MECHANISMS IN ENDOCRINOLOGY: Diabetes mellitus, a ......Diabetes mellitus, a state of low bone turnover – a systematic review and meta-analysis Katrine Hygum ... whether a bone signaling

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Published by Bioscientifica Ltd.DOI: 10.1530/EJE-16-0652

MECHANISMS IN ENDOCRINOLOGY

Diabetes mellitus, a state of low bone turnover – a systematic review and meta-analysisKatrine Hygum1,*, Jakob Starup-Linde1,2,*, Torben Harsløf1, Peter Vestergaard3 and Bente L Langdahl1

1Department of Endocrinology and Internal Medicine, Aarhus University Hospital, Aarhus C, Denmark, 2Department of Infectious Diseases, Aarhus University Hospital, Aarhus N, Denmark, and 3Department of Clinical Medicine and Endocrinology, Aalborg University Hospital, Aalborg, Denmark*(K Hygum and J Starup-Linde contributed equally to this work)

Abstract

Objective: To investigate the differences in bone turnover between diabetic patients and controls.

Design: A systematic review and meta-analysis.

Methods: A literature search was conducted using the databases Medline at PubMed and EMBASE. The free text

search terms ‘diabetes mellitus’ and ‘bone turnover’, ‘sclerostin’, ‘RANKL’, ‘osteoprotegerin’, ‘tartrate-resistant acid’

and ‘TRAP’ were used. Studies were eligible if they investigated bone turnover markers in patients with diabetes

compared with controls. Data were extracted by two reviewers.

Results: A total of 2881 papers were identified of which 66 studies were included. Serum levels of the bone resorption

marker C-terminal cross-linked telopeptide (−0.10 ng/mL (−0.12, −0.08)) and the bone formation markers osteocalcin

(−2.51 ng/mL (−3.01, −2.01)) and procollagen type 1 amino terminal propeptide (−10.80 ng/mL (−12.83, −8.77)) were

all lower in patients with diabetes compared with controls. Furthermore, s-tartrate-resistant acid phosphatase

was decreased in patients with type 2 diabetes (−0.31 U/L (−0.56, −0.05)) compared with controls. S-sclerostin was

significantly higher in patients with type 2 diabetes (14.92 pmol/L (3.12, 26.72)) and patients with type 1 diabetes

(3.24 pmol/L (1.52, 4.96)) compared with controls. Also, s-osteoprotegerin was increased among patients with diabetes

compared with controls (2.67 pmol/L (0.21, 5.14)).

Conclusions: Markers of both bone formation and bone resorption are decreased in patients with diabetes.

This suggests that diabetes mellitus is a state of low bone turnover, which in turn may lead to more fragile bone.

Altered levels of sclerostin and osteoprotegerin may be responsible for this.

Introduction

Patients with diabetes suffer from a higher risk of fracture than their healthy peers (1, 2).

One way of assessing fracture risk is by estimating the bone mineral density (BMD) by dual X-ray absorptiometry (DXA) (3). Interestingly, for patients with type 1 and type 2 diabetes, BMD underestimates

the fracture risk. Compared with controls, patients with type 1 diabetes have a lower BMD and type 2 diabetes have a higher BMD, but these differences in BMD do not explain the observed increased fracture risk (4). Bone tissue biopsies using histomorphometric analysis with dynamic indices may also evaluate bone turnover,

www.eje-online.org © 2017 European Society of Endocrinology

176:3 R137–R157K Hygum, J Starup-Linde and others

Bone turnover in diabetes mellitus

European Journal of Endocrinology (2017) 176, R137–R157

176:3

10.1530/EJE-16-0652

Review

Correspondence should be addressed to K Hygum Email [email protected]

Downloaded from Bioscientifica.com at 06/04/2021 04:41:50PMvia free access

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gy176:3 R138Review K Hygum, J Starup-Linde

and othersBone turnover in diabetes mellitus

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but at present, clinical studies investigating bone tissue biopsies in patients with diabetes have been scarce and with no comparison between patients with type 1 and type 2 diabetes (5, 6, 7). Bone turnover may be assessed by measuring biochemical markers. These bone markers reflect the bone turnover process and hence mirror the bone resorption and formation processes (8) and are known to be predictors of fracture in non-diabetes individuals (9). Figure 1 depicts the process, regulators and products of bone turnover.

Numerous previous studies indicate that bone turnover markers differ in patients with diabetes and healthy controls (10, 11), thus suggesting an altered bone metabolism in diabetic bone. A meta-analysis performed in 2014 revealed that osteocalcin and C-terminal cross-linked telopeptide (CTX) were significantly lower in patients with diabetes compared with controls, indicating a suppressed bone formation and resorption respectively (11). Since these findings were made, more studies have evaluated bone turnover markers in diabetes, including the bone marker sclerostin.

The role of sclerostin in diabetic bone turnover is controversial. Thus, it was recently proven that sclerostin levels are surprisingly inversely associated with fracture risk in patients with type 1 diabetes (12), whereas increasing sclerostin levels have been associated with increased fracture risk in patients with type 2 diabetes (13, 14, 15). The significance of this finding, however, so far defies solution.

The aim of the present study was to conduct an updated meta-analysis of the literature investigating the levels of biochemical markers of bone turnover in patients with diabetes types 1 and 2 compared with controls. The present study will also provide an overview of the current knowledge on the altered bone turnover in patients with diabetes.

Methods

The PRISMA guidelines (16) were used.

Data sources, searches and eligibility criteria

A systematic literature search was conducted in association with a research librarian in November 2015 and updated in September 2016. The databases Medline at PubMed (1966–2016) and EMBASE (1974–2016) were explored using the free text search terms: ‘diabetes mellitus’ and ‘bone turnover’. To avoid omitting studies investigating more seldom studied markers such as osteoprotegerin (OPG), receptor activator of nuclear factor kappa-B ligand (RANKL), sclerostin and tartrate-resistant acid phosphatase (TRAP), free text searches were performed using the terms: ‘diabetes mellitus’, ‘sclerostin’, ‘RANKL’, ‘osteoprotegerin’, ‘tartrate-resistant acid’, and ‘TRAP’.

No restriction was applied regarding publication date. We chose to use free text terms to gather as many eligible studies as possible; however, the free text terms also lead to a number of irrelevant papers.

The eligibility criterion for the included studies was to investigate biochemical bone turnover markers in both patients with diabetes mellitus and in non-diabetic controls. Both observational and interventional studies were included. Different studies exploring identical populations were excluded, and only the study deemed of best quality by the authors were included. We investigated markers of bone resorption (CTX, N-terminal cross-linked telopeptide of type 1 collagen (NTX), and TRAP), bone formation (procollagen type 1 amino terminal propeptide (P1NP)), osteocalcin, and bone-specific

RANKL

OPG

Scleros�n

OsteoblastOsteoclast

Osteocyte

Bone forma�on Bone resorp�on

P1NP, Osteocalcin, BAP CTX, NTX, TRAP

Bone

Blood

Figure 1

Overview of bone turnover and secreted products in the

blood. White arrows are inhibitory actions, gray arrows

stimulatory actions and black arrows secreted products.

Sclerostin is produced by the osteocytes and decreases bone

formation by inhibiting the Wnt pathway. Receptor activator

of nuclear factor kappa-B ligand (RANKL) and osteoprotegerin

(OPG) are produced by the osteoblast. RANKL induces

osteoclast differentiation and activation, and OPG is the

antagonist of RANKL. Procollagen type 1 amino terminal

propeptide (P1NP), osteocalcin and bone-specific alkaline

phosphatase (BAP) are products released to the blood during

bone formation. C-terminal cross-linked telopeptide (CTX),

N-terminal cross-linked telopeptide of type 1 collagen (NTX)

and tartrate-resistant acid phosphatase (TRAP) are products

released to the blood during bone resorption.


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alkaline phosphatase (BAP) and markers of bone turnover signaling (OPG, RANKL and sclerostin). Only the previously mentioned markers were eligible for our study. These specific markers were chosen to investigate whether bone turnover differs in patients with diabetes types 1 and 2 and in non-diabetic controls, and also to determine whether a bone signaling pathway may be affected.

Data extraction and quality assessment

The literature search recovered 1989 papers from EMBASE and 892 papers from Medline at PubMed after removing duplicates. Each full text paper was assessed by title and abstract, and if it was a possible candidate for inclusion in the meta-analysis, it was later assessed by full text to determine its eligibility. In total, 66 studies were included. The relevant data were extracted from each included paper and tabulated independently by J S-L and K H.

The data were screened by two authors (J S-L and K H). The data extracted from the papers included certain characteristics of the study population (age, BMI, gender, diabetes type and diabetes duration), study design, fasting status at the time of laboratory samples, follow-up years, glycated hemoglobin A1c (HbA1c), p-glucose at the time of measurement, markers of bone resorption and formation and bone turnover signaling markers. A single study may report several different populations available for analysis as they may present bone markers stratified by for example age or gender.

Data that may confound the observed bone turnover marker levels either due to clinical (age and gender) or methodological (design) impact were extracted from the relevant papers. A few studies classified diabetes as insulin-dependent diabetes mellitus (IDDM) or non-insulin-dependent diabetes mellitus (NIDDM). In the pooled analysis, these classifications have been converted to type 1 diabetes and type 2 diabetes respectively. NIDDM may only comprise patients with type 2 diabetes as patients with type 1 diabetes per definition are insulin dependent. The IDDM classification may hence contain both type 1 diabetes and type 2 diabetes patients, which may influence the results. Quality of studies was evaluated by two reviewers (J S-L and K H), and quality was ascertained by the modified Newcastle-Ottawa Scale adapted for cross-sectional studies (17), Supplementary Fig. 1 (see section on supplementary data given at the end of this article). Studies of longitudinal and randomized controlled designs were quality assessed by the same scale.

Statistical analysis

The mean values and standard deviation or 95% confidence intervals of biochemical markers were evaluated. The common weighted mean difference (MD) and the standardized mean difference (SMD) were analyzed using the random effects model. The SMD takes assay and inter-laboratory differences into account as percentages are calculated. If no discrepancies were found when applying either the MD or the SMD, only the MD has been reported. For bone-specific alkaline phosphatase, only the standardized mean difference was estimated owing to concentrations being provided in both µmol/L and U/L for which no conversion factor is known. Pooled analyses were implemented if at least three populations were available. Heterogeneity among studies was determined by I2 analysis. The possibility of a publication bias was evaluated visually by funnel plot. Subgroup analysis by type 1 diabetes and type 2 diabetes was performed. The RevMan 5.3 software program was applied. Meta-regression analysis was performed to assess the effect modification of plasma glucose values, HbA1c and diabetes duration using the difference in marker values between subjects with and without diabetes. Meta-regression was performed separately for patients with type 1 and type 2 diabetes. To perform a meta-regression, data from at least three populations had to be available.

Records iden�fied through database searching

(n = 2881 )

Records screened by �tle and abstract(n =2881)

Full-text ar�cles assessed for eligibility

(n = 79 )Records excluded

(n =13)

Studies included in qualita�ve synthesis

(n = 66 )

Figure 2

Flow diagram of studies.


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Table 1 Characteristics of the included studies.

Study Participants Comments HbA1c P-glucose BTM measured

Samples taken in fasting condition

NOS score (0–10) Renal disease

Cross-sectional studies Karaguzel et al. (46) 58 T1D, 44 controls Both boys and girls. Mean age 11.7 years

for T1D– – OC, P1NP, u-NTX Yes 8 No other chronic diseases

Alexopoulou et al. (47) 42 male T1D, 24 male controls

11 T1D with microalbuminuria 8.8% in T1D – CTX, OPG, OC Yes 8 All had normal eGFR

Lumachi et al. (48) 18 IDDM, 21 controls Mix of genders. BMI 22.5 in IDDM, thus likely to be T1D

– – PTH, OC, BAP Yes 6 Serum creatinine borderline significantly higher in IDDM than controls

Akin et al. (49) 57 T2D PM BMI significantly lower in controls 9.76% in T2D 5.10% in controls

204 mg/dL for T2D OC, u-NTX, BAP Yes 6 Chronic diseases excluded

20 controls PM Reyes-Garcia et al. (50) 78 T2D Both men and women 8.01% in T2D – BAP, OC, TRAP, CTX, PTH, 25 OHD Yes 8 No renal disease 55 controls T2D with significantly higher age and BMI Vertebral fractures in 27.7% of T2D and

21.7% of controls

Yamamoto et al. (51) 255 T2D, 240 controls Mix of genders, females were PM. VF in 90 T2D

9.1% in T2D, 5.6/5.7% in controls

169 mg/dL for T2D women and 166 mg/dL for T2D men

PTH, OC, P1NP, CTX, 25 OHD Yes 7 Excluded if serum creatinine was higher than normal range

Jiajue et al. (52) 236 T2D PM, 1055 controls PM

VF and non VF fractures assessed in the population. Controls were significantly younger than T2D

– 7.71 mmol/L for T2D CTX, P1NP, 25 OHD Yes 7 Renal disease excluded

Farr et al. (53) 30 T2D PM BMI significantly lower in controls 7.7% in T2D, 5.4% in controls

– P1NP, CTX, 25 OHD Yes 8 Stage 4 and 5 chronic kidney disease excluded

30 controls PM Performs microindentation Manavalan et al. (5) 18 T2D PM Performs bone biopsies on 9 subjects 8.4% in T2D, 5.8% in

controls169 mg/dL for T2D PTH, 25 OHD, P1NP, BAP, OC,

TRAP-5b, CTXYes 9 eGFR

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Table 1 Characteristics of the included studies.




Cross-sectional studies Karaguzel et al. (46) 58 T1D, 44 controls Both boys and girls. Mean age 11.7 years

for T1D– – OC, P1NP, u-NTX Yes 8 No other chronic diseases

Alexopoulou et al. (47) 42 male T1D, 24 male controls

11 T1D with microalbuminuria 8.8% in T1D – CTX, OPG, OC Yes 8 All had normal eGFR

Lumachi et al. (48) 18 IDDM, 21 controls Mix of genders. BMI 22.5 in IDDM, thus likely to be T1D

– – PTH, OC, BAP Yes 6 Serum creatinine borderline significantly higher in IDDM than controls

Akin et al. (49) 57 T2D PM BMI significantly lower in controls 9.76% in T2D 5.10% in controls

204 mg/dL for T2D OC, u-NTX, BAP Yes 6 Chronic diseases excluded

20 controls PM Reyes-Garcia et al. (50) 78 T2D Both men and women 8.01% in T2D – BAP, OC, TRAP, CTX, PTH, 25 OHD Yes 8 No renal disease 55 controls T2D with significantly higher age and BMI Vertebral fractures in 27.7% of T2D and

21.7% of controls

Yamamoto et al. (51) 255 T2D, 240 controls Mix of genders, females were PM. VF in 90 T2D

9.1% in T2D, 5.6/5.7% in controls

169 mg/dL for T2D women and 166 mg/dL for T2D men

PTH, OC, P1NP, CTX, 25 OHD Yes 7 Excluded if serum creatinine was higher than normal range

Jiajue et al. (52) 236 T2D PM, 1055 controls PM

VF and non VF fractures assessed in the population. Controls were significantly younger than T2D

– 7.71 mmol/L for T2D CTX, P1NP, 25 OHD Yes 7 Renal disease excluded

Farr et al. (53) 30 T2D PM BMI significantly lower in controls 7.7% in T2D, 5.4% in controls

– P1NP, CTX, 25 OHD Yes 8 Stage 4 and 5 chronic kidney disease excluded

30 controls PM Performs microindentation Manavalan et al. (5) 18 T2D PM Performs bone biopsies on 9 subjects 8.4% in T2D, 5.8% in

controls169 mg/dL for T2D PTH, 25 OHD, P1NP, BAP, OC,

TRAP-5b, CTXYes 9 eGFR

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Chailurkit et al. (25) 54 T2D, 55 controls All postmenopausal women – 6.8 mmol/L in T2D and 5.0 in controls

CTX, OPG Yes 6 No information on renal status

Tsentidis et al. (65) 40 T1D, 40 controls Mean age 13 years 8.2 vs 4.7% in T1D and controls, respectively

– Sclerostin No information

8 Chronic diseases excluded


9.2 and 4.6 mmol/L in T1D and controls, respectively

OPG,RANKL, CTX, OC Yes 9 Chronic diseases excluded

Inoue et al. (67) 53 T2D, 832 controls Evaluates the efficacy and safety of risedronate

– – NTX, CTX, BAP No information

5 Renal disease excluded

Lopes et al. (68) 23 T2D, 20 controls All females PM, younger than 65 years, osteoporotic/osteopenic

T2D: 7.8% Controls. Normal fasting glucose

CTX, OC No, after mixed meal test

8 Kidney failure excluded

Alselami et al. (69) 65 T2D, 20 controls All females, obese, PM, from Saudi Arabia. T2D divided into two groups (controlled n = 29/uncontrolled n = 36) according to HbA1c

T2D controlled: 5.43%. T2D uncontrolled: 9.19%. Controls: 5.13%

T2D controlled: 5.63 mmol/L. T2D uncontrolled: 11.2. Control: 4.00 mmol/L

Ca, Phosphorus, PTH, 1,25(OH)2-D, OC, P1NP, cathepsin K

No information

5 No information on renal status

Abdalrahman et al. (70, 71) 25 T1D, 24 controls All females, mean age 22 years T1D: 9.8% – OC, BAP, CTX, 25-OHD, leptin, IGF-1, PTH

Non-fasting (afternoon samples)


Petrova et al. (72) (Group 1) 35 DM and Charcot foot. (Group 2) 34 DM (Group 3) 12 healthy controls

(1) 17 with T1D and 18 with T2D. (2) 17 with T1D and 17 with T2D

(1) 7.9%. (2) 8.7%. (3) No information

– CTX, TRAP, BAP, OPG, RANKL No information

7 No information

Neumann et al. (73) 128 T1D, 77 controls Mean age 43 years T1D: 61 mmol/mol. Controls: 34.8 mmol/mol

T1D: 9.8 mmol/L. Controls 5.22 mmol/L

25-OHD, CTX, OC, calcium, sclerostin Overnight fast

8 Renal disease (eGFR less than 30 mL/min) excluded

Gennari et al. (74) 43 T1D, 40 T2D, 21 young healthy volunteers as controls to T1D and 62 older men and postmenopausal women as controls to T2D

T1D significantly older than their controls 7.7 and 7.2% for T1D and T2D, respectively

132 and 140 mg/dL of T1D and T2D, respectively

BAP, OC, CTX Yes 9 Renal disease excluded

Shu et al. (75) 25 postmenopausal T2D, 25 postmenopausal controls

T2D was defined as the presence of a fasting plasma glucose >126 mg/dL and use of an antiglycemic medication. As well as exclusion of T1D

7.9% in T2D 139 mg/dL for T2D P1NP, BAP, OC, CTX, NTX Yes 9 Renal disease excluded

Gerdhem et al. (76) 74 female diabetics, 1058

female controlsAll were 75 years old. Diabetics were

significantly heavier (5 kg) than non-diabetics. Yet BMI was not assessed

– – OC, CTX, BAP No 6 Normal mean creatinine levels

Okuno et al. (77) 189 hemodialysis patients, 96 of those with diabetes

Diabetics had a significantly higher BMI and lower duration in hemodialysis than non-diabetics

6.5% for T2D 165 mg/dL for T2D TRAP, BAP, OC No 6 Yes, all in hemodialysis

Galluzzi et al. (78) 26 prepubertal T1D, 45 age, sex and body sized controls

T1DM was defined by the National Diabetes Data Group. Recruited at a hospital

8.4% for T1D – OPG Yes 8 Renal disease excluded

Garcia-Martin et al. (79) 74 T2D, 50 controls Diagnosis of diabetes according to American Diabetes Association criteria

8.1% in T2D 176 mg/dL for T2D CTX, BAP, TRAP, OC, sclerostin Yes 9 Renal disease excluded

Lappin et al. (80) 63 T1D, 38 controls – T1D: 30 with HbA1c 8.5%

– RANKL, OPG, OC No information

5 No information

Dayem et al. (81) 47 young T1D, 30 sex and aged matched healthy controls

Outpatient clinic 8.8% in T1D – OC, P1NP, OPG Yes 6 Renal disease excluded

Heilmeier et al. (82) 40 T2D, 40 controls Women age 50–75. T2D and controls divided in fragility fracture group and non fracture group

8.0% and 7.9% for T2D with and without fragility fracture, respectively

151 and 160 mg/dL for T2D with and without fragility fracture, respectively

25-OHD, PTH, calcium, sclerostin, CTX P1NP

Yes 7 Renal disease excluded

Table 1 Continued.



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Chailurkit et al. (25) 54 T2D, 55 controls All postmenopausal women – 6.8 mmol/L in T2D and 5.0 in controls

CTX, OPG Yes 6 No information on renal status


– Sclerostin No information

8 Chronic diseases excluded


9.2 and 4.6 mmol/L in T1D and controls, respectively

OPG,RANKL, CTX, OC Yes 9 Chronic diseases excluded

Inoue et al. (67) 53 T2D, 832 controls Evaluates the efficacy and safety of risedronate

– – NTX, CTX, BAP No information


Lopes et al. (68) 23 T2D, 20 controls All females PM, younger than 65 years, osteoporotic/osteopenic

T2D: 7.8% Controls. Normal fasting glucose

CTX, OC No, after mixed meal test

8 Kidney failure excluded

Alselami et al. (69) 65 T2D, 20 controls All females, obese, PM, from Saudi Arabia. T2D divided into two groups (controlled n = 29/uncontrolled n = 36) according to HbA1c

T2D controlled: 5.43%. T2D uncontrolled: 9.19%. Controls: 5.13%

T2D controlled: 5.63 mmol/L. T2D uncontrolled: 11.2. Control: 4.00 mmol/L

Ca, Phosphorus, PTH, 1,25(OH)2-D, OC, P1NP, cathepsin K

No information

5 No information on renal status

Abdalrahman et al. (70, 71) 25 T1D, 24 controls All females, mean age 22 years T1D: 9.8% – OC, BAP, CTX, 25-OHD, leptin, IGF-1, PTH

Non-fasting (afternoon samples)


Petrova et al. (72) (Group 1) 35 DM and Charcot foot. (Group 2) 34 DM (Group 3) 12 healthy controls

(1) 17 with T1D and 18 with T2D. (2) 17 with T1D and 17 with T2D

(1) 7.9%. (2) 8.7%. (3) No information

– CTX, TRAP, BAP, OPG, RANKL No information

7 No information

Neumann et al. (73) 128 T1D, 77 controls Mean age 43 years T1D: 61 mmol/mol. Controls: 34.8 mmol/mol

T1D: 9.8 mmol/L. Controls 5.22 mmol/L

25-OHD, CTX, OC, calcium, sclerostin Overnight fast

8 Renal disease (eGFR less than 30 mL/min) excluded

Gennari et al. (74) 43 T1D, 40 T2D, 21 young healthy volunteers as controls to T1D and 62 older men and postmenopausal women as controls to T2D

T1D significantly older than their controls 7.7 and 7.2% for T1D and T2D, respectively

132 and 140 mg/dL of T1D and T2D, respectively

BAP, OC, CTX Yes 9 Renal disease excluded

Shu et al. (75) 25 postmenopausal T2D, 25 postmenopausal controls

T2D was defined as the presence of a fasting plasma glucose >126 mg/dL and use of an antiglycemic medication. As well as exclusion of T1D

7.9% in T2D 139 mg/dL for T2D P1NP, BAP, OC, CTX, NTX Yes 9 Renal disease excluded

Gerdhem et al. (76) 74 female diabetics, 1058

female controlsAll were 75 years old. Diabetics were

significantly heavier (5 kg) than non-diabetics. Yet BMI was not assessed

– – OC, CTX, BAP No 6 Normal mean creatinine levels

Okuno et al. (77) 189 hemodialysis patients, 96 of those with diabetes

Diabetics had a significantly higher BMI and lower duration in hemodialysis than non-diabetics

6.5% for T2D 165 mg/dL for T2D TRAP, BAP, OC No 6 Yes, all in hemodialysis

Galluzzi et al. (78) 26 prepubertal T1D, 45 age, sex and body sized controls

T1DM was defined by the National Diabetes Data Group. Recruited at a hospital

8.4% for T1D – OPG Yes 8 Renal disease excluded

Garcia-Martin et al. (79) 74 T2D, 50 controls Diagnosis of diabetes according to American Diabetes Association criteria

8.1% in T2D 176 mg/dL for T2D CTX, BAP, TRAP, OC, sclerostin Yes 9 Renal disease excluded

Lappin et al. (80) 63 T1D, 38 controls – T1D: 30 with HbA1c 8.5%

– RANKL, OPG, OC No information

5 No information

Dayem et al. (81) 47 young T1D, 30 sex and aged matched healthy controls

Outpatient clinic 8.8% in T1D – OC, P1NP, OPG Yes 6 Renal disease excluded

Heilmeier et al. (82) 40 T2D, 40 controls Women age 50–75. T2D and controls divided in fragility fracture group and non fracture group

8.0% and 7.9% for T2D with and without fragility fracture, respectively

151 and 160 mg/dL for T2D with and without fragility fracture, respectively

25-OHD, PTH, calcium, sclerostin, CTX P1NP


Continued



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Nan et al. (83) 49 T2D and 79 age and sex matched controls

Conference abstract – – OC, CTX No information

3 No information

Olmos et al. (84) 94 T1D, 64 controls T1D-group incl. 4 postmenopausal women T1D: 11.2%. Controls: 7.0%

177 mg/dL for T1D Ca, phosphorus, BAP, TRAP, OC, urinary hydroxyproline


Loureiro et al. (85) 75 T1D. 100 controls T1D age 6–20 years T1D: 10.1%. Controls: 6.9%

206 mg/dL for T1D Ca, phosphorus, ALP, TRAP, Mg, OC No information

7 No information

Lambronoudaki et al. (86) 56 T1D. 28 controls T1D mean age 12 years T1D: 8.02%. Controls: 4.12%

143 mg/dL for T1D OPG, RANKL Yes 9 Renal disease excluded

Singh et al. 2010 (87) 35 T1D. 25 controls T1D mean age 44 years T1D: 8.3%. Controls: 5.4% 8.4 mmol/L for T1D ALP, PTH, Ca, Phosphorus, Mg, OPG, RANKL, 25-OHD, 1,25-2OHD


Feldbrin et al. (88) 33 with T2D and hypertension. 39 with T2D without hypertension. 28 controls

55 postmenopausal women, 45 men T2D with hypertension: 8.1%. T2D without hypertension: 6.7%

T2D with hypertension: 173 mg/dL. T2D without hypertension: 103 mg/dL

OPG, P1NP Samples taken between 08:00 and 10:00 h – no information on fasting status


Oz et al. (89) 52 T2D, 48 controls of similar age, sex and BM

Diabetes diagnosis according to American Diabetes Association criteria

– 180 mg/dL for T2D CTX, OC, BAP Yes 8 Renal disease excluded

Achemlal et al. (90) 35 male T2D, 35 male controls

Blood samples were taken early in the morning

9.5% in T2D – CTX, OC No information


Dobnig et al. (91) 583 female T2D, 1081 female controls

Patients were classified as T2D if they had a diagnosis of DM in their medical chart, had anti diabetic drugs prescribed, or were found with a HbA1c level of more than 5.9%

6.5% for T2D – OC, CTX No 9 Renal disease excluded

Neumann et al. (92) 128 T1D, 77 controls Recruited from an outpatient clinic 7.8% for T1D – CTX, OC No information


Mastrandea et al. (93) 63 T1D females, 83

female controlsFollowed through 2 years. The T1D younger

than 20 years smoked significantly more than the controls

8.2 and 7.4% for T1D dependent on age

– OC, NTX No 9 Renal disease excluded

Zhou et al. (94) 890 postmenopausal T2D, 689 postmenopausal controls

In- and out-patients at a hospital. Divides by BMI

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Results

Search results

A total of 2881 papers were identified of which 66 studies were suitable for inclusion in the meta-analysis, Fig. 2 for study flow. The included studies comprised 62 cross-sectional studies, three randomized controlled trials and one longitudinal study and differed in number of participants ranging from 16 to 890 patients with diabetes and from ten to 2053 non-diabetic controls. In general, the studies reported fasting bone turnover marker values and excluded patients with renal disease. The investigated populations ranged from children to the elderly. The quality of the studies was fair with a study quality score ranging between three and ten, and only two studies scored a study quality less than five. Table 1 shows the included studies regarding characteristics of participants, study size, levels of HbA1c and p-glucose, Newcastle-Ottawa Scale score and features of measurements of bone

turnover markers. The total number of studies exploring the different bone turnover markers varied greatly from only seven studies reporting on levels of RANKL to 45 studies with data on osteocalcin.

Results for each meta-analysis

The resorptive bone turnover marker CTX was lower in patients with diabetes compared with controls (−0.10 ng/mL (−0.12, −0.08)). Figure 3 presents the pooled results of CTX. The bone formation markers osteocalcin (−2.51 ng/mL (−3.01, −2.01)) and P1NP (−10.80 ng/mL (−12.83, −8.77)) were also lower for patients with diabetes compared with controls. Figures 4 and 5 present the pooled results of P1NP and osteocalcin respectively. For CTX, osteocalcin and P1NP, neither the results nor the significance of the findings were different when analyzing the SMD. The bone turnover signaling marker OPG was higher in patients with diabetes compared with controls (2.67 pmol/L




Razi et al. (100) 55 diabetics, 55 controls All postmenopausal women. No information on type of diabetes

7.9% (diabetics), 5.5% (controls)

177 mg/dL (diabetics), 97 mg/dL (controls)

Ca, phosphorus, 25 OHD, ALP, BAP, PTH No information


Furst et al. (101) 16 T2D, 19 controls All postmenopausal. Biochemical analyses, microindentation and skin autofluorescence

8.3% (T2D), 5.8% (controls)

150 mg/dL (T2D), 87 mg/dL (controls)

25 OHD, PTH, TSH, P1NP, CTX Yes 8 Renal disease excluded

Chrysis et al. (102) 56 T1D, 46 controls Children age 12.1 (T1D) and 11.3 (controls) 8.15% (T1D), no information on controls

Yes OPG, RANKL No information

8 No information

Shou et al. (103) 373 T2D, 943 controls Chinese men older than 80 years – – CTX, P1NP, OC Yes 7 Renal disease excludedHua et al. (104) 46 T2D, 40 controls Measured BTM safer intake of steamed

bread– – P1NP, CTX Yes 4 No information

Randomized controlled trials Berberoglu et al. (105) 56 obese T2D PM, 26

controls PM12 weeks randomization to rosiglitazone

and diet or diet alone6.34% treated T2D, 5.96

in non treated T2D119 mg/dL for T2D BAP, OC, DPD, Interleukin 1 and 6,

TNF-αYes 6 Renal disorders excluded

Van Lierop et al. (106) 71 male T2D 24 weeks randomization to pioglitazone or metformin. Baseline compared with controls

– – Sclerostin, CTX, P1NP Yes 6 All had normal renal function

30 male controls Keegan et al. (107) 6458 PM of these 297 T2D Data from the fracture intervention trial.

Post hoc analysis of randomized controlled trial. Randomization to alendronate or placebo for 3 years

– – CTX, NTX, BAP 20% had fasting specimens

6 Factors that affect bone turnover were excluded

Longitudinal studies Pater et al. (108) 17 T1D, 17 controls Mix of genders. All children. Follow from

T1D onset and 12 months forward11.3% at T1D onset 7.1%

at 12 months after T1D onset. 5.6/5.5% in controls

– OC, CTX, TRAP5b Yes 7 No other chronic diseases

Table 1 Continued.



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(0.21, 5.14), Supplementary Fig. 2). When analyzing the SMD, the result remained in favor of a higher level of OPG in diabetes compared with controls, however, insignificant (0.83 (−0.17, 1.83)). Sclerostin was borderline significantly higher for patients with diabetes compared with controls (10.51 pmol/L (−0.80, 21.81), Supplementary Fig. 3), the result was consistent when analyzing the SMD. No differences were observed between patients with diabetes and controls regarding the markers TRAP, NTX, BAP and RANKL, Supplementary Fig. 4. All markers displayed significant heterogeneity with 65% heterogeneity being the lowest.

Funnel plots evaluated visually were found adequate for all analyses with no publication bias.

Subgroup analysis by diabetes type

TRAP was significantly lower in patients with type 2 diabetes compared with controls (−0.31 U/L (−0.56, −0.05)),

whereas no significance was apparent when comparing type 1 diabetes and controls (P = 0.90), Supplementary Fig. 5.

Sclerostin was significantly higher in patients with type 2 diabetes compared with controls (14.92 pmol/L (3.12, 26.72)), which was also the case for patients with type 1 diabetes compared with controls (3.24 pmol/L (1.52, 4.96)). Figure 6 presents the pooled results of sclerostin for patients with type 1 and type 2 diabetes. In consistency with results on all patients with diabetes compared with controls, CTX was significantly lower in both type 1 (−0.10 (−0.18, −0.01)) and type 2 (−0.11 (−0.14, −0.09)) diabetes compared with controls, and osteocalcin was lower in both type 1 (−3.08 (−4.32, −1.83)) and type 2 (−2.63 (−3.24, −2.02)) diabetes compared with controls, Supplementary Figs 6 and 7. P1NP was significantly lower in type 2 diabetes compared with controls (−10.45 (−12.53, −8.37)), but no significant difference was found regarding type 1 diabetes (P = 0.28), Supplementary Fig. 8.




Razi et al. (100) 55 diabetics, 55 controls All postmenopausal women. No information on type of diabetes

7.9% (diabetics), 5.5% (controls)

177 mg/dL (diabetics), 97 mg/dL (controls)

Ca, phosphorus, 25 OHD, ALP, BAP, PTH No information


Furst et al. (101) 16 T2D, 19 controls All postmenopausal. Biochemical analyses, microindentation and skin autofluorescence

8.3% (T2D), 5.8% (controls)

150 mg/dL (T2D), 87 mg/dL (controls)

25 OHD, PTH, TSH, P1NP, CTX Yes 8 Renal disease excluded

Chrysis et al. (102) 56 T1D, 46 controls Children age 12.1 (T1D) and 11.3 (controls) 8.15% (T1D), no information on controls

Yes OPG, RANKL No information

8 No information

Shou et al. (103) 373 T2D, 943 controls Chinese men older than 80 years – – CTX, P1NP, OC Yes 7 Renal disease excludedHua et al. (104) 46 T2D, 40 controls Measured BTM safer intake of steamed

bread– – P1NP, CTX Yes 4 No information

Randomized controlled trials Berberoglu et al. (105) 56 obese T2D PM, 26

controls PM12 weeks randomization to rosiglitazone

and diet or diet alone6.34% treated T2D, 5.96

in non treated T2D119 mg/dL for T2D BAP, OC, DPD, Interleukin 1 and 6,

TNF-αYes 6 Renal disorders excluded

Van Lierop et al. (106) 71 male T2D 24 weeks randomization to pioglitazone or metformin. Baseline compared with controls

– – Sclerostin, CTX, P1NP Yes 6 All had normal renal function

30 male controls Keegan et al. (107) 6458 PM of these 297 T2D Data from the fracture intervention trial.

Post hoc analysis of randomized controlled trial. Randomization to alendronate or placebo for 3 years

– – CTX, NTX, BAP 20% had fasting specimens

6 Factors that affect bone turnover were excluded

Longitudinal studies Pater et al. (108) 17 T1D, 17 controls Mix of genders. All children. Follow from

T1D onset and 12 months forward11.3% at T1D onset 7.1%

at 12 months after T1D onset. 5.6/5.5% in controls

– OC, CTX, TRAP5b Yes 7 No other chronic diseases

25 OHD, 25 hydroxy vitamin D; ALP, alkaline phosphatase; ADA, American Diabetes Association; BAP, bone specific alkaline phosphatase; BMD, bone mineral density; Ca, calcium; CICP, collagen type 1C propeptide; CTX, C-terminal cross-link of collagen; CVD, cardiovascular disease; DPD, deoxypyridinoline; eGFR, estimated glomerular filtration rate; FPG, fasting plasma glucose; HD, hemodialysis; HP, hydroxyproline; ICTP, type I collagen cross-linked carboxy-terminal telopeptide; IDDM, insulin dependent diabetes mellitus; IGF-1, insulin-like growth factor-1; MVD, microvascular disease; NIDDM, non-insulin-dependent diabetes mellitus; NOS, Newcastle Ottawa Scale; NTX, N-terminal propeptide type 1 collagen; OC, osteocalcin; OGTT, oral glucose tolerance test; OPG, osteoprotegerin; PM, postmenopausal; P1NP, procollagen type 1 N-terminal propeptide, RANKL, receptor activator of nuclear factor kappa-B ligand; TRAP, tartrate-resistant acid phosphatase; T1D, type 1 diabetes; T2D, type 2 diabetes; VF, vertebral fracture.


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For the remaining bone turnover markers, NTX, BAP, OPG and RANKL, no significant changes were observed when applying subgroup analyses, Supplementary Fig. 9.

For all subgroup analyses, analyzing the SMD neither changes the results nor the significance of the results, apart from sclerostin in type 1 diabetes that remained

Study or Subgroup

Abdalrahman 2015

Achemlal 2005

Alexopolou 2006

Ardawi 2013

Bhattoa 2013

Chailurkit 2008

Dobnig 2006

Farr 2014

Furst 2016

Garcia-Martin 2012

Gaudio 2012

Gennari 2012 (a)

Gennari 2012 (b)

Gerdheim 2005

Heilmeier 2015 (a)

Heilmeier 2015 (b)

Hernandez 2013 (a)

Hernandez 2013 (b)

Hernandez 2013 (c)

Hernandez 2013 (d)

Hua 2016

Jiajue 2015

Keegan 2004 (a)

Keegan 2004 (b)

Lopes 2015

Manavalan 2012

Movahed et al.

Nan et al.

Neumann 2011 females

Neumann 2011 males

Neumann et al. 2014

Oz 2006

Petrova et al.

Reyes-Garcia 2011

Shanbhogue et al. T1D

Shanbhogue et al. T2D (a)

Shanbhogue et al. T2D (b)

Shou 2016

Shu 2012

Tsentidis et al.

Yamamoto et al. men

Yamamoto et al. women

Total (95% CI)

Heterogeneity: Tau² = 0.00; Chi² = 332.11, df = 41 (P < 0.00001); I² = 88%

Test for overall effect: Z = 9.41 (P < 0.00001)

Mean

0.15

0.2

0.486

0.2425

0.19

0.37

0.34

0.305

0.322

0.212

0.4

0.31

0.272

0.217

0.315

0.267

0.219

0.273

0.286

0.378

0.319

0.356

0.382

0.34

0.49

0.44

0.47

0.257

0.35

0.38

0.37

0.3407

0.12

0.2

0.13

0.29

0.21

0.26

0.37

1.35

0.17

0.25

SD

0.09

0.1

0.226

0.0548

0.1925

0.23

0.18

0.153

0.028

0.13

0.25

0.15

0.09

0.173

0.17

0.12

0.183

0.205

0.183

0.205

0.089

0.156

0.338

0.148

0.25

0.2

1.63

0.14

0.24

0.19

0.22

0.2409

0.27

0.12

0.31

0.392

0.32

0.99

0.2

0.91

0.11

0.18

Total

30

35

42

482

68

54

359

30

16

74

40

43

40

67

20

19

84

105

84

105

46

236

148

149

23

18

102

76

65

36

127

52

34

78

25

55

26

373

25

40

132

123

3786

Mean

0.2

0.27

0.447

0.356

0.24

0.41

0.29

0.463

0.478

0.349

0.64

0.586

0.626

0.313

0.489

0.426

0.314

0.316

0.396

0.427

0.396

0.452

0.413

0.413

0.66

0.68

0.64

0.393

0.3

0.53

0.42

0.4572

0.15

0.33

0.43

0.41

0.49

0.33

0.45

1.94

0.27

0.41

SD

0.11

0.1

0.149

0.0423

0.168

0.24

0.24

0.153

0.034

0.154

0.43

0.31

0.21

0.203

0.25

0.28

0.67

0.335

0.275

0.335

0.106

0.217

0.209

0.195

0.22

0.3

1.62

0.22

0.21

0.28

0.27

0.2221

0.135

0.15

0.78

0.66

0.61

1.8

0.2

0.71

0.16

0.15

Total

28

35

24

482

68

55

588

30

19

50

40

21

62

961

19

19

189

1123

189

1123

40

1055

3087

3074

20

27

280

49

39

39

77

48

12

55

25

55

26

943

25

40

51

189

14381

Weight

3.1%

3.2%

2.3%

3.8%

2.9%

2.3%

3.6%

2.5%

3.7%

3.1%

1.3%

1.5%

3.0%

3.3%

1.5%

1.5%

2.0%

3.3%

3.0%

3.3%

3.3%

3.7%

3.1%

3.6%

1.4%

1.4%

0.3%

2.7%

2.3%

1.9%

2.7%

2.3%

1.8%

3.2%

0.4%

0.9%

0.6%

1.3%

1.9%

0.3%

3.2%

3.4%

100.0%

IV, Random, 95% CI

-0.05 [-0.10, 0.00]

-0.07 [-0.12, -0.02]

0.04 [-0.05, 0.13]

-0.11 [-0.12, -0.11]

-0.05 [-0.11, 0.01]

-0.04 [-0.13, 0.05]

0.05 [0.02, 0.08]

-0.16 [-0.24, -0.08]

-0.16 [-0.18, -0.14]

-0.14 [-0.19, -0.09]

-0.24 [-0.39, -0.09]

-0.28 [-0.42, -0.14]

-0.35 [-0.41, -0.29]

-0.10 [-0.14, -0.05]

-0.17 [-0.31, -0.04]

-0.16 [-0.30, -0.02]

-0.10 [-0.20, 0.01]

-0.04 [-0.09, 0.00]

-0.11 [-0.17, -0.05]

-0.05 [-0.09, -0.01]

-0.08 [-0.12, -0.04]

-0.10 [-0.12, -0.07]

-0.03 [-0.09, 0.02]

-0.07 [-0.10, -0.05]

-0.17 [-0.31, -0.03]

-0.24 [-0.39, -0.09]

-0.17 [-0.54, 0.20]

-0.14 [-0.21, -0.07]

0.05 [-0.04, 0.14]

-0.15 [-0.26, -0.04]

-0.05 [-0.12, 0.02]

-0.12 [-0.21, -0.03]

-0.03 [-0.15, 0.09]

-0.13 [-0.18, -0.08]

-0.30 [-0.63, 0.03]

-0.12 [-0.32, 0.08]

-0.28 [-0.54, -0.02]

-0.07 [-0.22, 0.08]

-0.08 [-0.19, 0.03]

-0.59 [-0.95, -0.23]

-0.10 [-0.15, -0.05]

-0.16 [-0.20, -0.12]

-0.10 [-0.12, -0.08]

Diabetes Control Mean Difference Mean Difference

IV, Random, 95% CI

-0.5 -0.25 0 0.25 0.5Favors [experimental] Favors [control]

Figure 3

Pooled analysis of C-terminal cross-linked telopeptide (CTX) levels in patients with diabetes compared with controls. Studies with

several populations comparing patients with diabetes and controls are explained as the author name followed by a, b, c or d to

indicate for example subdivision by age, gender or BMI.


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higher compared with controls, however, insignificant (0.22 (−0.16, 0.60)).

Meta-regression

When comparing the difference in bone turnover marker levels between patients with type 1 diabetes and controls, the plasma glucose level was a significant effect modificator of osteocalcin (β = −3.97) and RANKL (β = 124), whereas HbA1c was a significant effect modificator of sclerostin (β = −0.08), Supplementary Table 1. When comparing the differences in bone turnover marker levels between patients with type 2 diabetes and controls, the plasma glucose level was a significant effect modificator of NTX (β = −36.7) and osteoprotegerin (β = 3.47), whereas HbA1c was a significant effect modificator of P1NP (β = −1.10), osteocalcin (β = 1.28) and sclerostin (β = 9.23),

Supplementary Table 2. Diabetes duration was not a significant effect modificator for any marker in either patients with type 1 or type 2 diabetes.

Discussion

The results of the meta-analysis reported a decreased level of circulating bone turnover markers in patients with diabetes compared with non-diabetic controls concerning a variety of different bone resorption and formation markers. Increased levels of sclerostin and OPG may be responsible for this.

CTX and P1NP have been suggested by the International Osteoporosis Foundation as the appropriate bone markers when exploring bone resorption and formation in clinical and research settings (18). Levels of CTX and osteocalcin were consistently lower in diabetes

Study or Subgroup

Ardawi 2013

Bhattoa 2013

Farr 2014

Feldbrin 2015

Furst 2016

Heilmeier 2015 (a)

Heilmeier 2015 (b)

Hernandez 2013 (a)

Hernandez 2013 (b)

Hernandez 2013 (c)

Hernandez 2013 (d)

Hua 2016

Jiajue 2015

Karaguzel 2006

Manavalan 2012

Shanbhogue 2015

Shanbhogue 2015a (a)

Shanbhogue 2015a (b)

Shou 2016

Shu 2012

Van Lierop 2012

Yamamoto 2012 (a)

Yamamoto 2012 (b)

Total (95% CI)



Mean

33.7

33.7

34.3

21.5

38.4

41.3

51

29.5

34.1

38.3

45.8

40.6

45.27

356.2

42.9

39.4

36.7

32.7

32

34.3

33.8

32.1

48.8

SD

7.34

16.475

14.79

9.3

2.4

15.4

30.6

12.8

14.3

18.3

18.4

12.9

17.38

167.3

9

30.105

18.225

19.98

88.68

16

12.2

13.7

26.1

Total

482

68

30

33

16

20

19

84

105

84

105

46

236

58

18

55

26

25

373

25

71

132

123

2234

Mean

47.4

40.7

48.6

34.6

51.2

62.8

59.6

40.3

39.9

49.5

52.9

54.2

58.89

511.3

62.3

49.4

51.2

47.4

37

57.3

36

37.5

54.7

SD

7.35

20.95

14.788

15.6

3.7

19

35.6

21.37

26.81

24.75

23.46

14.8

29.66

206.5

29

31.185

40.23

41.175

148.84

28

13.8

13.4

16.6

Total

482

68

30

39

19

19

19

189

1123

189

1123

40

1055

44

27

55

26

25

943

25

20

51

189

5800

Weight

8.7%

4.7%

4.0%

5.1%

8.1%

2.5%

0.8%

6.5%

7.3%

5.5%

6.8%

5.1%

7.5%

0.1%

2.2%

2.3%

1.2%

1.1%

1.9%

2.0%

4.5%

6.3%

5.6%

100.0%

IV, Random, 95% CI

-13.70 [-14.63, -12.77]

-7.00 [-13.33, -0.67]

-14.30 [-21.78, -6.82]

-13.10 [-18.93, -7.27]

-12.80 [-14.84, -10.76]

-21.50 [-32.39, -10.61]

-8.60 [-29.71, 12.51]

-10.80 [-14.90, -6.70]

-5.80 [-8.95, -2.65]

-11.20 [-16.47, -5.93]

-7.10 [-10.88, -3.32]

-13.60 [-19.51, -7.69]

-13.62 [-16.47, -10.77]

-155.10 [-229.78, -80.42]

-19.40 [-31.10, -7.70]

-10.00 [-21.46, 1.46]

-14.50 [-31.48, 2.48]

-14.70 [-32.64, 3.24]

-5.00 [-18.09, 8.09]

-23.00 [-35.64, -10.36]

-2.20 [-8.88, 4.48]

-5.40 [-9.76, -1.04]

-5.90 [-11.08, -0.72]

-10.80 [-12.83, -8.77]


IV, Random, 95% CI

-20 -10 0 10 20Lower in diabetes Higher in diabetes

Figure 4

Pooled analysis of procollagen type 1 amino terminal propeptide (P1NP) levels in patients with diabetes compared with controls.

Studies with several populations comparing patients with diabetes and controls are explained as the author name followed by

a, b, c or d to indicate for example subdivision by age, gender or BMI.


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Study or Subgroup

Abdalrahman 2015

Aboelasrar 2010

Achemlal 2005

Akin et al.

Alexopolou et al.

Alselami et al.

Ardawi et al.

Berberoglu et al.

Bhattoa et al.

Chen et al.

Cutrim 2007 good control

Cutrim 2007 poor control

Danielson 2009

Dayem 2011

Dobnig 2006

Garcia-Martin 2012

Gennari 2012 (a)

Gennari 2012 (b)

Gerdheim 2005

Gregorio 1994 (a)

Gregorio 1994 (b)

Karaguzel 2006

Leon 1989

Lopes 2015

Loureiro 2014

Lumachi 2009

Manavalan 2012

Mastrandrea 2008 (a)

Mastrandrea 2008 (b)

Mastrandrea 2008 (c)

Mastrandrea 2008 (d)

Miazgowski 1998 (a)

Miazgowski 1998 (b)

Movahed 2012

Nan 2014

Neumann 2011 (a)

Neumann 2011 (b)

Neumann 2014

Olmos 1994

Oz 2006

Pater 2010

Reyes-Garcia 2013

Sarkar 2013

Shanbhogue 2015

Shanbhogue 2015a (a)

Shanbhogue 2015a (b)

Shou 2016

Shu 2012

Sosa 1996

Tsentidis 2015

Yamamoto 2012 (a)

Yamamoto 2012 (b)

Zhou 2010 (a)

Zhou 2010 (b)

Total (95% CI)



Mean

13.4

24.52

15.3

4.44

19.5

12.74

12.75

3.4

13.3

6.14

26.7

26.7

3.6

12.2

33.9

1.49

3.4

3.6

21.6

5.47

7.74

69.7

10.05

10.2

24.3

28.4

15.3

9.7

6.7

19.3

10.3

5.6

4.9

9.12

15.82

15.17

15.78

15.7

2.5

8.11

61.2

1.48

4.06

17.7

12.7

14.5

13

26.3

9.5

31.54

10.1

14.1

10.2

12.5

SD

4.3

10.84

4.1

3.53

8.8

4.19

4.3

3.7

13.5

2.66

3.5

3.5

1.7

14.7

20.8

1.27

2.3

1.5

9.9

0.77

0.46

39

4.9

5.4

68.9

16.4

6

5.2

3.3

8.8

4.6

1.9

2

1.31

6.77

8.18

6.93

7.37

1.3

5.72

21.8

1.25

1.97

13.8

11.5

11.2

29.56

11.7

6.5

18.19

18

5.1

0.2

0.3

Total

30

60

35

57

42

30

482

28

68

30

20

22

75

47

360

74

43

40

67

60

50

58

87

20

75

18

18

26

26

37

37

54

54

102

76

65

63

128

94

52

17

78

108

55

26

25

373

25

47

40

132

123

458

432

4749

Mean

14.3

35.69

18.3

8.82

23

18.34

17.66

3.6

20.3

10.89

17.1

17.1

4.6

49.4

40

1.5

4

5.7

29.3

7.97

7.97

127.8

10.48

14.8

44.7

41.2

20.3

10.4

7.7

18.9

12.6

4

3.5

11.22

21.12

17.17

22.17

19.7

3.4

15.78

104.3

1.45

9.62

21.6

24.9

21.3

16

36.3

8.3

37.85

30.8

22.9

12.8

16.9

SD

8.5

11.68

5.3

4.03

7.8

5.57

4.18

2

8

4.96

2.2

2.2

1.8

34.5

21.3

1.26

1.8

1.1

12.9

0.62

0.62

5.4

3.42

5.3

111

14.6

8

5.8

2.9

8.3

6.7

0.9

0.9

1.44

9.75

6.41

9.93

8.7

1.2

8.24

29.3

1.21

3.29

19.6

23

18.1

54.84

11.7

6.5

19.43

12.7

8.5

0.1

0.1

Total

28

40

35

20

24

28

482

26

68

27

24

24

75

30

588

50

21

62

961

50

50

44

49

23

100

21

27

49

49

36

36

25

25

280

49

39

39

77

64

48

17

55

50

55

26

25

943

25

252

40

51

189

371

318

6210

Weight

1.2%

0.9%

2.0%

2.2%

1.0%

1.8%

3.2%

2.5%

1.2%

2.1%

2.3%

2.4%

3.2%

0.1%

1.6%

3.2%

2.9%

3.2%

1.8%

3.3%

3.3%

0.2%

2.6%

1.4%

0.0%

0.2%

1.0%

1.8%

2.5%

1.1%

1.7%

3.2%

3.2%

3.3%

1.4%

1.6%

1.2%

1.9%

3.3%

1.6%

0.1%

3.3%

2.9%

0.5%

0.2%

0.3%

0.9%

0.5%

2.1%

0.3%

0.8%

2.5%

3.3%

3.3%

100.0%

IV, Random, 95% CI

-0.90 [-4.40, 2.60]

-11.17 [-15.71, -6.63]

-3.00 [-5.22, -0.78]

-4.38 [-6.37, -2.39]

-3.50 [-7.60, 0.60]

-5.60 [-8.15, -3.05]

-4.91 [-5.45, -4.37]

-0.20 [-1.77, 1.37]

-7.00 [-10.73, -3.27]

-4.75 [-6.85, -2.65]

9.60 [7.83, 11.37]

9.60 [7.89, 11.31]

-1.00 [-1.56, -0.44]

-37.20 [-50.24, -24.16]

-6.10 [-8.85, -3.35]

-0.01 [-0.46, 0.44]

-0.60 [-1.63, 0.43]

-2.10 [-2.64, -1.56]

-7.70 [-10.21, -5.19]

-2.50 [-2.76, -2.24]

-0.23 [-0.44, -0.02]

-58.10 [-68.26, -47.94]

-0.43 [-1.84, 0.98]

-4.60 [-7.81, -1.39]

-20.40 [-47.17, 6.37]

-12.80 [-22.62, -2.98]

-5.00 [-9.10, -0.90]

-0.70 [-3.28, 1.88]

-1.00 [-2.51, 0.51]

0.40 [-3.52, 4.32]

-2.30 [-4.94, 0.34]

1.60 [0.98, 2.22]

1.40 [0.76, 2.04]

-2.10 [-2.41, -1.79]

-5.30 [-8.43, -2.17]

-2.00 [-4.83, 0.83]

-6.39 [-9.95, -2.83]

-4.00 [-6.33, -1.67]

-0.90 [-1.29, -0.51]

-7.67 [-10.47, -4.87]

-43.10 [-60.46, -25.74]

0.03 [-0.39, 0.45]

-5.56 [-6.54, -4.58]

-3.90 [-10.24, 2.44]

-12.20 [-22.08, -2.32]

-6.80 [-15.14, 1.54]

-3.00 [-7.61, 1.61]

-10.00 [-16.49, -3.51]

1.20 [-0.82, 3.22]

-6.31 [-14.56, 1.94]

-20.70 [-25.35, -16.05]

-8.80 [-10.31, -7.29]

-2.60 [-2.62, -2.58]

-4.40 [-4.43, -4.37]

-2.51 [-3.01, -2.01]


IV, Random, 95% CI

-50 -25 0 25 50Lower in diabetes Higher in diabetes

Figure 5

Pooled analysis of osteocalcin levels in patients with diabetes compared with controls. Studies with several populations

comparing patients with diabetes and controls are explained as the author name followed by a, b, c or d to indicate for example

subdivision by age, gender or BMI.



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compared with controls, regardless of diabetes type, indicating that both bone resorption and formation are lower in both types of diabetes compared with controls. P1NP, a formation marker, was also consistently lower in diabetes compared with controls, but insignificant in patients with type 1 diabetes compared with controls. This difference in P1NP may partly be due to the fact that only two studies are included exploring P1NP in patients with type 1 diabetes, whereas 20 studies are included regarding P1NP in patients with type 2 diabetes. Sclerostin was increased in both patients with type 1 and type 2 diabetes; however, the levels were more than four times higher in patients with type 2 diabetes compared with controls than in patients with type 1 diabetes compared with controls. For TRAP, RANKL, OPG, NTX and BAP, all estimates were insignificant for both diabetes as a whole and for each diabetes type except for TRAP, which was significantly lower in patients with type 2 diabetes compared with controls and OPG, which was significantly higher in diabetes as a whole compared with controls. Taken together, these results suggest that both type 1 and type 2 diabetes are states of low bone turnover.

Patients with type 1 diabetes are insulinopenic though insulin sensitive and receive insulin treatment

throughout life, whereas patients with type 2 diabetes often have varying levels of insulin but are insulin resistant. Furthermore, patients with type 2 diabetes are likely to have a higher BMI than compared with patients with type 1 diabetes.

Patients with type 2 diabetes tend to have higher BMD possibly due to a higher BMI, but on the other hand, hyperglycemia and insulin resistance may tend to suppress bone turnover. A recent cross-sectional study examining more than 3000 men found that in men with the metabolic syndrome, bone formation and resorption, as judged by CTX, P1NP and osteocalcin, were lower than compared with men without the metabolic syndrome. The association between the metabolic syndrome and bone turnover markers was particularly correlated with insulin sensitivity, indicating that insulin-resistant individuals may have lower bone turnover than their healthy peers (19).

The decreased bone turnover in patients with diabetes may be explained by increased levels of sclerostin. Sclerostin levels were elevated in both patients with type 1 and type 2 diabetes compared with controls. Sclerostin levels were borderline significant when pooling patients with type 1 and type 2 diabetes probably due to wide

Study or Subgroup

Catalano 2014

Neumann 2014

Tsentidis 2015a

Total (95% CI)

Heterogeneity: Tau² = 0.00; Chi² = 1.03, df = 2 (P = 0.60); I² = 0%

Test for overall effect: Z = 3.69 (P = 0.0002)

Mean

576

23.32

51.56

SD

490

7.92

12.05

Total

69

128

40

237

Mean

625

19.8

50.98

SD

578

5.28

13.55

Total

10

77

40

127

Weight

0.0%

90.6%

9.4%

100.0%

IV, Random, 95% CI

-49.00 [-425.44, 327.44]

3.52 [1.71, 5.33]

0.58 [-5.04, 6.20]

3.24 [1.52, 4.96]


IV, Random, 95% CI

-4 -2 0 2 4Favors [experimental] Favors [control]

Study or Subgroup

Ardawi 2013

Garcia-Martin 2012

Gaudio 2012

Van Lierop 2012

Total (95% CI)


Test for overall effect: Z = 2.48 (P = 0.01)

Mean

68.12

54.56

53.18

59.2

SD

14.15

24.98

10.94

19.4

Total

482

74

40

71

667

Mean

41.22

42.11

47.5

45.2

SD

16.12

16.23

12.62

12.8

Total

482

50

40

30

602

Weight

26.3%

24.0%

25.2%

24.5%

100.0%

IV, Random, 95% CI

26.90 [24.99, 28.81]

12.45 [5.20, 19.70]

5.68 [0.50, 10.86]

14.00 [7.57, 20.43]

14.92 [3.12, 26.72]


IV, Random, 95% CI

-20 -10 0 10 20Favors [experimental] Favors [control]

Figure 6

Pooled analysis of sclerostin levels in patients with type 1 diabetes compared with controls at the top and pooled analysis of

sclerostin levels in patients with type 2 diabetes compared with controls at the bottom.



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confidence intervals resulting from the pooling of results. Sclerostin is released from the osteocytes and decreases osteoblast activity and indirectly also decreases osteoclast activity by inhibiting the secretion of OPG (20).

In vitro studies report that hyperglycemia increases OPG expression in osteoblastic cell lines (21, 22) and increases sclerostin expression by osteocyte cell lines (23). Increasing plasma glucose levels is associated with increasing levels of OPG in patients with diabetes (24). Furthermore, serum levels of OPG decrease in non-diabetic women during an oral glucose tolerance test, whereas it is unaffected in women with type 2 diabetes (25). The lack of OPG response to oral glucose in women with type 2 diabetes may be caused by somewhat chronic hyperglycemia, which limits further reductions in OPG. Although current evidence is limited, both OPG and sclerostin may be increased in diabetes due to hyperglycemia. These increased levels of OPG and sclerostin may hence decrease bone turnover in patients with diabetes.

The results of the meta-regression suggest that hyperglycemia is a significant contributor to the differences in osteocalcin, RANKL and sclerostin in patients with type 1 diabetes compared with controls and a significant contributor to the differences in P1NP, osteocalcin, NTX, osteoprotegerin, RANKL and sclerostin in patients with type 2 diabetes compared with controls. A methodological study has previously reported that hyperglycemia does not interfere with the measurement of CTX, P1NP and osteocalcin (11); thus, the observed association in this meta-analysis and meta-regression is unlikely to stem from measurement error. In vitro, hyperglycemia decreases osteoclast and osteoblast function and may thus lead to decreased bone turnover (26, 27). In patients with diabetes, increasing plasma glucose is associated with decreased levels of CTX, P1NP and osteocalcin (24). An oral glucose tolerance test decreases bone turnover markers in healthy individuals, but the effect is abolished by somatostatin (28), suggesting that hyperglycemia in combination with a gastro-intestinal hormone response may decrease bone turnover.

Incretins including gastric inhibitory polypeptide (GIP) and glucagon-like peptide-1 (GLP-1) have been suggested as being partly responsible for the altered bone turnover in diabetes. Physiologically, incretins are secreted postprandially and lower blood glucose by enhancing the insulin response. Incretins are known suppressors of bone resorption, and it has previously been shown in vitro and in animal studies that GLP-1 reduces bone resorption (29, 30, 31). A recent clinical trial concluded that treatment with a GLP-1 analogue increases bone formation possibly

by decreasing bone resorption in obese women (32). Patients with type 1 diabetes have normal postprandial levels of both GIP and GLP-1 (33), and traditionally, patients with type 2 diabetes are thought to have low levels of incretins, which would contribute to an impaired insulin response to hyperglycemia. Surprisingly, studies on plasma levels of GLP-1 in patients with type 2 diabetes report conflicting results with both reduced (34, 35) and non-reduced (36, 37) levels. Further clinical studies are warranted to establish the effect of incretins on bone turnover in diabetic individuals, especially in patients with type 2 diabetes.

Insulin-like growth factor-1 (IGF-1) recruits additional osteoblasts during bone formation and may be of importance when explaining the low bone turnover marker levels in patients with diabetes (38). Furthermore, decreased levels of IGF-1 have been associated with fractures in patients with diabetes and may be a potential fracture predictor (15). However, further research is needed to determine the effect of IGF on bone turnover and fracture risk.

Although bone tissue biopsies are the gold standard when estimating bone turnover, biopsies are difficult to obtain. Two human studies found low bone turnover in diabetes compared with controls evaluated by bone tissue biopsies (5, 6). Bone biopsies were performed in eight and five patients with diabetes respectively (5, 6). Another study in 18 patients with type 1 diabetes did not show any differences in bone turnover compared to non-diabetes subjects (7). These patients were well controlled with a mean HbA1c of 6.8% (7), which may influence the results as the fracture risk is highest in patients with HbA1c levels above 9% (39).

A decreased bone turnover may increase bone fragility in patients with diabetes. Diabetic bone is suggested to be more fragile due to glycation of the collagen, which decreases cross-link strength (40). BAP, a marker of mineralization, was in the present study not decreased in patients with diabetes compared with controls. We propose that the bone turnover process may in itself be uncoupled with a decreased bone resorption and formation but an intact mineralization. Thus, BMD may be increased by this mechanism in patients with diabetes. Although the meta-analysis does not evaluate fracture prediction by bone turnover markers, decreased levels of osteocalcin (41) and increased levels of sclerostin (13, 15) were previously associated with prevalent fractures in patients with diabetes. Larger cohort studies are needed to determine the predictive value of bone turnover markers in patients with diabetes and the consequences thereof.



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The strength of the meta-analysis is that a high number of studies are included and the results are thus likely to be generalizable to the entire population of patients with diabetes. Furthermore, we have been able to evaluate different bone turnover markers. Both the MD and SMD tests have been performed to limit confounding by inter-laboratory differences.

A limitation to the study is that the included data are based mainly on observational studies. No information on use of antidiabetic drugs or comorbidities was collected. The effects of antidiabetic drugs on bone and bone turnover differ greatly. Metformin has been shown in clinical and observational studies to execute a neutral or beneficial effect on bone regarding fracture risk, as has also been proposed for the incretins such as DPP4 inhibitors and GLP-1 analogues. The thiazolidinediones rosiglitazone and pioglitazone have a harmful effect on bone including an increased fracture risk, possibly due to increased bone loss. Sulfonylureas affect bone in a neutral way. SGLT2-inhibitors may have a neutral or possibly harmful effect on fracture risk. Insulin may have a favorable effect on bone with a lower risk of fracture, but clinical data are scarce and the effect may be secondary to a positive effect on blood glucose and diabetes as a whole (42, 43). As antidiabetic drugs may influence bone turnover and fracture risk in a variety of ways, it is unlikely to explain the observed results owing to the large number of heterogeneous studies included.

Studies of patients with different PTH and vitamin D levels have been included in the meta-analysis, which may affect the results.

Renal function is known to affect bone turnover and bone turnover markers (44). Renal dysfunction was a general exclusion criteria in most studies, and if not, both the diabetes and the control group had similar renal dysfunction, deeming kidney function unlikely to affect the study and the estimated effect.

The fasting status may affect especially CTX (45) and although not all samples were collected in a fasting state, similar circumstances were applied for patients with diabetes and for controls.

In conclusion, bone turnover markers were decreased in patients with diabetes compared with controls. Elevated sclerostin and OPG levels may be responsible for this. The decrease in bone turnover markers may be due to hyperglycemia and an altered incretin response. Clinically, the decreased bone turnover may be a contributor to increased bone fragility in patients with diabetes.

Supplementary dataThis is linked to the online version of the paper at http://dx.doi.org/10.1530/EJE-16-0652.

Declaration of interestThe authors declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of this review.

FundingThis work was supported by a research grant from the Danish Diabetes Academy funded by the Novo Nordisk Foundation.

Author contribution statementK H and J S-L conceived the idea for the publication and systematically reviewed the included papers. K H and J S-L conducted the statistics and wrote drafts of the manuscript. T H, P V and B L were involved in revising the manuscript critically for intellectual content. All authors read and approved the final manuscript.

AcknowledgementsThe authors acknowledge the assistance of Edith Clausen with the initial literature search.

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