Key words osteoporosis - QCT - bone turnover - menstrual cycle - estrogen - genetics
Introduction
The identification of clinical risk factors for fragility fracture provides the potential
for prevention of osteoporosis. One risk factor to predict hereditary risk of osteoporosis
is a biological relative who has experienced a low-trauma fracture – this is considered
a fragility fracture family history (FFFH+) [1 ]. The increased fracture risk conferred by a parent with a hip fracture is modest
(RR about 1.5), but it was independent of bone mineral density (BMD) in a meta-analysis
of population-based prospective studies [1 ]. BMD and the presence of fragility fractures have long been known to relate to genetic
as well as to environmental factors [2 ], [3 ]. In the era of densitometry, osteoporosis is commonly defined by a low T-score [4 ] or by a high estimated 10-year risk of fragility fracture as predicted by sex, age
and other clinical risk factors with or without BMD [5 ], [6 ], rather than, as commonly in the past, by a history of having personally experienced
a low trauma fracture [7 ].
Most research on the genetics of osteoporosis has been cross-sectional in nature,
whether using monozygous and dyzygous twins [8 ], [9 ] or performing genome-wide association studies (GWAS) [10 ], [11 ], [12 ]. In addition, until recently the genetics of BMD in older men and women (at higher
fracture risk) rather than in younger women and men (where genetics may play a larger
role) has been the focus of most GWAS and meta-analyses of genome-wide associations
[12 ]. However, several animal studies clearly show that rates of change in bone growth
and strength [13 ] as well as in acute post-oophorectomy bone change [14 ] differ by highly inbred genetic strain within rodent species. Twin studies also
show a small portion of BMD heritability is related to bone turnover markers [15 ].
By contrast, an association between longitudinal change in BMD and a family history of fragility fracture has proved more elusive. Although
bone remodelling rate is associated with both BMD and fracture [16 ], [17 ], the few prospective human studies that have assessed change in BMD in twins have been unable to show
associations. For example, radial bone change over 16-years in twin men was unrelated
to heredity [18 ]. Also, four-year change in lumbar spine BMD in women twins could show heritability
only by using a 1-tailed T-test [19 ]. Likewise, population-based prospective studies in younger women, the majority of
whom were either premenopausal [20 ] or perimenopausal [21 ], have been unable to show areal BMD change rate differences (by dual energy X-ray
[DXA] measurements) related to the presence or absence of FFFH.
Thus, although it is logical that an increased rate of BMD loss would be found in
those with a history of a family member who suffered a fragility fracture, this has
not yet been documented to date. The ability to detect differences in bone change
is related to sample size, duration of study, the sex of the sample, their position
within the lifecycle and to the type of bone that is being assessed. In particular,
cortical bone changes more slowly than trabecular bone; previous studies have assessed
peripheral cortical bone (radius) or areal BMD (by DXA) that includes both cortical
and trabecular bone compartments. These measures are less sensitive to change than
volumetric trabecular bone measured by quantitative computed tomography (QCT). Therefore
the purpose of this pooled analysis was to assess rates of BMD change in healthy menstruating
women who did or did not have a relative with a low trauma fracture by examining change
in spinal volumetric trabecular BMD by QCT.
Materials and Methods
Regularly menstruating, primarily white women from prospective, observational BMD
studies in two centers (Vancouver, Canada and Munich, Germany) were included. Both
cohorts included only volunteer community participants in whom bone-relevant or endocrine
disease had been excluded as reported in the original publications [22 ], [25 ], [26 ]. All 20 in the Munich cohort and 64 of 66 in the Vancouver cohort were Caucasian.
Quantitative Computer Tomography (QCT) was used for measuring spinal volumetric trabecular
bone. Within both cohorts, FFFH was assessed by questionnaire: “Has a biological relative
broken a bone without major trauma or developed height loss and become hunched?” Both
studies were approved by local university ethics boards (Clinical Research Ethics
Board, University of British Columbia; Ethikkommission der Medizinischen Fakultät
TUM) and followed the principles of Helsinki. All women provided written informed
consent.
Vancouver cohort
As previously reported, in 1985–1987 premenopausal women were recruited to a one-year
study of QCT bone change by exercise and menstrual cycle characteristics [22 ]. The 66 women were ages 20 to 42, healthy, non-smoking, of normal weight and not
taking hormones. According to complete dietary data they had healthy diets and none
were deficient in nutrients nor excessively supplementing. All reported regular menstrual
cycles and prior to study entry were required to have two consecutive, normal length
(21–36 day) cycles with normal ovulation (luteal phase lengths of ≥ 10 days) as assessed
by the validated quantitative basal temperature method [23 ], [24 ]. Women varied in exercise habits from normally active to training for and running
a marathon during the study. Menstrual cycle and ovulatory characteristics were similar
across exercise habits and menstruation remained regular throughout the one-year study
with no one developing oligomenorrhea or amenorrhea. The family history of a fragility
fracture was updated five years after baseline [25 ].
Munich cohort
Caucasian community women volunteers over age 30 were recruited to a prospective study
of midlife bone change [26 ]. Only those 20 of these who were initially and remained premenopausal at the two-year
QCT measurement were included in the present analysis. They were healthy, normally
active, not taking hormones, nor high-dose nutrition supplements or bone relevant
medications and a response about FFFH was obtained at baseline in 2001–2 [26 ]. The questionnaire data on whether or not a relative had experienced a fragility
fracture were reviewed and answers updated with participants in December 2010.
Bone measurement – volumetric trabecular spinal bone mineral density by QCT
In Vancouver, QCT of thoracic 12th through lumbar 3rd vertebrae was measured in duplicate
with repositioning at baseline and at 12 months by computed tomography (Siemens DR2,
96 kV, 300 mAs; slice thickness 8 mm), using an edge detection method with within-person
reproducibility with repositioning of 0.8 [22 ]. These data were converted into mineral equivalents of dibasic potassium phosphate
and reported as mg/cm3 using a phantom developed by Genant and Cann [28 ].
In Munich, QCT of lumbar vertebrae 1 through 3 was measured at baseline and two-years.
The center of each vertebra was located using a scout film [26 ]. The computed tomography instruments (two of identical make were utilized; Somatom
by Siemens, Erlangen, Germany; 80 kVp at 146 mAs) gave results that were calibrated,
reported as mg/cm3 and standardized using measurements of the hydroxyapatite-containing European Spine
Phantom [29 ]. This phantom shows parallel age-related cross-sectional data with the original
QCT Genant and Cann phantom [28 ]. All QCT change data were annualized before analysis.
Demographic, reproductive, educational and medical histories were obtained by questionnaire.
All women in Vancouver had their height measured in stocking feet and weight measured
on a balance beam in light clothing. In Munich, women reported their most recently
recalled height and weight. In Vancouver, Menstrual Cycle Diary records for the entire
year were used to compute average menstrual cycle length and average luteal phase
length was derived by quantitative basal temperature analysis [23 ], [24 ]. The Munich cohort was asked to recall their minimum and maximum menstrual cycle
lengths at 6-monthly intervals (5 times over two years); mean menstrual cycle length
was computed from the average of all these values.
Serum and urine specimens were collected in both studies. In the Vancouver cohort
serum and fasting urine were obtained in both the mid-follicular and the premenstrual
phases of the initial and final cycles of the study year. Methods for all biochemical
and hormonal measurements are as previously reported [22 ], [32 ]. In the Munich cohort, fasting serum and urine samples were obtained at baseline,
as well as at three, six, nine, 12 and 24 month visits and without cycle timing. Methods
for all these hormonal and biochemical variables are as previously reported [27 ], [32 ]. For each variable, a within-woman average was computed and used in this analysis.
Statistical analysis
The primary outcome was annualized QCT change [30 ]. Within each cohort, characteristics of women with and without a family fragility
fracture history were compared using T-tests, cross-tabulation or non-parametric tests,
as appropriate. Luteal phase length, a variable that has been previously found to
account for 20 % of variability in QCT change [22 ], was only available for the Vancouver cohort. Accordingly, tertile of mean luteal
phase length (luteal tertile) was included as a covariate for analysis of the Vancouver
FFFH data; thus annual QCT change was analyzed by two-factor Analysis of Variance
(ANOVA) by luteal phase length tertile and FFFH status. For combined cohorts, annual
QCT change was analyzed by two-factor ANOVA by center and FFFH. Data are reported
as the mean, median and standard deviation (SD). Differences by whether or not women
had FFFH+ are reported as mean and 95 % confidence intervals (CI) of the difference.
All tests were two-tailed with p = 0.05 accepted as statistically significant.
Results
Data are presented first for each cohort separately, their differences and then the
combined cohort that provided the important, primary results.
Vancouver cohort
Within the Vancouver cohort 22 of the 66 women (33 %) gave a positive history of a
family fragility fracture (FFFH+) ([Table 1 ]). This cohort averaged 33.7 years of age at baseline with a body mass index (BMI)
of 22.1 and an initial QCT of 154.3 mg/cm3 [22 ]. The presence or absence of FFFH was not associated with differences in age, weight,
height, BMI, exercise or the mean of four 7-day diet diary characteristics (not reported)
or with one-year changes in these variables ([Table 1 ]). Cycle lengths, however, averaged 29.2 in those with a FFFH+ versus 28 days in
women without (p = 0.06). Between those with/without FFFH there were no significant
differences in luteal phase lengths or exercise patterns – 61 % of FFFH− and 73 %
of FFFH+ women used running as their primary form of physical activity (Fisherʼs exact
test p = 0.42). Women with and without FFFH also did not differ in average serum levels
of estradiol, progesterone, calcium, or osteocalcin but women who were FFFH+ had significantly
lower total alkaline phosphatase levels ([Table 1 ]). Although both baseline and one-year cross-sectional QCT values were similar by
FFFH±, those with a family history of fragility fracture (FFFH+) showed a greater
annual QCT rate of BMD loss than those without ([Table 1 ]).
Table 1 Munich cohort and Vancouver cohort: baseline and final demographic and quantitative
computed tomography of volumetric trabecular spinal bone (QCT, mg/cm3 ) and QCT changes for the 20 Munich and 66 Vancouver women, by fragility fracture
family history (FFFH±). The 95 % confidence interval (CI) of the difference and p-values
are shown in the final two columns with significant differences in bold. Note: Munich:
2-year QCT interval, Vancouver: 1-year QCT interval.
Munich cohort
Vancouver cohort
FFFH− (n = 11)
FFFH+ (n = 9)
Difference (95 % CI)
p
FFFH− (n = 44)
FFFH+ (n = 22)
Difference (95 % CI)
p
# % runners: Fisherʼs exact test
Age (y)
43.6 (4.5)
43.2 (6.5)
0.4 (− 4.8 to 5.6)
0.87
33.5 (5.8)
34.3 (5.2)
− 0.9 (− 3.8 to 2.1)
0.56
Height (cm)
165.9 (6.4)
164.3 (8.9)
1.6 (− 5.6 to 8.7)
0.65
161.3 (6)
163.5 (7.1)
− 2.2 (− 5.5 to 1.1)
0.19
Baseline weight (kg)
67.2 (13.2)
62.1 (10.7)
5.2 (− 6.9 to 17.2)
0.38
58.1 (5.3)
58.3 (8.7)
− 0.2 (− 3.6 to 3.2)
0.92
Change in weight (kg)
0.2 (4.1)
− 0.6 (2.2)
0.7 (− 3.2 to 4.6)
0.69
0.5 (2.9)
− 0.6 (2.9)
1.1 (− 0.4 to 2.7)
0.14
Baseline BMI
24.3 (3.7)
23.2 (3)
1.1 (− 2.1 to 4.3)
0.49
22.4 (1.7)
21.7 (2.4)
0.7 (− 0.3 to 1.7)
0.18
Change in BMI
0.3 (1.4)
− 0.2 (0.8)
0.5 (− 0.9 to 1.8)
0.47
0.1 (1)
− 0.2 (1.2)
0.3 (− 0.3 to 0.8)
0.33
Baseline QCT (mg/cm3 )
142.9 (18.6)
139.9 (25.3)
3.0 (− 17.6 to 23.6)
0.76
155.4 (21.8)
152.1 (22.0)
3.3 (− 8.1 to 14.7)
0.57
Final QCT (mg/cm3 )
139.7 (18.2)
134.9 (23.6)
4.7 (− 14.9 to 24.3)
0.62
153.3 (22.1)
146.7 (21.7)
6.6 (− 4.9 to 18.0)
0.25
QCT change/y (mg/cm3 )
− 1.6 (3.5)
− 2.5 (3.3)
0.8 (− 2.4 to 4.1)
0.60
− 2.3 (4.7)
− 5.9 (5.2)
3.6 (1.1 to 6.2)
0.006
Menstrual cycle length (days)
28.0 (3.6)
30.3 (4.1)
− 2.3 (− 6.4 to 1.9)
0.26
28.0 (2.1)
29.2 (2.8)
− 1.2 (− 2.4 to 0.0)
0.06
Serum calcium (mmol/L)
2.33 (0.05)
2.30 (0.06)
0.03 (− 0.02 to 0.09)
0.19
2.3 (0.1)
2.3 (0.1)
− 0.1 (− 0.1 to 0.0)
0.09
Serum phosphate (mmol/L)
1.09 (0.09)
1.12 (0.12)
− 0.04 (− 0.14 to 0.07)
0.46
1.2 (0.1)
1.1 (0.1)
0.03 (− 0.2 to 0.8)
0.29
Alkaline phosphatase (IU/L)
54.6 (15.4)
46.6 (11.0)
− 8.0 (− 0.6 to − 15.4)
0.03
Pyridinoline (nmol/mmol Cr)
34.26 (5.52)
35.29 (7.61)
− 1.03 (− 7.20 to 5.14)
0.73
Deoxypyridinoline (nmol/mmol Cr)
7.72 (1.64)
8.02 (1.57)
− 0.30 (− 1.82 to 1.22)
0.68
Vitamin D (ng/ml)
24.01 (8.54)
24.08 (8.48)
− 0.07 (− 8.11 to 7.97)
0.99
Percent runners
27 (61.4 %)
16 (72.7 %)
0.42#
Osteocalcin (ng/ml)
4.82 (0.80)
5.49 (1.06)
− 0.68 (− 1.54 to 0.19)
0.12
4.0 (1.2)
4.0 (1.0)
0.1 (− 0.5 to 0.7)
0.86
Bone-specific alkaline phosphatase (ng/ml)
7.62 (2.03)
8.48 (2.27)
− 0.85 (− 2.87 to 1.17)
0.39
N-Telopeptide (nmol BCE/mmol Cr)
32.22 (8.09)
41.24 (9.63)
− 9.02 (− 17.34 to − 0.70)
0.04
C-Telopeptide (ng/ml)
0.16 (0.07)
0.30 (0.14)
−0.14 (− 0.24 to − 0.04)
0.01
Urinary calcium (mmol/mmol Cr)
0.3 (0.1)
0.5 (0.4)
− 0.2 (− 0.5 to 0.0)
0.08
0.4 (0.2)
0.4 (0.2)
0.0 (− 0.7 to 0.1)
0.56
Estradiol (pmol/L)
372.9 (173.3)
354.1 (211.5)
18.8 (− 161.8 to 199.4)
0.83
291.1 (19.3)
255.4 (84.6)
35.7 (− 23.9 to 95.2)
0.24
Progesterone (nmol/L)
15.5 (8.1)
12.3 (6.4)
− 3.2 (0.8 to − 7.1)
0.12
[Fig. 1 ] shows the one-year change in QCT in the Vancouver cohort with and without a FFFH
represented in tertiles of luteal phase length (Tertile 1: 4.6–10.1; Tertile 2: 10.2–11.3;
Tertile 3: 11.4–13.7 days) since luteal phase length explained 20 % of the variance
in QCT change [22 ]. By 2-factor ANOVA, QCT change/year was significantly related to luteal phase length
(F2, 59 = 5.51, p = 0.006) as well as to a family history of fragility fracture (F1, 59 = 9.74, p = 0.003). However, there was no luteal length by FFFH interaction (F2, 59 = 0.7) in the Vancouver cohort.
Fig. 1 Annual change in volumetric trabecular spinal bone by quantitative computed tomography
(QCT) in mg/cm3 /year in the 66 premenopausal, initially ovulatory women in the Vancouver Cohort,
as those without a fragility fracture family history (FFFH−, n = 44) and those with
FFFH+ (n = 22) by tertiles of luteal phase length (see manuscript for a further description).
Munich cohort
In the Munich cohort, nine of 20 women (45 %) gave a history of a family member with
fragility fracture (FFFH+). The women in this cohort were on average 43.5 years old
with a BMI of 23.8 and an initial QCT of 141.6 mg/cm3 . [Table 1 ] shows that Munich women with FFFH+ did not differ in any demographic or reproductive
variable from women without this history. However, women with FFFH+ had bone resorption
markers that were higher – mean N-telopeptide levels were 9.02 nmol BCE/mmol Cr (95 %
CI: 0.70 to 17.34) higher and C-telopeptide levels were 0.14 ng/ml (95 %CI: 0.04 to
0.24) higher than in women without FFFH. All other mean hormonal and bone metabolism
markers were not different ([Table 1 ]). The numerically greater rate of bone loss in Munich women with FFFH+ compared
to those without did not reach statistical significance.
Cohort comparisons and differences
The Vancouver and Munich cohorts, although both initially including premenopausal,
healthy and primarily white women, differed in age, weight, BMI, interval between
QCT measurements and baseline and final QCT values ([Table 2 ] B ). However, the two cohorts did not differ in the proportion of each cohort with FFFH+,
mean 36 % (95 % CI of the difference: − 0.4 to 0.1). Nor did they differ in the annual
volumetric trabecular bone change by QCT (Vancouver = − 3.5 and Munich = − 2.0 mg/cm3 per year; 95 % CI of the difference: − 3.9 to, 0.9).
Table 2 A Combined Vancouver and Munich cohorts showing the mean of the total cohort and data
stratified by the absence or presence of a fragility fracture family history (FFFH±):
baseline demographic (age, height, weight, body mass index [BMI]) and change characteristics
of 86 healthy menstruating, primarily white (84 of 86) women in the combined cohorts
including 36 % of women with FFFH+. Cross-sectional data and longitudinal rates of
change in quantitative computed tomography volumetric trabecular spinal bone mineral
density (QCT, mg/cm3 ) are shown as 95 % CI of the difference with significant differences in bold. B Comparison between the Vancouver and Munich cohorts: baseline demographics (age,
height, weight, body mass index [BMI]) and change characteristics of the premenopausal
women in both cohorts having quantitative computed tomography volumetric trabecular
spinal bone density (QCT, mg/cm3 ) and QCT change data: 66 women in the Vancouver cohort, studied over one year; 20
women in the Munich cohort, studied over two years. Values are mean (SD). The 95 %
confidence interval (CI) of the difference is shown with significant differences in
bold.
A Combined cohorts
B Comparison between Vancouver and Munich cohort
FFFH− (n = 55)
FFFH+ (n = 31)
Difference (95 % CI)
p
Vancouver (n = 66)
Munich (n = 20)
Difference (95 % CI)
p
Age (y)
35.5 (6.9)
36.9 (6.8)
− 1.4 (− 4.5 to 1.7)
0.36
33.7 (5.6)
43.5 (5.4)
− 9.7 (− 12.5 to − 6.9)
< 0.001
Height (cm)
162.2 (6.3)
163.7 (7.5)
− 1.5 (− 4.5 to 1.5)
0.32
162 (6.4)
165.2 (7.4)
− 3.2 (− 6.6 to 0.2)
0.06
Baseline weight (kg)
59.9 (8.2)
59.3 (9.2)
0.6 (− 3.2 to 4.5)
0.74
58.2 (6.5)
65.1 (12.2)
-6.9 (− 11.1 to − 2.7)
0.002
Change in weight (kg)
0.5 (3.1)
− 0.6 (2.7)
1.1 (− 0.3 to 2.5)
0.13
0.2 (2.9)
− 0.1 (3.4)
0.3 (− 1.4 to 2.0)
0.73
Baseline BMI
22.8 (2.4)
22.1 (2.6)
0.6 (− 0.5 to 1.7)
0.25
22.1 (2)
23.8 (3.4)
− 1.7 (− 2.9 to − 0.5)
0.006
Change in BMI
0.1 (1.1)
− 0.2 (1.1)
0.3 (− 0.2 to 0.8)
0.22
0.0 (1.0)
0.1 (1.2)
− 0.1 (− 0.7 to 0.5)
0.7
Baseline QCT (mg/cm³)
152.9 (21.6)
148.6 (23.3)
4.3 (− 5.6 to 14.2)
0.39
154.3 (21.7)
141.6 (21.3)
12.7 (1.8 to 23.7)
0.02
Final QCT (mg/cm³)
150.6 (21.9)
143.3 (22.5)
7.3 (− 2.6 to 17.1)
0.15
151.1 (22)
137.6 (20.4)
13.5 (2.5 to 24.5)
0.02
QCT change/y (mg/cm³)
− 2.2 (4.4)
− 4.9 (5)
2.7 (0.7 to 4.8)
0.01
− 3.5 (5.1)
− 2.0 (3.4)
− 1.5 (− 3.9 to 0.9)
0.56
Years between QCT
1.2 (0.5)
1.3 (0.6)
− 0.1 (− 0.3 to 0.1)
0.45
1.0 (0.2)
2.2 (0.3)
− 1.2 (− 1.2 to − 1.1)
< 0.001
Serum calcium (mmol/L)
2.27 (0.11)
2.31 (0.09)
− 0.03 (− 0.08 to 0.01)
0.17
2.28 (0.11)
2.32 (0.06)
− 0.04 (− 0.10 to 0.01)
0.112
Serum phosphate (mmol/L)
1.15 (0.10)
1.14 (0.12)
0.02 (− 0.03 to 0.06)
0.48
1.16 (0.10)
1.10 (0.11)
0.06 (0.00 to 0.11)
0.035
Osteocalcin (ng/ml)
4.18 (1.19)
4.40 (1.21)
− 0.22 (− 0.76 to 0.31)
0.41
3.99 (1.14)
5.12 (0.96)
− 1.13 (− 1.69 to − 0.57)
< 0.001
Estradiol (pmol/L)
308.1 (138.9)
284.1 (137.9)
24.0 (− 38.3 to 86.3)
0.45
278.84 (113.61)
364.40 (186.38)
− 85.57 (− 153.87 to − 17.26)
0.015
The combined cohorts as shown in [Table 2 ] A did not differ by FFFH in any baseline or change demographic variables. For the biochemical
data that were jointly available (serum calcium, phosphate, osteocalcin and estradiol
levels) there was no interaction or main effect of FFFH.
Combined cohort
In the combined cohort, women with a biological relative having had a fragility fracture
(FFFH+; n = 31) lost bone at a faster rate per year (− 4.9 mg/cm3 ) than did those without FFFH (n = 55; − 2.2 mg/cm3 ; 95 % CI of the difference: − 0.7, − 4.8). A 2-factor ANOVA of annual QCT change
by center and FFFH showed that center was not significant (F1, 83 = 2.41, p = 0.12) but that a fragility fracture family history was significantly
related to the rate of QCT change (F1, 83 = 7.88, p = 0.006).
A scatter-plot of individual data in the combined cohorts by the absence or presence
of FFFH is shown in [Fig. 2 ]. This illustrates the greater rate of loss in those who have a biological relative
with a fragility fracture. Fragility fracture family history explained 7.7 % of the
variance in QCT change (r = 0.27).
Fig. 2 Annual change in volumetric trabecular spinal bone mineral density by quantitative
computed tomography (QCT) in mg/cm3 /year in a cohort of 86 premenopausal women from Vancouver, Canada and Munich, Germany
depicted for those without a history of a fragility fracture in a relative (FFFH−)
or a positive history of fragility fractures in a family member (FFFH+).
Discussion
This prospective study in 86 healthy, menstruating Caucasian women shows that women
with a fragility fracture family history, compared to those without – lacking any
other demographic, historical, nutritional, menstrual cycle, luteal phase length,
exercise, hormonal or bone marker differences – have a significantly greater rate
of volumetric trabecular spinal bone loss by QCT. To our knowledge this is the first
time a family fragility fracture history has been shown to relate to trabecular bone
loss.
It was possible to show that the simple history of a relative with a fragility fracture
is associated with the rate of bone change because we studied premenopausal women in whom genetic influences on bone are more important than in older women (whose
BMD may be more influenced by lifestyle factors) [31 ], and because our measure of bone change assessed the most sensitive bone compartment
(spinal trabecular bone) using precise QCT methodology [22 ]. We were able to combine prospective data from two healthy cohorts of menstruating
primarily white women because, although residing on different continents and studied
a decade apart, they were all similarly queried about a fragility fracture in a family
member, were examined using similar QCT methodology and did not differ in annualized
QCT change.
In both cohorts, the history of osteoporosis in a relative is based on fragility fracture,
not on a low BMD. In addition, the Munich cohort measurements provided contemporary,
sensitive bone marker assays [32 ].
The strength of this study is that in both cohorts a wide range of variables related
to baseline QCT and QCT change were measured and were not different between those
with and without a family history of fragility fracture. We have shown that, by whether
or not they had FFFH+, women in the combined cohort did not differ in age, BMI, exercise,
menstrual cycle length (and ovulation and luteal phase length in Vancouver). Those
with FFFH+ versus FFFH− also did not differ in changes in weight, exercise or other variables that were comprehensively recorded. However,
the more sensitive and specific bone marker data from Munich showed higher bone resorption
marker levels (NTX and CTX) in those with FFFH+. In the Vancouver cohort, lower total
alkaline phosphatase levels occurred in the women with a family member who had a fragility
fracture. Also, in the Vancouver cohort for whom a mean of 10 cycles per year of continuous
data on luteal phase length were available, mean luteal phase length and FFFH did
not significantly interact (F2, 59 = 0.5029).
This study of longitudinal bone change in premenopausal women and family history of
fragility fracture needs to be replicated. Such a study should optimally be performed
within a population-based multicenter study of the premenopausal population with change
in BMD measures documented over ≥ five years. Ideally, in such a study luteal phase
length would also be documented because of its importance to the rate of change in
premenopausal bone density by QCT (22) as well as by DXA [34 ], [35 ]. A theoretical study of this design could do genetic analysis of potential bone-related
polymorphisms along with a comprehensive reproductive and lifestyle history to better
understand the bone loss occurring over womenʼs average of 30–45 years of premenopausal
menstruating life.
A family history of fragility fracture may add clinical information if a premenopausal
woman experienced a low peak bone mass related to a late menarche or anorexia [36 ], or is losing BMD more rapidly than normal related to oligomenorrhea [37 ] or recurrent ovulatory disturbances [22 ], [32 ], [33 ]. Such a history likely adds to her individual fracture risk [1 ] and suggests that she may be losing bone more rapidly.
In summary, these prospective data by QCT of volumetric trabecular spinal BMD change
show that a simple history of a fragility fracture in a biological relative predicts
a greater rate of premenopausal trabecular bone loss. Preliminary bone marker data
suggest that increased bone resorption, as might be hypothesized, mediates this inherited
increased rate of premenopausal bone loss. To our knowledge this is the first human
evidence that genetic risks for osteoporosis relate to premenopausal bone change as well as to cross-sectional BMD values. Larger and longer studies of younger men
and women of white and non-white races, ideally from a population-based cohort, in
whom detailed family fracture information has been collected, will likely advance
our clinical understanding of the role of heredity in rates of bone loss and thus
in risk for osteoporotic fractures. Also, new diagnostic techniques such as bone microstructural
assessments might validate this new risk factor for bone loss as has been done for
other previously under-recognized risk factors such as ankle fracture [38 ].
The implications of this study are that a family history of a fragility fracture in
a younger, premenopausal woman who herself has osteoporosis risk factors (e.g. late
menarche, previous childhood fractures, irregular cycles, oligo-amenorrhea or regular
cycles with frequent ovulatory disturbances, such as can be found in infertility patients)
should lead to increased awareness about that young womanʼs later risk for fracture.
A next step would be to study specific diagnostic algorithms for these young women,
before treatment options in this hitherto untreated population can be explored. The
data clearly need replicating before general recommendations can be made or guidelines
should change.
Acknowledgements
This joint analysis was made possible by a one-month stipend to JCP as visiting professor
by the Institute of Advanced Studies (IAS) of the Technical University of Munich (TUM).
