Circadian skin temperature rhythm and dysautonomia in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome: the role of endothelin-1 in the vascular dysregulation

doi:10.21203/rs.3.rs-2044838/v1

Download PDF

Research Article

Circadian skin temperature rhythm and dysautonomia in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome: the role of endothelin-1 in the vascular dysregulation

https://doi.org/10.21203/rs.3.rs-2044838/v1

This work is licensed under a CC BY 4.0 License

Version 1

posted

You are reading this latest preprint version

Purpose

There is accumulating evidence of autonomic dysfunction in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS); however, little is known about its association with circadian rhythms and endothelial dysfunction. This study aimed to explore the relationship between autonomic responses using an orthostatic test, skin temperature circadian variations, and circulating endothelial biomarkers in ME/CFS.

Methods

Sixty-seven adult female ME/CFS patients and 48 matched healthy controls were enrolled. Demographic and clinical characteristics suggestive of autonomic disturbances were assessed using validated self-reported outcome measures. Postural changes in blood pressure [BP], heart rate [HR], and wrist temperature (WT) were recorded during the orthostatic test. Actigraphy during one week was used to determine the 24-hour profile of peripheral temperature and motor activity. Circulating endothelial biomarkers were also measured as indicators of endothelial functioning.

Results

ME/CFS patients showed higher BP and HR values than healthy controls at rest (p < 0.05 for both), and also higher amplitude of the circadian activity rhythm (p < 0.01). Circulating levels of endothelin-1 (ET-1) and vascular cell adhesion molecule-1 (VCAM-1) were significantly higher in ME/CFS (p < 0.05). In ME/CFS, ET-1 levels were associated with the stability and amplitude of the temperature rhythm, (p < 0.01), and also with the self-reported questionnaires (p < 0.001).

Conclusions

ME/CFS patients exhibited alterations in circadian rhythms and hemodynamic measures that are associated with endothelial dysfunction, supporting previous evidence of dysautonomia in ME/CFS. Future investigation in this area is needed to assess vascular tone abnormalities and dysautonomia which may provide therapeutic targets for ME/CFS.

chronic fatigue syndrome

circadian rhythms

endothelin-1

myalgic encephalomyelitis

skin temperature

Myalgic Encephalomyelitis, also known as Chronic Fatigue Syndrome (ME/CFS) is a debilitating multifaceted disorder that affects more than 50 million people worldwide. The etiology of ME/CFS remains unknown, but it appears to be multifactorial, with immunogenetic and environmental factors influencing disease onset [1]. ME/CFS is characterized by debilitating post-exertional fatigue, neurocognitive impairments, autonomic dysfunction, and nonrestorative sleep possibly associated with disrupted circadian rhythms causing a marked reduction in daily activities, especially in women [2, 3]. Currently, there are no reliable diagnostic markers for ME/CFS, nor are any FDA-approved disease modifying drugs available [4].

Previous reports on autonomic dysfunction in ME/CFS confirm the imbalance between the sympathetic and parasympathetic nervous systems (SNS and PSNS). For example, there is evidence that ME/CFS patients have dysfunctional autonomic nervous systems (ANS), with decreased parasympathetic tone and increased sympathetic output [5]. Autonomic symptoms are highly prevalent in ME/CFS and include dizziness, orthostatic hypotension episodes, palpitations, lipotimias and alterations in sweating [6]. There is accumulating evidence in the literature that hemodynamic determinants related to blood pressure (systolic pressure, diastolic volume, cardiac output, heart rate variability, arterial stiffness, cerebral blood flow, etc.) are clearly disturbed in ME/CFS [7–9].

Barnden et al. correlated autonomic signs such as steady state blood pressure (BP) and heart rate (HR) with brain magnetic resonance imaging scans, concluding that in ME/CFS the functional consequences of normal anatomical variability may be distorted by impaired brainstem and midbrain signaling [10]. Dysregulation of the ANS also affects the cardiovascular system, leading to an impaired vasomotor response in ME/CFS, particularly postural orthostatic tachycardia syndrome (POTS). A prevalence of POTS of 23.7% has been reported in ME/CFS compared with only 4% in healthy controls [11]; however, other studies did not find differences between individuals with and without ME/CFS (5.7% vs. 6.9% respectively) [12].

The ANS also plays a key role in thermoregulation and circadian rhythms. These functions have not been studied in depth, even though ME/CFS patients frequently complain of feelings of excessive heat, night sweating and abnormal sensitivity to temperature [13]. The circadian system, whose master clock is the hypothalamic suprachiasmatic nuclei (SCN), regulates the manifestations of the circadian rhythm, ANS activity and sleep schedules. The SCN regulate peripheral clocks generating rhythms throughout the organism by means of hormones, temperature rhythm and regulation of the balance between the SNS, which peaks during the day, and the PSNS, which predominates at night [14–16].

Circadian alterations in peripheral temperature have been associated with dysautonomia in ME/CFS, reflecting alterations in the processes of vasoconstriction and vasodilation [13]. Peripheral temperature increases at night due to vessel dilation, in order to favor sleep, while alterations in this process have been related with difficulty in sleep onset [17]. However, vasoconstriction is due not only to the sympathetic effect on the vessels, but also to the regulation of local vessels by endothelial function which has been reported to be altered in ME/CFS [18–20].

Since endothelin-1 (ET-1), a strong endothelial vasoconstrictor, has been related with the regulation of the circadian rhythms [21], and high ET-1 levels have recently been reported in ME/CFS [19]. We hypothesized that there would be an alteration of the vasoconstrictor/vasodilation process, which might be reflected in temperature variations, and would indicate dysautonomia in ME/CFS. In addition, no previous studies have evaluated the association between VCAM-1 and ICAM-1 with dysautonomia and skin temperature circadian rhythms in ME/CFS.

In this study, we aimed to explore the utility of a passive standing test (10-minute NASA Lean Test, NLT) [22] to assess orthostatic intolerance (OI) and also to investigate peripheral temperature changes in the study participants by a) measuring the wrist temperature (WT) circadian rhythm (i.e., the temperature variation between day and night) and b) recording the skin temperature changes when participants change from a supine to standing position during the NLT. Moreover, we also explored the functioning endothelial status through the measurement of circulating endothelial biomarkers in the participants.

Participants

A single-center, prospective, cross-sectional case-control study of 67 consecutive females with ME/CFS and 48 age- and sex-matched non-fatigued healthy controls recruited at a single outpatient tertiary-referral center (ME/CFS Unit, Vall d’Hebron University Hospital, Barcelona, Spain) from October 2019 to March 2022. Following the suggestion made in a previous paper, data were not recorded during the summer [2]. Patients were potentially eligible if they were female, aged ≥ 18 years with a confirmed diagnosis by a specialist of ME/CFS according to the 2011 International Consensus Criteria [6]. Exclusion criteria were those as previously described by our group [2]. Forty-eight matched non-fatigued healthy controls were recruited through word-of-mouth from the local community. Demographic and clinical characteristics of the study population are displayed in Table 1.

Experimental procedures

An eligible population of 32 ME/CFS patients and 29 healthy controls came to the local hospital on Wednesday morning between 8 a.m. and 11 a.m. and another cohort (35 ME/CFS patients and 19 healthy controls) on Tuesday afternoon between 3 p.m. and 6 p.m. for a clinical assessment. Demographic and self-reported outcome measures were recorded, as described in our previous study [2]. Briefly, all eligible participants were asked about their fatigue status, sleep problems, anxiety/depression, autonomic complaints, and health-related quality of life. In participants who attended in the morning, a blood sample was taken for routine biochemical analysis. All participants underwent the same orthostatic test protocol (10-minute NLT) to evaluate orthostatic intolerance (see details below), and WT was also recorded using a temperature sensor (iButton^®Thermochron DS1921H) placed on the right wrist of each participant during the NLT procedures. Participants were asked to wear an ambulatory actigraphy device (ActTrust^®, Condor Instruments, Sao Paulo, Brazil) on the wrist of the non-dominant arm continuously for seven days, except when showering or at the swimming pool. The same actigraphy was programmed to collect data on motor activity (accelerometer), skin temperature (ºC) and light intensity (lux) at each-minute intervals. The data were recorded and stored in the device’s memory for further analysis. Subjects returned to the hospital after one week to hand in the actigraphy device, and completed health-related questionnaires.

Measures

Participants were also asked to provide complete validated self-report questionnaires on their current health status one week after the first clinical assessment. Changes in fatigue perception (FIS-40) [23], sleep quality (PSQI) [24], anxiety/depression (HADS) [25], autonomic symptoms (COMPASS-31) [26], and health-related quality of life (SF-36) [27] were assessed as described in our previous study [2], except for the assessment of frequency/severity and interference of orthostatic symptoms, which was performed using the orthostatic grading scale (OGS).

Orthostatic Grading Scale (OGS)

The OGS is a 5-item validated self-reported questionnaire designed to assess symptoms of orthostatic intolerance due to orthostatic hypotension. The five questions address the frequency/severity and interference of orthostatic symptoms in daily life activities. Respondents rate each item on a scale of 0 to 4. Adding the scores for the individual items produces an overall OGS score ranging from 0 (never or rarely orthostatic symptoms) to 20 (maximum orthostatic symptoms). Higher scores indicate greater severity of autonomic dysfunction [28].

Assessment of cardiovascular autonomic function

Autonomic response was evaluated using a passive standing test (10-min NASA Lean test, NLT) a simple and well-established non-invasive procedure used to assess impaired cardiovascular compensatory responses to standing in ME/CFS. The NLT classifies OI phenotypes as orthostatic hypotension (OH) and postural orthostatic tachycardia syndrome (POTS), and measures hemodynamic parameters (BP and HR) for both clinical and research purposes. The test was conducted in a consistent manner by the same examiner in the morning or in the afternoon, in a quiet room with an average relative temperature of 22.1±1.2ºC and humidity of 55±5.8%. The participants were first asked to lie down for five minutes and then to stand and lean against a wall, with heels 6-8 inches away from the wall. An automated BP cuff with monitor (Beurer BM-26, Beurer GmbH & Co., Ulm, Germany) was placed on the left arm, recording SBP/DBP and HR at 1-minute intervals and, simultaneously, a temperature sensor (iButton® Thermochron DS1921H) was placed on the right wrist to record the peripheral temperature changes throughout the orthostatic test. Systolic BP, diastolic BP and HR were recorded every minute for the two last minutes in supine position and the first 10 minutes after attaining the upright position. Throughout the recording, participants were asked to remain still, and any talking or movement was discouraged, except for reporting any symptoms of concern. The NLT was stopped early at the request of the subject, or in the event of severe pre-syncope [22]. After 10 minute upright, each participant was asked about the frequency/severity and impact of orthostatic symptoms on a 5-item OGS score [28].

Medication

In order to maintain patients’ functional status, medication was not withdrawn during the study. However, information on current medication use was collected from the medical records. Thirty-nine patients were taking non-steroidal anti-inflammatory drugs (ibuprofen, celecoxib for generalized pain), twenty-six serotonin-norepinephrine reuptake inhibitors (duloxetine for neuropathic pain), twelve anticonvulsants (gabapentin, pregabalin for chronic neuropathic pain), thirteen analgesics (paracetamol) and thirty-four anxiolytics (alprazolam, quetiapine for generalized anxiety disorder). Only seven patients were taking antihypertensive drugs, and none on the day of the NLT. None of the healthy controls were taking any medication.

Hemodynamic definitions recorded during the orthostatic test

Criteria for OI were based on the 2021 expert consensus statement and guidelines on the definition of OH and POTS as follows: (a) Orthostatic hypotension was defined as a decrease in systolic BP of ≥ 20 mmHg, or a decrease in diastolic BP of ≥ 10 mmHg in the first three minutes standing compared with resting supine values; and (b) POTS was defined as either an increase in HR ≥ 30 bpm and/or a current HR ≥ 120 bpm based on the average of the last three minutes standing [29, 30]. Classification of OI (OH and POTS) during the 10-minute NLT was quantified as the difference between supine and standing hemodynamic changes (ΔBP and ΔHR) as previously described [22]. For the purposes of this study, SBP/DBP and HR were used as raw values recorded during the NLT. For correlation analysis and grouping comparison, we calculated the mean values during the last two minutes in supine position (sp), and the mean values during minutes 1-3 standing (first three minutes, 3F), and mean values of minutes 8-10 standing (last three minutes, 3L). The changes in these variables at the end of the NLT were also calculated and compared with the values in supine position (Δ3L).

Actigraphy analysis

Skin temperature records (WT, wrist temperature) and activity values (accelerometer) obtained with the actigraphy device were analysed with “El-temps, version 314”, an integrated package for chronobiological analysis (A. Díez-Noguera, University of Barcelona, Spain; http://www.el-temps.com). The rhythmic variables were determined by adjusting the data to a 24-hour cosinusoidal curve. Thus, data of each variable (skin temperature and motor activity) were calculated: the mean 24-hour value (MESOR), the phase of the rhythm (acrophase) and the amplitude of the adjusted 24-hour rhythm (A_cos). Non-parametric circadian analysis was also performed as previously described [31]: M10 (or M5 in the case of WT) and L10 (or L5 in the case of WT) denoted the mean temperature in the 10 (or 5) consecutive hours with highest values (night temperature or activity during the day) and the 10 (or 5) hours with lowest values (day temperature or night activity values) respectively. Note that activity increases during the day and WT during the night. In addition, the intra-daily variability (IV), the stability of the rhythm (Rayleigh’s test, R), the percentage of variance explained by the 24-hour rhythm (PV) were also calculated.

Blood sampling and processing

Twenty milliliters of fasting blood samples from each participant were collected into K₂EDTA anticoagulant tubes (BD Vacutainer, Ontario, Canada) from an antecubital vein with a 19-gauge needle without venous stasis. One tube was transported to the local core Laboratory for the assessment of routine blood tests including a comprehensive metabolic panel. All other blood samples were immediately centrifuged at 2500 rpm for 15 min at 4ºC (Thermo Scientific, Waltham, MA, US) and then supernatants were collected and stored in aliquots at -80ºC until assayed. No sample was thawed more than twice. Repeated samples from each participant were measured in the same analytical batch.

Measurement of endothelial biomarkers

Circulating levels of soluble ET-1, vascular cell adhesion molecule-1 (VCAM-1) and intracellular adhesion molecule-1 (ICAM-1) were measured as indicators of endothelial functioning status. Plasma concentrations of ET-1 (Cat nº DET-100), VCAM-1 (Cat nº DVC00) and ICAM-1 (Cat nº DCIM00) proteins were assayed in each participant using commercially available ELISA kits according to the manufacturer’s instructions manual (Quantikine R&D Systems, Minneapolis, USA) using a Synergy™ H1M, Hybrid multi-mode microplate reader (BioTek Instruments, Inc., Winooski, USA) at O.D. 450 nm. Results were analysed by comparison with standard calibration curves in each well, and are presented as averages of two duplicated samples.

Statistical analysis

Data were tested for normality and homogeneity of variance with the Shapiro-Wilk and Levine tests, respectively. Values are presented as mean ± standard error of the mean (SEM) for continuous variables. Statistically significant differences for parametric variables were tested by means of one-way ANOVA, and p-values of less than 0.05 were considered statistically significant after Bonferroni’s correction for multiple testing. In cases of non-parametric variables such as those obtained in the questionnaires, the Mann-Whitney U test was assayed to test differences between groups. Meanwhile, differences in categorical variables were analyzed using the Fisher's exact test. Pearson’s correlation analyses were used in paired data to evaluate the associations between the different variables. For each variable studied, paired data with missing values were excluded from the analysis. In addition, stepwise linear regression models with backwards elimination was performed to select significant predictors of endothelial biomarkers (ET-1, VCAM-1 or ICAM-1). Subsequently, we tested the interaction between the autonomic symptoms assessed by COMPASS-31 and the significant predictors of endothelial biomarkers using stepwise linear regression models. Finally, we conducted a discriminant analysis using the variables obtained in the last analysis to evaluate which were the variables that could reliably classify the subjects into the two groups. Univariate F-tests were then calculated to determine the importance of each independent variable in forming the discriminant functions. Examining the Wilk’s lambda values for each of the predictors revealed how important the independent variable was to the discriminant function, with smaller values representing greater importance. Data were analysed using IBM SPSS Statistics for Windows, version 27.0 (IBM Corp., Armonk, NY, USA). All analyses were adjusted for age and BMI. A two-tailed p < 0.05 was considered statistically significant.

Demographic and clinical characteristics

Table 1 summarizes the demographic and clinical characteristics and the results of routine blood testing of the participants. The groups differed in terms of age (p = 0.016) and BMI (p < 0.001); therefore, the analysis of other variables was always carried out adjusting for age and BMI. In addition, ME/CFS patients showed higher levels of cholesterol, triglycerides, and low density lipoproteins (LDL) (all p < 0.01), and also of the hormone 17b-estradiol (p = 0.044) compared to healthy controls, although the values of this last variable were inside the normal range. Additionally, the groups differed in the self-reported outcome measures, with ME/CFS patients recording higher scores for fatigue status, anxiety/depression, sleep quality, autonomic symptoms and lower health-related quality of life (p < 0.001).

Passive standing test

Since the NLT was conducted during the morning in some participants and during the afternoon in others, we carried out a ANOVA for each dependent variable, considering as independent factors the group and the time of the day that the NLT was performed, including age and BMI as covariates. SBP/DBP and HR values were significantly higher in ME/CFS than in healthy controls, however; no differences according to time of the day were observed. As for changes in hemodynamic variables, there were no differences according to group (Table 2).

Seven ME/CFS patients had POTS (four in the morning and three in the afternoon) and eight healthy controls (six in the morning and two in the afternoon) also had POTS. Four ME/CFS patients had OH and one healthy control; thus, 16% of ME/CFS patients (11/67) and 13% of healthy controls (6/48) had abnormal cardiovascular responses to position changes after NLT, with no differences between two groups in terms of distribution. No participants had abnormal pulse pressure (PP) (less than 25% SBP). However, although no differences were found between groups in the postural autonomic responses, ME/CFS patients had higher values of BP and HR in both supine and standing position, and in individuals with and without POTS (p < 0.05 in all ANOVA comparisons) (Fig. 1a-d).

Since SBP/DBP and HR in supine position differed between the groups, we tested whether there might be a correlation according to illness duration. We carried out a Pearson regression analysis of these dependent variables considering age, BMI, and disease duration as predictors. Healthy controls were considered to have zero years of disease. Results showed that duration of illness was a significant predictor of SBP (p = 0.008) and DBP (p = 0.013), and almost significant for HR (p = 0.092) (data no shown).

Postural wrist temperature changes

Postural WT-related changes could only be measured in 42 ME/CFS patients (15 in the morning and 27 in the afternoon) and in 33 healthy controls (17 in the morning and 16 in the afternoon). Mean WT varied according to the time of the day, and was always higher in the afternoon (WT morning: 28.5±0.37ºC and WT afternoon: 31.5±0.27ºC) but no differences were found between the groups (Table 2). Wrist temperature rose significantly during the NLT (p < 0.01 in both ME/CFS and healthy controls), the increase being higher in the morning (mean value 2.35±0.23ºC vs. 0.76±0.22ºC in the afternoon), with no differences between ME/CFS patients and healthy controls.

Changes in WT during the NLT (ΔWT__NLT) were positively associated with nocturnal temperature (T_M5, p < 0.007), and with variables related with the stability of the WT circadian rhythm (T_R, p = 0.012, and T_PV, p = 0.014) in ME/CFS, but these associations were not present in controls. In addition, in patients, ΔWT__NLT was associated with hemodynamic variables such as SBP (p = 0.031), DBP (p = 0.028) and negatively with the decrease of DBP during the NLT. In healthy controls, these associations were not observed. ΔWT__NLT was negatively associated with ET-1 levels both in controls (p = 0.006) and in ME/CFS (p = 0.034). However, it should be remembered that these two variables could only be measured together in a few individuals (15 ME/CFS and 17 healthy controls), and ΔWT_NLT was analyzed in different regression models than the other variables.

Wrist temperature rhythms and motor activity measured by actigraphy

Circadian rhythm profiles differed between groups (Fig. 2a and b). However, once corrected for age and BMI, an ANOVA indicated that variables obtained from motor activity data differed between groups, but not those obtained from WT rhythm data (Table 2). Specifically, maximum activity, mean daily activity and the amplitude of the rhythm were lower in ME/CFS, while fragmentation (IV) was higher in ME/CFS. BMI emerged as the most important factor for WT rhythm variables.

We also tested the association between PSQI questionnaire (sleep alterations) and T_M5, since nocturnal temperature increases with sleep. As expected, in controls the correlation was negative, but in ME/CFS it did not reach significance. Moreover, since both motor activity and WT circadian rhythms tend to be associated, we tested whether this association occurred in a similar way in both groups, finding the stability of the activity rhythm to be positively associated with the stability of the WT rhythm in both ME/CFS (p = 0.025) and healthy controls (p = 0.04). However, in controls the nocturnal temperature (T_M5) was associated with high daily motor activity (p < 0.005), high rhythm amplitude (p < 0.005), and stability of the activity rhythm (p < 0.05); these associations were not found for ME/CFS (data no shown).

Endothelial biomarkers

ME/CFS patients showed significantly higher levels of plasma ET-1 and VCAM-1 proteins than healthy controls (p < 0.05 adjusted for both age and BMI). However, no differences were found for ICAM-1 protein (Table 2). We stress that these variables could only be studied in the morning participants due to the circadian rhythm of endothelial biomarkers.

Association analysis between variables

To relate endothelial dysfunction with the rest of the variables, we carried out several regression models with ET-1, VCAM-1 or ICAM-1 as dependent variables and considering the following variables as predictors: a) those obtained from temperature rhythms, b) those obtained from motor activity rhythms, and c) those obtained from the NLT. In all cases, age and BMI were included in the model. Table 3 shows the model of the selection process with the final coefficients and their statistical significance. Specifically, our results showed that:

Circadian variables of WT were significant predictors of ET-1 in ME/CFS and healthy controls. As such, the final model was obtained with the stability of the circadian rhythm, amplitude, and nocturnal value (T_M5). Meanwhile, in controls it was the amplitude of the WT circadian pattern which was the significant predictor of ET-1.
None of the circadian variables of motor activity were predictors of ET-1 in ME/CFS, nor in healthy controls. As such, no variables remained in the final model.
NLT variables were significant predictors of ET-1 in healthy controls. In the final model, ET-1 was associated with SBP/DBP, ΔSBP and ΔDBP in controls.

Interestingly VCAM-1 and ICAM-1 were not associated with the temperature variables. For VCAM-1, L10 and SBP were predictors in ME/CFS and BDP for controls. Interestingly, ET-1 levels were positively associated with the self-reported outcome measures in ME/CFS, but not in controls; the higher the ET-1 levels, the worse the symptomatology (Table 4).

Finally, to test the interactions between autonomic symptoms, hemodynamic variables, WT circadian rhythm variables and endothelial biomarkers in ME/CFS, we carried out a stepwise regression analysis with the global COMPASS-31 score as dependent variable, and the representative and non-redundant variables for each group as predictors: namely, the hemodynamic variables (SBP_sp DBP_sp, HR_sp, DSBP, DDBP, and DHR), temperature circadian rhythm variables (T_Acos, T_PV, and T_M5) and endothelial biomarkers (ET-1 and VCAM-1). Age and BMI were included in the first model as covariates. Again a stepwise linear regression model was applied and collinearity was analysed (Table 5). The results indicate that the predictors for the best model with COMPASS-31 as dependent variable were DBP_sp, ET-1, VCAM-1, T_PV, and T_M5. A MANOVA was followed up with discriminant analysis of these variables, which revealed significant differences between the two groups (Wilks' lambda = 0.372; Chi-square = 53.95; p < 0.0001). In all, 91.5% of participants of the original grouped cases (96% of ME/CFS patients and 85% of healthy controls) were correctly classified.

This study is the first to relate indicators of ANS dysfunction with the vasoconstriction/vasodilation process, also considering the subjective symptomatology of ME/CFS patients. Specifically, we studied the responses to the NLT (which includes measures of BP, HR and WT and their variations due to postural changes), the pattern of the circadian rhythms (separately for wrist temperature and motor activity) and endothelial dysfunction through the analysis of endothelial biomarkers.

The main result of this study is the association of circulating ET-1 levels with the frequency/severity of autonomic symptoms and WT-related variables, which suggests a potential role of endothelial dysfunction in ME/CFS [19]. A discriminant analysis of the variables in each group also obtained a statistically significant classification of the participants into patient and control groups.

This study also addresses secondary questions such as the usefulness of NLT, the measurement of peripheral WT, and the analysis of alterations of circadian rhythms in ME/CFS. In agreement with Roerink et al. [12], but not with Clayton et al. [11], we did not find differences in OI responses between ME/CFS and healthy controls; nor could we correlate the hemodynamic response with the symptom-related questionnaires. In any case, one should bear in mind that the diagnosis of POTS is not based on increases in HR alone, since other OI criteria should also be included; this methodological issue may explain the differences between studies [11]. Our results confirm that ME/CFS patients had higher values of BP and HR than healthy controls, independently of the manifestations of POTS, and that the values of these variables are associated with illness duration. This corroborates the idea that ME/CFS may induce a circulatory decompensation that is reflected in hemodynamic changes [22]. Increased HR in the supine position has already been reported in ME/CFS and may reflect increased sympatho-adrenomedullary activity [22, 32]. Although most ME/CFS patients were not hypertensive, the increase in BP could be related to arterial stiffness which has also been described in ME/CFS and in turn has been associated with more sympathetic dominance [33, 34].

To our knowledge, this is the first study to include the measurement of WT during the NLT. Postural skin temperature changes may be due to blood redistribution and may reflect individual variability of vasomotor activity [35]. Essentially, the skin (primarily distal sites) may serve as an ideal reservoir for blood redistribution due to changes in skin vascular tone [36]. With these considerations in mind, we assumed that the skin temperature would rise in the upright position, partially due to gravity which favours the presence of blood in the lower part of the arm, but also due to the vasodilator response.

Although we did not find differences in skin temperature between groups during NLT, these variables were of interest since they may be associated with the amplitude of the WT circadian rhythm and with ET-1 levels, which would suggest an impaired thermoregulatory response in ME/CFS. However, since postural changes of WT and ET-1 levels could only be measured in a relatively low number of individuals, further studies are needed to analyse this issue in greater depth.

A previous study by our group [2] found significant differences in the motor activity rhythm between ME/CFS and healthy controls, with ME/CFS showing less activity during the day, lower amplitude, and more fragmentation. In agreement with that earlier study, on this occasion we did not find differences in the WT rhythm. Nevertheless, only WT circadian rhythm variables were predictors of soluble ET-1 levels, a finding that corroborates the association between these variables. Thus, the fact that soluble ET-1 protein might be correlated with variables of the WT circadian rhythm but not with variables of the motor activity circadian rhythm in ME/CFS indicates that ET-1 and skin temperature are both markers of vasoconstriction/vasodilation processes, which may be impaired in ME/CFS and may be related to the intrinsic endothelial structure of the blood vessel [37]. Our study points to endothelial dysfunction as a prominent feature that may explain the autonomic symptoms in ME/CFS; in our view, measuring skin temperature might provide useful information for the clinical evaluation in ME/CFS.

On the other hand, endothelial damage alters the balance between vasoconstrictor/vasodilation events and also expresses higher levels of adhesion molecules. In our cohort, VCAM-1 levels were also high in ME/CFS, suggesting endothelial inflammation; however, the levels did not correlate with the severity of the symptomatology. Interestingly, levels of the vasoconstrictor ET-1 marker were elevated in ME/CFS, as other authors have recently reported [19]; since this is the variable that best correlated with the results of the self-reported questionnaires, it may be associated with illness severity. ME/CFS patients also had high levels of cholesterol, triglycerides and LDL which may cause endothelial dysfunction and cardiovascular disease, and may play a crucial role in the pathogenesis of ME/CFS [38].

Interestingly, sleep perception in healthy controls (as reflected by PSQI scores) was associated with nocturnal WT, an objective variable that increased during sleep due to vasodilation. However, this association was not found in ME/CFS patients, who often report unrefreshing sleep. This may have been due to the ANS dysfunction in our ME/CFS cohort, or to a decrease in circulating levels of melatonin, a key regulatory hormone of body temperature rhythm and sleep, which also affects autonomic vagal activity. Sleep alterations have been associated with elevated BP and HR and with HR variability, indicating reduced parasympathetic activity at night [39]. However, sleep and the cardiovascular function are regulated by the networks of the CNS nuclei, and therefore their study is also important for determining relationships between central sleep-wake control circuitry and the pathways regulating the autonomic function [40].

Limitations

This study has some limitations that should be mentioned. First, the single-center, cross-sectional nature of the design prevents us from identifying causation. In addition, the relatively small sample size, the use of self-reported data, and the inclusion only of women with mild/moderate disease severity may mean that the results are not representative of the entire population. Further limitations included the lack of data on comorbid health conditions, level of physical activity, and other sedentary lifestyles. Finally, the analyses derived from ET-1 associations are exploratory and may not have been appropriately powered.

This study is the first to relate indicators of ANS dysfunction with the vasoconstriction/vasodilation process, and also considers participants’ self-reported symptomatology. Specifically, we studied the responses to the NLT (which includes measures of SBP/DBP, HR and WT and their variations due to postural changes), the circadian rhythm pattern (separately for WT and motor activity) and endothelial dysfunction through the measurement of circulating endothelial biomarkers. Taken together, future studies in this area should aim to provide a better characterization of the underlying pathomechanisms of dysautonomia and endothelial dysfunction which may contribute to the development of new biological targets for therapeutic interventions in ME/CFS.

Competing interests

The authors declare that they have no conflict of interest.

Ethics statement

After receiving verbal and written information on the study protocol, all study participants gave signed informed consent to participate in the research protocol, which was approved by the local Institutional Ethical Committee on Human Research (Reference nº: PR/AG 201/2016). The study was carried out in accordance with the 1975 Declaration of Helsinki and with all the International Conference on Harmonization and Good Clinical Practice Guidelines.

Consent to participate

All participants provided written informed consent prior to enrollment.

Author contributions

Conceptualización and design: Trinitat Cambras, Antoni Díez-Noguera, José Alegre-Martín, Jesús Castro-Marrero.

Methodology: Trinitat Cambras, Antoni Díez-Noguera, Maria Cleofé Zaragozá, Joan Carles Domingo, Ramon Sanmartín-Sentañes, José Alegre-Martín, Jesús Castro-Marrero,

Formal analysis and investigation: Trinitat Cambras, Maria Fernanda Zerón-Rugerio, Antoni Díez-Noguera, Maria Cleofé Zaragozá, Jose Alegre-Martín, Jesús Castro-Marrero

Writing original draft preparation: Trinitat Cambras, Maria Fernanda Zerón-Rugerio, Jesús Castro-Marrero.

Writing, reviewing and editing final manuscript: Trinitat Cambras, Maria Fernanda Zerón-Rugerio, Antoni Díez-Noguera, Maria Cleofé Zaragozá, Joan Carles Domingo, José Alegre-Martín, Jesús Castro-Marrero.

Funding acquisition: Trinitat Cambras, Antoni Díez-Noguera, José Alegre-Martín, Jesús Castro-Marrero.

Consent for publication

The manuscript does not contain any individual personal data in any form. All authors commented on previous versions of draft and also reviewed and approved the final version of the manuscript.

Castro-Marrero J, Saez-Francas N, Santillo D, Alegre J (2017) Treatment and management of chronic fatigue syndrome/myalgic encephalomyelitis: all roads lead to Rome. Br J Pharmacol 174(5):345-369. https://doi.org/10.1111/bph.13702
Cambras T, Castro-Marrero J, Zaragoza MC, Diez-Noguera A, Alegre J (2018) Circadian rhythm abnormalities and autonomic dysfunction in patients with Chronic Fatigue Syndrome/Myalgic Encephalomyelitis. PLoS One 13(6):e0198106. https://doi.org/10.1371/journal.pone.0198106
Castro-Marrero J, Zaragoza MC, Gonzalez-Garcia S, Aliste L, Saez-Francas N, Romero O, Ferre A, Fernandez de Sevilla T, Alegre J (2018) Poor self-reported sleep quality and health-related quality of life in patients with chronic fatigue syndrome/myalgic encephalomyelitis. J Sleep Res 27(6):e12703. https://doi.org/10.1111/jsr.12703
Cortes Rivera M, Mastronardi C, Silva-Aldana CT, Arcos-Burgos M, Lidbury BA (2019) Myalgic Encephalomyelitis/Chronic Fatigue Syndrome: A Comprehensive Review. Diagnostics (Basel) 9(3). https://doi.org/10.3390/diagnostics9030091
Tanaka M, Tajima S, Mizuno K, Ishii A, Konishi Y, Miike T, Watanabe Y (2015) Frontier studies on fatigue, autonomic nerve dysfunction, and sleep-rhythm disorder. J Physiol Sci 65(6):483-498. https://doi.org/10.1007/s12576-015-0399-y
Carruthers BM, van de Sande MI, De Meirleir KL, Klimas NG, Broderick G, Mitchell T, Staines D, Powles AC, Speight N, Vallings R, Bateman L, Baumgarten-Austrheim B, Bell DS, Carlo-Stella N, Chia J, Darragh A, Jo D, Lewis D, Light AR, Marshall-Gradisnik S, Mena I, Mikovits JA, Miwa K, Murovska M, Pall ML, Stevens S (2011) Myalgic encephalomyelitis: International Consensus Criteria. J Intern Med 270(4):327-338. https://doi.org/10.1111/j.1365-2796.2011.02428.x
Nelson MJ, Bahl JS, Buckley JD, Thomson RL, Davison K (2019) Evidence of altered cardiac autonomic regulation in myalgic encephalomyelitis/chronic fatigue syndrome: A systematic review and meta-analysis. Medicine (Baltimore) 98(43):e17600. https://doi.org/10.1097/MD.0000000000017600
Natelson BH, Brunjes DL, Mancini D (2021) Chronic Fatigue Syndrome and Cardiovascular Disease: JACC State-of-the-Art Review. J Am Coll Cardiol 78(10):1056-1067. https://doi.org/10.1016/j.jacc.2021.06.045
Natelson BH, Lin JS, Blate M, Khan S, Chen Y, Unger ER (2022) Physiological assessment of orthostatic intolerance in chronic fatigue syndrome. J Transl Med 20(1):95. https://doi.org/10.1186/s12967-022-03289-8
Barnden LR, Crouch B, Kwiatek R, Burnet R, Mernone A, Chryssidis S, Scroop G, Del Fante P (2011) A brain MRI study of chronic fatigue syndrome: evidence of brainstem dysfunction and altered homeostasis. NMR Biomed 24(10):1302-1312. https://doi.org/10.1002/nbm.1692
Clayton EW (2015) Beyond myalgic encephalomyelitis/chronic fatigue syndrome: an IOM report on redefining an illness. JAMA 313(11):1101-1102. https://doi.org/10.1001/jama.2015.1346
Roerink ME, Lenders JW, Schmits IC, Pistorius AM, Smit JW, Knoop H, van der Meer JW (2017) Postural orthostatic tachycardia is not a useful diagnostic marker for chronic fatigue syndrome. J Intern Med 281(2):179-188. https://doi.org/10.1111/joim.12564
McCarthy MJ (2022) Circadian rhythm disruption in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome: Implications for the post-acute sequelae of COVID-19. Brain Behav Immun Health 20100412. https://doi.org/10.1016/j.bbih.2022.100412
Buijs RM, Escobar C, Swaab DF (2013) The circadian system and the balance of the autonomic nervous system. Handb Clin Neurol 117173-191. https://doi.org/10.1016/B978-0-444-53491-0.00015-8
Riganello F, Prada V, Soddu A, di Perri C, Sannita WG (2019) Circadian Rhythms and Measures of CNS/Autonomic Interaction. Int J Environ Res Public Health 16(13). https://doi.org/10.3390/ijerph16132336
Buijs RM, Soto Tinoco EC, Hurtado Alvarado G, Escobar C (2021) The circadian system: From clocks to physiology. Handb Clin Neurol 179233-247. https://doi.org/10.1016/B978-0-12-819975-6.00013-3
Krauchi K, Wirz-Justice A (2001) Circadian clues to sleep onset mechanisms. Neuropsychopharmacology 25(5 Suppl):S92-96. https://doi.org/10.1016/S0893-133X(01)00315-3
Kennedy G, Spence V, Khan F, Belch JJ (2004) Plasma endothelin-1 levels in chronic fatigue syndrome. Rheumatology (Oxford) 43(2):252-253; author reply 253-254. https://doi.org/10.1093/rheumatology/keg462
Haffke M, Freitag H, Rudolf G, Seifert M, Doehner W, Scherbakov N, Hanitsch L, Wittke K, Bauer S, Konietschke F, Paul F, Bellmann-Strobl J, Kedor C, Scheibenbogen C, Sotzny F (2022) Endothelial dysfunction and altered endothelial biomarkers in patients with post-COVID-19 syndrome and chronic fatigue syndrome (ME/CFS). J Transl Med 20(1):138. https://doi.org/10.1186/s12967-022-03346-2
Paschos GK, FitzGerald GA (2010) Circadian clocks and vascular function. Circ Res 106(5):833-841. https://doi.org/10.1161/CIRCRESAHA.109.211706
Douma LG, Barral D, Gumz ML (2021) Interplay of the Circadian Clock and Endothelin System. Physiology (Bethesda) 36(1):35-43. https://doi.org/10.1152/physiol.00021.2020
Lee J, Vernon SD, Jeys P, Ali W, Campos A, Unutmaz D, Yellman B, Bateman L (2020) Hemodynamics during the 10-minute NASA Lean Test: evidence of circulatory decompensation in a subset of ME/CFS patients. J Transl Med 18(1):314. https://doi.org/10.1186/s12967-020-02481-y
Fisk JD, Ritvo PG, Ross L, Haase DA, Marrie TJ, Schlech WF (1994) Measuring the functional impact of fatigue: initial validation of the fatigue impact scale. Clin Infect Dis 18 Suppl 1S79-83. https://doi.org/10.1093/clinids/18.supplement_1.s79
Buysse DJ, Reynolds CF, 3rd, Monk TH, Berman SR, Kupfer DJ (1989) The Pittsburgh Sleep Quality Index: a new instrument for psychiatric practice and research. Psychiatry Res 28(2):193-213. https://doi.org/10.1016/0165-1781(89)90047-4
Herrero MJ, Blanch J, Peri JM, De Pablo J, Pintor L, Bulbena A (2003) A validation study of the hospital anxiety and depression scale (HADS) in a Spanish population. Gen Hosp Psychiatry 25(4):277-283. https://doi.org/10.1016/s0163-8343(03)00043-4
Sletten DM, Suarez GA, Low PA, Mandrekar J, Singer W (2012) COMPASS 31: a refined and abbreviated Composite Autonomic Symptom Score. Mayo Clin Proc 87(12):1196-1201. https://doi.org/10.1016/j.mayocp.2012.10.013
Alonso J, Prieto L, Anto JM (1995) [The Spanish version of the SF-36 Health Survey (the SF-36 health questionnaire): an instrument for measuring clinical results]. Med Clin (Barc) 104(20):771-776.
Schrezenmaier C, Gehrking JA, Hines SM, Low PA, Benrud-Larson LM, Sandroni P (2005) Evaluation of orthostatic hypotension: relationship of a new self-report instrument to laboratory-based measures. Mayo Clin Proc 80(3):330-334. https://doi.org/10.4065/80.3.330
Vernino S, Bourne KM, Stiles LE, Grubb BP, Fedorowski A, Stewart JM, Arnold AC, Pace LA, Axelsson J, Boris JR, Moak JP, Goodman BP, Chemali KR, Chung TH, Goldstein DS, Diedrich A, Miglis MG, Cortez MM, Miller AJ, Freeman R, Biaggioni I, Rowe PC, Sheldon RS, Shibao CA, Systrom DM, Cook GA, Doherty TA, Abdallah HI, Darbari A, Raj SR (2021) Postural orthostatic tachycardia syndrome (POTS): State of the science and clinical care from a 2019 National Institutes of Health Expert Consensus Meeting - Part 1. Auton Neurosci 235102828. https://doi.org/10.1016/j.autneu.2021.102828
Raj SR, Bourne KM, Stiles LE, Miglis MG, Cortez MM, Miller AJ, Freeman R, Biaggioni I, Rowe PC, Sheldon RS, Shibao CA, Diedrich A, Systrom DM, Cook GA, Doherty TA, Abdallah HI, Grubb BP, Fedorowski A, Stewart JM, Arnold AC, Pace LA, Axelsson J, Boris JR, Moak JP, Goodman BP, Chemali KR, Chung TH, Goldstein DS, Darbari A, Vernino S (2021) Postural orthostatic tachycardia syndrome (POTS): Priorities for POTS care and research from a 2019 National Institutes of Health Expert Consensus Meeting - Part 2. Auton Neurosci 235102836. https://doi.org/10.1016/j.autneu.2021.102836
van Someren EJ, Mirmiran M, Swaab DF (1993) Non-pharmacological treatment of sleep and wake disturbances in aging and Alzheimer's disease: chronobiological perspectives. Behav Brain Res 57(2):235-253. https://doi.org/10.1016/0166-4328(93)90140-l
Timmers HJ, Wieling W, Soetekouw PM, Bleijenberg G, Van Der Meer JW, Lenders JW (2002) Hemodynamic and neurohumoral responses to head-up tilt in patients with chronic fatigue syndrome. Clin Auton Res 12(4):273-280. https://doi.org/10.1007/s10286-002-0014-1
Allen J, Murray A, Di Maria C, Newton JL (2012) Chronic fatigue syndrome and impaired peripheral pulse characteristics on orthostasis--a new potential diagnostic biomarker. Physiol Meas 33(2):231-241. https://doi.org/10.1088/0967-3334/33/2/231
Slomko J, Estevez-Lopez F, Kujawski S, Zawadka-Kunikowska M, Tafil-Klawe M, Klawe JJ, Morten KJ, Szrajda J, Murovska M, Newton JL, Zalewski P (2020) Autonomic Phenotypes in Chronic Fatigue Syndrome (CFS) Are Associated with Illness Severity: A Cluster Analysis. J Clin Med 9(8). https://doi.org/10.3390/jcm9082531
Shilco P, Roitblat Y, Buchris N, Hanai J, Cohensedgh S, Frig-Levinson E, Burger J, Shterenshis M (2019) Normative surface skin temperature changes due to blood redistribution: A prospective study. J Therm Biol 8082-88. https://doi.org/10.1016/j.jtherbio.2019.01.009
Krauchi K, Gompper B, Hauenstein D, Flammer J, Pfluger M, Studerus E, Schotzau A, Orgul S (2012) Diurnal blood pressure variations are associated with changes in distal-proximal skin temperature gradient. Chronobiol Int 29(9):1273-1283. https://doi.org/10.3109/07420528.2012.719961
Suganya N, Bhakkiyalakshmi E, Sarada DV, Ramkumar KM (2016) Reversibility of endothelial dysfunction in diabetes: role of polyphenols. Br J Nutr 116(2):223-246. https://doi.org/10.1017/S0007114516001884
Maloney EM, Boneva RS, Lin JM, Reeves WC (2010) Chronic fatigue syndrome is associated with metabolic syndrome: results from a case-control study in Georgia. Metabolism 59(9):1351-1357. https://doi.org/10.1016/j.metabol.2009.12.019
Jarrin DC, Ivers H, Lamy M, Chen IY, Harvey AG, Morin CM (2018) Cardiovascular autonomic dysfunction in insomnia patients with objective short sleep duration. J Sleep Res 27(3):e12663. https://doi.org/10.1111/jsr.12663
Fink AM, Bronas UG, Calik MW (2018) Autonomic regulation during sleep and wakefulness: a review with implications for defining the pathophysiology of neurological disorders. Clin Auton Res 28(6):509-518. https://doi.org/10.1007/s10286-018-0560-9

Table 1 Baseline demographic and clinical characteristics of the study population

Variables ^a	ME/CFS	HCs	Adjusted p-value ^b
Variables ^a	(n = 67)	(n = 48)	Adjusted p-value ^b
Age, years	49.0 ± 1.04	44.3 ± 1.90	0.016
BMI, kg/m²	27.6 ± 5.50	24.1 ± 0.60	< 0.001
Supine SBP, mmHg	124.18 ± 1.9	112.95 ± 1.6	< 0.05
Supine DBP, mmHg	78.97 ± 1.10	70.97 ± 1.06	< 0.01
Supine HR, bpm	74.47 ± 1.44	67.5 ± 1.18	< 0.01
Illness duration, years	6.21 ± 0.50	n/a	n/a
Routine blood tests ^§
Hematocrit, %	42.8 ± 0.82	42.4 ± 0.63	0.667
Glucose, mg/dL	89.1 ± 1.86	85.30 ± 1.58	0.122
Urea, mg/dL	31.2 ± 1.48	29.5 ± 1.47	0.406
Creatinine, mg/dL	0.69 ± 0.03	0.73 ± 0.02	0.310
Urate, mg/dL	4.69 ± 0.24	4.48 ± 0.19	0.493
Cholesterol, mg/dL	227.07 ± 7.87	200.33 ± 7.30	0.016
Triglycerides, mg/dL	113.90 ± 10.67	71.78 ± 4.86	0.001
HDL, mg/dL	66.86 ± 2.87	69.24 ± 3.19	0.582
LDL, mg/dL	141.61 ± 6.42	118.76 ± 6.05	0.012
eGFR, mL/min/1.73 m²	72.6 ± 7.22	76.0 ± 2.00	0.790
Sodium, mmol/L	139.75 ± 0.31	138.95 ± 0.29	0.060
Potassium, mmol/L	4.17 ± 0.06	4.22 ± 0.05	0.503
Phosphate, mg/dL	3.59 ± 0.12	3.49 ± 0.08	0.478
Calcium, mg/dL	9.66 ± 0.07	9.65 ± 0.05	0.973
Albumin, g/dL	4.35 ± 0.05	4.46 ± 0.05	0.137
Total protein, g/dL	7.14 ± 0.07	7.26 ± 0.08	0.284
TSH, mUI/L	2.12 ± 0.20	2.01 ± 0.23	0.715
Free T4, ng/dL	1.10 ± 0.20	1.18 ± 0.03	0.071
25-hydroxy-vitamin D, ng/mL	20.74 ± 2.08	23.50 ± 1.59	0.293
Cortisol, mg/dL	14.96 ± 1.18	12.61 ± 1.28	0.183
17b-estradiol, pg/mL	118.23 ± 27.65	52.07 ± 16.42	0.044
Progesterone, ng/mL	0.54 ± 0.25	0.72 ± 0.51	0.847
Aldosterone, ng/dL	10.35 ± 0.98	10.03 ± 0.51	0.772
Prolactin, ng/mL	8.53 ± 0.62	8.38 ± 0.58	0.864
Measures ^a
FIS-40
Global score (0-160)	130.3 ± 2.7	18.9 ± 3.0	<0.001
Physical	33.9 ± 0.6	82.6 ± 0.8	<0.001
Cognitive	61.9 ± 1.5	8.6 ± 1.5	<0.001
Psychosocial	34 ± 0.8	4.5 ± 0.8	<0.001
PSQI
Global score (0-21)	15.5 ± 0.5	5.9 ± 0.5	<0.001
Subjective sleep quality	2.2 ± 0.11	0.7 ± 0.11	<0.001
Sleep latency	2.1 ± 0.31	0.6 ± 0.16	<0.001
Sleep duration	1.9 ± 0.11	1.1 ± 0.09	<0.001
Habitual sleep efficiency	2.1 ± 0.14	0.6 ± 0.14	<0.001
Sleep disturbances	2.3 ± 0.18	1.1 ± 0.05	<0.001
Use of sleeping medication	2.1 ± 0.15	0.3 ± 0.11	<0.001
Daytime dysfunction	2.4 ± 0.08	0.6 ± 0.97	<0.001
HADS
Global score (0-42)	24.5 ± 0.9	6.9 ± 0.7	<0.001
Anxiety	12.8 ± 0.5	5.3 ± 0.5	<0.001
Depression	11.7 ± 0.5	1.7 ± 0.32	<0.001
COMPASS-31
Global score (0-100)	59.5 ± 1.68	13.9 ± 1.53	<0.001
Orthostatic intolerance	25.4 ± 0.9	5.9 ± 0.9	<0.001
Vasomotor	1.9 ± 0.18	0.1 ± 0.07	<0.001
Secretomotor	10.3 ± 0.32	1.4 ± 0.37	<0.001
Gastrointestinal	13.5 ± 0.50	4.8 ± 0.57	<0.001
Bladder	4.4 ± 0.35	0.6 ± 0.17	<0.001
Pupillomotor	3.8 ± 0.12	1.06 ± 0.13	<0.001
SF-36
Global score (0-100)	26.0 ± 3.1	85.5 ± 2.5	<0.001
Physical functioning	30.3 ± 2.5	96.9 ± 0.8	<0.001
Physical role functioning	1.8 ± 0.9	90.5 ± 3.3	<0.001
Bodily pain	20.9 ± 2.9	85.4 ± 2.9	<0.001
General health perception	23.1 ± 1.9	85.6 ± 1.7	<0.001
Vitality	13.5 ± 1.9	70.6 ± 2.7	<0.001
Social role functioning	34.4 ± 3.1	92.7 ± 2.2	<0.001
Emotional role functioning	39.4 ± 5.6	87.4 ± 4.1	<0.001
Mental health	43.9 ± 2.8	75.2 ± 2.5	<0.001
OGS ^†
Global score (0-20)	12.82 ± 4.39	0.87 ± 1.81	<0.001
Frequency of orthostatic symptoms	2.68 ± 1.04	0.26 ± 0.59	<0.001
Severity of orthostatic symptoms	2.59 ± 1.01	0.22 ± 0.47	<0.001
Conditions under which orthostatic symptoms occur occusymptoms occur	2.73 ± 1.12	0.24 ± 0.48	<0.001
Activities of daily living	2.50 ± 1.06	0.02 ± 0.15	<0.001
Standing time	2.32 ± 1.21	0.12 ± 0.55	<0.001

Data are shown as mean ± SEM for each item. ^aBaseline self-reported outcome measure scores (global and subscales) of core symptoms, as explained in Methods section. ^bp-values from Student’s t-test for continuous variables and from Mann-Whitney U test for categorical variables. Bold values denote statistical significance at p < 0.05 between groups. ^§Twenty-eight ME/CFS cases and 28 healthy controls underwent fasting laboratory blood tests. ^† Twenty-nine ME/CFS cases and 16 healthy controls completed the OGS questionnaire

ME/CFS Myalgic Encephalomyelitis/Chronic Fatigue Syndrome, HCs Healthy controls, BMI body mass index, SBP systolic blood pressure, DBP diastolic blood pressure, n/a not applicable, HDL high density lipoproteins, LDL low density lipoproteins, eGFR estimated glomerular filtration rate, TSH thyroid-stimulating hormone, FIS-40 40-item Fatigue Index Scale, HADS Hospital Anxiety and Depression Scale, PSQI Pittsburgh Sleep Quality Index, COMPASS-31 31-items Abbreviated Composite Autonomic Symptom Score, SF-36 Medical Outcome Study 36-item Short Form Health Survey, OGS Orthostatic Grading Scale.

Table 2 Differences between cardiovascular variables, wrist temperature, circadian-related variables and endothelial biomarkers in ME/CFS and healthy controls

Variables	ME/CFS (n = 67)	HCs (n = 48)	Adjusted p-value ^a
Cardiovascular variables
SBP_sp, mmHg	124.18 ± 1.99	112.95 ± 1.6	< 0.012
DSBP_3F, mmHg	1.06 ± 1.14	1.79 ± 1.01	0.979
DBP_sp, mmHg	78.97 ± 1.13	70.97 ± 1.06	< 0.001
DDBP_3F, mmHg	6.69 ± 0.84	6.66 ± 0.87	0.959
HR_sp, bpm	74.47 ± 1.44	67.5 ± 1.18	< 0.001
DHR_3L, bpm	14.65 ± 1.23	17.28 ± 1.64	0.961
PP_sp, a.u.	45.37 ± 1.24	41.98 ± 1.24	0.616
Wrist temperature during the NLT ^†
WT_sp, ºC	30.72 ± 0.32	29.67 ± 0.39	0.474
DWT_3L, ºC	1.08 ± 0.25	1.97 ± 0.28	0.173
Temperature rhythm variables
Mesor, ºC	30.35 ± 0.10	30.54 ± 0.12	0.745
Acrophase, min	318.77 ± 33.19	190.55 ± 12.91	0.391
Amplitude (cosinor), ºC	1.79 ± 0.10	1.73 ± 0.11	0.381
IV, a.u.	0.01 ± 0	0.01 ± 0	0.116
R, a.u.	0.83 ± 0.03	0.88 ± 0.02	0.423
PV, %	41.15 ± 2.03	42.07 ± 1.56	0.887
M5, ºC	32.52 ± 0.15	32.82 ± 0.12	0.621
L10, ºC	28.96 ± 0.11	29.28 ± 0.17	0.259
Motor activity rhythm variables
Mesor, a.u.	2058 ± 95	2746 ± 82	< 0.001
Acrophase, min	858 ± 11.4	856 ± 11	0.986
Amplitude (cosinor), ºC	1744 ± 80	2116 ± 72	< 0.009
IV, a.u.	0.42 ± 0.008	0.37 ± 0.01	0.102
R, a.u.	0.93 ± 0.009	0.92 ± 0.009	0.745
PV, %	32.73 ± 0.97	31.02 ± 0.88	0.107
M10, a.u.	3390 ± 149	4308 ± 127	< 0.001
L5, a.u.	199 ± 26	175 ± 20	0.911
Endothelial biomarkers ^§
ET-1, pg/mL	1.84 ± 0.14	1.12 ± 0.63	0.004
VCAM-1, ng/mL	739 ± 33	494 ± 17	< 0.001
ICAM-1, ng/mL	284 ± 10	285 ± 19	0.611

Data are expressed as mean ± SEM. ^a p-values were attained from ANOVA, which was adjusted for age and BMI. In cardiovascular and wrist temperature variables during the NLT, the time of the day was also considered as independent variable. Significant comparisons are highlighted in bold. n.s.: not statistically significant. ^† Wrist temperature was recorded during the NLT in 42 ME/CFS cases and 33 healthy controls. ^§Circulating endothelial biomarkers were measured in 32 ME/CFS cases and 29 healthy controls

ME/CFS Myalgic Encephalomyelitis/Chronic Fatigue Syndrome, HCs Healthy controls, SBP_sp systolic blood pressure in supine position, DSBP_3F variation of SBP in the first three minutes of standing, DBP_sp diastolic blood pressure in supine position, DDBP_3F variation of SBP in the first three minutes of standing, HR_sp heart rate in supine position, DHR_3 variation of HR in the last three minutes of standing, PP_sp pulse pressure in supine position, IV intraday variability, R Rayleigh test, PV variance (%) explained by the 24-hour rhythm; M10 (or M5) maximum value of the variable, L5 (or L10) minimum value of the variable (see text for further explanation), ET-1 endothelin-1, VCAM-1 vascular cell adhesion molecule-1, ICAM-1 intercellular adhesion molecule-1

Table 3 Stepwise regression models (backwards elimination) of the association of circulating endothelial biomarkers with circadian rhythm and orthostatic test variables for ME/CFS and healthy controls separately

	ET-1, pg/mL		VCAM-1, ng/mL		ICAM-1, ng/mL
Variables	ME/CFS	HCs	ME/CFS	HCs	ME/CFS	HCs
	B^a	B^a	B^a	B^a	B^a	B^a
Temperature
Step 1 (initial model)
Amplitude, ºC	0.063	0.553	-60.484	44.436	-27.118	102.581
IV, a.u.	-33.770	15.620	-1171.484	-8496.904	40.607	-18658.229
R, a.u.	-0.552	0.416	542.522	138.721	66.280	429.192
PV, %	-0.034	-0.024	-2.726	-5.450	0.571	-7.151
M5, ºC	0.537	0.013	-17.247	-0.443	2.547	-80.401
L10, ºC	0.040	0.035	-49.908	8.894	-16.097	47.057
Final model
PV, %	-0.034*	-	-	-	-	-
M5, ºC	0.564**	-	-	-	-	-
Amplitude, ºC	-	0.486*	-	-	-	-
Motor activity
Step 1 (initial model)
Mesor, a.u.	-0.002	0.002	0.107	-0.058	0.195	0.076
Amplitude, ºC	0.000	0.002	-0.167	-0.203	0.205	-0.075
IV, a.u	0.524	-3.459	1082.393	136.465	171.076	170.145
R, a.u.	-0.287	-1.141	152.340	-352.068	22.964	203.005
PV, %	-0.054	-0.023	0.436	1.572	2.958	-1.292
M10, a.u.	0.001	-0.002	0.034	0.165	-0.245	-0.006
L5, a.u.	-0.001	0.002	0.564	-0.360	0.165	-0.119
Final model
L10, a.u.	-	-	0.665*	-	-	-
Active standing test (NLT)
Step 1 (initial model)
SBP_sp, mmHg	-0.004	0.015	-2.117	-1.809	0.535	0.855
DBP_sp, mmHg	0.011	-0.033	-0.713	3.620	-0.352	7.752
HR_sp, bpm	0.014	-0.012	-2.286	5.209	1.605	5.633
DSBP_3F, mmHg	0.010	0.033	-4.509	6.352	-0.588	-0.913
DDBP_3F, mmHg	-0.069	-0.063	0.742	-2.246	-2.822	-5.600
DHR_3, bpm	0.051	-0.011	-10.802	1.260	-2.959	2.758
DWT_3, ºC	-0.454	-0.053	-34.913	8.589	-11.224	26.378
Final model
SBP_sp, mmHg	-	0.022**	-3.348*	-	-	-
DBP_sp, mmHg	-	-0.033**	-	-	-	5.290*
DSBP_3F, mmHg	-	0.043*	-	-	-	-
DDBP_3F, mmHg	-	-0.065**	-	-	-	-
DWT_3, ºC	-0.374*	-	-	-	-	31.939*

^a Values are unstandardized beta coefficients derived from stepwise regression models. Table shows Step 1 (initial model, which was conducted with all predictors entered together) and the predictors obtained in the final step after iteration (final model). Significance at *p < 0.05 and **p < 0.01 are shown in bold

ET-1 endothelin-1, VCAM-1 vascular cell adhesion molecule-1, ICAM-1 intercellular adhesion molecule-1, ME/CFS Myalgic Encephalomyelitis/Chronic Fatigue Syndrome, HCs Healthy controls, NLT 10-min NASA Lean Test, IV intraday variability, R Rayleigh test, PV Percentage of variance explained by the 24-hour rhythm, M10 (or M5) maximum value of the variable, L5 (or L10) minimum value of the variable (see text for further explanation), SBP_sp systolic blood pressure in supine position, DSBP_3F variation of SBP in the first three minutes of standing, DBP_sp diastolic blood pressure in supine position, DDBP_3F variation of SBP in the first three minutes of standing, HR_sp heart rate in supine position, DHR_3 variation of HR in the last three minutes of standing, DWT_3 variation of wrist temperature in the first three minutes of standing

Table 4 Partial correlations between endothelial biomarkers and self-reported outcome measures for ME/CFS and HC groups separately

	ME/CFS						Healthy controls
Measures	ET-1, pg/mL		VCAM-1, ng/mL		ICAM-1, ng/mL		ET-1, pg/mL		VCAM-1, ng/mL		ICAM-1, ng/mL
	r	p-value	r	p-value	r	p-value	r	p-value	r	p-value	r	p-value
FIS-40	0.529	0.005	-0.098	0.626	0.180	0.369	-0.165	0.430	-0.149	0.477	-0.322	0.117
HADS	0.407	0.035	-0.148	0.462	0.136	0.500	0.011	0.957	0.233	0.263	0.232	0.265
COMPASS-31	0.452	0.018	-0.104	0.607	0.042	0.834	0.063	0.764	0.046	0.826	-0.009	0.965
SF-36	-0.501	0.008	0.090	0.654	-0.205	0.304	0.140	0.503	-0.142	0.498	-0.052	0.805
OGS	-0.021	0.947	-0.166	0.587	0.178	0.561	0.127	0.529	-0.183	0.360	-0.049	0.810
PSQI	0.468	0.014	-0.296	0.134	-0.055	0.783	0.038	0.861	0.357	0.086	0.494	0.014

Values shown correlation coefficients (r) and p-values from partial correlations adjusted for age and BMI. Significant p-values are shown in bold

ME/CFS Myalgic Encephalomyelitis/Chronic Fatigue Syndrome, ET-1 endothelin-1, ICAM-1 intercellular adhesion molecule-1, VCAM-1 vascular cell adhesion molecule-1, FIS-40 40-item Fatigue Index Scale, HADS Hospital Anxiety and Depression Scale, COMPASS-31 31-items Abbreviated Composite Autonomic Symptom Score, SF-36 Medical Outcome Study 36-item Short Form Health Survey, OGS Orthostatic Grading Scale, PSQI Pittsburgh Sleep Quality Index

Table 5 Stepwise regression models (backwards elimination) of the association of COMPASS-31 questionnaire with all the groups of studied variables for ME/CFS and healthy controls together

	COMPASS-31
	B^a	p-value
Step 1 (initial model)
SBP_sp, mmHg	-0.184	0.539
DBP_sp, mmHg	0.787	0.103
HR_sp, bpm	0.089	0.725
DSBP_3L, mmHg	-0.456	0.219
DDBP_3L, mmHg	0.527	0.338
DHR_3L, bpm	-0.320	0.287
ET-1, pg/mL	15.012	0.000
VCAM-1, ng/mL	0.064	0.000
Amplitude (T), ºC	3.709	0.420
PV (T), %	0.610	0.062
M5 (T); ºC	-10.565	0.009
Age, years	-0.177	0.460
BMI, kg/m²	-0.132	0.804
Final model
DBP_sp, mmHg	0.559	0.028
ET-1, pg/mL	14.727	0.000
VCAM-1, ng/mL	0.059	0.000
PV (T), %	0.657	0.009
M5 (T), ºC	-9.263	0.007

^a Values are unstandardized beta coefficients derived from stepwise regression models. Table shows step 1 (initial model, which was conducted with all predictors entered together) and the predictors obtained in the final step after iteration (final model). Significant p-values of the coefficients at the final model are shown in bold

ME/CFS Myalgic Encephalomyelitis/Chronic Fatigue Syndrome, BMI body mass index, SBP_sp systolic blood pressure in supine position, DBP_sp diastolic blood pressure in supine position, HR_sp heart rate in supine position, DSBP_3L variation of SBP in the last three minutes of standing, DDBP_3L variation of SBP in the last three minutes of standing, DHR_3L variation of HR in the last three minutes of standing, ET-1 endothelin-1, VCAM-1 vascular cell adhesion molecule-1, Amplitude (T) amplitude of the temperature rhythm, PV (T) percentage of variance explained by the 24-hour temperature rhythm, M5 (T) nocturnal temperature (see text for further explanation)

Download PDF

Version 1

posted

You are reading this latest preprint version

Circadian skin temperature rhythm and dysautonomia in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome: the role of endothelin-1 in the vascular dysregulation

Status:

Version 1

Abstract

Purpose

Methods

Results

Conclusions

Figures

Introduction

Methods

Results

Discussion

Conclusions

Declarations

References

Tables

Status:

Version 1