Circadian changes in CSF dopaminergic measures in restless legs syndrome

Sleep Medicine 7 (2006) 263–268 www.elsevier.com/locate/sleep

Original article

Circadian changes in CSF dopaminergic measures in restless legs syndrome Christopher J. Earley a,*, Keith Hyland b, Richard P. Allen a a

Department of Neurology, Johns Hopkins Bayview Medical Center, Johns Hopkins School of Medicine, 5501 Hopkins Bayview circle, Rm 1B-82, Baltimore, MD 21224, USA b Department of Neurochemistry, Horizon Molecular Medicine, Atlanta, GA, USA Received 6 June 2005; received in revised form 6 September 2005; accepted 17 September 2005

Abstract Background and purpose: Restless legs syndrome (RLS) has a circadian component with symptoms being prominent at night. The dopaminergic (DAergic) system, which plays a role in RLS, entails circadian changes that parallel RLS symptom changes. The aim of this study was to look for relative and diurnal differences in DAergic activity. Patients and methods: All RLS subjects were treated prior to their enrollment in the study but were all drug-free for at least 2 weeks prior to evaluation. Cerebrospinal fluid (CSF) collected at 10 p.m. was used to determine DA-related co-factors and metabolites. These were compared to CSF values collected in a previous study at 10 a.m. Results: The only significant finding from the 10 p.m. samples (30 RLS; 22 control) was increased 3-ortho-methyldopa (3OMD) for RLS compared to controls. A comparison of the 10 p.m. to 10 a.m. values (16 RLS; 9 controls) showed small, non-significant diurnal changes for controls but large diurnal changes in tetrahydrobiopterin (BH4), HVA:5HIAA ratio and 3OMD for RLS, with the 10 a.m. sample showing increases in all three CSF factors compared to the 10 p.m. sample. Conclusions: The greater diurnal changes in RLS suggest greater fluctuations than normal in DAergic circadian dynamics. The increased 3OMD concentration in the absence of concurrent exogenous levodopa (L-dopa) suggests changes in synthesis or metabolism of L-dopa in RLS. q 2005 Elsevier B.V. All rights reserved. Keywords: Dopaminergic; Biopterin; 3-Ortho-methyldopa; Cerebrospinal fluid; Restless legs syndrome; Circadian

1. Introduction It has been suggested that the dopaminergic (DAergic) system plays a prominent role in restless legs syndrome (RLS). This premise is based in large part on the known effectiveness of levodopa (L-dopa) and dopamine agonists used to treat RLS symptoms [1]. Studies using positron emission tomography (PET) or single photon emission computed tomography (SPECT) imaging of dopamine-2 receptors (D2R) have shown inconsistent results. Two studies have reported no difference [2,3], and two studies have reported lower D2R binding potentials in RLS

* Corresponding author. Tel.: C1 410 550 1044; fax: C1 410 550 3364. E-mail address: [email protected] (C.J. Earley).

1389-9457/$ - see front matter q 2005 Elsevier B.V. All rights reserved. doi:10.1016/j.sleep.2005.09.006

compared to controls [4,5]. One of the primary characteristics of RLS is the occurrence of the symptoms predominantly at night or during sleep [6]. These changes in RLS symptoms across the day appear to reflect underlying circadian processes [7,8]. Intriguingly, central nervous system DAergic activity also varies during the day with the lowest activity occurring at night or during the equivalent period in rodents [9–11]. It has been suggested that RLS may occur because of an abnormality in the mechanism underlying circadian regulation of DAergic system [12]. Using prolactin secretion as a measure of DAergic activity, one study demonstrated a greater inhibition of prolactin release in RLS compared to controls. This greater inhibition seen in RLS occurred with the nighttime but not with the daytime administration of levodopa [13]. However, another study failed to find any circadian difference between RLS and controls in prolactin pulsatility [14], which is considered the most sensitive

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measure of DAergic effects on prolactin secretion [15]. Our previous cerebrospinal fluid (CSF) analysis failed to find a difference in CSF homovanillic acid (HVA) but did find that the RLS group had an increase in CSF tetrahydrobiopterin (BH4) [16]. BH4 is an important co-factor and regulator of tyrosine hydroxylase (TH) activity [17]. The increased BH4 could reflect an increased demand for dopamine production in RLS, but perhaps only at the specific point in the circadian cycle of dopamine (DA) synthesis. Diurnal or circadian changes in brain, CSF or serum dopamine or its metabolites have been reported for rats [11,18], monkey [10] and humans [9]. It is possible that any change in DA release (and therefore any change in HVA) that would result from changes in synthesis may not be found until later in the circadian cycle. This time lag between DA synthesis and DA release has been reported in rats [19,20]. Our previous study [16] obtained CSF at 10 a.m. when RLS symptoms are usually minimal. In the current study, CSF was obtained at 10 p.m. when subjects are symptomatic. With the 12-h time difference, these two studies provide data from opposite phases of the DA circadian cycle. Therefore, given the circadian nature of RLS, the CSF changes found in this study may differ considerably from those reported in the previous study. More importantly, since the methods and CSF analysis are identical in both studies, assessment of both data sets permits us to look at relative diurnal changes in these factors. Of potential importance to our understanding of the clinicopathological aspects of RLS is the role that certain phenotypes play in the disease process. The obvious and best-explored phenotype is the age at which symptoms first appear [21]. The phenotypic differences between an early and late-onset of RLS symptoms have been established primarily for the degree of genetic susceptibility. The first family history study showed greater rates of familial occurrence of RLS for probands whose RLS started before age 45 [22]. A subsequent segregation analyses reported model fits for a dominant single gene for patients, with RLS starting by age 30, and no genetic model for RLS patients with symptoms starting after 30 years of age [23]. Disease progress also differs between these two phenotypes, with much slower progression of symptoms reported for earlyonset RLS [21]. Therefore, this study was designed to examine potential differences between early early-and lateonset RLS with regard to the variables and correlations measured in this study.

2. Methods

nightly symptoms for at least 6 months prior to commencement of any treatment, and had a clinical response to dopaminergic agents. Subjects who had no symptoms to suggest RLS, no first-degree relatives with RLS, and PLMS!15/h were considered eligible as control subjects for this study. To rule out RLS in living, first-degree relatives of control, telephone interviews were performed using methods previously described [24]. PLMS rates were assessed during initial screening by leg activity meters. However, those subjects who were admitted to the General Clinical Research Center (GCRC) were included or excluded based on the PLMS from the second polysomnogram (PSG). Subjects with neurodegenerative disorders, organ failure, anemia, iron deficiency (serum ferritin ! 18 mg/l, or percent iron saturation !16%;), clinically significant sleep apnea/hypopnea (sleep-disordered breathing rates of O30/h), medical or surgical factors that might limit the performance or interpretation of the investigations to be performed, were excluded. 2.2. Procedures Each RLS subject’s earliest experience with RLS symptoms was documented during the GCRC admission evaluation and was used as the age at which symptoms first started. Subjects were then grouped into early onset RLS (symptoms starting before 45 years of age) or into late-onset RLS (symptoms starting at or after 45 years of age). In order to maintain age- and gender-balance within diagnostic groups, enrollment was limited to subjects older than 45 years of age and approximately half of each gender. Control subjects were selected to balance for age (G5 years), race and gender of the enrolled RLS subjects. RLS-related and any psychoactive medications (except nicotine and caffeine) as well as any supplements with iron were stopped two weeks or six half-lives (whichever was the longest) prior to admission to the GCRC for the study. Eligible candidates were admitted to the GCRC for the study investigations. A standard full-night polysomnogram was performed on the first two nights. The Johns Hopkins RLS severity scale (JHRLSS) was determined based on the patient’s report of the usual time that RLS symptoms had started for the last four days prior to the GCRC visit [25]. A blood sample and lumbar puncture (LP) were performed at 10 p.m. on the third night. CSF samples were collected as previously described [26]. CSF analyses were performed exactly as with the prior study and included HVA, 5-hydroxyindole acetic acid (5HIAA), neopterin (NEO), tetrahydrobiopterin (BH4), and 3-O-methlydopa (3OMD).

2.1. Patient population 2.3. Statistical analysis Patients who were considered eligible as RLS subjects for this study were those who met all four criteria for RLS [6]: had periodic leg movements in sleep (PLMS) O20/h when off medications, had no obvious secondary cause, had

A random five-digit number was assigned to each subject and served as the only source of identity on all data sets. All data sets were processed blind to the status of subjects.

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All decisions about potential errors in the data set were made prior to breaking the blind. The first primary aim of the study was to determine whether CSF HVA will be decreased and CSF BH4 increased in RLS compared to controls when assessed at night. The second primary aim was to determine if any of the CSF factors differed for early and late-onset RLS compared to each other and to controls. The third primary aim was to compare the current CSF values, which would be collected at 10 p.m. to the previous study values where samples were collected at 10 a.m. [16]. The study protocols for both the current study and the previous study provided for a two-week medication withdrawal and the same CSF sampling techniques and analyses, thereby permitting assessment for circadian changes in CSF factors. Unlike the current study, the control and RLS subjects in the prior study were not limited to being over age 45. In order to make the samples age-balanced, we imposed this same age limit (45 years and older) on the data collected from our prior study for comparison of circadian effects. This provided reasonably age-matched groups permitting analyses without the complication of uncertain accuracy of statistical correction for age. In these analyses, we included the evaluation of our primary hypothesis that age-of-onset phenotype represents different biological aspects of RLS differentially altering circadian DA patterns. We, therefore, analyzed time-of-day effects using an analysis of variance (ANOVA) with independent variables of diagnosis (earlyonset RLS, late-onset RLS and control) and time of day (morning, evening) where appropriate for the data. The statistical tests included chi-squared tests for examining categorical differences between groups, t-tests for testing differences between nearly normally distributed continuous data samples using two-tailed t-tests for nondirectional hypotheses, Mann–Whitney U test for comparing two groups, where the data were too skewed to be considered normally distributed, ANOVA or Kruskal– Wallis non-parametric test for evaluating differences between the three groups (controls, early-onset RLS and

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late-onset RLS depending on the normality of the distribution of the data). Pearson-product moment and correlations were used as appropriate. A secondary aim was to test for any gender effects on the CSF variables using separate sub-group analyses for each gender.

3. Results Out of a total of 302 consented subjects, 207 were screening failures, 32 withdrew consent, and three failed to commit to a GCRC visit date prior to study closure. Therefore, 60 subjects who appeared to be eligible after screening were admitted to the GCRC. Of the 60 subjects, four controls (three had PLMO20; one had apnea ratesO 30/h) and four RLS (one with secondary RLS; one with unclear symptoms; one with no CSF; one with apnea ratesO 30) were excluded, leaving 52 subjects for analysis. Data from 30 RLS (15 early and 15 late-onset) and 22 controls subjects were analyzed for this study (Table 1). The RLS and control groups were well balanced for gender and age, but within the RLS group the late-onset group was significantly older than early onset or controls (P!0.01). CSF HVA, 5HIAA, BH4, NEO, and the HVA:5HIAA ratio for the RLS group were not significantly different from that of the control group (see Table 1). An evaluation of the differences between controls, early onset RLS and late-onset RLS also found no significant difference for these CSF indices. Separate analyses for gender also found no significant differences on five CSF indices. The only significant difference was the higher concentration of CSF 3OMD for RLS compared to controls (Mann–Whitney UZ197.5, PZ 0.006). The higher 3OMD concentrations were seen for all RLS sub-groups. The effects of gender and age-of-symptomonset phenotype were not significant (see Table 1). As reported in the previous study [16], the 10 a.m. CSF samples from RLS subjects had lower 5HIAA and higher BH4 and NEO than controls. The 3OMD had been

Table 1 Mean (Gstandard error) for CSF measures (nmol/l) from night (10 p.m.) and day (10 p.m.) samples of control and RLS patients and the difference between night and day as a percentage of the day value n Night (10 p.m.) Control 22 RLS 30 Day (10 a.m.) Control 9 RLS 16 Percentage diurnal differencec Control (%) RLS

AgeGSDa

HVA

5HIAA

HVA:5HIAA

BH4

NEOP

3OMD

59.2G8.3 62.9G10.1

216.9G18.8 240.7G24.3

98G7.2 112.6G9.4

2.21G0.09 2.15G0.11

16.6G1.41 16.4G1.07

16.86G1.87 18.6G1.81

12.09G2.05 21.4G3.38*

60.1G9.3 64.2G10.9

222.4G15.7 218.9G19.6

105.2G8.1 87.3G10.0

2.2G0.22 2.81G0.28

13.1G1.41 20.9G2.11

17.9G1.5 22.09G2.02

!10b 31.8G5.47**

K2.5 10.0

K6.8 29.0

0.5 K23.5*

26.7 K21.5*

K5.8 K15.8

34.3 K32.8

* indicates P!0.05; ** indicates P!0.01. For RLS compared to control values or for a.m.–p.m. CSF differences within diagnostic groups. a Age values are given as meanGSD all others as meanGstandard error. b All values reported as less than 10 nmol/l. c Difference (night–day) as a percentage of the day value. Negative values indicate dayOnight.

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performed in the 10 a.m. CSF collection but had not been part of the initial analysis and therefore not published with the other data (see Table 1). The 10 a.m. CSF 3OMD significantly increased in RLS compared to controls (Mann– Whitney UZ28, PZ0.0001). The night-time values for HVA, 5HIAA, BH4, NEO and HVA:5HIAA ratio were compared to the similar daytime values from a previous study to look for potential circadian changes in these values (see Table 1). The comparison of 10 p.m. values to the 10 a.m. values tended to show small, nonsignificant circadian changes in the controls (K3% for HVA, K7% for 5HIAA; C34% for 3OMD; C27% for BH4,C6% NEO, and C1% for HVA:5HIAA ratio). The night-to-day comparisons in RLS subjects tended toward larger circadian differences with most of the changes occurring in the opposite direction to that seen in controls (C10% for HVA, C29% for 5HIAA; K33% for 3OMD; K22% for BH4, K16% for NEO, and K24% for HVA:5HIAA ratio). The ANOVA showed no significant circadian effects for HVA, 5HIAA or NEO for either control or RLS groups. The ANOVA for the ratio of HVA:5HIAA showed no significant diagnosis effect but showed a significant circadian effect (PZ0.009) with daytime samples significantly greater than night-time samples (Fisher’s PLSD PZ0.017). The differences for night-time values compared to daytime values for 3OMD were marginally non-significant but in opposite directions for control (C20%, UZ126, PZ0.096) and RLS subjects (K33%, UZ164, PZ0.072). The ANOVA for BH4 showed a complicated pattern. There was a significant overall diagnosis effect (PZ0.012) with Fisher’s PLSD post hoc tests showing values that were significantly greater for early-onset RLS compared to either controls (PZ0.014) or late-onset RLS (PZ0.030), but values for late-onset RLS did not differ significantly from controls (PZ0.92). The overall ANOVA also showed a marginally, non-significant interaction term of circadian and diagnosis effects (PZ0.065). The day-to-night changes showed significant decrease (P!0.05) for RLS patients compared to a non-significant increase for controls (see Fig. 1 and Table 1). 30

BH4(nmol/L)

25 20

day night

15 10 5 0

Control

Early-onset

Late-onset

Fig. 1. Mean values with standard error bars of CSF tetrahydrobiopterin (BH4) concentrations for day (10 a.m.) and night (10 p.m.) samples from control subjects and early-onset and late-onset RLS patients.

The age at which symptoms first started did not correlate with any of the CSF variables. CSF HVA was strongly correlated with CSF 5HIAA for controls (rZ0.88, P! 0.001) and for RLS (rZ0.86, P!0.001). This finding was unaffected by gender and diagnostic subcategories. CSF HVA was significantly correlated with CSF 3OMD for RLS (rZ0.57, P!0.001) but not for control (rZ0.19, PZ0.40). The CSF HVA-3OMD correlation was stronger for earlyonset (rZ0.70, P!0.004) than for late-onset (rZ0.31, PO 0.2), and stronger for RLS males (rZ0.78, P!0.001) than for RLS females(rZ0.43, PZ0.079).

4. Discussion The first primary aim of the study was to determine whether RLS subjects would show a change in CSF HVA and BH4 compared to controls when assessed at night. There were no significant differences for these two primary study measures of DAergic function, but 3OMD, which is a metabolite in the DAergic metabolic pathway, was significantly increased in RLS subjects for both 10 p.m. and 10 a.m. Although the values for 3OMD were relatively higher in the 10 a.m. sample, circadian differences were not significant. CSF 3OMD is a result of L-dopa catabolism by catecholO-methyl transferase (COMT) in concert with methionine adenosyl transferase (MAT) [27]. The majority of L-dopa is converted to dopamine by L-aromatic amino acid decarboxylase (AAD) [27]. As a result, 3OMD is found in very low concentrations under normal conditions. Increased concentrations of 3OMD have been reported almost exclusively from studies of patients with Parkinson’s disease [28]. This is the first report of a significant increase in 3OMD in a condition other than Parkinson’s disease. However, the 100fold increases in 3OMD in Parkinson’s are attributable to the use of L-dopa for treatment, as untreated patients with Parkinson’s have about a tenth the level compared to normal subjects [28]. Normal subjects given 250 mg of L-dopa will also show a 100-fold increase in 3OMD [29]. In the current and in our previous [16] CSF evaluations, RLS subjects were off all RLS medications for at least two weeks prior to the lumbar puncture. Only two of the 30 RLS patients in the current study and none from the previous study were on L-dopa at the time their medications were stopped. In addition, the degree of increase in the RLS group compared to controls was only about 2–3 times higher than controls, not the 100-fold increase seen with L-dopa. So how do we account for the elevated 3OMD? In the absence of exogenous L-dopa, the increase in 3OMD must reflect a change in one or more of the enzymatic pathways that are involved in its metabolism: increased tyrosine hydroxylase (TH), decreased AAD, or increased COMT. Those changes may reflect the disease process or long-term consequences of drug treatment. A recent study by Stiasny-Kolster et al. [30] showed

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a similarly large increase in mean CSF 3OMD in RLS (30 nmol/l) compared to control (17 nmol/l) though the differences were not statistically significant. The majority (87%) of RLS subjects in that study had not previously been treated for their RLS and those that had been off all treatment for five days prior to the lumbar puncture. Therefore, some of the increase in 3OMD seen in our data may have occurred independent of drug treatment. Mice chronically treated with L-dopa showed a progressive increase in brain COMT and MAT, which suggests that under certain circumstances at least the COMT and MAT synthesis can be altered by chronic treatment [31]. One can see why L-dopa could up-regulate the enzyme but why would a dopamine agonist, which most of the subjects had been on prior to the study, produce such an effect; and why after two weeks of having been drug-free? A recent autopsy study reported an increase in total and phosphorylated tyrosine hydroxylase in neuromelanin cells of the substantia nigra from RLS patients (Dr James Connor, abstract presented at the Society of Neurosciences Meeting 2004). These findings would suggest the presence of increased L-dopa synthesis and would favor the interpretation of the increase in 3OMD in our studies as reflecting a similar process. Commiserate with those findings and interpretation of increased L-dopa synthesis was the circadian increase in BH4. BH4 is a co-factor for and a regulator of tyrosine hydroxylase activity [27], and, therefore, the increase in CSF BH4 would also support the premise that tyrosine hydroxylase activity is increased in RLS patients. The larger increases of BH4 for early-than for late-onset RLS seen in this study may reflect etiological differences in phenotypes driving the changes in the DA metabolism or, given the sample sizes of the 10 a.m. samples, may be a type-1 error. The third primary aim of this study was to compare the current CSF values, which would be collected at 10 p.m. to the previous study values, where samples were collected at 10 a.m. [16]. The pronounced circadian variation in RLS symptoms [7], the known circadian changes in the DAergic system [9–11] and the implied role of the DAergic system in those symptoms, drives the argument that circadian differences in measures of DAergic function might be preferable to looking at absolute difference across groups. Continuous, three-day ventricular CSF HVA analysis in rhesus monkey demonstrates a distinct circadian change in HVA [10], but the percentage change between peak and trough was only about 10%, which is relatively small. The repeated-measures and within-subjects design used with the monkeys gave sufficient power to detect such small amplitude differences in HVA. The current study did not have sufficient power to find small circadian amplitude differences of 10%, if in fact they existed, but did appear sufficiently powered to detect 24% circadian amplitude difference in BH4 found only for the RLS groups. Striatal biopterin levels in rats also shows circadian changes being maximal during the rest period and minimal during

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the activity period [32], which parallels the results seen in RLS in this study. Another significant circadian change found in this study was the 24% circadian difference in the CSF HVA:5HIAA ratio for RLS subjects. The CSF HVA:5HIAA ratio is used as a measure of the well-recognized, highly reproducible strong correlation found between CSF HVA and HIAA [33, 34], which was also found in our study. Although CSF HVA and 5HIAA independently show variability over the day, the ratio appears to be highly consistent across hours, days and even weeks under normal conditions [33,34]. The ratio is suggested to reflect some intrinsic biological balance between the dopaminergic and serotonergic systems [33]. If interpreted as such, then the changes in the ratio in RLS suggest greater DA turnover relative to the 5HT turnover in the daytime sample. The changes in the CSF HVA:5HIAA ratio, the BH4 and the 3OMD when taken together support the argument of a change in the circadian dynamics of the DAergic system, with the change being a relative increase in circadian amplitude of DAergic activity. The current theory of RLS pathology implies an interaction between iron and DAergic system with low brain iron leading to changes in DAergic activity [35]. The iron–DA interaction is supported by animal studies, which have shown a four-fold increase in the amplitude of the circadian cycle of striatal dopamine with iron deficiency [20,36]. Therefore, the greater circadian changes in the CSF values relative to control would be consistent with the current theory of reduced brain iron in RLS subjects, leading to an increased circadian amplitude of changes in dopaminergic synthesis and metabolism.

Acknowledgements This research was supported by NIH/NCRR grant M01RR02719 received by Johns Hopkins GCRC and NIH grant R01-NS38704 received by Dr Earley.

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