static-curis.ku.dk...Bone turnover in pediatric diabetes Abstract: Background and objectives:...

u n i ve r s i t y o f co pe n h ag e n

Bone turnover markers in children and adolescents with type 1 diabetes

Madsen, Jens O.B.; Jørgensen, Niklas R.; Pociot, Flemming; Johannesen, Jesper

Published in:Pediatric Diabetes

DOI:10.1111/pedi.12853

Publication date:2019

Document versionPeer reviewed version

Citation for published version (APA):Madsen, J. O. B., Jørgensen, N. R., Pociot, F., & Johannesen, J. (2019). Bone turnover markers in children andadolescents with type 1 diabetes. Pediatric Diabetes, 20(5), 510-522. https://doi.org/10.1111/pedi.12853

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https://doi.org/10.1111/pedi.12853

Bone turnover in pediatric diabetes

Bone turnover markers in children and adolescents with Type-1-Diabetes

— A systematic review

Jens Otto Broby Madsen1; Niklas Rye Jørgensen2,3; Flemming Pociot1,4,5, Jesper Johannesen1,4,6

1Herlev University Hospital, Department of Pediatrics, Herlev Ringvej, 2730 Herlev, Denmark

2Department of Clinical Biochemistry, Rigshospitalet, 2600 Glostrup, Denmark.

3OPEN, Odense Patient Data Explorative Network, Odense University Hospital/Institute of Clinical Research,

University of Southern Denmark, 5000 Odense, Denmark.

4University of Copenhagen Faculty of Health and Medical Sciences, Blegdamsvej, 2200 København N, Denmark

5StenoDiabetes Center Copenhagen, 2820 Gentofte, Denmark

6Corrosponding author: email: [email protected], Phone: 0045 38689979

This article is protected by copyright. All rights reserved.

This article has been accepted for publication and undergone full peer review but has not been through the copyediting, typesetting, pagination and proofreading process, which may lead to differences between this version and the Version of Record. Please cite this article as doi: 10.1111/pedi.12853

Running title:


Corresponding author:

Jesper Johannesen

Herlev Ringvej 75, 2730 Herlev, Denmark

Tlf: +45 38689979

[email protected]



Abstract:

Background and objectives: Type-1-Diabetes (T1D) is associated with impaired bone health and both

osteocalcin and P1NP (markers of bone formation) and CTX (marker of bone resorption) are decreased in

adult patients with T1D. We review the existing literature characterizing bone turnover markers in children

and adolescents with T1D and by meta-analysis examine whether alterations in OCN, P1NP and CTX are

evident and if potential changes correlate to the metabolic control (HbA1c).

Subjects and methods: Systematic searches at MEDLINE and EMBASE were conducted in January 2018

identifying all studies describing OCN, P1NP or CTX in children and adolescents with T1D.

A total of 26 studies were included, representing data from more than 1000 patients with T1D. Pooled

analyses of standard mean difference and summary effects analysis were performed when sufficient data

were available.

Results: Pooled analysis revealed mean OCN to be significantly lower in children and adolescents with T1D

compared to healthy controls (standard mean difference -1.87 95%CI: -2.83; -0.91) whereas both P1NP and

CTX did not differ from the controls. Only data on OCN was sufficient to make pooled correlation analysis

revealing a negative correlation between OCN and HbA1c (-0.31 95%CI: -0.45; -0.16).

Conclusion: OCN is decreased in children and adolescents with T1D. Whether CTX and P1NP are affected

as well is unclear, due to very limited data available. New and large studies including OCN, P1NP and CTX

(preferably as Z-scores adjusting for age-variability) is needed to further elucidate the status of bone turnover

in children and adolescents with T1D.



Key words:

Osteocalcin; Diabetes Mellitus, Type 1; Bone Remodeling; Child; Adolescent



Abbreviations:

T1D: Type 1 diabetes

T2D: Type 2 diabetes

BMD: Bone mineral Density

OCN: Osteocalcin

P1NP: Procollagen type 1 amino terminal propetide

CTX: C-terminal cross-linked telopeptide

FBG: Fasting Blood Glucose

SD: Standard Deviation

CSII: Continuous Subcutaneus Insulin Infusion

MDI: Multiple Daily Injections

MVD: Microvascular Disease

NTX: N-telopeptide of type 1 collagen

BMI: Body Mass Index



Introduction:

Bone health is affected by diabetes. Both Type-1-Diabetes (T1D) and Type-2-Diabetes (T2D) are associated

with a higher risk of hip fractures, altered bone mineral density (BMD) and prolonged fracture healing time

(1–3). In T1D, the BMD is significantly lower than in controls, whereas T2D patients have a higher BMD

compared to controls (4,5). It has been suggested that these alterations of bone could be aligned with other

long-term complications to diabetes, such as microvascular and neurological complications (6,7). Proposed

mechanisms behind these alterations in BMD and fracture healing have been many and include altered

calcium metabolism (8,9), decreased osteoblast maturation (10) and dissociation of the otherwise coupled

formation and resorption of bone (11). Further it has been suggested that hyperglycemia, as seen T1D,

impairs the anabolic effect of physical activity (mechanical stimulation) on bone potentially explaining the

impaired bone seen in diabetes (12).

A recent review by Hygum et al. concluded that both markers of bone formation and bone resorption were

decreased in patients with diabetes compared to healthy controls (5). Several markers were examined

including the bone formation markers osteocalcin (OCN) and procollagen type-1 amino terminal propetide

(P1NP) and the resorption marker C-terminal cross-linked telopeptide (CTX). The review included both T1D

and T2D, but subgroup analysis confirmed that OCN and CTX were significantly lower in T1D compared to

controls. The review did not make subgroup analysis based on age to examine the bone status in children and

adolescents, separately. Only a limited number of studies have focused on the bone turnover markers in

growing children and adolescents with T1D. However, several studies have concluded that even at young

ages, BMD is lower compared to age and sex matched controls (13–18) and a recent review concluded that

even in young and middle-aged adults with T1DM fracture risk remained increased (19).



The incidence of T1D is highest in children and adolescents and more than 130,000 individuals under 20

years of age are expected to be diagnosed with T1D annually worldwide according to the International

Diabetes Federation (20). A better understanding of the bone turnover in children and adolescents with T1D

is of utmost importance due to the nature of skeletal development during growth. The bone turnover is

continuously changing during growth and puberty and especially OCN is higher in children and adolescents

compared to adults, with peak levels around puberty and the growth spurt (21,22). Hence, the consequences

of impaired bone turnover during this period of growth could have potential life-long consequences. Further,

if changes in bone turnover markers can be detected before alterations in BMD, they could have the potential

to be markers of future impaired bone health.

Objectives

In this paper, we review the literature characterizing selected bone turnover markers in children and

adolescents with T1D. We have chosen to focus on the classical markers of bone turnover (OCN, P1NP and

CTX) for several reasons. First, these markers can be measured on automated platforms with high precision

making them available in clinical practice (23). Secondly, these markers were among the most frequently

reported amongst adults increasing the chances of sufficient data for meta-analysis (5). Finally, whereas

P1NP and CTX have been recommended as prioritized markers of bone formation and resorption in clinical

trials (by the International Osteoporosis Foundation and the International Federation of Clinical Chemistry

and Laboratory Medicine) (23), OCN was included due to the suspected close relationship to glucose

metabolism as suggested by Lee et al. (24).

We focus on newly diagnosed patients during the remission phase as well as those with a longer duration of

diabetes. The remission phase is characterized by initiation of insulin treatment and a typical temporary



increase in endogenous insulin secretion, whereas the endogenous insulin is minimal in those with a longer

disease duration.

The objective is to investigate whether the markers of bone turnover in a clinical setting can reveal

alterations even at a very young age. We perform a meta-correlation analysis to evaluate the association

between bone turnover markers and the glycemic control, represented by values of glycosylated hemoglobin

(HbA1c).



Material and Methods:

The review was made using the PRISMA guidelines (25) and the full protocol has been registered in the

International prospective register of systematic reviews (https://www.crd.york.ac.uk/prospero/)

(Prospero registration number: CRD42018089962).

Data sources and search strategy

A systematic literature search within the MEDLINE (at PubMed) and EMBASE databases were conducted

on the 8th of January 2018 to identify all possibly relevant studies for the review. The search string was made

with either MeSH terms or truncation according to the database. The final string combined the following

search terms:

(("Diabetes Mellitus, Type 1") AND (("Child") OR "Adolescent")) AND (((("Osteocalcin") OR

"procollagen Type I N-terminal peptide") OR "collagen type I trimeric cross-linked peptide") OR “bone

remodeling)

The full list of abstracts obtained from these searches was imported into the systematic review software

COVIDENCE (https://www.covidence.org). The software facilitates the review process by removing all

imported duplicates and structures the screening process of abstracts and full text articles.

Eligible criteria for study selection

Two of the authors (JOBM and JJ) screened all eligible abstracts against the inclusion criteria. Upon

disagreement, the relevance of an abstract was decided by discussion.

Inclusion criteria were:



- Studies should include separate results for children and/or adolescent spanning 0–20 years

of age

- Subjects should be diagnosed with T1D

- Measurements of either OCN, P1NP or CTX should be presented in the article

Exclusion criteria included any other type of diabetes than T1D and any other condition or medication

affecting the bone turnover i.e. steroids or recent/present fractures. Further, we excluded all animal studies

and non-English-language articles.

Only full length, original articles were included. Abstracts from conferences were excluded in the full text

screening if the results had not yet been published as full text articles. References were cross examined to

include potentially overlooked publications fit for inclusion. If several publications were made by the same

research group and the results were based on the same population, the most recent publication with the most

complete set of results was included and the duplicates were excluded.

Data extraction and quality assessment

The final included articles were thoroughly examined, and the following data of interest were extracted if

possible: mean age of participants, duration of diabetes, metabolic control (HbA1c), fasting blood glucose

(fBG), measured bone turnover markers (OCN, CTX and P1NP), assays used to analyze bone turnover

markers and whether the blood tests were done on fasting samples or not.

If necessary for analyzes and comparisons, extracted data were converted into the International units as

following; OCN (µg/L), CTX (ng/L), P1NP (µg/L) and fBG (mmol/L). HbA1c will be reported in both

mmol/mol and % in the text, however, in Table 1 the values are reported as they appear in the original

manuscript.



If an included study was an intervention study the data from the baseline visit were included in our meta-

analysis whilst the post-intervention data were excluded.

All included articles were evaluated using the Newcastle-Ottawa scale (NOS) being a tool developed to

assess the quality of non-randomized studies in relations to design and content (26). For the cross-sectional

studies a modified scale was used (27). Each study was rewarded between 0 and 10 points (9 for the cohorts)

based on selection, comparability and outcome. Evaluation forms can be retrieved from:

http://www.ohri.ca/programs/clinical_epidemiology/oxford.asp

Statistical analysis

Mean values together with the 95% confidence intervals were retrieved from the articles. If data were

published as subgroups, each subgroup was entered separately in the meta-analysis. Common mean

differences were analyzed using the random effects model due to expected large degree of heterogeneity

between studies. Heterogeneity between studies was estimated by I2 analysis, estimating the percentage of

variation between studies caused by heterogeneity (28). Test for publication bias was done visually using

funnel plots. The meta-analyses were done using Review Manager Version 5.2.10.

Since bone turnover changes during childhood and adolescence in relation to growth, z-scores would have

been a preferred presentation of bone turnover markers. However, only very few publications used z-scores,

whereas most studies use age and sex matched controls to avoid confounding.

Summary effect analysis were calculated using Pearson correlation coefficients from studies presenting

correlation analysis of HbA1c together with one or more of the bone turnover markers. Correlations

coefficients were transformed to Fishes Z to obtain normal distribution before analysis. The meta-correlation



analyses were performed if four or more correlation coefficients, for a given bone turnover marker, were

accessible. The meta-correlation analyses were done using RStudio Version 1.0.153.



Results

A total of 99 abstracts were identified in the databases and screening revealed 64 to be eligible for inclusion

(Figure 1). 38 studies were then excluded after full text assessment, and the by far most common reason

(N=24) being that the abstracts were from international conferences and had not yet made it to publication in

scientific journals at the time of the literature search (8th of January 2018). Five articles were based on data

from already included studies and contributed with no further information for this review. Other reasons for

exclusion were articles in foreign languages or the included patients did not fulfill our inclusion criteria.

Unfortunately, one article could not be retrieved. Finally, three articles proved to be reviews, however, none

of these focused on the same outcome and age group as in the current meta-analysis. Though our inclusion

criteria stated that children and adolescents should be under the age of 20, one study by Leon et al. included

adolescents up to the age of 21 years, but was kept in the analysis since the mean age was 11.2 (± 3.9) (29).

Leaving out the study did not change the outcome or the significance of the pooled analysis (data are not

shown).

In the end, 26 studies matched our criteria and were included; 20 cross-sectional studies (13,18,29–46) and 6

prospective cohort studies (17,47–51). One cohort by Saggese et al. was an intervention cohort study, but

since we did not use post-intervention data, baseline data were used in the pooled meta-analysis (50).

Cross-sectional studies

As seen in Table 1, the number of participants varied greatly in the different cross-sectional studies; from 23

to 106 patients with T1D and from 11 to 420 controls. Mean age ranged from 8.0 to 15.5 years and the

duration of T1D varied tremendously from 0 months to 18 years. Three studies did not include control

groups (13,33,38). Most studies made it clear that the included participants and controls had no concurrent

diseases, and only two articles did not state this (44,48). Seven studies did not state whether the blood tests



were drawn in a fasting state (17,32,37,39,40,45,49) and only 6 studies reported on blood glucose levels

when tested, ranging from 9.3 to 16.52 mmol/L (29,34,35,40,42,46).

Osteocalcin was the most commonly analyzed of the bone turnover markers included in this review. 17

studies had measurements of OCN, whereas only eight studies reported on CTX and just four studies

reported on P1NP. Seven studies included more than one of the bone turnover markers

(33,34,36,37,41,42,47), and of these only two included all three markers (37,41). Though the specific assays

differed, all bone turnover markers were analyzed by immunoassays. Four studies did not report HbA1c

(31,32,36,48) and for the remaining the mean values ranged from 46 to 99 mmol/mol (6.4 to 11.2%).

DeSchepper et al. and Loureiro et al. used unusual units for their OCN measurements (ng/L and mg/dl

respectively) (13,40). For both articles the corresponding authors were unsuccessfully contacted. Since the

numeric values presented in the articles are similar to those from the other studies, and do not differ by a

factor 100 or 1000 as the units would imply, it was perceived as mistakes. None of these studies entered the

meta-analysis (for reasons specified later) and hence did not wrongly affect the pooled estimates. Khoshhal

et al. presented CTX values for both T1D and controls approximately 50 times higher than those presented in

other articles (37). No differences in units or obvious analytical methods could be identified to explain this

difference. Excluding these results from the meta-analysis of CTX did not change the outcome (data not

shown).

As seen in Table 1, NOS scores ranged between 4 and 9 points, with a mean of 7 points for both the cross-

sectional studies and the cohorts. The most common cause of reduction in NOS scores was lack of

information on recruitment and the sample representativeness of the study population.



The pooled analysis revealed that OCN levels were significantly lower amongst T1D children and

adolescents (-1.87 (-2.83; -0.91)) whereas the difference in P1NP was insignificant (P=0.09) (Figure 2). The

bone resorption marker CTX, was also without significant difference between T1D and controls (P=0.18).

Regarding all three markers of bone turnover, the heterogeneity between included studies was high and I2

ranged between 95% and 98%.

Unfortunately, five studies could not be included in the pooled analysis. These studies were those without a

control group (13,33) and those who presented data logarithmically transformed to obtain near normal

distribution or those, that did not present results as mean and SD ie median and interquartile range

(32,38,40). There is no reason to believe that the results from these omitted studies should change the overall

outcome of the meta-analysis significantly. Three of the omitted studies had significantly lower values of

OCN in T1D compared to controls (32,38,40) whereas one study just stated that OCN levels were within the

normal range in T1D children and adolescents (13). The last study compared boys and girls with T1D (no

control group), and observed that boys had higher levels of OCN and CTX without correcting for age or

puberty (33).

One study reported on OCN in both the total and the undercarboxylated form and showed that both types

were significantly lower in T1D compared to the control group. In the pooled analysis only data on total

OCN were included (35).

Finally, because the time span of included articles is very wide and methods and assays for BTM analysis

indisputably have evolved, the meta-analysis was repeated including only studies published after 2010. The



analysis did not change the outcome and still only OCN was significantly different in children and

adolescents with T1D (-1.22; 95% CI: -3.65,-0.72) (data not shown).

Correlation analysis between OCN and HbA1c were reported in 13 of the included studies (29–

33,35,38,40,43,47,51). Five of these studies did not publish data with a correlation coefficient

(29,33,37,41,42) and one study only published a correlation coefficient for the undercarboxylated form of

OCN (35). These studies could not be included in the pooled correlation analysis. The summary effects

model for the remaining seven studies revealed a negative correlation between HbA1c and OCN -0.31

(95% CI: -0.45; -0.12), which was significant (P=0.0001) (Figure 3). Though not as pronounced as in the

differences between means, the heterogeneity in the included correlation coefficients remained high with an

I2 score of 51.43%. Noteworthy, though two of the studies with no presented correlation coefficient also

reported on negative correlation between OCN and HbA1c (41,42) the remaining three found no significant

correlations (29,33,37). Only two studies reported on CTX and one on P1NP in correlation with HbA1c, and

all of these showed negative correlations as well (41,42).

Cohort studies

To a higher extend than the cross-sectional studies, the included cohorts differed in design. Two studies

followed recently diagnosed patients for one year with up to two follow-up visits in between. Pater et al.

observed significantly lower OCN and LogCTX at onset but both markers normalized after 3 and 12 months

(47). Reverse results were reported by Bonfanti et al. who observed CTX levels similar to the control group

at onset of T1D, but significantly lower after 3, 6 and 12 months of disease (49).



Gunczler et al. examined T1D patients with a diabetes duration of 4.3 (±2.9) years twice in one year. There

were no difference in OCN in patients and controls at any time point and no change over time in any of the

groups (17).

The last two studies investigated OCN at the time of onset. One study compared bone turnover markers

before and after 15 days of insulin treatment (51) whereas the other described OCN in patients who presented

with diabetic ketoacidosis at onset and again after normalized pH 10–15 days later (48). Both studies

reported significantly lower levels of OCN in T1D at the time of T1D onset compared to the control groups,

and both studies observed no difference between T1D and controls after 15 days of insulin treatment (48,51).



Discussion

Our review shows that OCN is significantly lower in children and adolescents with T1D compared to

healthy children and adolescents. Altered levels of P1NP and CTX was not observed. These findings suggest

a shift, in the otherwise coupled bone turnover, towards impaired bone formation rather than increased bone

resorption. Interestingly, at onset of T1D, levels of OCN were lower compared to controls but then

normalized later in the remission phase.

Bone turnover markers and the metabolic control

Pooled correlation analysis showed a significant negative correlation between OCN and metabolic control in

children and adolescents with T1D, indicating that an increase in HbA1c reduces bone formation. This may

partially explain why decreased OCN is observed at the time of diagnosis, since this period naturally

involves high levels of plasma glucose and hence increased HbA1c levels. When insulin therapy is initiated,

and the blood sugar levels approaches normal levels, OCN levels normalize. However, the cause of these

alterations remains to be determined.

Faienza et al. observed that patients treated with continuous subcutaneous insulin infusion (CSII) had

significantly lower HbA1c compared to patients treated with multiple daily injections (MDI). Despite the

lower HbA1c levels, the CSII-treated patients did not have different levels of OCN and CTX compared to

the MDI-treated patients (34). Similar observations were made in other studies, but these studies could

demonstrate a significant negative correlation between HbA1c and OCN, CTX and P1NP (36,41). The

results from these studies imply that, even though levels of HbA1c is negatively correlated to levels of bone

turnover markers, differences in HbA1c alone are not enough to alter the bone turnover, other factors must

be involved. Interestingly, one study observed that even though T1D patients had significantly higher levels



of OCN compared to healthy controls, adjusting for age and body mass index (BMI) revealed a significant

negative correlation between OCN and HbA1c (43).

Although it is generally agreed that HbA1c measurements should be used to assess metabolic control in

patients with diabetes, HbA1c only reveals glycemic control within the preceding weeks to months. To

obtain a more long-term idea of the glycemic control, some studies used averages of several measurements.

One study used the mean of four HbA1c measurements from the past year whereas another used available

measurements from the 2 preceding years (30,33). The study using the mean of four HbA1c measurements

found a negative correlation between OCN and HbA1c as those mentioned earlier (33). The study using

HbA1c measurements from the preceding two years found no significant correlation (30), suggesting that

alterations in OCN might be more related to the current metabolic status than the past. Supporting this

theory, studies made in children and adolescents at onset of T1D, observed that OCN levels went from

significantly lower at onset, to be indifferent from the levels in the control groups, in just 10–15 days (48,51).

Altered bone turnover as a long-term complication

In healthy people, bone turnover is the ongoing process of coupled formation and resorption of bone.

Impaired bone health, and even osteoporosis, develop if an uncoupling of the processes occur with an

increase of resorption and/or decrease of bone formation (52). Our analyses indicated decreased bone

formation in children and adolescents with T1D but no sign of altered bone resorption. These alterations may

be the cause of the impaired bone health as seen in T1D (2,4). Impaired bone formation, for a given bone

resorption, resulting in bone loss and decreased BMD was also suggested by Tsentidis et al. (42).

If altered bone turnover should result in long-term skeletal complications to T1D such as increased fracture

risk and impaired fracture healing, disease duration would be expected to be an important factor. Just a few

studies investigated the association to disease duration this(18,30,33,38,46). Two studies found that duration



of T1D had a significant negative correlation with CTX (46) and OCN (30) whereas the rest found no

correlation (18,33,38).

If both CTX and OCN decreases with an increasing disease duration, the theory of uncoupled bone formation

and resorption in T1D might be wrong. However, the study, that found a negative correlation between

disease duration and CTX, observed that CTX was significantly higher in patients with T1D for less than 1

year, compared to healthy controls, whereas, no difference was observed in patients with T1D for >1 and >5

years compared to controls (46). Again, if CTX decreased to the same level as the control group whereas

OCN decreases to levels lower than controls, the bone turnover could still be perceived as uncoupled.

If changes in bone turnover markers precede changes in BMD in children and adolescents with T1D, we

might consider screening to identify patients in risk of poor bone health as is done with other long-term

complications to T1D (53). Only few studies have investigated bone health in relations to other long-term

complications to T1D.

A large study, comprising 819 adolescents with T1D and a disease duration between 2–5 years, revealed that

long-term complications were already present in up to 16% (54). Even if complications were present in the

children and adolescents in the included studies, only Karaguzel et al. focused on this (36). Their subgroup

analysis of participants with and without present microvascular disease (MVD) showed no difference in

BMD regardless of the presence of MVD (36). They did, however, observe that both OCN and P1NP were

significantly lower in T1D compared to controls. Unfortunately, they did not investigate OCN and P1NP

levels in relation to presence of MVD.

In adults with T1D, Shanbhogue et al. evaluated bone microarchitecture using high-resolution peripheral

quantitative computed tomography (HR-pQCT) (55). The study concluded that patients with long-lasting

T1D without MVD had normal bone microarchitecture, while the presence of MVD was associated with



impaired bone microarchitecture. Though there were no significant differences in OCN, P1NP and CTX

between the patients with T1D with or without MVD, the bone turnover markers were all lower when

comparing all patients with T1D to the control group (55). Another study in adults with T1D investigated

bone health in relation to microalbuminuria. The study found that bone mass correlated negatively to

microalbuminuria and the prevalence of microalbuminuria was increased in patients with BMD below the

mean (56). The study further observed lower OCN in T1D compared to controls, but no difference in

BMD (56).

The relationship between bone turnover markers and BMD in children and adolescents with T1D was

investigated in three articles (17,33,37). Khoshhal et al. found a significant positive correlation between

OCN and BMD, whereas the other two studies observed no correlation at all (37). Noteworthy, the

participants in the study by Khoshhal et al. were all prepubertal with a mean age of 7.99 years, whereas the

other two studies had mean ages of 12.1 (17) and 15.5 (33) years which could be a reason for the conflicting

results.

As the data is limited, the results on the relationship between markers of bone turnover and BMD and bone

architecture remains unclear. A possible explanation of the conflicting results might lay in the fact that

markers of bone turnover changes rapidly ie in response to food, BMD and architecture changes slowly and

are more likely to be a product of previous changes in turnover more so than the snapshot of bone turnover

available from one measurement.

Bone turnover, age and puberty



Because of the skeletal development during growth in childhood and adolescence, age is an important factor

when investigating bone turnover markers (21,22). One study showed higher levels of OCN and CTX in

boys with T1D compared to girls with T1D (33). Though boys and girls were not different in age, the study

reported that girls had entered puberty at an earlier age than boys (33). Because bone turnover changes

during puberty and peaks during the growth spurt, girls entering puberty (and the growth spurt) earlier than

boys, may very well be the cause of the observed differences. The theory is supported by the same study in

which it is further observed that Tanner stage negatively correlates to both OCN and CTX (33).

One study divided patients with T1D and controls into groups based on Tanner stages. The study showed

that OCN was lower in T1D in Tanner stage I through III and CTX and P1NP were lower in T1D in Tanner

stage I compared to controls (41). Interestingly, BMD was not different from controls before the very end of

puberty (Tanner IV–V) (41). Again, this suggests that alterations in bone turnover markers could be a

precursor for changes in BMD.

Strengths and limitations

This review has some obvious limitations. First, the number of studies investigating bone turnover markers

in T1D children and adolescents was very limited and most of these were cross-sectional. Especially studies

investigating CTX and P1NP were missing, and only seven studies reported data on more than one of the

markers OCN, CTX and P1NP making analysis of their interactions difficult. Secondly, the included studies

were quite heterogeneous. The pooled analysis revealed unambiguous heterogeneity with I2 test ranging from

95–98% (28). This could naturally be due to the large time span in the publication year of the studies (from

1986 to 2017), however, sub-analysis excluding data published data prior to 2010 (to limit variation in

techniques and methods) did confirmed the overall finding. Several other factors may contribute to the large



heterogeneity including differences in age and disease duration in the included patients. Further, pre-

analytical conditions largely affect the markers of bone turnover, i.e the fact that several articles abstain from

reporting on the fasting state of their participants, could pose as a confounder when comparing the results

(57). Several other factors such as geography, season of measurement, recent fractures and physical activity

could also influence the comparisons of the results and should ideally be taken into account (57).

We know bone turnover changes dramatically during puberty and growth spurt (58). Heterogeneity could not

be solved by further subdivision of data, owing to the limited data available at present, so we had to accept

the use of a random effects model. Some “outlayer” observations were found in the presented data as two

articles used unusual units in their OCN results (ng/L and mg/dl) which was not clear from looking at the

actual numbers and another article presented inexplainable high values of CTX for both T1D and controls

(13,37,40). None of these results affected the results of meta-analysis but stresses the need for larger

investigations.

Funnel plots were made to assess the risk of publication bias. The funnel plots were quite asymmetrical for

all three markers (OCN, CTX and P1NP) but especially for CTX and P1NP where the number of

publications were very limited. This result was not surprising. A clear example of publication bias was

identified in our pooled correlation analysis. Three out of five studies not publishing their correlation

coefficient identified no correlation, but since there were no estimates, they could not be included in the

pooled correlation analysis (29,33,38). Since no consensus exits on whether the bone turnover markers in

T1D should be lower, higher or equal to controls, there should not be a predisposition to publish any specific

results.

In this review, we focused solely on OCN, CTX and P1NP though other factors are involved in bone health

and believed to play a part in the altered bone status of T1D. Some of these factors are analyzed in the



included studies, together with OCN, CTX and P1NP, and includes vitamin D and PTH. These well-known

influencers of calcium metabolism and bone health showed inconsistent results with levels equal to controls

in most studies for both vitamin D (13,18,37,41,42,44,50) and PTH (13,18,29,34). However, low (36,42,50)

and high PTH levels (44) were reported along with high (34,36) and low (35) vitamin D levels. Other

markers examined in the included studies were physical activity and calcium intake (41,42), insulin-like

growth factor (32,42) and the regulatory hormones from fat tissue, leptin/adiponectin (43,46). Further, new

biological markers of bone turnover can be related to the changes observed in T1D, including sclerostin,

osteoprotegerin (OPG) and receptor activator of nuclear factor kappa-’ ligand (RANKL) (40,42–44). So

even though the number of studies included is relatively small, they tend to focus on a wide pallet of players

in bone health. Larger studies examining several factors simultaneously are warranted, ideally prospective

cohort studies where patients are followed from onset of diabetes and onwards.

Conclusion

In conclusion, we find that OCN is decreased in children and adolescents with T1D. OCN is decreased

already at the time of onset of T1D, normalizes after initiation of insulin treatment, and then after having had

T1D for a while, OCN again decreases compared to controls. CTX and P1NP do not differ significantly from

healthy children and adolescents, but data on these bone turnover markers are sparse. A wide range of factors

seem to influence the markers of bone turnover, including age, gender, puberty, growth, BMI, metabolic

control and disease duration. Larger studies are needed to elucidate the relationship between T1D and bone

turnover markers in growing children and adolescents further. Studies with a more detailed focus on all

markers and their relationship to each other, metabolic control and BMD from onset and further on are

needed. Further, prospective studies looking at the causal relationship between metabolic control, bone



turnover markers and BMD would add important new information to the current knowledge on T1D. Finally,

the use of z-scores by age and gender for the bone turnover markers in children and adolescents seems

mandatory to obtain valid comparisons.

Conflicts of interest:

No conflicts of interest.

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Legends:

FIGURE 1: Flowchart of the article screening procedure reducing the number of articles from the potential

227 articles to the final 26 articles.

TABLE 1: Overview of included studies divided into cross-sectional and cohort studies and further

subdivided according to analyzed bone turnover marker. Studies are listed with name of the first author and

the year of publication. N= number of participants and controls (if any) and N Girls = number of girls in the

study. Method = method of analyzing bone turnover marker. Units = units that the article has presented their

results in. NOS = Newcastle-Ottawa Scale. P = significance level. P<0.05 is considered significant. N/A =

Data not available. NS = Non-significant. CTX values presented by Pater et al were Logarithmically

transformed. Age, duration of T1D in years, HbA1c, CTX, P1NP and OCN are all presented as mean ±SD

unless otherwise stated. For comparison, the non-logarithmically results are chosen if available. IQR=

interquartile range. SEM = standard error of mean. * is used when the P-value is only calculated from the

logarithmically changed data.

FIGURE 2: Pooled analysis of OCN, CTX and P1NP in children and adolescents with T1D compared to

healthy age matched controls. Studies with subgroups are marked with a number after the author name and

year of publication. The following subgroups are entered (1) Boys; (2) Girls; (3) Boys; (4) Girls; (5) HbA1c

< 53 mmol/mol (< 7%); (6) HbA1c 53-75 mmol/mol (7-9%); (7) HbA1c >75 mmol/mol (9%); (8) Boys; (9)

girls; (10) Disease duration < 1 year; (11) Disease duration 1-5 years; (12) Disease duration > 5 years.



FIGURE 3: Results from the pooled correlation analysis using the available Pearson correlation coefficients

and the sample sizes. Using a random effect model, we got a summary effect size of -0.31 with a P-value of

0.0001.


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PEDI_12853_Figure 2.tiff


pedi_12853_figure_3.eps


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Table 1: Study

Ref N

N

Girls Age in years Duration in years HbA1c in %

Bone

turnover

marker unit

Bone turnover marker T1D Bone turnover marker

Control P NOS

Cross-sectional Mean ±SDM; Median

(95% CI) or Median (IQR)

Mean ±SD; Mean (range);

Mean ±SEM or Range

Mean ±SD; Median (IQR),

Mean ±SEM or Range

Mean ±SD; Median (Range) or

Median (IQR)

Mean ±SD; Median (Range) or

Median (IQR)

CTX

Brandao 2007 (29) 22 T1D 0 15.5 ±2.4 6.6 ±3.9 10.2 ±2.0 ng/mL 0.49 ±0.2 N/A N/A 8

Brandao 2007 (29) 22 T1D 22 15.5 ±2.4 6.6 ±3.9 12.0 ±2.3 ng/mL 0.28 ±0.16 N/A N/A 8

Franceschi 2017 (40) 96 T1D + 40 Control 51 10.5 ±3.1 4.4 ±2.8 7.7 ±1.4 ng/mL 1.41 ±0.67 1.35 ±0.48 NS 8

Gunczler 2001 (41) 23 T1D + 17 Control 16 9.5 ±2.2 0.5 ±0.1 8.0 ±2.4 ug/L 9.3 ±1.3 5.7 ±1.5 NS 7

Hashim 2016 (42) 27 T1D + 20 Control 11 10.2 ±0.6 0.3 ±0.1 (SEM) 10.5 ±0.6 ng/mL 1.932 ±0.292 0.952 ±0.068 P < 0.01 7

Hashim 2016 (42) 17 T1D + 20 Control 9 10.3 ±0.7 2.8 ±0.2 (SEM) 9.0 ±0.5 ng/mL 0.976 ±0.053 0.952 ±0.068 NS 7

Hashim 2016 (42) 16 T1D + 20 Control 8 12.8 ±0.6 7.1 ±0.5 (SEM) 9.7 ±0.7 ng/mL 1.065 ±0.164 0.952 ±0.068 NS 7

Khoshhal 2015 (33) 36 T1D + 39 Control 39 8.0 4.5 ±0.3 10.7 ±0.3 ng/mL 54.73 ±5.68 48.18 ±1.67 P < 0.05 7

Maggio 2010 (37) 27 T1D + 32 Control 14 10.5 ±2.4 3.2 ±2.3 7.9 ±0.7 ng/mL 0.97 ±0.04 1.2 ±0.08 P = 0.042 7

Tsentidis 2016 (38) 40 T1D + 40 Control 22 13.0 ±3.5 5.15 ±3.3 8.2 ±1.8 ng/mL 1.35 (Range: 0.42-4-05) 1.94 (Range: 0.68-3.53) P = 0.015* 9

OCN

AbdElDayem 2011 (26) 47 T1D + 30 Control 33 13.3 ±3.4 6.3 ±3.0 8.2 ±2.1 ng/mL 12.2 ±14.7 49.4 ±34.5 P = 0.002 7

Abo-El-Asrar 2011 (27) 60 T1D + 40 Control 35 12.2 ±4.3 N/A N/A ng/mL 24.52 ±10.84 36.69 ±11.68 P < 0.0000 7

Bouillon 1995 (28) 60 T1D + 215 Control 0 13.5 (95% CI: 5–20) 5.8 (Range: 0.1–18) N/A ug/L 52 (Range: 16–126) 74 (Range: 205–191) P < 0.001 6

Bouillon 1995 (28) 44 T1D + 205 Control 44 13.5 (95% CI: 5–20) 5.8 (Range: 0.1–18) N/A ug/L 44 (Range: 13–106) 60 (Range: 16–159) NS 6

Brandao 2007 (29) 22 T1D 0 15.5 ±2.4 6.6 ±3.9 10.2 ±2.0 ng/mL 41.43 ±19.79 N/A Boys > girls 8

Brandao 2007 (29) 22 T1D 22 15.5 ±2.4 6.6 ±3.9 12.0 ±2.3 ng/mL 25.71 ±18.94 N/A Boys > girls 8

DeSchepper 1998 (17) 23 T1D 8 12.5 ±3.7 2.8 ±1.5 9.2 ±2.1 ng/L 13.7 ±6.1 N/A N/A 4

Ersoy 1999 (12) 30 T1D + 23 Control 14 14.5 3.3 ±3.1 9.3 ±3.1 ng/mL 10.10 ±3.4 23.12 ±2.74 P < 0.01 7

Faienza 2017 (30) 106 T1D + 80 Controls 53 12.2 ±4.0 4.4 ±3.1 8.1 ±0.9 ng/mL 46.88 ±21.6 36.67 ±24.5 NS 7

Huneif 2017 (31) 132 T1D + 72 Control 56 10.5 ±3.9 N/A 9.9 ±1.8 ng/mL 2.42 ±1.36 14.1 ±1.52 P < 0.001 8

Kruse 1986 (34) 29 T1D + 64 Control 19 2–14.9 Range: 0.1–12 Range: 7.3–13.9 ng/mL 8.6 (Range: 2.7–15.3) 11.9 (Range: 7.7–15.3) NS 6

Leon 1989 (25) 87 T1D + 49 Control 37 11.2 ±3.9 3.5 ±4.1 8.5 ±1.9 ng/mL 10.0 ±4.9 9.79 ±3.34 NS 5

Liu 2003 (35) 39 T1D + 37 Control 39 16.4 ±1.8 7.1 ±3.9 8.4 ±1.7 ng/mL 19.2 ±8.5 18.6 ±8.3 NS 7

Loureiro 2014 (36) 75 T1D + 100 Control 39 12 (IQR: 6–20) 5.0 ±3.5 10.1 (IQR: 8.1-17.3) mg/dl 24.3 (IQR: 30.0–81.0) 44.7 (IQR: 18.0–100.0) P < 0.05 7

Karaguzel 2006 (32) 58 T1D + 44 Control 29 11.7 ±3.1 Range: 0.1–15 N/A ng/mL 69.7 ±39.0 127.8 ±59.4 P < 0.001 8


Acc

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Study Ref N N

Girls Age in years Duration in years HbA1c in %

Bone

turnover

marker unit


Control P NOS

Cross-sectional Mean ±SDM; Median

(95% CI) or Median (IQR) Mean ±SD; Mean (range);

Mean ±SE or Range Mean ±SD; Median (IQR)

or Range Mean ±SD; Median (Range) or

Median (IQR) Mean ±SD; Median (Range) or

Median (IQR)


Maggio 2010 (37) 27 T1D + 32 Control 14 10.5 ±2.4 3.2 ±2.3 7.9 ±0.7 ng/mL 70.29 ±3.27 105.32 ±6.78 P < 0.001 7

Tsentidis 2016 (38) 40 T1D + 40 Control 22 13.0 ±3.5 5.2 ±3.33 8.2 ±1.8 ng/mL 31.54 (Range: 9.49-82.25) 37.85 (Range: 11.47-89.21) P = 0.028* 9

Wedrychowicz 2014 (39) 24 T1D + 11 Control N/A 10.5 ±4.2 3.0 ±2.0 6.4 ±0.4 ng/mL 37.5 ±17.9 21.7 ±15.9 P = 0.04 7



P1NP

Franceschi 2017 (40) 96 T1D + 40 Control 51 10.5 ±3.1 4.4 ±2.8 7.7 ±1.4 ng/mL 645.29 ±304.35 487.85 ±324.85 P < 0.01 8

Karaguzel 2006 (32) 58 T1D + 44 Control 29 11.7 ±3.1 0.1–15 N/A µg/L 356.2 ±167.3 511.3 ±206.5 P < 0.001 8


Maggio 2010 (37) 27 T1D + 32 Control 14 10.5 ±2.4 3.2 ±2.3 7.9 ±0.7 ng/mL 556.42 ±47.55 716.31 ±53.80 P = 0.031 7

Study Ref N N

Girls Age in years Duration HbA1c in %

Bone

turnover

marker unit


Control P NOS

Cohorts Mean ±SDM; Median

(95% CI) or Median (IQR) Mean ±SD; Mean (range);

Mean ±SE or Range Mean ±SD; Median (IQR)

or Range Mean ±SD; Median (Range) or

Median (IQR) Mean ±SD; Median (Range) or

Median (IQR)

CTX

Bonfanti 1996 (46) 27 T1D + 30 Control 12 6.4 ±2.2

Onset

3 months

6 months

12 months

11.3 ±0.4 (SEM)

6.8 ±1.9 (SEM)

7.2 ±0.2 (SEM)

7.7 ±0.2 (SEM)

µg/L

15.1 (Range: 6.2–28.2)

14.6 (Range: 7–25.7)

12.3 (Range: 6.8–20.4)

13.1 (Range: 6.2–25.8)

17.3 (Range: 7.7–37.1)

NS

P = 0.04

P = 0.002

P = 0.03

7

Pater 2010 (44) 17 T1D + 17 Control 5 11.4 ±1.4

Onset

3 months

12 months

11.3 ±2.4

6.9 ±0.9

7.1 ±0.8

µg/L

1.607 (Range: 1.333-2.084)

2.480 (Range: 1.892-3.342)

2.198 (Range: 1.360-2.616)

2.355 (Range: 2.146-2.533)

N/A

2.352 (Range: 2.187-2.566)

P < 0.003*

N/A

NS*

7

OCN

Guarneri 1993 (47) 31 T1D + 31 Control 14 N/A Onset

15 days

12.1 ±0.4

N/A ng/mL

N/A

N/A

N/A

N/A

P < 0.001

P = 0.54 7

Gunczler 1998 (16) 26 T1D + 27 Control 11 12.1 ±3.1 4.3 ±2.9 yr

+ 1 yr 9.2 ±2.3 µg/L

15.1 ±4.7

14.4 ±6.8

16.3 ±7.0

15.6 ±7.1

NS

NS 8

Pater 2010 (44) 17 T1D + 17 Control 5 11.4 ±1.4

Onset

3 months

12 months

11.3 ±2.4

6.9 ±0.9

7.1 ±0.8

µg/L

61.2 ±21.8

104.9 ±64.2

107.6 ±58.9

104.3 ±29.3

N/A

115.7 ±36.2

P < 0.0002

N/A

NS

7

Saggese 1991 (48) 23 T1D + 20 Control 12 9.4 ±2.5 1.3 ±0.9 yr 7.7 ±1.2 ng/mL 9.81 ±2.54 14.5 ±3.2 P < 0.01 7

Topaloglu 2005 (45) 16 T1D + 25 Control 8 2.4 ±1.7 Onset

10–15 days

N/A

N/A ng/mL

4.37 ±1.8

7.06 ±2.1 7.2 ±2.9

P < 0.01

NS 5


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