ORIGINAL
ARTICLE
Trabecular Bone Score as an Indicator for Skeletal
Deterioration in Diabetes
Jung Hee Kim, Hyung Jin Choi, Eu Jeong Ku, Kyoung Min Kim, Sang Wan Kim,
Nam H. Cho, and Chan Soo Shin
Department of Internal Medicine (J.H.K., E.J.K., K.M.K., S.W.K., C.S.S.), Seoul National University
College of Medicine, Seoul 110-744, Republic of Korea; Department of Internal Medicine (E.J.K.,
K.M.K.), Seoul National University Bundang Hospital, Seongnam 463-707, Republic of Korea;
Department of Internal Medicine (H.J.C.), Chungbuk National University College of Medicine, Cheongju
Si 361-763, Republic of Korea; and Department of Preventive Medicine (N.H.C.), Ajou University School
of Medicine, Suwon 443-721, Republic of Korea
Context: Trabecular bone score (TBS) is a novel texture index that evaluates the pixel gray-level
variations in lumbar spine dual-energy X-ray absorptiometry images and is related to bone microarchitecture independent of bone mineral density (BMD).
Objective: We investigated lumbar spine TBS as an indicator for skeletal deterioration in diabetes.
Design and Setting: Cross-sectional data were collected from subjects participating in an ongoing
prospective, community-based, cohort study from 2009 to 2010.
Participants: We included 1229 men and 1529 postmenopausal women older than 50 years in the
Ansung cohort.
Outcome Measures: Biochemical parameters, lumbar spine TBS, and BMD from dual-energy X-ray
absorptiometry images were measured.
Results: Lumbar spine TBS was lower in men with diabetes than in nondiabetic men (1.287 ⫾ 0.005
vs 1.316 ⫾ 0.003, P ⬍ .001), whereas lumbar spine BMD was higher in men with diabetes (1.135 ⫾
0.010 vs 1.088 ⫾ 0.006 g/cm2). Lumbar spine TBS was lower in women with diabetes than in
nondiabetic women only in an unadjusted model (1.333 ⫾ 0.004 vs 1.353 ⫾ 0.003). However,
women younger than 65 years (n ⫽ 707) with diabetes had a lower TBS than those without diabetes,
even after adjusted for covariates (P ⬍ .001). Diabetes was not associated with BMD at femur sites
in both genders. TBS was negatively correlated with glycated hemoglobin, fasting plasma glucose,
fasting insulin, and homeostasis model assessment for insulin resistance but not with homeostasis
model assessment for ␤-cell function in both genders.
Conclusions: The inverse association between lumbar spine TBS and insulin resistance may make
it an indicator for determining skeletal deterioration in diabetic patients who have high BMD.
(J Clin Endocrinol Metab 100: 475– 482, 2015)
O
steoporosis is a systemic skeletal disease characterized by low bone mass or bone microarchitecture
deficit, leading to decreased bone strength and increased
fracture risk. Type 2 diabetes is also a common chronic
disease and a large public health burden associated with
aging worldwide. Patients with type 2 diabetes have an
increased risk for mortality and morbidity from microvascular and macrovascular complications (1). Although
type 1 diabetes is considered to be a secondary cause of
osteoporosis according to the World Health Organiza-
ISSN Print 0021-972X ISSN Online 1945-7197
Printed in U.S.A.
Copyright © 2015 by the Endocrine Society
Received April 12, 2014. Accepted October 27, 2014.
First Published Online November 4, 2014
Abbreviations: AGE, advanced glycosylation end-product; ANCOVA, analysis of covariance; BMD, bone mineral density; DXA, dual-energy X-ray absorptiometry; HbA1c, glycated hemoglobin; HOMA-␤, homeostasis model assessment for ␤-cell function; HOMAIR, homeostasis model assessment for insulin resistance; hs-CRP, high-sensitivity C-reactive
protein; TBS, trabecular bone score.
doi: 10.1210/jc.2014-2047
J Clin Endocrinol Metab, February 2015, 100(2):475– 482
jcem.endojournals.org
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475
476
Kim et al
Diabetes and Trabecular Bone Score
tion Fracture Risk Assessment tool version, type 2 diabetes is not included due to interdependence with other variables (2). However, a wealth of evidence shows that
patients with type 2 diabetes are also at increased risk for
fragility fracture at all skeletal sites (3–7), even though
patients with type 2 diabetes have a higher or normal bone
mineral density (BMD) (8). Diabetic neuropathy or retinopathy may increase fall risk, but fracture risk remains
increased in patients with type 2 diabetes, even after
adjusting for fall risk (4, 5). Alteration of skeletal material or microstructure may be an underlying mechanism for the seeming discrepancy between BMD and
fracture risk in diabetes (2).
Although BMD measured by dual-energy X-ray absorptiometry (DXA) is a major predictor of fracture risk
(9), half of individuals with a fragility fracture have BMD
values in the osteopenic or even normal range (10). This
observation implied that factors other than BMD such as
bone microarchitecture, bone geometry, microdamage,
mineralization, and bone turnover influence bone strength
and fracture risk (11–13). However, DXA is incapable of
evaluating these material and structural properties of bone
(14). Consequently, additional bone quality-related
markers are needed to identify patients with type 2 diabetes at risk for fracture.
Trabecular bone score (TBS), a textural index that evaluates pixel gray-level variations in the projected lumbar
spine DXA image, has been introduced as an indirect measure of bone quality. TBS is calculated as the slope of the
log-log transform of variograms computed by the projection of the three-dimensional structure onto a two-dimensional plane. Currently TBS was available only for lumbar
spines, which consisted mainly of trabecular bones. A
steep variogram slope with a high TBS value is associated
with a dense bone microstructure, whereas low TBS values
indicate a porous bone microstructure (15). Lumbar spine
TBS has been shown to predict osteoporotic fractures in
postmenopausal white women with diabetes and capture
a greater portion of the diabetes-associated fracture risk
than does BMD (16). Although several cross-sectional and
prospective studies have shown that TBS predicts fracture
risk (16 –20), no studies have indicated the implication of
TBS in both male and female Asian patients with type 2
diabetes.
We investigated the ability of the lumbar spine TBS to
predict skeletal deterioration in diabetic men and women
and elucidated the underlying mechanism in a communitybased Korean cohort.
Materials and Methods
Study population
This cross-sectional study was a part of the Ansung cohort
study, an ongoing prospective, community-based cohort study
J Clin Endocrinol Metab, February 2015, 100(2):475– 482
that was part of the Korean Health and Genome Study in 2001
that investigated the prevalence of chronic diseases in Korea The
details of the Ansung cohort study have been previously published (21). In brief, Ansung is a representative rural farming
community with a population of 132 906 in 2000 (22). The
eligibility criteria included an age of 40 – 69 years at baseline,
residence within the borders of the survey area for at least 6
months before testing, and sufficient mental and physical ability
to participate. Of 7192 eligible individuals in Ansung, 5018 were
surveyed (70% response rate) using a cluster-sampling method
stratified by age, sex, and residential district. DXA was commenced in 2006, but the maximal number of participants underwent DXA from 2009 to 2010. We included 1229 men and
1529 postmenopausal women older than 50 years in the Ansung
cohort from 2009 to 2010 and collected data such as lumbar
spine TBS, BMD, and clinical parameters during this period.
Study procedures were in accordance with institutional guidelines and approved by an institutional review board. Informed
consent was obtained from the study participants.
Bone mineral density and trabecular bone score
The BMD (grams per square centimeter) of skeletal sites (lumbar spine, femoral neck, and total hip) was measured using DXA
(Lunar Prodigy; GE Medical Systems) and analyzed (Encore
Software version 11.0) in accordance with manufacturer guidance. The BMD precision error (percentage of the coefficient of
variation) was 1.7% for lumbar spine, 1.8% for femoral neck,
and 1.7% for total hip. For lumbar spine BMD, the L1– 4 value
was chosen for the analyses. When L1– 4 was not suitable for
analysis due to a compression fracture or severe sclerotic change,
L2– 4 was used. All TBS measurements were retrospectively performed using TBS iNsight Software, version 2.0.0.1 (MedImaps) using spine DXA files from the database to ensure blinding of the investigators to all clinical parameters and outcomes.
The software used the raw DXA image of the anteroposterior
spine for the same region of interest as the BMD measurement.
Instruments were calibrated using anthropomorphic phantoms.
Diabetes and other covariates
Diabetes was ascertained at the time of the DXA measurement. Diabetes was assessed based on plasma glucose results
during the 75-g oral glucose tolerance test and glycated hemoglobin (HbA1c) values and was defined according to the American Diabetes Association criteria (23): fasting plasma glucose
concentration of 7.0 mmol/L or greater (126 mg/dL), 2-hour
plasma glucose of 11.1 mmol/L or greater (200 mg/dL), HbA1c
of 6.5% or greater, or current treatment by oral antidiabetic
drugs or insulin. Hypertension was defined as a systolic blood
pressure of 140 mm Hg or greater, diastolic blood pressure of 90
mm Hg or greater, or treatment by antihypertensive medication.
Information regarding dietary calcium intake, prior major fracture, arthritis, current alcohol intake, current smoking habits,
regular exercise, and prior osteoporosis treatment were recorded
at the time of DXA measurement using a standardized questionnaire and a face-to-face interview. Prior major fragility fracture
was defined as a low-trauma fracture at the hip, vertebral, proximal humerus, and radius that occurred after the age of 40 years.
High-trauma events included a traffic accident, violence, and
falls from more than the standing height of the individual. Regular exercise was defined as engaging in any of a variety of ac-
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doi: 10.1210/jc.2014-2047
Table 1.
jcem.endojournals.org
477
Baseline Characteristics of Study Subjects
Age, y
Height, cm
Weight, kg
Body mass index, kg/m2
Lumbar spine TBS (unitless)
Lumbar spine BMD, g/cm2
Femur neck BMD, g/cm2
Total hip BMD, g/cm2
HbA1c, %
Fasting plasma glucose, mg/dL
Fasting insulin, ␮IU/mL
HOMA-IR
HOMA-␤
Total cholesterol, mg/dL
HDL cholesterol, mg/dL
Triglycerides, mg/dL
LDL cholesterol, mg/dL
hs-CRP, mg/dL
Dietary calcium intake, mg/d
Current drinkers, %
Current smokers, %
Regular exercisers, %
Prior major fracture, %
Arthritis, %
Hypertension, %
Treatment of osteoporosis, %
Men Without
Diabetes
(n ⴝ 894)
Men With
Diabetes
(n ⴝ 325)
62.5 ⫾ 8.5
165.8 ⫾ 5.8
64.8 ⫾ 9.4
23.5 ⫾ 2.9
1.317 ⫾ 0.088
1.088 ⫾ 0.178
0.901 ⫾ 0.144
0.967 ⫾ 0.145
5.58 ⫾ 0.39
96.5 ⫾ 9.6
8.10 ⫾ 3.78
1.95 ⫾ 1.00
91.6 ⫾ 44.8
184.7 ⫾ 33.0
41.6 ⫾ 10.8
145.1 ⫾ 110.5
117.4 ⫾ 34.3
2.03 ⫾ 5.93
399.9 ⫾ 269.5
574 (64.3)
313 (35.1)
226 (25.3)
40 (4.5)
10 (1.1)
55 (6.2)
9 (1.0)
64.2 ⫾ 8.2
166.0 ⫾ 5.6
67.4 ⫾ 10.1
24.4 ⫾ 3.1
1.287 ⫾ 0.092
1.135 ⫾ 0.174
0.890 ⫾ 0.158
0.966 ⫾ 0.148
6.83 ⫾ 1.27
131.0 ⫾ 37.9
10.04 ⫾ 11.63
3.43 ⫾ 5.50
63.4 ⫾ 50.2
178.7 ⫾ 35.0
39.1 ⫾ 10.6
171.1 ⫾ 121.9
110.9 ⫾ 33.7
2.24 ⫾ 5.49
387.4 ⫾ 257.6
205 (63.1)
103 (31.7)
111 (34.2)
15 (4.7)
1 (0.3)
28 (8.6)
1 (0.36)
P
Women Without
Diabetes
(n ⴝ 1144)
Women With
Diabetes
(n ⴝ 370)
P
.002
.532
⬍.001
⬍.001
⬍.001
⬍.001
.269
.933
⬍.001
⬍.001
⬍.001
⬍.001
⬍.001
.006
⬍.001
⬍.001
.003
.570
.475
.013
.009
.003
.876
.306
.157
.305
63.8 ⫾ 8.1
152.0 ⫾ 6.0
56.7 ⫾ 8.8
24.5 ⫾ 3.4
1.353 ⫾ 0.092
0.930 ⫾ 0.170
0.780 ⫾ 0.131
0.840 ⫾ 0.142
5.67 ⫾ 0.41
93.3 ⫾ 8.7
9.18 ⫾ 5.76
2.13 ⫾ 1.38
115.4 ⫾ 73.5
196.2 ⫾ 32.8
43.8 ⫾ 10.2
130.7 ⫾ 74.0
127.7 ⫾ 30.1
1.45 ⫾ 3.45
429.9 ⫾ 362.2
245 (21.4)
16 (1.4)
310 (27.1)
129 (11.3)
25 (2.2)
62 (5.4)
140 (12.2)
66.6 ⫾ 7.5
151.2 ⫾ 5.8
57.9 ⫾ 8.7
25.3 ⫾ 3.3
1.333 ⫾ 0.085
0.955 ⫾ 0.181
0.760 ⫾ 0.122
0.827 ⫾ 0.133
7.12 ⫾ 1.43
130.5 ⫾ 45.4
12.46 ⫾ 9.26
4.05 ⫾ 3.48
86.0 ⫾ 77.2
192.4 ⫾ 35.2
40.6 ⫾ 9.5
156.1 ⫾ 83.9
121.7 ⫾ 33.0
2.03 ⫾ 4.07
386.5 ⫾ 284.1
42 (11.4)
11 (3.0)
100 (27.1)
56 (15.2)
9 (2.4)
12 (3.3)
51 (13.8)
⬍.001
.024
.021
⬍.001
⬍.001
.026
.012
.120
⬍.001
⬍.001
⬍.001
⬍.001
⬍.001
⬍.001
⬍.001
⬍.001
.001
.007
.041
⬍.001
.027
1.000
.055
.840
.097
.419
Variables are expressed as mean ⫾ SD or n (percentage).
tivities for the purpose of exercise and was recorded as once or
more than once per week.
error rate. All statistical analyses were performed using PASW
SPSS for Windows (version 21; SPSS Inc).
Anthropometric and biochemical parameters
Height and body weight were measured in light clothing at the
time of DXA by standard methods. The BMI was calculated as
weight divided by height squared (kilograms per square meter).
The 8-hour fasting plasma concentrations of glucose, insulin,
total cholesterol, triglycerides, high-density lipoprotein (HDL)
cholesterol, low-density lipoprotein (LDL) cholesterol, and highsensitivity C-reactive protein (hs-CRP) were measured in a central laboratory. HbA1c was measured using HPLC (Variant II;
Bio-Rad Laboratories). Pancreatic ␤-cell function and insulin
resistance were calculated by homeostasis model assessment
(HOMA-␤ and HOMA-IR, respectively) (24).
Statistical analysis
Data were expressed as mean ⫾ SD or n (percentage). We
analyzed constitutive variables with a Student t test and categorical variables with a ␹2 test. In the first adjusted model, we
used analysis of covariance (ANCOVA) models adjusted for age
and BMI (model 1) and further adjusted this model for age, BMI,
prior major fracture, arthritis, current alcoholics, current smokers, regular exercise, and osteoporosis treatment (model 2). The
correlation analyses between TBS and biochemical parameters
were performed using Pearson’s correlation. Partial correlation
analyses were used to extract the correlation coefficient after
adjusting for age and BMI. A value of P ⬍ .05 was considered
statistically significant. In a subgroup analysis (see Table 3), we
applied the significance level of P ⫽ .025 to reduce the type 1
Results
Table 1 summarizes the baseline characteristics of the
study subjects based on diabetic status and gender.
Women were slightly older and had a higher BMI. Lumbar
spine TBS was lower and all BMD values were higher in
men. HbA1c, plasma insulin, HOMA-IR, and HOMA-␤
levels were higher and plasma fasting glucose level was
lower in women. Serum total cholesterol, HDL cholesterol, and LDL cholesterol were lower, and triglycerides
and hs-CRP were higher in men. The prevalence of current
drinkers and smokers were higher in men, but hypertension was more prevalent in women. The prevalence of
diabetes was 26.7% (325 of 1229) in men and 24.4% (370
of 1529) in women.
Lumbar spine TBS was lower in men with diabetes than
those without diabetes in unadjusted models, and the least
squares means remained significantly lower after adjusting for age, BMI, prior major fracture, arthritis, current
alcoholics, current smokers, regular exercise, and osteoporosis treatment (models 1 and 2) (Table 2). By contrast,
lumbar spine BMD was significantly higher in diabetic
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478
Kim et al
Diabetes and Trabecular Bone Score
J Clin Endocrinol Metab, February 2015, 100(2):475– 482
Table 2. Least Squares Means for TBS and BMD in Subjects Without and With Diabetes From ANCOVA Models
Adjusted for Covariates
Lumbar spine TBS (unitless)
Lumbar spine BMD, g/cm2
Femur neck BMD, g/cm2
Total hip BMD, g/cm2
Model 1
Lumbar spine TBS (unitless)
Lumbar spine BMD, g/cm2
Femur neck BMD, g/cm2
Total hip BMD, g/cm2
Model 2
Lumbar spine TBS (unitless)
Lumbar spine BMD, g/cm2
Femur neck BMD, g/cm2
Total hip BMD, g/cm2
Lumbar spine TBS (unitless)
Lumbar spine BMD, g/cm2
Femur neck BMD, g/cm2
Total hip BMD, g/cm2
Model 1
Lumbar spine TBS (unitless)
Lumbar spine BMD, g/cm2
Femur neck BMD, g/cm2
Total hip BMD, g/cm2
Model 2
Lumbar spine TBS (unitless)
Lumbar spine BMD, g/cm2
Femur neck BMD, g/cm2
Total hip BMD, g/cm2
Men Without
Diabetes (n ⫽ 894)
1.316 ⫾ 0.003
1.088 ⫾ 0.006
0.901 ⫾ 0.005
0.967 ⫾ 0.005
Men With
Diabetes (n ⫽ 325)
1.287 ⫾ 0.005
1.135 ⫾ 0.010
0.890 ⫾ 0.009
0.966 ⫾ 0.008
P
⬍.001
⬍.001
.269
.933
1.314 ⫾ 0.003
1.091 ⫾ 0.006
0.901 ⫾ 0.004
0.968 ⫾ 0.004
1.294 ⫾ 0.005
1.124 ⫾ 0.010
0.891 ⫾ 0.007
0.963 ⫾ 0.007
⬍.001
.004
.261
.590
1.316 ⫾ 0.003
1.090 ⫾ 0.006
0.903 ⫾ 0.005
0.969 ⫾ 0.005
1.294 ⫾ 0.005
1.122 ⫾ 0.010
0.890 ⫾ 0.008
0.964 ⫾ 0.008
⬍.001
.007
.171
.601
Women Without
Diabetes (n ⫽ 1144)
1.353 ⫾ 0.003
0.930 ⫾ 0.005
0.780 ⫾ 0.004
0.840 ⫾ 0.004
Women With
Diabetes (n ⫽ 370)
1.333 ⫾ 0.004
0.955 ⫾ 0.010
0.760 ⫾ 0.007
0.827 ⫾ 0.007
P
⬍.001
.026
.012
.120
1.350 ⫾ 0.002
0.927 ⫾ 0.005
0.776 ⫾ 0.003
0.836 ⫾ 0.003
1.343 ⫾ 0.004
0.965 ⫾ 0.008
0.774 ⫾ 0.006
0.840 ⫾ 0.006
.170
⬍.001
.856
.630
1.350 ⫾ 0.002
0.926 ⫾ 0.005
0.775 ⫾ 0.003
0.836 ⫾ 0.004
1.345 ⫾ 0.004
0.967 ⫾ 0.009
0.777 ⫾ 0.006
0.843 ⫾ 0.006
.241
⬍.001
.773
.374
Variables are expressed as means ⫾ SE. Model 1 was adjusted for age and BMI; model 2 was adjusted for age, BMI, dietary calcium intake, prior
major fracture, arthritis, current alcoholics, current smokers, regular exercise, and osteoporosis treatment.
men in unadjusted and adjusted models. Femur neck and
total hip BMD were not different between in men with and
without diabetes. Lumbar spine TBS was significantly
lower in women with diabetes than in those without diabetes, but this difference was eliminated after adjusting for
multiple covariates. Lumbar spine BMD was significantly
higher in women with diabetes than in nondiabetic
women, even in adjusted models. Femur neck and total hip
BMD were similar between diabetic and nondiabetic
women. We performed a subgroup analysis according to
age (⬍65 y and ⱖ65 y) (Table 3) and found that diabetic
women younger than 65 years had a lower lumbar spine
TBS compared with their age-matched nondiabetic counterparts, even after adjusting for covariates (P ⫽ .032).
We carried out correlation analyses between TBS and
skeletal or biochemical parameters (Table 4 and Figures 1
and 2). TBS was inversely correlated with age and BMI in
both genders, whereas BMD was positively correlated
with BMI. TBS was positively related with BMD at all
sites, with a stronger relationship in women than in men.
TBS was negatively correlated with HbA1c, fasting
plasma glucose, fasting insulin, and HOMA-IR but not
with HOMA-␤ cell function in both genders after adjustment for age and BMI. Regarding lipid parameters, only
serum triglycerides were negatively associated with TBS in
both genders in unadjusted and adjusted models. TBS was
also inversely related with hs-CRP, an inflammatory
marker, in both genders, irrespective of age and BMI.
Discussion
In community-dwelling older adults, lumbar spine TBS
was lower in diabetic men of all ages and in diabetic
women younger than 65 years compared with their respective nondiabetic counterparts, and subjects with low
TBS values were more insulin resistant than those with
high TBS. On the other hand, unadjusted and adjusted
models showed that diabetes was associated with higher
lumbar spine BMD in both genders. TBS was also related
with an inflammatory marker, hs-CRP, and serum triglyceride levels.
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doi: 10.1210/jc.2014-2047
jcem.endojournals.org
Table 3. Least Squares Means of TBS in Subjects
Without and With Diabetes According to Age 65 Years or
Older and Younger Than 65 Years From ANCOVA Models
Men
Age 65 y or older
(n ⫽ 558)
Fracture rate
Age younger than
65 y (n ⫽ 671)
Fracture rate
Women
Age 65 y or older
(n ⫽ 822)
Fracture rate
Age younger than
65 y (n ⫽ 707)
Fracture rate
Subjects
Without
Diabetes
Subjects
With
Diabetes
P
1.296 ⫾ 0.005
1.279 ⫾ 0.007
.065
17/393 (4.3%)
1.332 ⫾ 0.004
10/165 (6.1%)
1.304 ⫾ 0.007
.519
⬍.001
23/517 (4.4%)
5/154 (3.2%)
.649
1.316 ⫾ 0.004
1.318 ⫾ 0.006
.713
93/587 (15.8%) 49/235 (20.9%) .127
1.392 ⫾ 0.003 1.361 ⫾ 0.007 ⬍.001
36/574 (6.2%)
7/133 (5.3%)
.404
Variables are expressed as means ⫾ SE and are adjusted for BMI,
dietary calcium intake, prior major fracture, arthritis, current alcoholics,
current smokers, regular exercise, and osteoporosis treatment.
Type 2 diabetic patients are at increased fracture risk
despite normal or higher BMD (6). Although extraskeletal
factors such as vision disturbance or peripheral neuropathy may contribute to this discrepancy by increasing the
fall risk (6), the fracture risk in diabetic patients remained
higher than in nondiabetic patients, even after adjusting
for fall frequency (3, 4). We showed that lumbar spine TBS
may account for the conundrum between high BMD and
elevated fracture risk in diabetic patients. TBS, an overall
score computed by the projection of the three-dimensional
structure onto a two-dimensional plane, represents bone
microarchitecture and provides a global estimate of bone
quality (25). Silva et al (25) shows through high-resolution-peripheral quantitative computed tomography that
Table 4.
although TBS was positively associated with cortical
thickness and whole-bone stiffness at the tibia, its correlation with trabecular number and separation was not
significant and was not associated with trabecular thickness or stiffness in postmenopausal women. Therefore,
TBS is likely an indicator of bone microarchitecture rather
than trabecular bone specifically as its name denotes. Although the skeletal properties that affect TBS in diabetes
are uncertain, TBS can identify poor bone quality that is
not captured by DXA (8). TBS improved the fracture risk
prediction in addition to BMD in nondiabetics, and the
low TBS may explain higher fracture risk in patients with
diabetes (18, 20, 26).
Several studies have investigated poor bone quality or
weak bone strength in patients with type 2 diabetes.
Pritchard et al (27) shows through magnetic resonance
imaging that postmenopausal women with type 2 diabetes
had larger holes within the trabecular bone network at the
distal radius than nondiabetic women. In histomorphometric studies, the number of trabeculae in diabetic patients is significantly lower compared with nondiabetics
(28). Cortical porosity is increased at the radius in diabetic
women compared with nondiabetics (29). According to
Burghardt et al (30), microarchitectural deficits in the cortical bone of diabetic patients, as assessed using high-resolution-peripheral quantitative computed tomography,
may be associated with impaired bending strength due to
the inefficient redistribution of bone mass, which is characterized by cortical bone loss with higher trabecular volumetric BMD. Thus, both intracortical porosity and impaired trabecular microstructure may contribute to weak
bone strength in diabetes. Although lumbar spine TBS did
not distinguish the trabecular from the cortical compartment, it discerned the areas of missing bones in both compartments indirectly.
Correlation Analysis Between Trabecular Bone Scores and Skeletal or Biochemical Measures in All Subjects
Men
Lumbar spine BMD
Femur neck BMD
Total hip BMD
HbA1C
Fasting plasma glucose
Fasting insulin
HOMA-IR
HOMA-␤
Total cholesterol
HDL cholesterol
Triglycerides
LDL cholesterol
hs-CRP
a
479
Women
R
R2
Age and
BMI-Adjusted r
r
R2
Age and
BMI-Adjusted r
0.305a
0.294a
0.303a
⫺0.111a
⫺0.129a
⫺0.157a
⫺0.183a
⫺0.016
0.007
0.016
⫺0.135a
0.045
⫺0.196a
0.093
0.086
0.012
0.016
0.024
0.033
0.001
0.001
0.001
0.001
0.018
0.002
0.038
0.411a
0.300a
0.359a
⫺0.073a
⫺0.102a
⫺0.122a
⫺0.144a
0.004
0.020
⫺0.035
⫺0.118a
0.057
⫺0.147a
0.529a
0.491a
0.495a
⫺0.116a
⫺0.090a
⫺0.142a
⫺0.138a
⫺0.036
0.040
0.070a
⫺0.080a
0.045
⫺0.139a
0.280
0.241
0.245
0.013
0.008
0.020
0.019
0.001
0.002
0.005
0.006
0.002
0.019
0.436a
0.307a
0.341a
⫺0.061a
⫺0.066a
⫺0.147a
⫺0.150a
⫺0.049
0.012
0.025
⫺0.077a
0.023
⫺0.122a
P ⬍ .05.
The Endocrine Society. Downloaded from press.endocrine.org by [Andrew Harmon] on 15 May 2015. at 13:11 For personal use only. No other uses without permission. . All rights reserved.
480
Kim et al
Diabetes and Trabecular Bone Score
J Clin Endocrinol Metab, February 2015, 100(2):475– 482
a
a
b
b
Figure 1. Scatter plots between TBS and age in men (A) and women (B).
Although a Canadian study by Leslie et al (16) also
shows that lumbar spine TBS was a BMD-independent
predictor of fracture risk in subjects with diabetes, the
relationship between TBS and diabetes has never been assessed in Asians, although a novel finding of our study was
that TBS was related with metabolic risk factors because
a high blood glucose level and HbA1c were associated
with low TBS, even after adjustment for age and BMI,
implying impaired bone quality. Low TBS in diabetic patients may be due to the accumulation of advanced glycosylation end-products (AGEs) in bone collagens (32, 33)
The accumulation of cross-links induced by nonenzymatic
glycation may contribute to a reduction in bone turnover
resulting from the altered responses of osteoblasts and
osteoclasts to AGEs (32). A low turnover state and glycated collagen matrix in type 2 diabetes may lead to brittle
bones, regardless of BMD (32). Elevated urine pentosidine, one of the AGEs, is associated with a 42% increase
in clinical fracture incidence in type 2 diabetes (34). TBS
may reflect the accumulation of AGEs as a bone quality
marker, which was underpinned by the observed relationship between HOMA-IR and TBS. We showed that high
Figure 2. Scatter plots between TBS and BMI in men (A) and women (B).
glucose and insulin levels were associated with TBS, which
was contributed by insulin resistance, not by ␤-cell function. Insulin resistance is the main pathophysiology of type
2 diabetes (35). Therefore, the inverse relationship between insulin resistance and TBS corroborated the bone
microarchitecture alterations in type 2 diabetes. However,
further study is needed to elucidate the role of insulin resistance on bone quality independently of hyperglycemia.
Chronic low-grade inflammation is also associated
with both diabetes and fractures (36, 37). Serum hs-CRP,
an inflammatory biomarker, was associated with weak
bone strength and high fracture risk (37, 38). In the Osteoporotic Fractures in Men Sweden study, individuals
with high serum levels of hs-CRP have an increased fracture risk independent of BMD, which is mediated by impaired bone microarchitecture (37). In our study, we similarly found that lumbar spine TBS as a bone quality
marker was inversely related with serum hs-CRP levels.
In the present study, high serum triglycerides were also
associated with low TBS but not with lumbar or hip BMD
values (data not shown). This contradicts previous studies
that suggested high serum triglycerides predict a low risk
The Endocrine Society. Downloaded from press.endocrine.org by [Andrew Harmon] on 15 May 2015. at 13:11 For personal use only. No other uses without permission. . All rights reserved.
doi: 10.1210/jc.2014-2047
of fractures. However, the association between serum triglycerides and BMD is controversial because the inverse
relationship between serum triglyceride level and TBS is
lost after adjusting for fat mass (39). Thus, the relationship
between serum triglycerides and TBS may be dependent on
fat mass.
Our study had several strengths. We directly evaluated
the relationship between TBS and plasma glucose, insulin,
HbA1c, lipid profiles, and serum hs-CRP and found that
insulin resistance is associated with low TBS in diabetes. In
addition, we included male subjects, in whom TBS was not
been studied extensively (19). Although a higher TBS
value in men than in women may influence our findings,
the trends in TBS values in relation to diabetes were similar
in both genders.
Our study had some limitations. We did not consider
the onset, duration, or severity of diabetes, or the use of
antidiabetic drugs, which may be important because severe and a long duration of diabetes appears to increase
fracture risk. Specific types of osteoporosis medication
were not available, so those were not included in our analysis. We did not analyze several confounding factors due
to the lack of data. However, bone health-related factors
such as calcium, vitamin D, and muscle strength may affect
both BMD and TBS. Therefore, the confounding factors
may not explain the discrepancy between TBS and BMD.
We did not measure bone turnover markers, and as a
cross-sectional study, we did not link our study results to
future fracture outcomes. Thus, future studies should investigate prospectively the effect of low TBS on fracture
outcome. In men, TBS was not established regarding the
reference value or fracture prediction. TBS values were
higher in men than that in women, which was also criticized elsewhere (15). Glycemic status may affect stronger
TBS in women younger than 65 years than those older
than 65 years. In women 65 years old or older, TBS values
in persons with diabetes were not different from those in
nondiabetics. The annual rate of TBS loss is accelerated
after 65 years, indicating the age effect may be stronger
than glycemic status in older women (31).
Taken together, the lumbar spine TBS was related to
glycemic control, insulin resistance, and inflammation, indicating that the lumbar spine TBS may recognize impaired bone quality in type 2 diabetes that BMD measures
do not. Therefore, the lumbar spine TBS may helpful to
identify bone health in type 2 diabetes in which BMD is
paradoxically increased.
Acknowledgments
Address all correspondence and requests for reprints to: Chan
Soo Shin, MD, PhD, Department of Internal Medicine, Seoul
jcem.endojournals.org
481
National University College of Medicine, 101 Daehak-ro,
Jongno-gu, Seoul 110-744, Korea. E-mail: [email protected]; or
Nam H. Cho, PhD, Department of Preventive Medicine, Ajou
University School of Medicine, #5 Wonchon-Dong, YoungtongGu, Suwon, 443-721, Korea. E-mail: [email protected].
This work was supported by the Research Program funded by
the Korea Centers for Disease Control and Prevention (Grants
2009-E71007-00 and 2010-E71004-00) and the Ministry of
Health and Welfare of Korea (Grant A121445).
Disclosure Summary: The authors have nothing to disclose.
References
1. Shaw JE, Sicree RA, Zimmet PZ. Global estimates of the prevalence
of diabetes for 2010 and 2030. Diabetes Res Clin Pract. 2010;87:
4 –14.
2. Leslie WD, Rubin MR, Schwartz AV, Kanis JA. Type 2 diabetes and
bone. J Bone Miner Res. 2012;27:2231–2237.
3. Strotmeyer ES, Cauley JA, Schwartz A V, et al. Nontraumatic fracture risk with diabetes mellitus and impaired fasting glucose in older
white and black adults: the health, aging, and body composition
study. Arch Intern Med. 2005;165:1612–1617.
4. Schwartz AV, Sellmeyer DE, Ensrud KE, et al. Older women with
diabetes have an increased risk of fracture: a prospective study. J Clin
Endocrinol Metab. 2001;86:32–38.
5. Bonds DE, Larson JC, Schwartz AV, et al. Risk of fracture in women
with type 2 diabetes: the Women’s Health Initiative Observational
Study. J Clin Endocrinol Metab. 2006;91:3404 –3410.
6. Melton LJ, Leibson CL, Achenbach SJ, Therneau TM, Khosla S.
Fracture risk in type 2 diabetes: update of a population-based study.
J Bone Miner Res. 2008;23:1334 –1342.
7. Janghorbani M, Van Dam RM, Willett WC, Hu FB. Systematic
review of type 1 and type 2 diabetes mellitus and risk of fracture.
Am J Epidemiol. 2007;166:495–505.
8. Schwartz AV, Vittinghoff E, Bauer DC, et al. Association of BMD
and FRAX score with risk of fracture in older adults with type 2
diabetes. JAMA. 2011;305:2184 –2192.
9. Johnell O, Kanis JA, Oden A, et al. Predictive value of BMD for hip
and other fractures. J Bone Miner Res. 2005;20:1185–1194.
10. Siris ES, Miller PD, Barrett-Connor E, et al. Identification and fracture outcomes of undiagnosed low bone mineral density in postmenopausal women: results from the National Osteoporosis Risk
Assessment. JAMA. 2001;286:2815–2822.
11. Link TM, Majumdar S. Current diagnostic techniques in the evaluation of bone architecture. Curr Osteoporos Rep. 2004;2:47–52.
12. Rubin CD. Emerging concepts in osteoporosis and bone strength.
Curr Med Res Opin. 2005;21:1049 –1056.
13. Dalle Carbonare L, Giannini S. Bone microarchitecture as an important determinant of bone strength. J Endocrinol Invest. 2004;
27:99 –105.
14. Seeman E. Is a change in bone mineral density a sensitive and specific
surrogate of anti-fracture efficacy? Bone. 2007;41:308 –317.
15. Bousson V, Bergot C, Sutter B, Levitz P, Cortet B. Trabecular bone
score (TBS): available knowledge, clinical relevance, and future
prospects. Osteoporos Int. 2012;23:1489 –1501.
16. Leslie WD, Aubry-Rozier B, Lamy O, Hans D. TBS (trabecular bone
score) and diabetes-related fracture risk. J Clin Endocrinol Metab.
2013;98:652– 659.
17. Winzenrieth R, Dufour R, Pothuaud L, Hans D. A retrospective
case-control study assessing the role of trabecular bone score in
postmenopausal Caucasian women with osteopenia: analyzing the
odds of vertebral fracture. Calcif Tissue Int. 2010;86:104 –109.
18. Boutroy S, Hans D, Sornay-Rendu E, Vilayphiou N, Winzenrieth R,
Chapurlat R. Trabecular bone score improves fracture risk predic-
The Endocrine Society. Downloaded from press.endocrine.org by [Andrew Harmon] on 15 May 2015. at 13:11 For personal use only. No other uses without permission. . All rights reserved.
482
19.
20.
21.
22.
23.
24.
25.
26.
27.
28.
Kim et al
Diabetes and Trabecular Bone Score
tion in non-osteoporotic women: the OFELY study. Osteoporos Int.
2013;24:77– 85.
Leib E, Winzenrieth R, Aubry-Rozier B, Hans D. Vertebral microarchitecture and fragility fracture in men: a TBS study. Bone. 2014;
62:51–55.
Hans D, Goertzen AL, Krieg M-A, Leslie WD. Bone microarchitecture assessed by TBS predicts osteoporotic fractures independent of
bone density: the Manitoba study. J Bone Miner Res. 2011;26:
2762–2769.
Cho NH, Jang HC, Choi SH, et al. Abnormal liver function test
predicts type 2 diabetes: a community-based prospective study. Diabetes Care. 2007;30:2566 –2568.
Korea National Statistical Office. STAT-Korea Census. Seoul, Korea: Korea National Statistical Office; 2000.
American Diabetes Association. Standards of medical care in diabetes—2014. Diabetes Care. 2014;37(suppl 1):S14 –S80.
Matthews DR, Hosker JP, Rudenski AS, Naylor BA, Treacher DF,
Turner RC. Homeostasis model assessment: insulin resistance and
␤-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia. 1985;28:412– 419.
Silva BC, Boutroy S, Zhang C, et al. Trabecular bone score (TBS)—a
novel method to evaluate bone microarchitectural texture in patients with primary hyperparathyroidism. J Clin Endocrinol Metab.
2013;98:1963–1970.
Iki M, Tamaki J, Kadowaki E, et al. Trabecular bone score (TBS)
predicts vertebral fractures in Japanese women over 10 years independently of bone density and prevalent vertebral deformity: the
Japanese Population-Based Osteoporosis (JPOS) cohort study.
J Bone Miner Res. 2014;29:399 – 407.
Pritchard JM, Giangregorio LM, Atkinson SA, et al. Association of
larger holes in the trabecular bone at the distal radius in postmenopausal women with type 2 diabetes mellitus compared to controls.
Arthritis Care Res (Hoboken). 2012;64:83–91.
La Fontaine J, Shibuya N, Sampson HW, Valderrama P. Trabecular
quality and cellular characteristics of normal, diabetic, and charcot
bone. J Foot Ankle Surg. 2011;50:648 – 653.
J Clin Endocrinol Metab, February 2015, 100(2):475– 482
29. Patsch JM, Burghardt AJ, Yap SP, et al. Increased cortical porosity
in type 2 diabetic postmenopausal women with fragility fractures.
J Bone Miner Res. 2013;28:313–324.
30. Burghardt AJ, Issever AS, Schwartz AV, et al. High-resolution peripheral quantitative computed tomographic imaging of cortical and
trabecular bone microarchitecture in patients with type 2 diabetes
mellitus. J Clin Endocrinol Metab. 2010;95:5045–5055.
31. Dufour R, Winzenrieth R, Heraud A, Hans D, Mehsen N. Generation and validation of a normative, age-specific reference curve for
lumbar spine trabecular bone score (TBS) in French women. Osteoporos Int. 2013;24:2837–2846.
32. Vashishth D. The role of the collagen matrix in skeletal fragility.
Curr Osteoporos Rep. 2007;5:62– 66.
33. Schwartz A V. Diabetes mellitus: does it affect bone? Calcif Tissue
Int. 2003;73:515–519.
34. Schwartz AV, Garnero P, Hillier TA, et al. Pentosidine and increased
fracture risk in older adults with type 2 diabetes. J Clin Endocrinol
Metab. 2009;94:2380 –2386.
35. DeFronzo RA, Ferrannini E. Insulin resistance. A multifaceted syndrome responsible for NIDDM, obesity, hypertension, dyslipidemia, and atherosclerotic cardiovascular disease. Diabetes Care.
1991;14:173–194.
36. Duncan BB, Schmidt MI. The epidemiology of low-grade chronic
systemic inflammation and type 2 diabetes. Diabetes Technol Ther.
2006;8:7–17.
37. Eriksson AL, Movérare-Skrtic S, Ljunggren Ö, Karlsson M, Mellström D, Ohlsson C. High-sensitivity CRP is an independent risk
factor for all fractures and vertebral fractures in elderly men: the
MrOS Sweden study. J Bone Miner Res. 2014;29:418 – 423.
38. Oei L, Campos-Obando N, Dehghan A, et al. Dissecting the relationship between high-sensitivity serum C-reactive protein and increased fracture risk: the Rotterdam Study. Osteoporos Int. 2014;
25:1247–1254.
39. Esposito K, Capuano A, Sportiello L, Giustina A, Giugliano D.
Should we abandon statins in the prevention of bone fractures?
Endocrine. 2013;44:326 –333.
The Endocrine Society. Downloaded from press.endocrine.org by [Andrew Harmon] on 15 May 2015. at 13:11 For personal use only. No other uses without permission. . All rights reserved.