34. doi: 10.1191/1352458505ms1140oa. [DOI] [PubMed] [Google Scholar]
  39. Vowinckel E, Reutens D, Becher B, Verge G, Evans A, Owens T, et al. PK11195 binding to the peripheral benzodiazepine receptor as a marker of microglia activation in multiple sclerosis and experimental autoimmune encephalomyelitis. J Neurosci Res. 1997;50:345–53. doi: 10.1002/(SICI)1097-4547(19971015)50:2<345::AID-JNR22>3.0.CO;2-5. [DOI] [PubMed] [Google Scholar]
  40. Wattjes MP, Harzheim M, Lutterbey GG, Bogdanow M, Schild HH, Träber F. High field MR imaging and 1H-MR spectroscopy in clinically isolated syndromes suggestive of multiple sclerosis: correlation between metabolic alterations and diagnostic MR imaging criteria. J Neurol. 2008;255:56–63. doi: 10.1007/s00415-007-0666-9. [DOI] [PubMed] [Google Scholar]
  41. Wheeler D, Bandaru VVR, Calabresi PA, Nath A, Haughey NJ. A defect of sphingolipid metabolism modifies the properties of normal appearing white matter in multiple sclerosis. Brain. 2008;131:3092–102. doi: 10.1093/brain/awn190. [DOI] [PMC free article] [PubMed] [Google Scholar]
  42. Yaqub M, van Berckel BN, Schuitemaker A, Hinz R, Turkheimer FE, Tomasi G, et al. Optimization of supervised cluster analysis for extracting reference tissue input curves in (R)-[(11)C]PK11195 brain PET studies. J Cereb Blood Flow Metab. 2012;32:1600–8. doi: 10.1038/jcbfm.2012.59. [DOI] [PMC free article] [PubMed] [Google Scholar]

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