Endocrine Care 789
Authors
D. J. F. Stuijver1, 2, L. P. B. Elbers1, 2, B. van Zaane1, 2, O. M. Dekkers3, 4, C. A. Spek5, V. E. A. Gerdes1, 2, P. H. Reitsma6, 7, D. P. M. Brandjes1
Affiliations
Affiliation addresses are listed at the end of the article
Key words ▶ hyperthyroidism ● ▶ inflammation ● ▶ coagulation ● ▶ venous thrombosis ●
Abstract
received 26.11.2013 accepted 17.02.2014 Bibliography DOI http://dx.doi.org/ 10.1055/s-0034-1370975 Published online: April 1, 2014 Horm Metab Res 2014; 46: 789–793 © Georg Thieme Verlag KG Stuttgart · New York ISSN 0018-5043 Correspondence L. P. B. Elbers Department of Internal Medicine Slotervaart Hospital Louwesweg 6 1066 EC Amsterdam The Netherlands Tel.: + 31/20/5125 194 Fax: + 31/20/5124 783 [email protected]
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An excess of thyroid hormone leads to a prothrombotic state; however, the underlying pathophysiological mechanisms remain unknown. As evidence points towards an extensive “crosstalk” between the inflammatory and coagulation cascade, inflammation has been claimed as a possible mechanism through which different risk factors trigger venous thrombus formation. We aimed to study changes in expression of inflammation-related genes of the leukocyte RNA expression profile in healthy subjects in response to supraphysiological doses of levothyroxine. In a randomized single-blinded crossover design, 12 healthy volunteers (aged 18–40 years) received levothyroxine and no medication, both for 14 days with a wash-out period of at least 28 days between the periods. Blood was sampled at base-
Introduction
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Since the beginning of the past century, case reports have suggested a link between thyroid dysfunction and haemostatic abnormalities [1, 2]. From then onwards several studies have been performed to further elucidate this relationship. An excess of thyroid hormone is thought to induce a prothrombotic state, which led to the hypothesis that hyperthyroidism is a risk factor for venous thrombosis [3]. Indeed, high levels of free thyroxine (FT4) are associated with an increased risk of venous thrombosis, whereas a reduced risk was found for lower levels of FT4 [4]. The underlying pathophysiological mechanisms by which thyroid hormones may influence coagulation remain ill-defined. Several mechanisms have been suggested to underlie this relation including autoimmunity, indirect effects of endothelial dysfunction and atherosclerosis, and increased peripheral sensitivity to catechol-
line and day 14 of each study period. MRNA was isolated from whole blood and used for multiplex ligation-dependent probe amplification to study the expression of inflammation-related genes. Compared to the control situation no significant changes were found in the expression of proinflammatory cytokines and mediators after the intake of levothyroxine. The results of this study show that high thyroid hormone levels do not lead to an altered inflammatory profile. This provides evidence against a major role of the inflammatory system as mediator in the effect of thyroid hormone on the coagulation system. The mechanisms by which thyroid hormone may influence coagulation proteins remain to be elucidated.
amines [5–8]. Other studies have suggested a role for thyroid hormone receptor-mediated regulation of gene transcription at the hepatic and/or endothelial cell level, or both, causing an upregulation of coagulation factors [9, 10]. There is increasing evidence of a “cross-talk” between the coagulation and inflammatory systems. During the last years, inflammation has been accepted as a possible mechanism through which different risk factors trigger thrombus formation [11, 12]. Previous studies have investigated the relationship between the inflammatory and thyroid system, however, the results are contradictory and the interpretation was often impeded by existing concomitant diseases [13– 15]. Therefore, the aim of this study was to assess whether the induction of pronounced thyroid hormone excess by supraphysiological doses of levothyroxine leads to the upregulation of inflammation-related genes in healthy volunteers.
Stuijver DJF et al. Hyperthyroidism and Inflammation … Horm Metab Res 2014; 46: 789–793
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The Effect of Levothyroxine on Expression of Inflammation-Related Genes in Healthy Subjects: A Controlled Randomized Crossover Study
790 Endocrine Care
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Table 1 Characteristics of participants.
Study design The effects of thyroid hormone excess on expression of inflammation-related genes were studied in a single blinded randomized crossover design. The study design and procedures have previously been described in detail [16]. Briefly, participants received levothyroxine or no medication for 14 days, separating each exposure period by a wash-out of at least 28 days which was chosen on the basis of the half life of levothyroxine (7–10 days). The order of the 2 periods was determined by randomization. Fasting venous blood samples were drawn at baseline and day 14 of each exposure period, at the same time of day. For safety reasons, the original study was performed in 2 stages (Study A and B characterized by a difference in dose of levothyroxine that was administered). The current analyses only apply to Study B in which participants with a body weight below 80 kg received levothyroxine 0.45 mg per day, and levothyroxine 0.6 mg per day for those with a body weight of 80 kg and above.
Participants Healthy volunteers aged 18–40 years were recruited, regardless of sex or race, by local advertisements. Volunteers were excluded if they had any of the following: history of thyroid disease or venous thrombosis, ongoing medical (especially infectious) or psychiatric illnesses, regular use of prescription or nonprescription medications including oral contraceptive agents, illicit drug use or excessive alcohol use, surgery or hospitalization in the previous 3 months, or nontraditional sleep/wake habits (e. g., night shift work or frequent travel across time zones). Potentially eligible participants were invited for a first screening and blood sampling for routine laboratory tests (including blood count, inflammation parameters, renal, hepatic, and thyroid function) was performed. In case of any significant abnormalities, volunteers were excluded from further study participation, and referred to their general physician or a specialist, if indicated. All participants provided written informed consent. The study protocol was approved by the Medical Ethical Committee of the Slotervaart Hospital. The experiments comply with the current laws of the Netherlands. Participants were instructed to start drug intake on day 1 of either the first or second exposure period, depending on randomization. Levothyroxine was to be taken every morning, on awakening, 30 min prior to ingesting any food or drinks. Participants were advised to maintain their usual sleep-wake schedule, exercise, and dietary habits during the study.
Blood collection Fasting morning blood samples were collected in 4.5 ml plain tubes for assessment of thyroid function. Levels of free thyroxine (FT4), tri-iodothyronine (T3), thyroid stimulating hormone (TSH), thyroid-receptor antibodies (anti-TG) and thyroid peroxidase antibodies (anti-TPO) were assessed at the laboratory of the Slotervaart Hospital Amsterdam on the day of blood sampling, using commercially available assays (ADVIA Centaur® immunoassay system, Siemens Healthcare Diagnostics, Marburg, Germany). Whole blood was collected in PAXgeneTM Blood RNA tubes and stored upright in − 70 °C, after a minimum of 24 h and a maximum of 72 h storage at room temperature followed by 24 h at − 20 °C before transferring to − 70 °C freezer (according to pro-
Participants (n = 12) Age, years, mean (range) Male, n ( %) Body mass index, kg/m2, mean (range) Leukocytes, 109/l, mean (range) C-Reactive protein (CRP), mg/l, mean (range) Systolic blood pressure, mm Hg, mean (range) Diastolic blood pressure, mm Hg, mean (range)
29 (26–40) 6 (50) 23.3 (21.1–26.2) 5.5 (4.0–8.4) 2.7 (2.0–9.7) 117.3 (99.0–130.0) 72.3 (61.0–83.0)
tocol of the manufacturer). Isolation and purification of intracellular RNA from the PAXgeneTM Blood RNA tubes (4.8 × 106–1.1 × 107 leukocytes/ml) was performed using a PAXgene Blood RNA Kit (QIAGEN GmbH for PreAnalytiX, Hombrechtikon, Switzerland). Multiplex Ligation Probe Amplification (MLPA kit p009; MRCHolland, Amsterdam, the Netherlands) was performed with RNA in a concentration of 40–60 ng RNA/μl. With the MLPA assay, 40 genes can be determined simultaneously using 40 different probes. These genes comprise of interleukins, oncogenes and transcription factors/inhibitors, various intracellular enzymes and chemokines [17, 18]. In line with the manufacturer’s instruction for the application of the MLPA kit in blood cells, beta-2-microglobulin (B2M) was used as a house keeping (reference) gene. The reason is that previous studies have shown that the expression of the B2M gene was similar in control cells and in cells after exposure to IL-α. The expression of the B2M gene was set at 1.0 (i. e., 100 %) to which changes in gene expression were compared [17–19].
Statistical analysis Statistical analysis was performed using SPSS software, version 16.0 (SPSS Inc, Chicago, IL, USA). The general characteristics of the participants are reported as means and ranges. For parameters of thyroid function, we calculated median levels with their 95 % confidence intervals (95 % CI) at baseline and day 14 of each exposure period. We compared baseline and day 14 levels of each expressed gene between the 2 exposure periods with the Wilcoxon signed ranks test. We calculated relative changes per gene for each individual by subtracting the baseline value from the day 14 value, dividing it by the baseline value and multiplying the result by 100 %. We calculated the medians (95 % CI) of these individual relative changes, and performed betweenexposure comparisons using the Wilcoxon signed ranks test.
Results
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We enrolled 12 participants, 6 men and 6 women, with a mean ▶ Table 1). Three participants had age of 29 (range 26–40) years (● a body weight ≥ 80 kg. Levels of FT4 and T3 markedly increased (median FT4 40.0 pmol/l, T3 3.80 nmol/l), and TSH levels decreased after levothyroxine exposure (median TSH 0.02 mIU/l), whereas these values remained within the normal reference range during the ▶ Table 2). control period (● Median baseline values of the inflammatory markers were simi▶ Table 2 shows the change in expreslar for both study periods. ● sion of inflammation-related genes. Compared with the control situation no significant changes were found for any of the inflammation-related genes. Remarkably, although not statistically
Stuijver DJF et al. Hyperthyroidism and Inflammation … Horm Metab Res 2014; 46: 789–793
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Methods
Endocrine Care 791
Table 2 Parameters of thyroid function and inflammation related genes. No medication
Levothyroxine
p-values for between
Baseline
t = 14
Change ( %)
Baseline
t = 14
Change ( %)
Median
Median
Median
Median
Median
Median
(iq range)
(iq range)
(iq range)
(iq range)
(iq range)
(iq range)
0.0 ( − 6.67; 8.17) 2.78 ( − 4.87; 30.95) 7.77 ( − 30.02; 29.9)
14.5# (14.0; 16.5) 2.35 (2.13; 2.60) 1.86 (1.48; 3.22)
40 (36.75; 47.75) 3.8 (3.33; 4.08) 0.02 (0.02; 0.03)
185.71 (133.75; 216.57) 58.01 (46.88; 86.11) − 98.86 ( − 99.3; − 98.43)
− 2.91 ( − 16.72; 16.57) − 3.81 ( − 17.03; 4.77) 0.00 ( − 40.0; 37.5) 0.00 (0.00; 100.0) − 5.56 ( − 36.35; 14.04) − 9.17 ( − 28.38; 21.71) − 40.0 ( − 61.36; 16.96) − 4.02 ( − 20.16; 4.61) − 16.25 ( − 25.11; 8.97) 0.00 ( − 43.75; 37.50) 0.00 ( − 54.17; 87.50) − 5.28 ( − 25.23; 14.34) − 22.5 ( − 45.83; − 3.13) − 11.11 ( − 26.81; 15.44) 0.00 ( − 55.36; 25.0) − 11.25 ( − 24.31; − 1.92) 4.0 ( − 25.78; 20.0) − 17.5 ( − 20.8; 31.30) − 18.42 ( − 25.60; 8.25) − 7.86 ( − 16.5; 16.51) − 5.95 ( − 29.67; 9.95) − 5.88 ( − 26.98; 4.17) − 17.62 ( − 23.06; 22.02) − 5.0 ( − 29.64; 12.5)
0.515 (0.32; 0.68) 0.495 (0.32; 0.60) 0.03 (0.02; 0.04) 0.01 (0.01; 0.01) 0.115 (0.08; 0.17) 0.225 (0.14; 0.44) 0.045 (0.03; 0.08) 0.545 (0.40; 0.63) 0.155 (0.11; 0.18) 0.015 (0.01; 0.02) 0.045 (0.03; 0.06) 0.615 (0.49; 0.83) 0.03 (0.02; 0.05) 0.26 (0.17; 0.33) 0.35 (0.02; 0.05) 0.750 (0.05; 0.09) 0.15 (0.07; 0.23) 0.545 (0.29; 0.89) 0.215 (0.16; 0.25) 0.49 (0.30; 0.56) 0.50 (0.33; 0.58) 0.12 (0.08; 0.15) 1.16 (0.80; 1.40) 0.07 (0.05; 0.10)
0.515 (0.26; 0.69) 0.4150 (0.20; 0.57) 0.03 (0.02; 0.04) 0.01 (0.01; 0.02) 0.075 (0.06; 0.13) 0.230 (0.14; 0.39) 0.040 (0.03; 0.06) 0.435 (0.21; 0.61) 0.14 (0.07; 0.20) 0.02 (0.01; 0.02) 0.045 (0.02; 0.06) 0.535 (0.31; 0.84) 0.02 (0.02; 0.03) 0.24 (0.11; 0.29) 0.25 (0.02; 0.06) 0.07 (0.04; 0.09) 0.12 (0.04; 0.24) 0.405 (0.20; 0.82) 0.15 (0.08; 0.21) 0.415 (0.20; 0.60) 0.385 (0.21; 0.54) 0.11 (0.05; 0.15) 1.0 (0.59; 1.33) 0.65 (0.02; 0.10)
− 9.71 ( − 23.26; 38.71) − 4.25 ( − 21.88; 15.76) 0.00 ( − 18.75; 43.75) 0.00 (0.00; 100.0) − 11.21 ( − 44.51; 0.00) 0.31 ( − 23.37; 63.52) − 16.25 ( − 31.25; 37.50) − 4.79 ( − 35.33; 10.93) 2.17 ( − 31.96; 31.25) 0.00 (0.00; 100.0) 22.5 ( − 29.17; 50.0) 1.07 ( − 29.65; 16.66) − 16.67 ( − 50.0; 47.50) − 14.13 ( − 30.17; − 1.52) − 8.33 ( − 47.5; 68.75) − 6.25 ( − 33.13; 15.63) − 13.54 ( − 39.21; 23.36) − 3.45 ( − 32.96; 27.82) − 16.52 ( − 53.70; − 1.14) − 9.27 ( − 23.75; 24.39) − 14.94 ( − 44.10; 3.35) − 11.69 ( − 28.25; 11.54) − 3.02 ( − 45.78; 13.43) 0.00 ( − 62.5; 23.75)
Thyroid function fT4 (pmol/L) 15.0 14.0 (12.25; 15.0) (13.25; 15.0) T3 nmol/L 1.90 2.10 (1.70; 2.20) (1.93; 2.40) TSH mIU/L 1.64 1.65 (1.18; 3.22) (1.49; 3.07) mRNA expression from different genes NF- κBIα 0.565 0.575 (0.42; 0.76) (0.38; 0.71) NF- κB1 0.485 0.445 (0.31; 0.60) (0.27; 0.60) TNF 0.025 0.030 (0.02; 0.048) (0.02; 0.05) IL-18 0.010 0.010 (0.01; 0.01) (0.01; 0.02) 0.100 IL-1β 0.120 (0.10; 0.13) (0.08; 0.15) IL-1RN 0.260 0.270 (0.22; 0.35) (0.20; 0.37) IL-8 0.050 0.350 (0.03; 0.08) (0.02; 0.06) MYC 0.58 0.54 (0.37; 0.79) (0.33; 0.68) ScyA4 0.17 0.16 (0.16; 0.24) (0.11; 0.24) ScyA3 0.02 0.015 (0.01; 0.02) (0.01; 0.02) NF- κB2 0.055 0.055 (0.04; 0.09) (0.04; 0.09) SerpinB9 0.685 0.655 (0.46; 0.92) (0.45; 0.87) PDGFb 0.04 0.035 (0.03; 0.07) (0.01; 0.06) PARN 0.295 0.24 (0.20; 0.36) (0.19; 0.34) THBS1 0.04 0.045 (0.03; 0.06) (0.01; 0.07) LTα 0.095 0.075 (0.05; 0.11) (0.05; 0.10) CDKN1a 0.175 0.18 (0.07; 0.24) (0.08; 0.22) Tnfrsf1a 0.595 0.490 (0.40; 0.74) (0.38; 0.74) BMI1 0.205 0.170 (0.14; 0.27) (0.14; 0.26) MIF 0.465 0.485 (0.37; 0.61) (0.30; 0.67) PDE4B 0.4850 0.505 (0.39; 0.65) (0.33; 0.64) PTPN1 0.14 0.135 (0.09; 0.18) (0.08; 0.15) PTP4A2 1.105 0.98 (0.94; 1.33) (0.79; 1.31) GSTP1 0.07 0.07 (0.05; 0.10) (0.04; 0.10)
t = 14
change
< 0.01
< 0.01
< 0.01
< 0.01
< 0.01
< 0.01
0.27
0.75
0.39
0.75
0.83
0.61
0.32
0.53
0.43
0.64
0.94
0.39
0.78
0.13
0.48
0.75
0.19
0.70
0.41
0.38
0.28
0.75
0.43
0.81
0.18
0.33
0.18
0.58
0.32
0.56
0.24
0.79
0.56
0.58
0.53
0.70
0.25
0.27
0.24
0.58
0.182
0.35
0.285
0.72
0.58
0.94
0.36
0.75
#
p < 0.05 levothyroxine vs. no medication (baseline) Wilcoxon signed rank test; FT4 indicates free thyroxine; T3, tri-iodothyronine; TSH, thyroid stimulating hormone (thyro-
tropin); mRNA, messengerRNA; NF- κBIα, nuclear factor of kappa light polypeptide gene enhancer in B-cells inhibitor, alpha; NF- κB1, nuclear factor of kappa light polypeptide gene enhancer in B-cells 1; TNF, Tumor necrosis factor; IL-18, interleukin 18; IL-1β, interleukin 1, beta; IL1RN, interleukin 1 receptor antagonist; IL-8, interleukin 8; MYC, myelocytomatose viral oncogen; ScyA4, Small inducible cytokine A4; ScyA3, small inducible cytokine A3; NF- κB2, nuclear factor of kappa light polypeptide gene enhancer in B-cells 2; SerpinB9, serine proteinase inhibitor of the ovalbumin like B clade of serpins; PDGFb, Platelet-derived growth factor subunit B; PARN, Poly(A)-specific ribonuclease; THBS1, thrombospondin I; LTA, lymphotoxin alpha; CDKN1a, cyclin-dependent kinase inhibitor 1; Tnfrsf1a, Tumor necrosis factor receptor superfamily member 1A; BMI1, polycomb ring finger oncogene; MIF, Macrophage migration inhibitory factor; PDE4B, phosphodiesterase 4B; PTPN1, protein tyrosine phosphatase nonreceptor type1; PTP4A2, protein tyrosine phosphatase type 4A 2; GSTP1, Glutathione S-transferase P. Data are presented as medians (95 % confidence intervals)
Stuijver DJF et al. Hyperthyroidism and Inflammation … Horm Metab Res 2014; 46: 789–793
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group comparison Parameter
792 Endocrine Care
Discussion
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Based on our data we conclude that supraphysiological serum levels of FT4 do not lead to an upregulation of proinflammatory cytokines and mediators in healthy volunteers, as measured by the sensitive Multiplex Ligation Probe Amplification assay. Previous studies have shown contradictory results for the relationship between thyroid hormones and inflammatory system. Several studies have demonstrated raised serum cytokines in thyrotoxic patients in comparison to healthy controls, but disentangling the contribution of the elevated thyroid hormones from that of confounding factors such as autoimmune inflammation present in Graves’ disease was not possible due to the study design [14]. Also, discrepancies can be the result of variations in the population studied. Two studies investigated the relationship between free triiodothyronine (FT3) and proinflammatory cytokines in either peritoneal dialysis patients or in patients with heart failure and compared to healthy controls. Both studies reported that low FT3 levels were linked to an enhanced inflammatory status [13, 20]. It was proposed that the increased production of different cytokines most likely originated from bone osteoblasts, although bone markers did not correlate with acute changes in thyroid hormone status after antithyroid therapy [15]. As several studies have demonstrated a tight interplay between the coagulation and inflammatory system, different risk factors might trigger thrombus formation in veins via the inflammatory system [11]. However, the question whichever comes first, inflammation or thrombus formation, is frequently brought up. It is known that the procoagulant thrombin is capable of stimulating multiple inflammatory pathways, and, inflammatory cytokines, such as interleukin (IL)-6 and IL-8 are capable of activating coagulation. One study found that elevated plasma levels of inflammatory cytokines were associated with VTE [21]. The authors suggest that as these levels of inflammation markers did not differ in patients with recent VTE compared to those with more remote VTE, it is possible that the inflammatory state precedes the VTE, although this was not directly established. Two other studies, however, reported the inflammation markers measured at the time of diagnoses not to be different several days later, possibly indicating that inflammation is a consequence rather than a cause of DVT [22, 23]. Despite these uncertainties surrounding the inflammation-coagulation cross-talk, we conclude that, although thyroid hormone excess has repeatedly been proven to result in a procoagulant state, it appears not to do so by an upregulation of inflammatory cytokines. A limitation of our study is the relatively small sample size, and thus we cannot exclude that modest changes went undetected due to the small number of participants in this study. However, changes in levels of fibrinogen, von Willebrand factor, coagulation factors VIII, IX and X, and plasminogen activator inhibitor-1 were easily detectable in the same patients [16]. Also, the treatment time might not be long enough to induce changes to the inflammatory system. Finally, it is known that messengerRNA levels of inflammation related genes do not always precisely reflect amounts of proteins that are produced due to post-transcriptional regulation [18]. For that reason, extrapolations of messengerRNA levels to protein levels for individual genes
should be interpreted with caution. In this study, however, we did not measure plasma protein levels of inflammatory markers after the intake of levothyroxine or no medication. In conclusion, the results of this study show that thyroid hormone excess does not lead to an altered inflammatory profile, which provides evidence against a major role of the inflammatory system as mediator in the effect of thyroid hormone on coagulation. The mechanisms by which thyroid hormone may influence coagulation proteins remain to be elucidated.
Conflict of Interest
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The authors declare that they have no conflicts of interest in the authorship or publication of this contribution. Affiliations Department of Internal Medicine, Slotervaart Hospital, Amsterdam, The Netherlands 2 Department of Vascular Medicine, Academic Medical Centre, Amsterdam, The Netherlands 3 Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands 4 Department of Endocrinology and Metabolism, Leiden University Medical Centre, Leiden, The Netherlands 5 Centre for Experimental and Molecular Medicine, Academic Medical Centre, Amsterdam, The Netherlands 6 Thrombosis and Haemostasis Research Centre, Leiden University Medical Centre, Leiden, The Netherlands 7 Einthoven Laboratory for Experimental Vascular Medicine, Leiden University Medical Centre, Leiden, The Netherlands 1
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Authors
D. J. F. Stuijver1, 2, L. P. B. Elbers1, 2, B. van Zaane1, 2, O. M. Dekkers3, 4, C. A. Spek5, V. E. A. Gerdes1, 2, P. H. Reitsma6, 7, D. P. M. Brandjes1
Affiliations
Affiliation addresses are listed at the end of the article
Key words ▶ hyperthyroidism ● ▶ inflammation ● ▶ coagulation ● ▶ venous thrombosis ●
Abstract
received 26.11.2013 accepted 17.02.2014 Bibliography DOI http://dx.doi.org/ 10.1055/s-0034-1370975 Published online: April 1, 2014 Horm Metab Res 2014; 46: 789–793 © Georg Thieme Verlag KG Stuttgart · New York ISSN 0018-5043 Correspondence L. P. B. Elbers Department of Internal Medicine Slotervaart Hospital Louwesweg 6 1066 EC Amsterdam The Netherlands Tel.: + 31/20/5125 194 Fax: + 31/20/5124 783 [email protected]
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An excess of thyroid hormone leads to a prothrombotic state; however, the underlying pathophysiological mechanisms remain unknown. As evidence points towards an extensive “crosstalk” between the inflammatory and coagulation cascade, inflammation has been claimed as a possible mechanism through which different risk factors trigger venous thrombus formation. We aimed to study changes in expression of inflammation-related genes of the leukocyte RNA expression profile in healthy subjects in response to supraphysiological doses of levothyroxine. In a randomized single-blinded crossover design, 12 healthy volunteers (aged 18–40 years) received levothyroxine and no medication, both for 14 days with a wash-out period of at least 28 days between the periods. Blood was sampled at base-
Introduction
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Since the beginning of the past century, case reports have suggested a link between thyroid dysfunction and haemostatic abnormalities [1, 2]. From then onwards several studies have been performed to further elucidate this relationship. An excess of thyroid hormone is thought to induce a prothrombotic state, which led to the hypothesis that hyperthyroidism is a risk factor for venous thrombosis [3]. Indeed, high levels of free thyroxine (FT4) are associated with an increased risk of venous thrombosis, whereas a reduced risk was found for lower levels of FT4 [4]. The underlying pathophysiological mechanisms by which thyroid hormones may influence coagulation remain ill-defined. Several mechanisms have been suggested to underlie this relation including autoimmunity, indirect effects of endothelial dysfunction and atherosclerosis, and increased peripheral sensitivity to catechol-
line and day 14 of each study period. MRNA was isolated from whole blood and used for multiplex ligation-dependent probe amplification to study the expression of inflammation-related genes. Compared to the control situation no significant changes were found in the expression of proinflammatory cytokines and mediators after the intake of levothyroxine. The results of this study show that high thyroid hormone levels do not lead to an altered inflammatory profile. This provides evidence against a major role of the inflammatory system as mediator in the effect of thyroid hormone on the coagulation system. The mechanisms by which thyroid hormone may influence coagulation proteins remain to be elucidated.
amines [5–8]. Other studies have suggested a role for thyroid hormone receptor-mediated regulation of gene transcription at the hepatic and/or endothelial cell level, or both, causing an upregulation of coagulation factors [9, 10]. There is increasing evidence of a “cross-talk” between the coagulation and inflammatory systems. During the last years, inflammation has been accepted as a possible mechanism through which different risk factors trigger thrombus formation [11, 12]. Previous studies have investigated the relationship between the inflammatory and thyroid system, however, the results are contradictory and the interpretation was often impeded by existing concomitant diseases [13– 15]. Therefore, the aim of this study was to assess whether the induction of pronounced thyroid hormone excess by supraphysiological doses of levothyroxine leads to the upregulation of inflammation-related genes in healthy volunteers.
Stuijver DJF et al. Hyperthyroidism and Inflammation … Horm Metab Res 2014; 46: 789–793
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The Effect of Levothyroxine on Expression of Inflammation-Related Genes in Healthy Subjects: A Controlled Randomized Crossover Study
790 Endocrine Care
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Table 1 Characteristics of participants.
Study design The effects of thyroid hormone excess on expression of inflammation-related genes were studied in a single blinded randomized crossover design. The study design and procedures have previously been described in detail [16]. Briefly, participants received levothyroxine or no medication for 14 days, separating each exposure period by a wash-out of at least 28 days which was chosen on the basis of the half life of levothyroxine (7–10 days). The order of the 2 periods was determined by randomization. Fasting venous blood samples were drawn at baseline and day 14 of each exposure period, at the same time of day. For safety reasons, the original study was performed in 2 stages (Study A and B characterized by a difference in dose of levothyroxine that was administered). The current analyses only apply to Study B in which participants with a body weight below 80 kg received levothyroxine 0.45 mg per day, and levothyroxine 0.6 mg per day for those with a body weight of 80 kg and above.
Participants Healthy volunteers aged 18–40 years were recruited, regardless of sex or race, by local advertisements. Volunteers were excluded if they had any of the following: history of thyroid disease or venous thrombosis, ongoing medical (especially infectious) or psychiatric illnesses, regular use of prescription or nonprescription medications including oral contraceptive agents, illicit drug use or excessive alcohol use, surgery or hospitalization in the previous 3 months, or nontraditional sleep/wake habits (e. g., night shift work or frequent travel across time zones). Potentially eligible participants were invited for a first screening and blood sampling for routine laboratory tests (including blood count, inflammation parameters, renal, hepatic, and thyroid function) was performed. In case of any significant abnormalities, volunteers were excluded from further study participation, and referred to their general physician or a specialist, if indicated. All participants provided written informed consent. The study protocol was approved by the Medical Ethical Committee of the Slotervaart Hospital. The experiments comply with the current laws of the Netherlands. Participants were instructed to start drug intake on day 1 of either the first or second exposure period, depending on randomization. Levothyroxine was to be taken every morning, on awakening, 30 min prior to ingesting any food or drinks. Participants were advised to maintain their usual sleep-wake schedule, exercise, and dietary habits during the study.
Blood collection Fasting morning blood samples were collected in 4.5 ml plain tubes for assessment of thyroid function. Levels of free thyroxine (FT4), tri-iodothyronine (T3), thyroid stimulating hormone (TSH), thyroid-receptor antibodies (anti-TG) and thyroid peroxidase antibodies (anti-TPO) were assessed at the laboratory of the Slotervaart Hospital Amsterdam on the day of blood sampling, using commercially available assays (ADVIA Centaur® immunoassay system, Siemens Healthcare Diagnostics, Marburg, Germany). Whole blood was collected in PAXgeneTM Blood RNA tubes and stored upright in − 70 °C, after a minimum of 24 h and a maximum of 72 h storage at room temperature followed by 24 h at − 20 °C before transferring to − 70 °C freezer (according to pro-
Participants (n = 12) Age, years, mean (range) Male, n ( %) Body mass index, kg/m2, mean (range) Leukocytes, 109/l, mean (range) C-Reactive protein (CRP), mg/l, mean (range) Systolic blood pressure, mm Hg, mean (range) Diastolic blood pressure, mm Hg, mean (range)
29 (26–40) 6 (50) 23.3 (21.1–26.2) 5.5 (4.0–8.4) 2.7 (2.0–9.7) 117.3 (99.0–130.0) 72.3 (61.0–83.0)
tocol of the manufacturer). Isolation and purification of intracellular RNA from the PAXgeneTM Blood RNA tubes (4.8 × 106–1.1 × 107 leukocytes/ml) was performed using a PAXgene Blood RNA Kit (QIAGEN GmbH for PreAnalytiX, Hombrechtikon, Switzerland). Multiplex Ligation Probe Amplification (MLPA kit p009; MRCHolland, Amsterdam, the Netherlands) was performed with RNA in a concentration of 40–60 ng RNA/μl. With the MLPA assay, 40 genes can be determined simultaneously using 40 different probes. These genes comprise of interleukins, oncogenes and transcription factors/inhibitors, various intracellular enzymes and chemokines [17, 18]. In line with the manufacturer’s instruction for the application of the MLPA kit in blood cells, beta-2-microglobulin (B2M) was used as a house keeping (reference) gene. The reason is that previous studies have shown that the expression of the B2M gene was similar in control cells and in cells after exposure to IL-α. The expression of the B2M gene was set at 1.0 (i. e., 100 %) to which changes in gene expression were compared [17–19].
Statistical analysis Statistical analysis was performed using SPSS software, version 16.0 (SPSS Inc, Chicago, IL, USA). The general characteristics of the participants are reported as means and ranges. For parameters of thyroid function, we calculated median levels with their 95 % confidence intervals (95 % CI) at baseline and day 14 of each exposure period. We compared baseline and day 14 levels of each expressed gene between the 2 exposure periods with the Wilcoxon signed ranks test. We calculated relative changes per gene for each individual by subtracting the baseline value from the day 14 value, dividing it by the baseline value and multiplying the result by 100 %. We calculated the medians (95 % CI) of these individual relative changes, and performed betweenexposure comparisons using the Wilcoxon signed ranks test.
Results
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We enrolled 12 participants, 6 men and 6 women, with a mean ▶ Table 1). Three participants had age of 29 (range 26–40) years (● a body weight ≥ 80 kg. Levels of FT4 and T3 markedly increased (median FT4 40.0 pmol/l, T3 3.80 nmol/l), and TSH levels decreased after levothyroxine exposure (median TSH 0.02 mIU/l), whereas these values remained within the normal reference range during the ▶ Table 2). control period (● Median baseline values of the inflammatory markers were simi▶ Table 2 shows the change in expreslar for both study periods. ● sion of inflammation-related genes. Compared with the control situation no significant changes were found for any of the inflammation-related genes. Remarkably, although not statistically
Stuijver DJF et al. Hyperthyroidism and Inflammation … Horm Metab Res 2014; 46: 789–793
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Methods
Endocrine Care 791
Table 2 Parameters of thyroid function and inflammation related genes. No medication
Levothyroxine
p-values for between
Baseline
t = 14
Change ( %)
Baseline
t = 14
Change ( %)
Median
Median
Median
Median
Median
Median
(iq range)
(iq range)
(iq range)
(iq range)
(iq range)
(iq range)
0.0 ( − 6.67; 8.17) 2.78 ( − 4.87; 30.95) 7.77 ( − 30.02; 29.9)
14.5# (14.0; 16.5) 2.35 (2.13; 2.60) 1.86 (1.48; 3.22)
40 (36.75; 47.75) 3.8 (3.33; 4.08) 0.02 (0.02; 0.03)
185.71 (133.75; 216.57) 58.01 (46.88; 86.11) − 98.86 ( − 99.3; − 98.43)
− 2.91 ( − 16.72; 16.57) − 3.81 ( − 17.03; 4.77) 0.00 ( − 40.0; 37.5) 0.00 (0.00; 100.0) − 5.56 ( − 36.35; 14.04) − 9.17 ( − 28.38; 21.71) − 40.0 ( − 61.36; 16.96) − 4.02 ( − 20.16; 4.61) − 16.25 ( − 25.11; 8.97) 0.00 ( − 43.75; 37.50) 0.00 ( − 54.17; 87.50) − 5.28 ( − 25.23; 14.34) − 22.5 ( − 45.83; − 3.13) − 11.11 ( − 26.81; 15.44) 0.00 ( − 55.36; 25.0) − 11.25 ( − 24.31; − 1.92) 4.0 ( − 25.78; 20.0) − 17.5 ( − 20.8; 31.30) − 18.42 ( − 25.60; 8.25) − 7.86 ( − 16.5; 16.51) − 5.95 ( − 29.67; 9.95) − 5.88 ( − 26.98; 4.17) − 17.62 ( − 23.06; 22.02) − 5.0 ( − 29.64; 12.5)
0.515 (0.32; 0.68) 0.495 (0.32; 0.60) 0.03 (0.02; 0.04) 0.01 (0.01; 0.01) 0.115 (0.08; 0.17) 0.225 (0.14; 0.44) 0.045 (0.03; 0.08) 0.545 (0.40; 0.63) 0.155 (0.11; 0.18) 0.015 (0.01; 0.02) 0.045 (0.03; 0.06) 0.615 (0.49; 0.83) 0.03 (0.02; 0.05) 0.26 (0.17; 0.33) 0.35 (0.02; 0.05) 0.750 (0.05; 0.09) 0.15 (0.07; 0.23) 0.545 (0.29; 0.89) 0.215 (0.16; 0.25) 0.49 (0.30; 0.56) 0.50 (0.33; 0.58) 0.12 (0.08; 0.15) 1.16 (0.80; 1.40) 0.07 (0.05; 0.10)
0.515 (0.26; 0.69) 0.4150 (0.20; 0.57) 0.03 (0.02; 0.04) 0.01 (0.01; 0.02) 0.075 (0.06; 0.13) 0.230 (0.14; 0.39) 0.040 (0.03; 0.06) 0.435 (0.21; 0.61) 0.14 (0.07; 0.20) 0.02 (0.01; 0.02) 0.045 (0.02; 0.06) 0.535 (0.31; 0.84) 0.02 (0.02; 0.03) 0.24 (0.11; 0.29) 0.25 (0.02; 0.06) 0.07 (0.04; 0.09) 0.12 (0.04; 0.24) 0.405 (0.20; 0.82) 0.15 (0.08; 0.21) 0.415 (0.20; 0.60) 0.385 (0.21; 0.54) 0.11 (0.05; 0.15) 1.0 (0.59; 1.33) 0.65 (0.02; 0.10)
− 9.71 ( − 23.26; 38.71) − 4.25 ( − 21.88; 15.76) 0.00 ( − 18.75; 43.75) 0.00 (0.00; 100.0) − 11.21 ( − 44.51; 0.00) 0.31 ( − 23.37; 63.52) − 16.25 ( − 31.25; 37.50) − 4.79 ( − 35.33; 10.93) 2.17 ( − 31.96; 31.25) 0.00 (0.00; 100.0) 22.5 ( − 29.17; 50.0) 1.07 ( − 29.65; 16.66) − 16.67 ( − 50.0; 47.50) − 14.13 ( − 30.17; − 1.52) − 8.33 ( − 47.5; 68.75) − 6.25 ( − 33.13; 15.63) − 13.54 ( − 39.21; 23.36) − 3.45 ( − 32.96; 27.82) − 16.52 ( − 53.70; − 1.14) − 9.27 ( − 23.75; 24.39) − 14.94 ( − 44.10; 3.35) − 11.69 ( − 28.25; 11.54) − 3.02 ( − 45.78; 13.43) 0.00 ( − 62.5; 23.75)
Thyroid function fT4 (pmol/L) 15.0 14.0 (12.25; 15.0) (13.25; 15.0) T3 nmol/L 1.90 2.10 (1.70; 2.20) (1.93; 2.40) TSH mIU/L 1.64 1.65 (1.18; 3.22) (1.49; 3.07) mRNA expression from different genes NF- κBIα 0.565 0.575 (0.42; 0.76) (0.38; 0.71) NF- κB1 0.485 0.445 (0.31; 0.60) (0.27; 0.60) TNF 0.025 0.030 (0.02; 0.048) (0.02; 0.05) IL-18 0.010 0.010 (0.01; 0.01) (0.01; 0.02) 0.100 IL-1β 0.120 (0.10; 0.13) (0.08; 0.15) IL-1RN 0.260 0.270 (0.22; 0.35) (0.20; 0.37) IL-8 0.050 0.350 (0.03; 0.08) (0.02; 0.06) MYC 0.58 0.54 (0.37; 0.79) (0.33; 0.68) ScyA4 0.17 0.16 (0.16; 0.24) (0.11; 0.24) ScyA3 0.02 0.015 (0.01; 0.02) (0.01; 0.02) NF- κB2 0.055 0.055 (0.04; 0.09) (0.04; 0.09) SerpinB9 0.685 0.655 (0.46; 0.92) (0.45; 0.87) PDGFb 0.04 0.035 (0.03; 0.07) (0.01; 0.06) PARN 0.295 0.24 (0.20; 0.36) (0.19; 0.34) THBS1 0.04 0.045 (0.03; 0.06) (0.01; 0.07) LTα 0.095 0.075 (0.05; 0.11) (0.05; 0.10) CDKN1a 0.175 0.18 (0.07; 0.24) (0.08; 0.22) Tnfrsf1a 0.595 0.490 (0.40; 0.74) (0.38; 0.74) BMI1 0.205 0.170 (0.14; 0.27) (0.14; 0.26) MIF 0.465 0.485 (0.37; 0.61) (0.30; 0.67) PDE4B 0.4850 0.505 (0.39; 0.65) (0.33; 0.64) PTPN1 0.14 0.135 (0.09; 0.18) (0.08; 0.15) PTP4A2 1.105 0.98 (0.94; 1.33) (0.79; 1.31) GSTP1 0.07 0.07 (0.05; 0.10) (0.04; 0.10)
t = 14
change
< 0.01
< 0.01
< 0.01
< 0.01
< 0.01
< 0.01
0.27
0.75
0.39
0.75
0.83
0.61
0.32
0.53
0.43
0.64
0.94
0.39
0.78
0.13
0.48
0.75
0.19
0.70
0.41
0.38
0.28
0.75
0.43
0.81
0.18
0.33
0.18
0.58
0.32
0.56
0.24
0.79
0.56
0.58
0.53
0.70
0.25
0.27
0.24
0.58
0.182
0.35
0.285
0.72
0.58
0.94
0.36
0.75
#
p < 0.05 levothyroxine vs. no medication (baseline) Wilcoxon signed rank test; FT4 indicates free thyroxine; T3, tri-iodothyronine; TSH, thyroid stimulating hormone (thyro-
tropin); mRNA, messengerRNA; NF- κBIα, nuclear factor of kappa light polypeptide gene enhancer in B-cells inhibitor, alpha; NF- κB1, nuclear factor of kappa light polypeptide gene enhancer in B-cells 1; TNF, Tumor necrosis factor; IL-18, interleukin 18; IL-1β, interleukin 1, beta; IL1RN, interleukin 1 receptor antagonist; IL-8, interleukin 8; MYC, myelocytomatose viral oncogen; ScyA4, Small inducible cytokine A4; ScyA3, small inducible cytokine A3; NF- κB2, nuclear factor of kappa light polypeptide gene enhancer in B-cells 2; SerpinB9, serine proteinase inhibitor of the ovalbumin like B clade of serpins; PDGFb, Platelet-derived growth factor subunit B; PARN, Poly(A)-specific ribonuclease; THBS1, thrombospondin I; LTA, lymphotoxin alpha; CDKN1a, cyclin-dependent kinase inhibitor 1; Tnfrsf1a, Tumor necrosis factor receptor superfamily member 1A; BMI1, polycomb ring finger oncogene; MIF, Macrophage migration inhibitory factor; PDE4B, phosphodiesterase 4B; PTPN1, protein tyrosine phosphatase nonreceptor type1; PTP4A2, protein tyrosine phosphatase type 4A 2; GSTP1, Glutathione S-transferase P. Data are presented as medians (95 % confidence intervals)
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group comparison Parameter
792 Endocrine Care
Discussion
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Based on our data we conclude that supraphysiological serum levels of FT4 do not lead to an upregulation of proinflammatory cytokines and mediators in healthy volunteers, as measured by the sensitive Multiplex Ligation Probe Amplification assay. Previous studies have shown contradictory results for the relationship between thyroid hormones and inflammatory system. Several studies have demonstrated raised serum cytokines in thyrotoxic patients in comparison to healthy controls, but disentangling the contribution of the elevated thyroid hormones from that of confounding factors such as autoimmune inflammation present in Graves’ disease was not possible due to the study design [14]. Also, discrepancies can be the result of variations in the population studied. Two studies investigated the relationship between free triiodothyronine (FT3) and proinflammatory cytokines in either peritoneal dialysis patients or in patients with heart failure and compared to healthy controls. Both studies reported that low FT3 levels were linked to an enhanced inflammatory status [13, 20]. It was proposed that the increased production of different cytokines most likely originated from bone osteoblasts, although bone markers did not correlate with acute changes in thyroid hormone status after antithyroid therapy [15]. As several studies have demonstrated a tight interplay between the coagulation and inflammatory system, different risk factors might trigger thrombus formation in veins via the inflammatory system [11]. However, the question whichever comes first, inflammation or thrombus formation, is frequently brought up. It is known that the procoagulant thrombin is capable of stimulating multiple inflammatory pathways, and, inflammatory cytokines, such as interleukin (IL)-6 and IL-8 are capable of activating coagulation. One study found that elevated plasma levels of inflammatory cytokines were associated with VTE [21]. The authors suggest that as these levels of inflammation markers did not differ in patients with recent VTE compared to those with more remote VTE, it is possible that the inflammatory state precedes the VTE, although this was not directly established. Two other studies, however, reported the inflammation markers measured at the time of diagnoses not to be different several days later, possibly indicating that inflammation is a consequence rather than a cause of DVT [22, 23]. Despite these uncertainties surrounding the inflammation-coagulation cross-talk, we conclude that, although thyroid hormone excess has repeatedly been proven to result in a procoagulant state, it appears not to do so by an upregulation of inflammatory cytokines. A limitation of our study is the relatively small sample size, and thus we cannot exclude that modest changes went undetected due to the small number of participants in this study. However, changes in levels of fibrinogen, von Willebrand factor, coagulation factors VIII, IX and X, and plasminogen activator inhibitor-1 were easily detectable in the same patients [16]. Also, the treatment time might not be long enough to induce changes to the inflammatory system. Finally, it is known that messengerRNA levels of inflammation related genes do not always precisely reflect amounts of proteins that are produced due to post-transcriptional regulation [18]. For that reason, extrapolations of messengerRNA levels to protein levels for individual genes
should be interpreted with caution. In this study, however, we did not measure plasma protein levels of inflammatory markers after the intake of levothyroxine or no medication. In conclusion, the results of this study show that thyroid hormone excess does not lead to an altered inflammatory profile, which provides evidence against a major role of the inflammatory system as mediator in the effect of thyroid hormone on coagulation. The mechanisms by which thyroid hormone may influence coagulation proteins remain to be elucidated.
Conflict of Interest
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The authors declare that they have no conflicts of interest in the authorship or publication of this contribution. Affiliations Department of Internal Medicine, Slotervaart Hospital, Amsterdam, The Netherlands 2 Department of Vascular Medicine, Academic Medical Centre, Amsterdam, The Netherlands 3 Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands 4 Department of Endocrinology and Metabolism, Leiden University Medical Centre, Leiden, The Netherlands 5 Centre for Experimental and Molecular Medicine, Academic Medical Centre, Amsterdam, The Netherlands 6 Thrombosis and Haemostasis Research Centre, Leiden University Medical Centre, Leiden, The Netherlands 7 Einthoven Laboratory for Experimental Vascular Medicine, Leiden University Medical Centre, Leiden, The Netherlands 1
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