Thyroid and bone turnover markers in type 2 diabetes: results from the METAL study

in Endocrine Connections
Authors:
Yi Chen Institute and Department of Endocrinology and Metabolism, Shanghai Ninth People’s Hospital, Shanghai JiaoTong University School of Medicine, Shanghai, China

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Wen Zhang Institute and Department of Endocrinology and Metabolism, Shanghai Ninth People’s Hospital, Shanghai JiaoTong University School of Medicine, Shanghai, China

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Chi Chen Institute and Department of Endocrinology and Metabolism, Shanghai Ninth People’s Hospital, Shanghai JiaoTong University School of Medicine, Shanghai, China

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Yuying Wang Institute and Department of Endocrinology and Metabolism, Shanghai Ninth People’s Hospital, Shanghai JiaoTong University School of Medicine, Shanghai, China

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Ningjian Wang Institute and Department of Endocrinology and Metabolism, Shanghai Ninth People’s Hospital, Shanghai JiaoTong University School of Medicine, Shanghai, China

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Yingli Lu Institute and Department of Endocrinology and Metabolism, Shanghai Ninth People’s Hospital, Shanghai JiaoTong University School of Medicine, Shanghai, China

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https://orcid.org/0000-0002-5117-1614

Correspondence should be addressed to Y Chen or Y Lu: chenyi9h@126.com or luyl1615@sh9hospital.org.cn
DOI:
https://doi.org/10.1530/EC-21-0484
Volume/Issue:
Volume 11: Issue 3
Article ID:
e210484
Article Type:
Research Article
Online Publication Date:
31 Mar 2022
Copyright:
© The authors 2022
Collections:
Metabolic Syndrome and Diabetes
Open access

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Objective

We aimed to evaluate whether thyroid hormones, autoimmune and thyroid homeostasis status were related to bone turnover in type 2 diabetes.

Methods

The data were obtained from a cross-sectional study, the METAL study. In this study, 4209 participants (2059 men and 2150 postmenopausal women) with type 2 diabetes were enrolled. Thyroid function, thyroid antibodies and three bone turnover markers (BTMs), including a large N-mid fragment of osteocalcin (N-MID osteocalcin), β-C-terminal cross-linked telopeptides of type I collagen (β-CTX) and procollagen type I N-terminal propeptide (P1NP), were measured. Thyroid homeostasis parameters, including the sum activity of step-up deiodinases (SPINA-GD), thyroid secretory capacity (SPINA-GT), Jostel’s TSH index (TSHI) and the thyrotroph thyroid hormone resistance index (TTSI), were calculated. The associations of thyroid parameters with BTMs were analyzed using linear regression.

Results

Free and total triiodothyronine were positively associated with N-MID osteocalcin and P1NP in both sexes and positively associated with β-CTX in postmenopausal women. Thyroid-stimulating hormone was negatively associated with β-CTX in postmenopausal women, and free thyroxine was negatively associated with N-MID osteocalcin and P1NP in men. SPINA-GD was positively associated with N-MID osteocalcin and P1NP in both sexes. There was a positive relationship of SPINA-GT with β-CTX, a negative relationship of TTSI with β-CTX, and a negative relationship of TSHI with β-CTX and P1NP in postmenopausal women.

Conclusions

Among men and postmenopausal women with type 2 diabetes, significant associations were observed between N-MID osteocalcin, β-CTX and P1NP with thyroid function and thyroid homeostasis. Further prospective studies are warranted to understand the causal relationship and underlying mechanism.

Abstract

Objective

We aimed to evaluate whether thyroid hormones, autoimmune and thyroid homeostasis status were related to bone turnover in type 2 diabetes.

Methods

The data were obtained from a cross-sectional study, the METAL study. In this study, 4209 participants (2059 men and 2150 postmenopausal women) with type 2 diabetes were enrolled. Thyroid function, thyroid antibodies and three bone turnover markers (BTMs), including a large N-mid fragment of osteocalcin (N-MID osteocalcin), β-C-terminal cross-linked telopeptides of type I collagen (β-CTX) and procollagen type I N-terminal propeptide (P1NP), were measured. Thyroid homeostasis parameters, including the sum activity of step-up deiodinases (SPINA-GD), thyroid secretory capacity (SPINA-GT), Jostel’s TSH index (TSHI) and the thyrotroph thyroid hormone resistance index (TTSI), were calculated. The associations of thyroid parameters with BTMs were analyzed using linear regression.

Results

Free and total triiodothyronine were positively associated with N-MID osteocalcin and P1NP in both sexes and positively associated with β-CTX in postmenopausal women. Thyroid-stimulating hormone was negatively associated with β-CTX in postmenopausal women, and free thyroxine was negatively associated with N-MID osteocalcin and P1NP in men. SPINA-GD was positively associated with N-MID osteocalcin and P1NP in both sexes. There was a positive relationship of SPINA-GT with β-CTX, a negative relationship of TTSI with β-CTX, and a negative relationship of TSHI with β-CTX and P1NP in postmenopausal women.

Conclusions

Among men and postmenopausal women with type 2 diabetes, significant associations were observed between N-MID osteocalcin, β-CTX and P1NP with thyroid function and thyroid homeostasis. Further prospective studies are warranted to understand the causal relationship and underlying mechanism.

Keywords: bone turnover marker; thyroid hormone; thyroid homeostasis parameters; type 2 diabetes mellitus

Introduction

Type 2 diabetes mellitus (T2DM) is associated with an increased fracture risk (1, 2, 3), which has aroused great concern. One of the most commonly used indicators to assess fracture risk is the bone mineral density (BMD) estimated by dual energy X-ray absorptiometry (4). However, compared with controls, patients with T2DM have a higher BMD, which cannot explain the observed increased fracture risk (5). Thus, many studies have investigated bone turnover status in patients with T2DM.

Bone turnover status may be assessed by measuring biochemical markers and bone turnover markers (BTMs), which ideally reflect bone resorption and formation processes (1). Previous studies have indicated that BTMs of both bone formation and bone resorption are decreased in patients with diabetes (1, 6, 7), which suggested that a state of low bone turnover in diabetes mellitus may lead to increased fracture risk. The International Osteoporosis Foundation and the International Federation of Clinical Chemistry and Laboratory Medicine recommend that a marker of bone formation (serum procollagen type I N propeptide, s-P1NP) and a marker of bone resorption (serum C-terminal telopeptide of type I collagen, s-CTX) be used as reference analytes for BTMs (8). Osteocalcin (OC) is also used as a bone formation marker in clinical and research settings (8).

There has been growing interest in the effect of thyroid dysfunction and even mild or transient disturbances in thyroid status on bone physiology and pathology (9, 10, 11). Moreover, the hypothalamic–pituitary–thyroid axis also plays a key role in skeletal development, acquisition of peak bone mass and regulation of the bone turnover process (12).

To the best of our knowledge, there have been few reports on the relationship of BTMs with thyroid hormones (9), thyroid homeostasis parameters and thyroid antibodies in patients with T2DM. We hypothesized that thyroid hormones, thyroid autoimmune status, hypothalamic–pituitary–thyroid axis is involved in the regulation of bone formation and resorption process in T2DM. In this observational explorative study, we evaluated whether thyroid hormones, including thyroid-stimulating hormone (TSH), free and total thyroxine (FT4, TT4), free and total triiodothyronine (FT3, TT3), thyroid antibodies, including thyroid peroxidase antibody (TPOAb) and thyroglobulin antibody (TgAb), and four calculated thyroid homeostasis parameters, including the sum activity of step-up deiodinases (SPINA-GD), thyroid secretory capacity (SPINA-GT), Jostel’s TSH index (TSHI) and the thyrotroph thyroid hormone resistance index (TTSI), were related to three BTMs, including large N-mid fragment of OC (N-MID OC), β-CTX and P1NP, in a population with T2DM.

Methods

Study design and participants

The data of this study were obtained from a cross-sectional study, the METAL study (Environmental Pollutant Exposure and Metabolic Diseases in Shanghai, www.chictr.org.cn, ChiCTR1800017573) (13, 14), which was designed to investigate the association between exposure to heavy metals and diabetes complications in Chinese adults with diabetes in 2018. Participants were from the seven communities in Shanghai, China, and were randomly selected from half of the patients with T2DM in the registration platform of each community health care center (n  = 4937). We excluded participants who were missing laboratory results (n  = 8) or questionnaire data (n  = 116), missing BTMs (n  = 45), missing thyroid parameters (n  = 4), had a history of thyroid surgery or known thyroid dysfunction,that is, all potential users of drugs for thyroid dysfunction (n  = 274), had a history of glucocorticoid or amiodarone treatment (n  = 177), had an estimated glomerular filtration rate (eGFR) <30 mL/min/1.73 m2 (n  = 18) or were premenopausal women (n  = 86). Finally, 4209 participants (2059 men and 2150 postmenopausal women) were involved in this study.

All participants provided written informed consent before data collection. The study protocol was approved by the Ethics Committee of Shanghai Ninth People’s Hospital, Shanghai JiaoTong University School of Medicine. All procedures were in accordance with the ethical standards of the responsible committee on human experimentation (institutional and national) and with the 1975 Declaration of Helsinki, as revised in 2008.

Laboratory measurements

Fasting blood samples for laboratory assays were obtained by venipuncture from 07:00 to 10:00 h. Blood samples were stored at 2–8°C when collected and shipped to local central laboratories, which were certified by the College of American Pathologists), within 2–4 h of collection. On the day of blood sample collection, as soon as the blood samples arrived in the laboratory, serum separation and sample testing began.

Serum TSH, FT3, FT4, TT3, TT4, TPOAb and TgAb were measured by electrochemiluminescence (Roche, E601). The normal reference ranges for TSH, FT3, FT4, TT3, TT4, TPOAb and TgAb were 0.27–4.20 mIU/L, 3.10–6.80 pmol/L, 12.00–22.00 pmol/L, 1.30–3.10 nmol/L, 66.00–181.00 nmol/L, 0–34.00 U/mL and 0–115.00 U/mL, respectively. The interassay coefficients of variation were as follows: 8.33% (TSH), 8.33% (FT3), 8.33% (FT4), 8.33% (TT3), 6.67% (TT4), 10.00% (TPOAb) and 10.00% (TgAb). The intra-assay coefficients of variation were as follows: 6.25% (TSH), 6.25% (FT3), 6.25% (FT4), 6.25% (TT3), 5.00% (TT4), 7.50% (TPOAb) and 7.50% (TgAb).

BTMs, including N-MID OC, β-CTX and P1NP, were detected with a chemiluminescence method (Roche E602). The inter-assay coefficients of variation were as follows: 3.30% (P1NP), 1.81% (N-MID OC) and 7.60% (β-CTX). The intra-assay coefficients of variation were as follows: 3.0% (P1NP), 0.80% (N-MID OC) and 5.50% (β-CTX).

HbA1c was measured via HPLC (MQ-2000PT, Medconn, Shanghai, China). Creatinine (Cr) was measured by a Beckman Coulter AU 680 (Brea, USA). Serum 25(OH)D was measured using the chemiluminescence method (SIEMENS ADVIA Centaur XP, Siemens).

Clinical parameters

A questionnaire about sociodemographic characteristics, medical history, family history, and lifestyle factors was adopted during the interview. The same group of trained and experienced personnel in the SPECT-China study (Survey on Prevalence in East China for Metabolic Diseases and Risk Factors, ChiCTR-ECS-14005052, www.chictr.org.cn) (15, 16) conducted the interviews and clinical examinations, including measurements of weight, height and blood pressure, according to a standard protocol.

Current smoking was defined as having smoked at least 100 cigarettes in one’s lifetime and currently smoking cigarettes (17). Anti-thyroid antibody positivity (ATA+) was defined as serum TPOAb positivity (TPOAb+) (>34.00 U/mL) and/or TgAb positivity (TgAb+) (>115.00 U/mL).

Two structural parameters of thyroid homeostasis, SPINA-GD and SPINA-GT, and two pituitary thyrotropic function indices, TSHI and TTSI, were calculated using the following equations according to a previous study (18):
article image

BMI was calculated as weight in kilograms divided by height in meters squared. The eGFR was calculated according to the Chronic Kidney Disease Epidemiology Collaboration equation for ‘Asian origin’ (19).

Statistical analysis

Survey analyses were performed with IBM SPSS Statistics. All analyses were two-sided. A P-value <0.05 was taken to indicate a significant difference. Normally and non-normally distributed continuous variables were expressed as the mean ± s.d. and medians (interquartile range), respectively. Categorical variables are presented as percentages. Normally distributed continuous variables were compared using Student’s t-test. The Mann–Whitney U test was used for non-normally distributed continuous variables. The Pearson’s chi-square test was used for dichotomous variables. Associations of thyroid function, ATA+ and thyroid homeostasis parameters with three BTMs, including N-MID OC, β-CTX and P1NP, were analyzed using linear regression models with each measure as the outcome. N-MID OC, β-CTX and P1NP were ln-transformed for normal distribution before linear regression analysis. The regression models were adjusted for age, BMI, duration of diabetes, current smoking, concentration of HbA1c, 25(OH)D and Cr, and the use of metformin and thiazolidinediones. The results were expressed as B values and 95% CIs. Considering the significant sex differences in bone metabolism between men and women, all statistical analyses were performed separately for men and postmenopausal women.

Results

Clinical characteristics of the participants

This study recruited 4209 participants with T2DM, including 2059 men and 2150 postmenopausal women. The mean ages of men and postmenopausal women were 67.43 and 67.65 years old, respectively. Their median duration of diabetes was 8 years. There was no significant difference between men and postmenopausal women in the use of metformin or thiazolidinedione. Compared to postmenopausal women, men had higher levels of HbA1c, Cr, 25(OH)D, FT3, FT4 and SPINA-GT, lower levels of TSH, TT4, TTSI, TSHI and BTMs (N-MID OC, β-CTX and P1NP) and a lower prevalence of TPOAb+, TgAb+ and ATA+ (Table 1). In addition, compared to participants with ATA−, ATA+ participants had higher levels of TSH, SPINA-GD, TTSI, TSHI, N-MID OC, β-CTX and P1NP and lower levels of HbA1c, Cr, FT3, FT4 and SPINA-GT (Table 2).

Table 1

Characteristics of the study participants.
Characteristic Men Postmenopausal women P
n 2059 2150 -
Age (years) 67.43 ± 8.76 67.65 ± 7.71 0.399
Duration of diabetes (years) 8.00 (12.00) 8.00 (12.00) 0.605
HbA1c (%) 7.30 (1.60) 7.10 (1.50) <0.001
BMI (kg/m2) 25.01 ± 3.30 24.89 ± 3.79 0.255
Cr (μmol/L) 76.00 (20.00) 57.00 (15.00) <0.001
25(OH)D (nmol/L) 42.69 ± 14.68 38.93 ± 13.35 <0.001
Current smoking (%) 36.5 2.3 <0.001
Metformin in use (%) 38.2 38.7 0.728
Thiazolidinediones in use (%) 3.1 3.2 0.781
Thyroid-related parameters
 TSH (mIU/L) 2.32 (1.59) 2.76 (1.96) <0.001
 FT3 (pmol/L) 4.78 ± 0.59 4.50 ± 0.56 <0.001
 FT4 (pmol/L) 16.95 ± 2.28 16.58 ± 2.25 <0.001
 TT3 (nmol/L) 1.66 ± 0.30 1.64 ± 0.28 0.054
 TT4 (nmol/L) 98.94 ± 17.88 103.06 ± 17.47 <0.001
 TPOAb+ (%) 5.1 10.0 <0.001
 TgAb+ (%) 3.2 8.9 <0.001
 ATA+ (%) 6.2 14.2 <0.001
Thyroid homeostasis parameters
 SPINA-GD (nmol/s) 15.26 ± 3.23 15.42 ± 3.01 0.085
 SPINA-GT (pmol/s) 2.38 (1.05) 2.25 (1.05) <0.001
 TTSI (mIU/L) 179.75 (123.04) 207.83 (145.02) <0.001
 TSHI 3.13 ± 0.58 3.22 ± 0.59 <0.001
Bone turnover markers
 N-MID osteocalcin (ng/mL) 9.40 (4.30) 12.30 (6.03) <0.001
 β-CTX (ng/mL) 0.17 (0.11) 0.22 (0.12) <0.001
 P1NP (ng/mL) 34.53 (16.48) 44.53 (23.01) <0.001

Data were summarized as median (interquartile range) or mean ± s.d. for continuous variables or a proportion for categorical variables. Normally distributed continuous variables were compared using Student’s t-test. The Mann–Whitney U test and the Kruskal–Wallis test were used for non-normally distributed continuous variables. Pearson’s chi-square test was used for dichotomous variables. ATA+ was defined as the serum TPOAb+ (>34.00 U/mL) and/or TgAb+ (>115.00 U/mL).

ATA, anti-thyroid antibody; Cr, creatinine; eGFR, estimated glomerular filtration rate; FT3, free triiodothyronine; FT4, free thyroxine; N-MID osteocalcin, large N-mid fragment of osteocalcin; P1NP, procollagen type I N-terminal propeptide; SPINA-GT, thyroid’s secretory capacity; SPINA-GD, sum activity of peripheral deiodinases; TgAb, thyroglobulin antibody; TPOAb, thyroid peroxidase antibody; TSH, thyroid-stimulating hormone; TSHI, Jostel’s TSH index; TT3, total triiodothyronine; TT4, total thyroxin; TTSI, thyrotroph thyroid hormone resistance index; β-CTX, β-C-terminal cross-linked telopeptides of type I collagen.

Table 2

Characteristics of the study participants according to the presence of ATA positivity.
Characteristic ATA− ATA+ P
n 3777 432 -
Men/women (n) 1932/1845 127/305 -
Age (years) 67.55 ± 8.26 67.50 ± 8.10 0.923
HbA1c (%) 7.20 (1.60) 7.00 (1.50) 0.023
BMI (kg/m2) 24.94 ± 3.55 24.99 ± 3.60 0.820
Cr (μmol/L) 67.00 (23.00) 63.00 (20.75) <0.001
25(OH)D (nmol/L) 40.78 ± 14.19 40.72 ± 13.77 0.939
TSH (mIU/L) 2.48 (1.75) 3.04 (2.45) <0.001
FT3 (pmol/L) 4.65 ± 0.59 4.54 ± 0.59 <0.001
FT4 (pmol/L) 16.80 ± 2.22 16.42 ± 2.64 0.004
TT3 (nmol/L) 1.65 ± 0.29 1.65 ± 0.32 0.710
TT4 (nmol/L) 100.98 ± 17.63 101.59 ± 19.19 0.503
SPINA-GD (nmol/s) 15.29 ± 3.02 15.84 ± 3.86 0.004
SPINA-GT (pmol/s) 2.33 (1.06) 2.14 (1.06) <0.001
TTSI 189.29 (128.84) 223.19 (172.59) <0.001
TSHI 3.16 ± 0.58 3.30 ± 0.64 <0.001
N-MID osteocalcin (ng/mL) 10.70 (5.50) 11.70 (5.90) <0.001
β-CTX (ng/mL) 0.19 (0.12) 0.20 (0.14) 0.012
P1NP (ng/mL) 38.97 (21.41) 42.55 (21.52) <0.001

Data were summarized as median (interquartile range) or mean ± s.d. for continuous variables or a proportion for categorical variables. Normally distributed continuous variables were compared using Student’s t-test. The Mann–Whitney U test and the Kruskal–Wallis test were used for non-normally distributed continuous variables.

ATA, anti-thyroid antibody; Cr, creatinine; eGFR, estimated glomerular filtration rate; FT3, free triiodothyronine; FT4, free thyroxine; N-MID osteocalcin, large N-mid fragment of osteocalcin; P1NP, procollagen type I N-terminal propeptide; SPINA-GT, thyroid’s secretory capacity; SPINA-GD, sum activity of peripheral deiodinases; TgAb, thyroglobulin antibody; TPOAb, thyroid peroxidase antibody; TSH, thyroid-stimulating hormone; TSHI, Jostel’s TSH index; TT3, total triiodothyronine; TT4, total thyroxin; TTSI, thyrotroph thyroid hormone resistance index; β-CTX, β-C-terminal cross-linked telopeptides of type I collagen.

Association of BTMs with thyroid function and ATA+ in type 2 diabetes

We analyzed the associations of thyroid function and ATA+ with three BTMs using linear regression models. The regression models were adjusted for related factors, including age, BMI, duration of diabetes, current smoking, concentrations of HbA1c, 25(OH)D and Cr, and the use of metformin and thiazolidinediones. We found that TSH levels were negatively associated with β-CTX only in postmenopausal women (B = −0.047, 95% CI = −0.077 to −0.016). FT4 levels were negatively associated with N-MID OC (B = −0.007, 95% CI = −0.014 to −0.001) and P1NP (B = −0.013, 95% CI = −0.021 to −0.006) in men. FT3 and TT3 were positively associated with β-CTX only in postmenopausal women (FT3: B = 0.085, 95% CI = 0.050–0.120; TT3: B = 0.092, 95% CI = 0.023–0.161) and positively associated with N-MID OC and P1NP in both sexes (N-MID OC: men: FT3: B = 0.064, 95% CI = 0.036–0.092; TT3: B = 0.143, 95% CI = 0.091–0.194; postmenopausal women: FT3: B = 0.097, 95% CI = 0.069–0.124; TT3: B = 0.173, 95% CI = 0.119–0.227 and P1NP: men: FT3: B = 0.049, 95% CI = 0.018–0.081; T3: B = 0.174, 95% CI = 0.112–0.235; postmenopausal women: FT3: B = 0.096, 95% CI = 0.065–0.128; TT3: B = 0.174, 95% CI = 0.112–0.235) (Fig. 1).

Figure 1
Figure 1

Associations between BTMs and thyroid parameters in patients with type 2 diabetes mellitus by linear regression analysis. The data were expressed as B value and 95% CI. TSH, SPINA-GT and TTSI were ln-transformed for normal distribution before linear regression analysis. The regression model was adjusted for age, BMI, duration of diabetes, current smoking, concentration of HbA1c, 25(OH) D and Cr, and the use of metformin and thiazolidinediones.

Citation: Endocrine Connections 11, 3; 10.1530/EC-21-0484

Association of BTMs with thyroid homeostasis parameters in type 2 diabetes

We then analyzed the associations of thyroid homeostasis parameters with three BTMs using linear regression models (Fig. 1). After full adjustment, we found that SPINA-GD was positively associated with N-MID OC (B = 0.014, 95% CI = 0.009–0.018) and P1NP (B = 0.015, 95% CI = 0.010–0.021) in men. For postmenopausal women, more significant differences were found. For example, SPINA-GD levels were positively associated with N-MID OC (B = 0.012, 95% CI = 0.007–0.017) and P1NP (B = 0.017, 95% CI = 0.011–0.023), β-CTX was positively associated with SPINA-GT (B = 0.055, 95% CI = 0.010–0.100) and negatively associated with TTSI (B = −0.049, 95% CI = −0.081 to −0.017) and TSHI levels were negatively associated with β-CTX (B = −0.049, 95% CI = −0.077 to −0.013) and P1NP (B = −0.032, 95% CI = −0.061 to −0.003).

Association of BTMs with thyroid function and thyroid homeostasis parameters by the presence of ATA positivity

In this study, among all the participants, 6.2% of men and 14.2% of women had ATA positivity. After full adjustment, we evaluated the associations between BTMs and thyroid parameters among the participants with or without ATA+. For men, we were surprised to find that significant associations between BTMs and thyroid parameters were only found in men without ATA+. For women, regardless of whether or not the participants were ATA+, FT3 and TT3 levels were positively associated with three BTMs. However, for other thyroid parameters, significant associations between BTMs and thyroid parameters were also found only among women without ATA+ (Table 3).

Table 3

Associations between bone turnover markers and thyroid function and thyroid homeostasis parameters by the presence of ATA.
N-MID osteocalcin β-CTX P1NP
ATA (−) ATA (+) ATA (−) ATA (+) ATA (−) ATA (+)
B (95% CI) P B (95% CI) P B (95% CI) P B (95% CI) P B (95% CI) P B (95% CI) P
Men
 TSH 0.015 (−0.015, 0.045) 0.339 −0.014 (−0.096, 0.069) 0.741 −0.007 (−0.046, 0.031) 0.713 −0.061 (−0.168, 0.047) 0.265 0.003 (−0.030, 0.037) 0.844 0.010 (−0.087, 0.108) 0.834
 FT4 −0.008 (−0.015, −0.001) 0.024 0.000 (−0.021, 0.022) 0.985 −0.007 (−0.016, 0.002) 0.119 0.020 (−0.008, 0.048) 0.156 −0.014 (−0.022, −0.006) <0.001 0.002 (−0.024, 0.027) 0.901
 TT4 0.001 (0.000, 0.002) 0.137 −0.001 (−0.004, 0.002) 0.483 0.000 (−0.001, 0.001) 0.930 0.000 (−0.004, 0.004) 0.900 0.000 (−0.001, 0.001) 0.590 −0.001 (−0.005, 0.003) 0.664
 FT3 0.066 (0.037, 0.095) <0.001 0.037 (−0.066, 0.140) 0.477 0.020 (−0.017, 0.058) 0.294 0.110 (−0.023, 0.243) 0.103 0.049 (0.016, 0.082) 0.003 0.057 (−0.064, 0.179) 0.353
 TT3 0.159 (0.104, 0.214) <0.001 −0.001 (−0.161, 0.159) 0.992 0.064 (−0.007, 0.135) 0.077 −0.159 (−0.366, 0.048) 0.130 0.134 (0.072, 0.195) <0.001 0.022 (−0.168, 0.212) 0.821
 SPINA-GD 0.017 (0.012, 0.022) <0.001 −0.004 (−0.015, 0.008) 0.553 0.009 (0.002, 0.016) 0.008 −0.018 (−0.033, 0.003) 0.076 0.018 (0.012, 0.024) <0.001 −0.003 (−0.017, 0.011) 0.695
 SPINA-GT 0.004 (−0.040, 0.048) 0.868 −0.033 (−0.176, 0.109) 0.644 0.011 (−0.045, 0.067) 0.694 0.073 (−0.113, 0.259) 0.439 −0.009 (−0.058, 0.040) 0.725 −0.054 (−0.223, 0.114) 0.524
 TTSI 0.007 (−0.024, 0.037) 0.673 −0.012 (−0.104, 0.079) 0.791 −0.015 (−0.054, 0.024) 0.446 −0.048 (−0.168, 0.071) 0.427 −0.012 (−0.046, 0.022) 0.496 0.019 (−0.090, 0.128) 0.728
 TSHI −0.005 (−0.033, 0.023) 0.748 −0.017 (−0.109, 0.075) 0.719 −0.021 (−0.057, 0.014) 0.239 −0.026 (−0.146, 0.095) 0.671 −0.028 (−0.059, 0.004) 0.083 0.017 (−0.093, 0.127) 0.759
Women
 TSH −0.012 (−0.039, 0.016) 0.411 0.003 (−0.049, 0.056) 0.899 −0.057 (−0.092, −0.022) 0.001 −0.022 (−0.091, 0.046) 0.517 −0.025 (−0.057, 0.007) 0.123 0.000 (−0.060, 0.060) 0.996
 FT4 0.002 (−0.006, 0.009) 0.683 0.004 (−0.011, 0.020) 0.598 0.001 (−0.008, 0.011) 0.792 0.010 (−0.010, 0.030) 0.332 −0.008 (−0.016, 0.001) 0.066 −0.001 (−0.019, 0.017) 0.932
 TT4 0.001 (0.000, 0.002) 0.167 0.000 (−0.002, 0.002) 0.706 0.000 (−0.001, 0.001) 0.862 0.001 (−0.001, 0.004) 0.378 0.000 (−0.001, 0.001) 0.545 0.000 (−0.003, 0.002) 0.707
 FT3 0.094 (0.064, 0.125) <0.001 0.119 (0.049, 0.189) 0.001 0.079 (0.041, 0.118) <0.001 0.124 (0.032, 0.216) 0.008 0.096 (0.061, 0.131) <0.001 0.109 (0.028, 0.189) 0.008
 TT3 0.171 (0.112, 0.230) <0.001 0.191 (0.053, 0.329) 0.007 0.078 (0.003, 0.153) 0.041 0.159 (−0.023, 0.340) 0.086 0.176 (0.109, 0.243) <0.001 0.166 (0.007, 0.325) 0.041
 SPINA-GD 0.012 (0.007, 0.018) <0.001 0.012 (−0.001, 0.024) 0.065 0.005 (−0.002, 0.012) 0.165 0.005 (−0.011, 0.021) 0.563 0.018 (0.012, 0.024) <0.001 0.014 (0.000, 0.028) 0.057
 SPINA-GT 0.019 (−0.023, 0.061) 0.373 0.005 (−0.063, 0.073) 0.881 0.061 (0.008, 0.113) 0.024 0.040 (−0.049, 0.129) 0.378 0.015 (−0.033, 0.063) 0.536 0.013 (−0.065, 0.091) 0.747
 TTSI −0.011 (−0.040, 0.018) 0.456 0.007 (−0.050, 0.064) 0.881 −0.060 (−0.096, −0.024) 0.001 −0.019 (−0.094, 0.056) 0.618 −0.034 (−0.067, −0.001) 0.042 −0.002 (−0.068, 0.063) 0.950
 TSHI −0.009 (−0.037, 0.019) 0.533 0.014 (−0.049, 0.077) 0.658 −0.056 (−0.091, −0.020) 0.002 −0.011 (−0.093, 0.072) 0.801 −0.041 (−0.073, −0.009) 0.012 −0.002 (−0.074, 0.070) 0.958

ATA+ was defined as TPOAb+ (>34.00 U/mL) and/or TgAb+ (>115.00 U/mL). The regression models were adjusted for age, BMI, duration of diabetes, current smoking, concentration of HbA1c, 25(OH)D and Cr, and the use of metformin and thiazolidinediones. The results were expressed as B values and 95% CIs. N-MID osteocalcin, β-CTX, P1NP, TSH, GT and TTSI were ln-transformed for normal distribution before linear regression analysis.

ATA, anti-thyroid antibody; Cr, creatinine; eGFR, estimated glomerular filtration rate; FT3, free triiodothyronine; FT4, free thyroxine; N-MID osteocalcin, large N-mid fragment of osteocalcin; P1NP, procollagen type I N-terminal propeptide; SPINA-GT, thyroid’s secretory capacity; SPINA-GD, sum activity of peripheral deiodinases; TgAb, thyroglobulin antibody; TPOAb, thyroid peroxidase antibody; TSH, thyroid-stimulating hormone; TSHI, Jostel’s TSH index; TT3, total triiodothyronine; TT4, total thyroxin; TTSI, thyrotroph thyroid hormone resistance index; β-CTX, β-C-terminal cross-linked telopeptides of type I collagen.

Discussion

Several studies have found that BTMs can predict fracture risk independently of BMD in men and postmenopausal women (8). Recently, some evidence has suggested that BTMs, such as CTX, OC and P1NP, of patients with T2DM are lower than those of healthy controls (6, 20, 21, 22, 23). Thus, the main purpose of this study was to understand the factors that may be involved in the changes in BTMs in patients with T2DM, especially the regulation by thyroid-related parameters. This study mainly discusses three BTMs, that is, P1NP, N-MID OC and β-CTX, which have been recommended for use in epidemiological studies as reference markers of bone formation and resorption (8). Several reports have suggested that anti-thyroid dysfunction treatment may influence the bone metabolism. Long-term levothyroxine substitution therapy, including treatment for hypothyroidism, and TSH suppressive levothyroxine doses in the therapy of thyroidectomy may influence BTMs (24, 25). On the other hand, bone loss could be reversed by the treatment of hyperthyroidism (26). Thus, considering the effects of anti-thyroid dysfunction treatment on BTMs, participants who had a history of thyroid surgery or known thyroid dysfunction, that is, all potential users of drugs for thyroid dysfunction were excluded in this study. None of the participants in this study had a history of taking anti-thyroid treatment.

In T2DM patients, BTMs may be affected by several factors (6),that is, increasing plasma glucose (6, 27), obesity (or BMI) (28) and renal function (29). Furthermore, antidiabetic drugs (6), such as metformin and thiazolidinediones (30, 31), have been suggested to influence bone turnover with inconsistent results (32, 33, 34). Thus, in this study, all of these above factors were adjusted in regression models. In addition, some of the BTMs, such as CTX, were reported to be decreased by food intake (35, 36). Considering the immediate impact of diet on bone metabolism, blood samples collected in this study were all fasting blood samples.

Thyroid hormones regulate skeletal development, longitudinal growth and bone homeostasis (12). The relationship between thyroid function and BTMs has been evaluated in several cross-sectional and prospective studies with controversial results. Although some reports have suggested that overt hyperthyroidism increases the rate of both bone formation and resorption (9, 11, 37), hypothyroidism results in a low bone turnover state (38), and subclinical hyper- and hypothyroidism are correlated with bone loss (39, 40, 41). Other studies have failed to confirm these associations (42, 43, 44, 45). TSH was negatively correlated with bone formation markers (N-MID OC) (46), and in vitro data showed that TSH inhibits osteoclastogenesis in a murine osteoclast cell line (47). However, in the current study, we found that TSH levels were negatively associated with bone resorption (β-CTX) in postmenopausal women. Our observation results may be explained by the presence of thyrotropin (TSH) receptors (TSHRs) in both osteoclasts and osteoblasts (48). In line with a previous study suggesting that FT3 was significantly positively correlated with N-MID OC and CTX (46), we found that FT3 and TT3 were positively associated with N-MID OC and P1NP in both sexes and positively associated with β-CTX only in postmenopausal women. T3 is essential for normal bone growth and bone metabolism. T3 stimulates bone formation directly through T3 receptors in osteoblasts and stimulates bone resorption by osteoclasts, perhaps secondarily through osteoblasts (49). Thus, in patients with T2DM, low T3 levels may be associated with impaired bone formation and bone resorption processes. Moreover, the differential regulation of BTMs in different sexes in the current study may be due to the effect of sex steroids on modulating the interplay between thyroid and bone.

The hypothalamic–pituitary–thyroid axis plays a key role in the regulation of bone turnover (12). To date, no epidemiologic studies have focused on the association between thyroid homeostasis parameters and BTMs among participants with T2DM. By extending the classic concept of separate measurements of thyroid hormone parameters, these thyroid homeostasis parameters add new qualitative and quantitative dimensions to the evaluation of thyroid homeostasis status, offer a more integrated and systemic view and deliver important insights into the physiology of pituitary–thyroid feedback control (18). SPINA-GD, which reflects the maximum stimulated activity of step-up deiodination (i.e. calculated peripheral deiodinase (DIO) activity), is well-correlated with peripheral DIO activity. Positive associations between calculated peripheral DIO activity and bone formation markers in both sexes may also explain the positive association between TT3 and bone formation markers in the present population. DIO catalyzes the conversion from inactive T4 to active T3, and most circulating T3 in blood is derived from peripheral T4 deiodination (50). SPINA-GT, referred to as thyroid capacity, provides an estimate for the maximum secretion rate of the thyroid gland. In vivo validation confirmed that SPINA-GT is able to clearly differentiate between euthyroidism and functional thyroid disorders of primary origin (51). Unlike TSH, it is unaffected by hypothalamic–pituitary dysfunction. We found a positive relationship between SPINA-GT and β-CTX in postmenopausal women. The present observation suggested that changes in thyroid capacity may play a role in bone resorption. TSHI and TTSI were introduced as quantitative markers for pituitary thyrotropic function. Negative relationships of TTSI with β-CTX and TSHI with β-CTX and P1NP were found in postmenopausal women. We hypothesized that pituitary thyrotropic function may also be a possible mechanism of bone metabolism (18).

Different patterns of associations between BTMs and thyroid measures by the status of thyroid autoantibodies suggest that thyroid autoantibodies should be considered in the regulation of bone metabolism by thyroid hormones. Although one study reported that the presence of TPOAb is a potential marker of higher fracture risk in these patients (52), associations between BTMs and TPOAb or TgAb status have rarely been assessed in the human population. In the current observational study, while no direct associations were observed between BTMs and thyroid autoantibody status, the associations with TSH, FT4, SPINA-GD, SPINA-GT, TTSI and TSHI appeared to be influenced by ATA status. Indeed, many significant associations that were observed among the ATA− subjects disappeared among the ATA+ group. The relationship between thyroid antibody and bone metabolism, and its regulatory mechanism are still unclear. More large-scale prospective studies are needed to evaluate these findings.

Although our study had some strengths, including a relatively larger sample size of community-dwelling participants and strong quality control, there were also some limitations. First, this was a cross-sectional study; thus, a causal relationship could not be identified between BTMs and thyroid function and thyroid homeostasis parameters. Larger cohort studies are needed. Secondly, although determination of bone turnover in diabetes may require bone biopsies to reveal microscopic changes, bone tissue biopsies are difficult to obtain in such a large population. Thirdly, combinations of multiple antidiabetic drug treatments are very common in patients with T2DM. In this study, although the effects of metformin and thiazolidinedione on bone metabolism were considered, the effects of multiple antidiabetic drugs on bone metabolism were not discussed in this study. Fourthly, calcium concentration, parathyroid hormone concentration and BMD were not measured in this study and should be measured in future research. Considering the limitation of the small sample size of fracture history (n  = 27), fracture was not included in the statistical analysis in this study. Moreover, although the participants with a history of thyroid surgery or known thyroid dysfunction were recorded, what kind of anti-thyroid dysfunction treatment and the dosing the patient was currently taking were not recorded. The issue on the association of high and low dosing of levothyroxine substitution therapy with bone metabolism would be explored in future study.

Conclusion

Among men and postmenopausal women with T2DM, significant associations of N-MID OC, β-CTX and P1NP with thyroid function and thyroid homeostasis were observed. Further prospective and animal studies are warranted to understand the causal relationship and underlying mechanism.

Declaration of interest

The authors declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research reported.

Funding

This study was supported by National Natural Science Foundation of China (81800694, 91857117); Science and Technology Commission of Shanghai Municipality (19140902400, 18410722300); the Major Science and Technology Innovation Program of Shanghai Municipal Education Commission (2019-01-07-00-01-E00059); Commission of Health and Family Planning of Pudong District (PWZxq2017-17); Municipal Human Resources Development Program for Outstanding Young Talents in Medical and Health Sciences in Shanghai (2017YQ053); Shanghai JiaoTong University School of Medicine (19XJ11007). The funders played no role in the design or conduct of the study, collection, management, analysis, or interpretation of data or in the preparation, review, or approval of the article.

Author contribution statement

Yingli Lu and Yi Chen designed, performed and supervised this investigation, and had full access to all of the data and took responsibility for the integrity of the data and the accuracy of the data analysis. Yi Chen performed this investigation, analyzed the data, contributed to the discussion, interpretation of the data and the manuscript writing. Wen Zhang, Chi Chen, Yuying Wang and Ningjian Wang provided technical or material support, and contributed to the discussion. All authors read and approved the final manuscript.

Data availability

The data used to support the findings of this study are included within the article.

Acknowledgements

The authors thank all team members and participants in the METAL study.

References

  • 1↑

    Starup-Linde J, Vestergaard P. Biochemical bone turnover markers in diabetes mellitus – a systematic review. Bone 2016 82 69–78. (https://doi.org/10.1016/j.bone.2015.02.019)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 2↑

    Leslie WD, Rubin MR, Schwartz AV, Kanis JA. Type 2 diabetes and bone. Journal of Bone and Mineral Research 2012 27 2231–2237. (https://doi.org/10.1002/jbmr.1759)

  • 3↑

    Janghorbani M, Van Dam RM, Willett WC, Hu FB. Systematic review of type 1 and type 2 diabetes mellitus and risk of fracture. American Journal of Epidemiology 2007 166 495–505. (https://doi.org/10.1093/aje/kwm106)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 4↑

    Marshall D, Johnell O, Wedel H. Meta-analysis of how well measures of bone mineral density predict occurrence of osteoporotic fractures. BMJ 1996 312 1254–1259. (https://doi.org/10.1136/bmj.312.7041.1254)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 5↑

    Vestergaard P Discrepancies in bone mineral density and fracture risk in patients with type 1 and type 2 diabetes – a meta-analysis. Osteoporosis International 2007 18 427–444. (https://doi.org/10.1007/s00198-006-0253-4)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 6↑

    Hygum K, Starup-Linde J, Harslof T, Vestergaard P, Langdahl BL. MECHANISMS IN ENDOCRINOLOGY: Diabetes mellitus, a state of low bone turnover – a systematic review and meta-analysis. European Journal of Endocrinology 2017 176 R137–R157. (https://doi.org/10.1530/EJE-16-0652)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 7↑

    Starup-Linde J, Eriksen SA, Lykkeboe S, Handberg A, Vestergaard P. Biochemical markers of bone turnover in diabetes patients – a meta-analysis, and a methodological study on the effects of glucose on bone markers. Osteoporosis International 2014 25 1697–1708. (https://doi.org/10.1007/s00198-014-2676-7)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 8↑

    Vasikaran S, Eastell R, Bruyere O, Foldes AJ, Garnero P, Griesmacher A, McClung M, Morris HA, Silverman S & Trenti T et al.Markers of bone turnover for the prediction of fracture risk and monitoring of osteoporosis treatment: a need for international reference standards. Osteoporosis International 2011 22 391–420. (https://doi.org/10.1007/s00198-010-1501-1)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 9↑

    Bassett JH, Williams GR. Role of thyroid hormones in skeletal development and bone maintenance. Endocrine Reviews 2016 37 135–187. (https://doi.org/10.1210/er.2015-1106)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 10↑

    Abrahamsen B, Jorgensen HL, Laulund AS, Nybo M, Brix TH, Hegedus L. Low serum thyrotropin level and duration of suppression as a predictor of major osteoporotic fractures-the OPENTHYRO register cohort. Journal of Bone and Mineral Research 2014 29 2040–2050. (https://doi.org/10.1002/jbmr.2244)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 11↑

    Vestergaard P, Mosekilde L. Hyperthyroidism, bone mineral, and fracture risk – a meta-analysis. Thyroid 2003 13 585–593. (https://doi.org/10.1089/105072503322238854)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 12↑

    Gogakos AI, Duncan Bassett JH, Williams GR. Thyroid and bone. Archives of Biochemistry and Biophysics 2010 503 129–136. (https://doi.org/10.1016/j.abb.2010.06.021)

  • 13↑

    Wang C, Zhang W, Wang Y, Wan H, Chen Y, Xia F, Zhang K, Wang N, Lu Y. Novel associations between sex hormones and diabetic vascular complications in men and postmenopausal women: a cross-sectional study. Cardiovascular Diabetology 2019 18 97. (https://doi.org/10.1186/s12933-019-0901-6)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 14↑

    Chen Y, Zhang W, Wang N, Wang Y, Wang C, Wan H, Lu Y. Thyroid parameters and kidney disorder in type 2 diabetes: results from the METAL study. Journal of Diabetes Research 2020 2020 4798947. (https://doi.org/10.1155/2020/4798947)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 15↑

    Wang N, Chen Y, Ning Z, Li Q, Han B, Zhu C, Chen Y, Xia F, Jiang B & Wang B et al.Exposure to famine in early life and nonalcoholic fatty liver disease in adulthood. Journal of Clinical Endocrinology and Metabolism 2016 101 2218–2225. (https://doi.org/10.1210/jc.2016-1076)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 16↑

    Chen Y, Chen Y, Xia F, Wang N, Chen C, Nie X, Li Q, Han B, Zhai H & Jiang B et al.A higher ratio of estradiol to testosterone is associated with autoimmune thyroid disease in males. Thyroid 2017 27 960–966. (https://doi.org/10.1089/thy.2016.0661)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 17↑

    Xu Y, Wang L, He J, Bi Y, Li M, Wang T, Wang L, Jiang Y, Dai M & Lu J et al.Prevalence and control of diabetes in Chinese adults. JAMA 2013 310 948–959. (https://doi.org/10.1001/jama.2013.168118)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 18↑

    Dietrich JW, Landgrafe-Mende G, Wiora E, Chatzitomaris A, Klein HH, Midgley JE, Hoermann R. Calculated parameters of thyroid homeostasis: emerging tools for differential diagnosis and clinical research. Frontiers in Endocrinology 2016 7 57. (https://doi.org/10.3389/fendo.2016.00057)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 19↑

    Stevens LA, Claybon MA, Schmid CH, Chen J, Horio M, Imai E, Nelson RG, Van Deventer M, Wang HY & Zuo L et al.Evaluation of the chronic kidney disease epidemiology collaboration equation for estimating the glomerular filtration rate in multiple ethnicities. Kidney International 2011 79 555–562. (https://doi.org/10.1038/ki.2010.462)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 20↑

    Jiajue R, Jiang Y, Wang O, Li M, Xing X, Cui L, Yin J, Xu L, Xia W. Suppressed bone turnover was associated with increased osteoporotic fracture risks in non-obese postmenopausal Chinese women with type 2 diabetes mellitus. Osteoporosis International 2014 25 1999–2005. (https://doi.org/10.1007/s00198-014-2714-5)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 21↑

    Reyes-Garcia R, Rozas-Moreno P, Lopez-Gallardo G, Garcia-Martin A, Varsavsky M, Aviles-Perez MD, Munoz-Torres M. Serum levels of bone resorption markers are decreased in patients with type 2 diabetes. Acta Diabetologica 2013 50 47–52. (https://doi.org/10.1007/s00592-011-0347-0)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 22↑

    Yamamoto M, Yamaguchi T, Nawata K, Yamauchi M, Sugimoto T. Decreased PTH levels accompanied by low bone formation are associated with vertebral fractures in postmenopausal women with type 2 diabetes. Journal of Clinical Endocrinology and Metabolism 2012 97 1277–1284. (https://doi.org/10.1210/jc.2011-2537)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 23↑

    Movahed A, Larijani B, Nabipour I, Kalantarhormozi M, Asadipooya K, Vahdat K, Akbarzadeh S, Farrokhnia M, Assadi M & Amirinejad R et al.Reduced serum osteocalcin concentrations are associated with type 2 diabetes mellitus and the metabolic syndrome components in postmenopausal women: the crosstalk between bone and energy metabolism. Journal of Bone and Mineral Metabolism 2012 30 683–691. (https://doi.org/10.1007/s00774-012-0367-z)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 24↑

    Delitala AP, Scuteri A, Doria C. Thyroid hormone diseases and osteoporosis. Journal of Clinical Medicine 2020 9 1034. (https://doi.org/10.3390/jcm9041034)

  • 25↑

    Martini G, Gennari L, De Paola V, Pilli T, Salvadori S, Merlotti D, Valleggi F, Campagna S, Franci B & Avanzati A et al.The effects of recombinant TSH on bone turnover markers and serum osteoprotegerin and RANKL levels. Thyroid 2008 18 455–460. (https://doi.org/10.1089/thy.2007.0166)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 26↑

    Amato G, Mazziotti G, Sorvillo F, Piscopo M, Lalli E, Biondi B, Iorio S, Molinari A, Giustina A, Carella C. High serum osteoprotegerin levels in patients with hyperthyroidism: effect of medical treatment. Bone 2004 35 785–791. (https://doi.org/10.1016/j.bone.2004.04.021)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 27↑

    Starup-Linde J, Lykkeboe S, Gregersen S, Hauge EM, Langdahl BL, Handberg A, Vestergaard P. Differences in biochemical bone markers by diabetes type and the impact of glucose. Bone 2016 83 149–155. (https://doi.org/10.1016/j.bone.2015.11.004)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 28↑

    Viljakainen H, Ivaska KK, Paldanius P, Lipsanen-Nyman M, Saukkonen T, Pietilainen KH, Andersson S, Laitinen K, Makitie O. Suppressed bone turnover in obesity: a link to energy metabolism? A case-control study. Journal of Clinical Endocrinology and Metabolism 2014 99 2155–2163. (https://doi.org/10.1210/jc.2013-3097)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 29↑

    Nickolas TL, Jamal SA. Bone kidney interactions. Reviews in Endocrine and Metabolic Disorders 2015 16 157–163. (https://doi.org/10.1007/s11154-015-9314-3)

  • 30↑

    Meier C, Schwartz AV, Egger A, Lecka-Czernik B. Effects of diabetes drugs on the skeleton. Bone 2016 82 93–100. (https://doi.org/10.1016/j.bone.2015.04.026)

  • 31↑

    Gilbert MP, Pratley RE. The impact of diabetes and diabetes medications on bone health. Endocrine Reviews 2015 36 194–213. (https://doi.org/10.1210/er.2012-1042)

  • 32↑

    Okazaki R, Miura M, Toriumi M, Taguchi M, Hirota Y, Fukumoto S, Fujita T, Tanaka K, Takeuchi A. Short-term treatment with troglitazone decreases bone turnover in patients with type 2 diabetes mellitus. Endocrine Journal 1999 46 795–801. (https://doi.org/10.1507/endocrj.46.795)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 33↑

    Gruntmanis U, Fordan S, Ghayee HK, Abdullah SM, See R, Ayers CR, McGuire DK. The peroxisome proliferator-activated receptor-gamma agonist rosiglitazone increases bone resorption in women with type 2 diabetes: a randomized, controlled trial. Calcified Tissue International 2010 86 343–349. (https://doi.org/10.1007/s00223-010-9352-5)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 34↑

    Berberoglu Z, Gursoy A, Bayraktar N, Yazici AC, Bascil Tutuncu N, Guvener Demirag N. Rosiglitazone decreases serum bone-specific alkaline phosphatase activity in postmenopausal diabetic women. Journal of Clinical Endocrinology and Metabolism 2007 92 3523–3530. (https://doi.org/10.1210/jc.2007-0431)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 35↑

    Bjarnason NH, Henriksen EE, Alexandersen P, Christgau S, Henriksen DB, Christiansen C. Mechanism of circadian variation in bone resorption. Bone 2002 30 307–313. (https://doi.org/10.1016/s8756-3282(0100662-7)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 36↑

    Bunck MC, Poelma M, Eekhoff EM, Schweizer A, Heine RJ, Nijpels G, Foley JE, Diamant M. Effects of vildagliptin on postprandial markers of bone resorption and calcium homeostasis in recently diagnosed, well-controlled type 2 diabetes patients. Journal of Diabetes 2012 4 181–185. (https://doi.org/10.1111/j.1753-0407.2011.00168.x)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 37↑

    Al-Shoumer KA, Vasanthy BA, Al-Zaid MM. Effects of treatment of hyperthyroidism on glucose homeostasis, insulin secretion, and markers of bone turnover. Endocrine Practice 2006 12 121–130. (https://doi.org/10.4158/EP.12.2.121)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 38↑

    Eriksen EF, Mosekilde L, Melsen F. Kinetics of trabecular bone resorption and formation in hypothyroidism: evidence for a positive balance per remodeling cycle. Bone 1986 7 101–108. (https://doi.org/10.1016/8756-3282(8690681-2)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 39↑

    Belaya ZE, Melnichenko GA, Rozhinskaya LY, Fadeev VV, Alekseeva TM, Dorofeeva OK, Sasonova NI, Kolesnikova GS. Subclinical hyperthyroidism of variable etiology and its influence on bone in postmenopausal women. Hormones 2007 6 62–70.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 40↑

    Grimnes G, Emaus N, Joakimsen RM, Figenschau Y, Jorde R. The relationship between serum TSH and bone mineral density in men and postmenopausal women: the Tromso study. Thyroid 2008 18 1147–1155. (https://doi.org/10.1089/thy.2008.0158)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 41↑

    Nagata M, Suzuki A, Sekiguchi S, Ono Y, Nishiwaki-Yasuda K, Itoi T, Yamamoto S, Imamura S, Katoh T & Hayakawa N et al.Subclinical hypothyroidism is related to lower heel QUS in postmenopausal women. Endocrine Journal 2007 54 625–630. (https://doi.org/10.1507/endocrj.k06-201)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 42↑

    Siru R, Alfonso H, Chubb SAP, Golledge J, Flicker L, Yeap BB. Subclinical thyroid dysfunction and circulating thyroid hormones are not associated with bone turnover markers or incident hip fracture in older men. Clinical Endocrinology 2018 89 93–99. (https://doi.org/10.1111/cen.13615)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 43↑

    Tsourdi E, Wallaschofski H, Rauner M, Nauck M, Pietzner M, Rettig R, Ittermann T, Volzke H, Volker U & Hofbauer LC et al.Thyrotropin serum levels are differentially associated with biochemical markers of bone turnover and stiffness in women and men: results from the SHIP cohorts. Osteoporosis International 2016 27 719–727. (https://doi.org/10.1007/s00198-015-3276-x)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 44↑

    Murphy E, Gluer CC, Reid DM, Felsenberg D, Roux C, Eastell R, Williams GR. Thyroid function within the upper normal range is associated with reduced bone mineral density and an increased risk of nonvertebral fractures in healthy euthyroid postmenopausal women. Journal of Clinical Endocrinology and Metabolism 2010 95 3173–3181. (https://doi.org/10.1210/jc.2009-2630)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 45↑

    Schneider R, Schneider M, Reiners C, Schneider P. Effects of levothyroxine on bone mineral density, muscle force, and bone turnover markers: a cohort study. Journal of Clinical Endocrinology and Metabolism 2012 97 3926–3934. (https://doi.org/10.1210/jc.2012-2570)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 46↑

    Olkawa M, Kushida K, Takahashi M, Ohishi T, Hoshino H, Suzuki M, Ogihara H, Ishigaki J, Inoue T. Bone turnover and cortical bone mineral density in the distal radius in patients with hyperthyroidism being treated with antithyroid drugs for various periods of time. Clinical Endocrinology 1999 50 171–176. (https://doi.org/10.1046/j.1365-2265.1999.00626.x)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 47↑

    Zhang W, Zhang Y, Liu Y, Wang J, Gao L, Yu C, Yan H, Zhao J, Xu J. Thyroid-stimulating hormone maintains bone mass and strength by suppressing osteoclast differentiation. Journal of Biomechanics 2014 47 1307–1314. (https://doi.org/10.1016/j.jbiomech.2014.02.015)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 48↑

    Abe E, Marians RC, Yu W, Wu XB, Ando T, Li Y, Iqbal J, Eldeiry L, Rajendren G & Blair HC et al.TSH is a negative regulator of skeletal remodeling. Cell 2003 115 151–162. (https://doi.org/10.1016/s0092-8674(0300771-2)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 49↑

    Ejima E, Fujiyama K, Kiriyama T, Eguchi K. Bone changes in thyrotoxicosis. Nihon Rinsho 1998 56 1587–1590.

  • 50↑

    Gereben B, Zavacki AM, Ribich S, Kim BW, Huang SA, Simonides WS, Zeold A, Bianco AC. Cellular and molecular basis of deiodinase-regulated thyroid hormone signaling. Endocrine Reviews 2008 29 898–938. (https://doi.org/10.1210/er.2008-0019)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 51↑

    Wang X, Liu H, Chen J, Huang Y, Li L, Rampersad S, Qu S. Metabolic characteristics in obese patients complicated by mild thyroid hormone deficiency. Hormone and Metabolic Research 2016 48 331–337. (https://doi.org/10.1055/s-0042-105150)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 52↑

    Polovina SP, Miljic D, Zivojinovic S, Milic N, Micic D, Brkic VP. The impact of thyroid autoimmunity (TPOAb) on bone density and fracture risk in postmenopausal women. Hormones 2017 16 54–61. (https://doi.org/10.14310/horm.2002.1719)

    • PubMed
    • Search Google Scholar
    • Export Citation

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Online ISSN:
2049-3614
Copyright:
© The authors 2022
Article ID:
e210484
Article Type:
Research Article
Received Date:
17 Feb 2022
Accepted Date:
23 Feb 2022
Online Publication Date:
31 Mar 2022
Keywords:
bone turnover marker; thyroid hormone; thyroid homeostasis parameters; type 2 diabetes mellitus
  • Figure 1
    View in gallery
    Figure 1

    Associations between BTMs and thyroid parameters in patients with type 2 diabetes mellitus by linear regression analysis. The data were expressed as B value and 95% CI. TSH, SPINA-GT and TTSI were ln-transformed for normal distribution before linear regression analysis. The regression model was adjusted for age, BMI, duration of diabetes, current smoking, concentration of HbA1c, 25(OH) D and Cr, and the use of metformin and thiazolidinediones.

Figure 1

Associations between BTMs and thyroid parameters in patients with type 2 diabetes mellitus by linear regression analysis. The data were expressed as B value and 95% CI. TSH, SPINA-GT and TTSI were ln-transformed for normal distribution before linear regression analysis. The regression model was adjusted for age, BMI, duration of diabetes, current smoking, concentration of HbA1c, 25(OH) D and Cr, and the use of metformin and thiazolidinediones.
  • 1

    Starup-Linde J, Vestergaard P. Biochemical bone turnover markers in diabetes mellitus – a systematic review. Bone 2016 82 69–78. (https://doi.org/10.1016/j.bone.2015.02.019)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 2

    Leslie WD, Rubin MR, Schwartz AV, Kanis JA. Type 2 diabetes and bone. Journal of Bone and Mineral Research 2012 27 2231–2237. (https://doi.org/10.1002/jbmr.1759)

  • 3

    Janghorbani M, Van Dam RM, Willett WC, Hu FB. Systematic review of type 1 and type 2 diabetes mellitus and risk of fracture. American Journal of Epidemiology 2007 166 495–505. (https://doi.org/10.1093/aje/kwm106)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 4

    Marshall D, Johnell O, Wedel H. Meta-analysis of how well measures of bone mineral density predict occurrence of osteoporotic fractures. BMJ 1996 312 1254–1259. (https://doi.org/10.1136/bmj.312.7041.1254)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 5

    Vestergaard P Discrepancies in bone mineral density and fracture risk in patients with type 1 and type 2 diabetes – a meta-analysis. Osteoporosis International 2007 18 427–444. (https://doi.org/10.1007/s00198-006-0253-4)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 6

    Hygum K, Starup-Linde J, Harslof T, Vestergaard P, Langdahl BL. MECHANISMS IN ENDOCRINOLOGY: Diabetes mellitus, a state of low bone turnover – a systematic review and meta-analysis. European Journal of Endocrinology 2017 176 R137–R157. (https://doi.org/10.1530/EJE-16-0652)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 7

    Starup-Linde J, Eriksen SA, Lykkeboe S, Handberg A, Vestergaard P. Biochemical markers of bone turnover in diabetes patients – a meta-analysis, and a methodological study on the effects of glucose on bone markers. Osteoporosis International 2014 25 1697–1708. (https://doi.org/10.1007/s00198-014-2676-7)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 8

    Vasikaran S, Eastell R, Bruyere O, Foldes AJ, Garnero P, Griesmacher A, McClung M, Morris HA, Silverman S & Trenti T et al.Markers of bone turnover for the prediction of fracture risk and monitoring of osteoporosis treatment: a need for international reference standards. Osteoporosis International 2011 22 391–420. (https://doi.org/10.1007/s00198-010-1501-1)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 9

    Bassett JH, Williams GR. Role of thyroid hormones in skeletal development and bone maintenance. Endocrine Reviews 2016 37 135–187. (https://doi.org/10.1210/er.2015-1106)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 10

    Abrahamsen B, Jorgensen HL, Laulund AS, Nybo M, Brix TH, Hegedus L. Low serum thyrotropin level and duration of suppression as a predictor of major osteoporotic fractures-the OPENTHYRO register cohort. Journal of Bone and Mineral Research 2014 29 2040–2050. (https://doi.org/10.1002/jbmr.2244)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 11

    Vestergaard P, Mosekilde L. Hyperthyroidism, bone mineral, and fracture risk – a meta-analysis. Thyroid 2003 13 585–593. (https://doi.org/10.1089/105072503322238854)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 12

    Gogakos AI, Duncan Bassett JH, Williams GR. Thyroid and bone. Archives of Biochemistry and Biophysics 2010 503 129–136. (https://doi.org/10.1016/j.abb.2010.06.021)

  • 13

    Wang C, Zhang W, Wang Y, Wan H, Chen Y, Xia F, Zhang K, Wang N, Lu Y. Novel associations between sex hormones and diabetic vascular complications in men and postmenopausal women: a cross-sectional study. Cardiovascular Diabetology 2019 18 97. (https://doi.org/10.1186/s12933-019-0901-6)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 14

    Chen Y, Zhang W, Wang N, Wang Y, Wang C, Wan H, Lu Y. Thyroid parameters and kidney disorder in type 2 diabetes: results from the METAL study. Journal of Diabetes Research 2020 2020 4798947. (https://doi.org/10.1155/2020/4798947)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 15

    Wang N, Chen Y, Ning Z, Li Q, Han B, Zhu C, Chen Y, Xia F, Jiang B & Wang B et al.Exposure to famine in early life and nonalcoholic fatty liver disease in adulthood. Journal of Clinical Endocrinology and Metabolism 2016 101 2218–2225. (https://doi.org/10.1210/jc.2016-1076)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 16

    Chen Y, Chen Y, Xia F, Wang N, Chen C, Nie X, Li Q, Han B, Zhai H & Jiang B et al.A higher ratio of estradiol to testosterone is associated with autoimmune thyroid disease in males. Thyroid 2017 27 960–966. (https://doi.org/10.1089/thy.2016.0661)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 17

    Xu Y, Wang L, He J, Bi Y, Li M, Wang T, Wang L, Jiang Y, Dai M & Lu J et al.Prevalence and control of diabetes in Chinese adults. JAMA 2013 310 948–959. (https://doi.org/10.1001/jama.2013.168118)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 18

    Dietrich JW, Landgrafe-Mende G, Wiora E, Chatzitomaris A, Klein HH, Midgley JE, Hoermann R. Calculated parameters of thyroid homeostasis: emerging tools for differential diagnosis and clinical research. Frontiers in Endocrinology 2016 7 57. (https://doi.org/10.3389/fendo.2016.00057)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 19

    Stevens LA, Claybon MA, Schmid CH, Chen J, Horio M, Imai E, Nelson RG, Van Deventer M, Wang HY & Zuo L et al.Evaluation of the chronic kidney disease epidemiology collaboration equation for estimating the glomerular filtration rate in multiple ethnicities. Kidney International 2011 79 555–562. (https://doi.org/10.1038/ki.2010.462)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 20

    Jiajue R, Jiang Y, Wang O, Li M, Xing X, Cui L, Yin J, Xu L, Xia W. Suppressed bone turnover was associated with increased osteoporotic fracture risks in non-obese postmenopausal Chinese women with type 2 diabetes mellitus. Osteoporosis International 2014 25 1999–2005. (https://doi.org/10.1007/s00198-014-2714-5)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 21

    Reyes-Garcia R, Rozas-Moreno P, Lopez-Gallardo G, Garcia-Martin A, Varsavsky M, Aviles-Perez MD, Munoz-Torres M. Serum levels of bone resorption markers are decreased in patients with type 2 diabetes. Acta Diabetologica 2013 50 47–52. (https://doi.org/10.1007/s00592-011-0347-0)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 22

    Yamamoto M, Yamaguchi T, Nawata K, Yamauchi M, Sugimoto T. Decreased PTH levels accompanied by low bone formation are associated with vertebral fractures in postmenopausal women with type 2 diabetes. Journal of Clinical Endocrinology and Metabolism 2012 97 1277–1284. (https://doi.org/10.1210/jc.2011-2537)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 23

    Movahed A, Larijani B, Nabipour I, Kalantarhormozi M, Asadipooya K, Vahdat K, Akbarzadeh S, Farrokhnia M, Assadi M & Amirinejad R et al.Reduced serum osteocalcin concentrations are associated with type 2 diabetes mellitus and the metabolic syndrome components in postmenopausal women: the crosstalk between bone and energy metabolism. Journal of Bone and Mineral Metabolism 2012 30 683–691. (https://doi.org/10.1007/s00774-012-0367-z)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 24

    Delitala AP, Scuteri A, Doria C. Thyroid hormone diseases and osteoporosis. Journal of Clinical Medicine 2020 9 1034. (https://doi.org/10.3390/jcm9041034)

  • 25

    Martini G, Gennari L, De Paola V, Pilli T, Salvadori S, Merlotti D, Valleggi F, Campagna S, Franci B & Avanzati A et al.The effects of recombinant TSH on bone turnover markers and serum osteoprotegerin and RANKL levels. Thyroid 2008 18 455–460. (https://doi.org/10.1089/thy.2007.0166)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 26

    Amato G, Mazziotti G, Sorvillo F, Piscopo M, Lalli E, Biondi B, Iorio S, Molinari A, Giustina A, Carella C. High serum osteoprotegerin levels in patients with hyperthyroidism: effect of medical treatment. Bone 2004 35 785–791. (https://doi.org/10.1016/j.bone.2004.04.021)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 27

    Starup-Linde J, Lykkeboe S, Gregersen S, Hauge EM, Langdahl BL, Handberg A, Vestergaard P. Differences in biochemical bone markers by diabetes type and the impact of glucose. Bone 2016 83 149–155. (https://doi.org/10.1016/j.bone.2015.11.004)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 28

    Viljakainen H, Ivaska KK, Paldanius P, Lipsanen-Nyman M, Saukkonen T, Pietilainen KH, Andersson S, Laitinen K, Makitie O. Suppressed bone turnover in obesity: a link to energy metabolism? A case-control study. Journal of Clinical Endocrinology and Metabolism 2014 99 2155–2163. (https://doi.org/10.1210/jc.2013-3097)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 29

    Nickolas TL, Jamal SA. Bone kidney interactions. Reviews in Endocrine and Metabolic Disorders 2015 16 157–163. (https://doi.org/10.1007/s11154-015-9314-3)

  • 30

    Meier C, Schwartz AV, Egger A, Lecka-Czernik B. Effects of diabetes drugs on the skeleton. Bone 2016 82 93–100. (https://doi.org/10.1016/j.bone.2015.04.026)

  • 31

    Gilbert MP, Pratley RE. The impact of diabetes and diabetes medications on bone health. Endocrine Reviews 2015 36 194–213. (https://doi.org/10.1210/er.2012-1042)

  • 32

    Okazaki R, Miura M, Toriumi M, Taguchi M, Hirota Y, Fukumoto S, Fujita T, Tanaka K, Takeuchi A. Short-term treatment with troglitazone decreases bone turnover in patients with type 2 diabetes mellitus. Endocrine Journal 1999 46 795–801. (https://doi.org/10.1507/endocrj.46.795)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 33

    Gruntmanis U, Fordan S, Ghayee HK, Abdullah SM, See R, Ayers CR, McGuire DK. The peroxisome proliferator-activated receptor-gamma agonist rosiglitazone increases bone resorption in women with type 2 diabetes: a randomized, controlled trial. Calcified Tissue International 2010 86 343–349. (https://doi.org/10.1007/s00223-010-9352-5)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 34

    Berberoglu Z, Gursoy A, Bayraktar N, Yazici AC, Bascil Tutuncu N, Guvener Demirag N. Rosiglitazone decreases serum bone-specific alkaline phosphatase activity in postmenopausal diabetic women. Journal of Clinical Endocrinology and Metabolism 2007 92 3523–3530. (https://doi.org/10.1210/jc.2007-0431)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 35

    Bjarnason NH, Henriksen EE, Alexandersen P, Christgau S, Henriksen DB, Christiansen C. Mechanism of circadian variation in bone resorption. Bone 2002 30 307–313. (https://doi.org/10.1016/s8756-3282(0100662-7)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 36

    Bunck MC, Poelma M, Eekhoff EM, Schweizer A, Heine RJ, Nijpels G, Foley JE, Diamant M. Effects of vildagliptin on postprandial markers of bone resorption and calcium homeostasis in recently diagnosed, well-controlled type 2 diabetes patients. Journal of Diabetes 2012 4 181–185. (https://doi.org/10.1111/j.1753-0407.2011.00168.x)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 37

    Al-Shoumer KA, Vasanthy BA, Al-Zaid MM. Effects of treatment of hyperthyroidism on glucose homeostasis, insulin secretion, and markers of bone turnover. Endocrine Practice 2006 12 121–130. (https://doi.org/10.4158/EP.12.2.121)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 38

    Eriksen EF, Mosekilde L, Melsen F. Kinetics of trabecular bone resorption and formation in hypothyroidism: evidence for a positive balance per remodeling cycle. Bone 1986 7 101–108. (https://doi.org/10.1016/8756-3282(8690681-2)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 39

    Belaya ZE, Melnichenko GA, Rozhinskaya LY, Fadeev VV, Alekseeva TM, Dorofeeva OK, Sasonova NI, Kolesnikova GS. Subclinical hyperthyroidism of variable etiology and its influence on bone in postmenopausal women. Hormones 2007 6 62–70.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 40

    Grimnes G, Emaus N, Joakimsen RM, Figenschau Y, Jorde R. The relationship between serum TSH and bone mineral density in men and postmenopausal women: the Tromso study. Thyroid 2008 18 1147–1155. (https://doi.org/10.1089/thy.2008.0158)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 41

    Nagata M, Suzuki A, Sekiguchi S, Ono Y, Nishiwaki-Yasuda K, Itoi T, Yamamoto S, Imamura S, Katoh T & Hayakawa N et al.Subclinical hypothyroidism is related to lower heel QUS in postmenopausal women. Endocrine Journal 2007 54 625–630. (https://doi.org/10.1507/endocrj.k06-201)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 42

    Siru R, Alfonso H, Chubb SAP, Golledge J, Flicker L, Yeap BB. Subclinical thyroid dysfunction and circulating thyroid hormones are not associated with bone turnover markers or incident hip fracture in older men. Clinical Endocrinology 2018 89 93–99. (https://doi.org/10.1111/cen.13615)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 43

    Tsourdi E, Wallaschofski H, Rauner M, Nauck M, Pietzner M, Rettig R, Ittermann T, Volzke H, Volker U & Hofbauer LC et al.Thyrotropin serum levels are differentially associated with biochemical markers of bone turnover and stiffness in women and men: results from the SHIP cohorts. Osteoporosis International 2016 27 719–727. (https://doi.org/10.1007/s00198-015-3276-x)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 44

    Murphy E, Gluer CC, Reid DM, Felsenberg D, Roux C, Eastell R, Williams GR. Thyroid function within the upper normal range is associated with reduced bone mineral density and an increased risk of nonvertebral fractures in healthy euthyroid postmenopausal women. Journal of Clinical Endocrinology and Metabolism 2010 95 3173–3181. (https://doi.org/10.1210/jc.2009-2630)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 45

    Schneider R, Schneider M, Reiners C, Schneider P. Effects of levothyroxine on bone mineral density, muscle force, and bone turnover markers: a cohort study. Journal of Clinical Endocrinology and Metabolism 2012 97 3926–3934. (https://doi.org/10.1210/jc.2012-2570)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 46

    Olkawa M, Kushida K, Takahashi M, Ohishi T, Hoshino H, Suzuki M, Ogihara H, Ishigaki J, Inoue T. Bone turnover and cortical bone mineral density in the distal radius in patients with hyperthyroidism being treated with antithyroid drugs for various periods of time. Clinical Endocrinology 1999 50 171–176. (https://doi.org/10.1046/j.1365-2265.1999.00626.x)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 47

    Zhang W, Zhang Y, Liu Y, Wang J, Gao L, Yu C, Yan H, Zhao J, Xu J. Thyroid-stimulating hormone maintains bone mass and strength by suppressing osteoclast differentiation. Journal of Biomechanics 2014 47 1307–1314. (https://doi.org/10.1016/j.jbiomech.2014.02.015)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 48

    Abe E, Marians RC, Yu W, Wu XB, Ando T, Li Y, Iqbal J, Eldeiry L, Rajendren G & Blair HC et al.TSH is a negative regulator of skeletal remodeling. Cell 2003 115 151–162. (https://doi.org/10.1016/s0092-8674(0300771-2)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 49

    Ejima E, Fujiyama K, Kiriyama T, Eguchi K. Bone changes in thyrotoxicosis. Nihon Rinsho 1998 56 1587–1590.

  • 50

    Gereben B, Zavacki AM, Ribich S, Kim BW, Huang SA, Simonides WS, Zeold A, Bianco AC. Cellular and molecular basis of deiodinase-regulated thyroid hormone signaling. Endocrine Reviews 2008 29 898–938. (https://doi.org/10.1210/er.2008-0019)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 51

    Wang X, Liu H, Chen J, Huang Y, Li L, Rampersad S, Qu S. Metabolic characteristics in obese patients complicated by mild thyroid hormone deficiency. Hormone and Metabolic Research 2016 48 331–337. (https://doi.org/10.1055/s-0042-105150)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 52

    Polovina SP, Miljic D, Zivojinovic S, Milic N, Micic D, Brkic VP. The impact of thyroid autoimmunity (TPOAb) on bone density and fracture risk in postmenopausal women. Hormones 2017 16 54–61. (https://doi.org/10.14310/horm.2002.1719)

    • PubMed
    • Search Google Scholar
    • Export Citation