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Insulin resistance and bone strength: findings from the study of midlife in the united statesInsulin Resistance and Bone Strength: Findings From theStudy of Midlife in the United States Preethi Srikanthan,1 Carolyn J Crandall,1 Dana Miller‐Martinez,1 Teresa E Seeman,1 Gail A Greendale,1 NeilBinkley,2 and Arun S Karlamangla1 1Department of Medicine, David Geffen School of Medicine at University of California, Los Angeles (UCLA), Los Angeles, CA, USA2Osteoporosis Clinical Center, University of Wisconsin‐Madison, Madison, WI, USA ABSTRACTAlthough several studies have noted increased fracture risk in individuals with type 2 diabetes mellitus (T2DM), the pathophysiologicmechanisms underlying this association are not known. We hypothesize that insulin resistance (the key pathology in T2DM)negatively inﬂuences bone remodeling and leads to reduced bone strength. Data for this study came from 717 participants in theBiomarker Project of the Midlife in the United States Study (MIDUS II). The homeostasis model assessment of insulin resistance(HOMA‐IR) was calculated from fasting morning blood glucose and insulin levels. Projected 2D (areal) bone mineral density (BMD) wasmeasured in the lumbar spine and left hip using dual‐energy X‐ray absorptiometry (DXA). Femoral neck axis length and width weremeasured from the hip DXA scans, and combined with BMD and body weight and height to create composite indices of femoral neckstrength relative to load in three different failure modes: compression, bending, and impact. We used multiple linear regressions toexamine the relationship between HOMA‐IR and bone strength, adjusted for age, gender, race/ethnicity, menopausal transition stage(in women), and study site. Greater HOMA‐IR was associated with lower values of all three composite indices of femoral neck strengthrelative to load, but was not associated with BMD in the femoral neck. Every doubling of HOMA‐IR was associated with a 0.34 to 0.40SD decrement in the strength indices (p < 0.001). On their own, higher levels of fasting insulin (but not of glucose) wereindependently associated with lower bone strength. Our study conﬁrms that greater insulin resistance is related to lower femoral neckstrength relative to load. Further, we note that hyperinsulinemia, rather than hyperglycemia, underlies this relationship. Althoughcross‐sectional associations do not prove causality, our ﬁndings do suggest that insulin resistance and in particular, hyperinsulinemia,may negatively affect bone strength relative to load. 2014 American Society for Bone and Mineral Research.
KEY WORDS: INSULIN RESISTANCE; BONE STRENGTH formation,(8,9,22,23) so that although BMD is increased in T2DMin response to increased skeletal loading, it is not increased Osteoporotic fractures represent a signiﬁcant morbidity and enough relative to the increased impact forces in a fall.
ﬁnancial cost burden to individuals and society.(1,2) The Consistent with this hypothesis, composite indices of femoral scope of this problem is expected to increase worldwide with neck strength relative to load are indeed lower in midlife women the graying of the population and is likely to be exacerbated by with diabetes than in nondiabetic women.(24) The composite the rapidly increasing prevalence of type 2 diabetes mellitus strength indices combine femoral neck areal BMD and size (T2DM) in both developed and developing economies.(3–5) obtained from dual‐energy X ray absorptiometry (DXA) hip scans Indeed, multiple studies have noted the increased fracture risk in with body size to gauge strength relative to load (impact forces) individuals with T2DM.(6–9) as may be borne during a fall.(25) They are inversely associated The pathophysiology underlying this increase in fracture risk in with incident hip fracture risk in community‐dwelling older white T2DM is not well understood. For instance, low bone mineral women(25) and in young U.S. white and Chinese men and density (BMD) is a major risk factor for fracture, yet BMD in women,(26) and unlike BMD, predict fragility fracture risk in diabetics is greater than that in nondiabetic individuals.(8,10–12) middle‐aged women without requiring knowledge of the But T2DM is also associated with greater body weight, which can increase fracture risk by several mechanisms, including increas- Ishii and colleagues(24) also noted a signiﬁcant inverse ing the forces on bone during a fall.(13–19) Greater body weight is association between insulin resistance (measured using the also expected to increase BMD by the impact of skeletal loading Homeostatic Model of Insulin Resistance [HOMA‐IR]) and on osteoblast differentiation and activity.(20,21) However, the composite indices for bone strength in a multiethnic sample pathophysiology of T2DM may negatively inﬂuence bone of premenopausal women. A few small studies have also found Received in original form March 29, 2013; revised form July 30, 2013; accepted August 13, 2013. Accepted manuscript online August 26, 2013.
Address correspondence to: Preethi Srikanthan, MD, MS, University of California, Los Angeles, David Geffen School of Medicine, BOX 951679, A2‐237 CHS, LosAngeles, CA 90095‐1679, USA. E‐mail: firstname.lastname@example.org Journal of Bone and Mineral Research, Vol. 29, No. 4, April 2014, pp 796–803DOI: 10.1002/jbmr.2083 2014 American Society for Bone and Mineral Research inverse associations between insulin resistance and markers of funding for DXA scanning at the UCLA and Georgetown sites was bone formation, such as osteocalcin,(28,29) osteoprotegerin,(30) obtained after the Biomarker Project had commenced), an and even BMD in some subpopulations.(31–33) additional 15 individuals for whom data for fasting insulin and We therefore hypothesized that insulin resistance plays a key glucose data was lacking or fasting insulin values were less role in the increased fracture risk observed in T2DM, and used than or equal to 68 mU/mL, 91 participants who were taking data from a national midlife sample to examine the association medications known to inﬂuence bone strength (oral cortico- between insulin resistance and bone strength. Thus we hope to steroids, alendronate, anastrazole, calcitonin, ibandronate, extend the results of Ishii and colleagues(24) to a population of leuprolide, letrozole, raloxifene, risedronate, tamoxifen, zole- men and women, and uniquely, we used DXA‐derived femoral dronic acid, testosterone, ﬁnasteride, or dutasteride), and 85 bone strength relative to load, in addition to BMD, as markers of women whose menopause transition stage could not be bone strength.
determined, resulting in an analytic sample of 717.
For those models in which insulin resistance, fasting insulin, or Subjects and Methods fasting glucose were primary predictors, 83 individuals who weretaking hypoglycemic medications (glimepiride, glipizide, Met- Data came from the second wave of the Midlife in the United formin, glyburide, Nateglinide, Pioglitazone, Pramlintide, Repa- States Study (MIDUS II), which included blood and urine assays glinide, Rosiglitazone, or Sitagliptin) or insulin analogues for biomarkers and bone scans for a subsample of the overall (Humalog, Novalog, Humulin N, Novolin N, Lantus, or Levemir) MIDUS II cohort. The MIDUS II study, initiated in 1995, was were excluded, leaving an analytic sample of size 634 for these designed to determine how social, psychological, and behavioral factors interrelate to inﬂuence mental and physical health. The ﬁrst wave (MIDUS I) collected sociodemographic and psychoso- Measurements: primary predictors cial data on 7108 English‐speaking, noninstitutionalized Ameri-can adults residing in the contiguous 48 states, ages 25 to Details of the sequence and methodology of biological specimen 74 years, whose household included at least one telephone collection in the MIDUS II Biomarker Project have been described (recruited by random digit dialing), with oversampling of in detail.(35) Biomarker Project participants also provided ﬁve metropolitan areas, twin pairs, and siblings.(34) To increase information on health conditions and medication usage.
the representation of African Americans from urban, low Medication information was veriﬁed by examination of medica- socioeconomic strata in the sample, 592 additional African tion bottles brought to the clinical research center.
American residents were recruited from Milwaukee, WI, USA, to Blood HbA1c measurements were obtained from fasting participate in MIDUS II.
blood draws in the morning. Blood glucose and insulin levels Of the 4963 participants who completed the MIDUS II survey, measured from fasting morning blood samples were used to 3191 participants were deemed medically safe to travel. Of them, calculate insulin resistance by the HOMA‐IR, which is approxi- 1255 agreed to participate in the MIDUS II biomarker project, mated using the formula below(37): which required a 2‐day commitment, including travel to one ofthree general clinical research centers (GCRC): the University of HOMA-IR ¼ fasting glucose ðin mg=dLÞ California at Los Angeles, Georgetown University, and the fasting insulin ðin mU=mLÞ 0:00247 University of Wisconsin–Madison. Reasons given for nonpartici-pation were travel, family, and work obligations. MIDUS II Participants were said to have diabetes if they met any of the Biomarker Project participants were similar to the MIDUS II following four criteria: (1) HbA1c 6.5%; (2) fasting glucose sample with respect to key characteristics (eg, subjective health, 126 mg/dL; (3) reported having diabetes (categorical answer to chronic conditions, physical activity, alcohol use),(35) and the the question "In past 12 months have you experienced or been complete MIDUS II sample was similar to the MIDUS I sample.(36) treated for any of the following conditions: diabetes or high Data were collected during a 24‐hour stay at a GCRC between blood sugar?"); or (4) were taking medication(s) for diabetes July 2004 and May 2009. The protocol included a medical history including insulin analogue agents or hypoglycemic medications and physical examination (including medication review), a mentioned earlier in the Subjects and Methods section.
fasting blood draw, and DXA scans of the lumbar spine and Participants were said to have prediabetes if they met all of left hip.(35) Height and weight were measured during the GCRC the following three criteria: (1) 5.7% HbA1c < 6.5% OR 100 mg/ visit. Blood samples were frozen and shipped to a central dL < fasting glucose < 126 mg/dL; (2) did NOT report having laboratory for assays. The glycosylated hemoglobin (HbA1c) and diabetes; AND (3) were NOT taking medication(s) for diabetes.
lipid assays were performed at Meriter Labs (GML) in Madison, Participants were deemed to not have either prediabetes or WI, USA using a Cobra Integra Analyzer (Roche Diagnostics, diabetes if they met all of the following criteria: (1) HbA1c Indianapolis, IN, USA). The glucose assays were performed at < 5.7%; (2) fasting glucose 100 mg/dL; (3) did NOT report ARUP Laboratories in Salt Lake City, UT, USA. Insulin assays were having diabetes; AND (4) were NOT taking medication(s) for performed on a Siemens Advia Centaur Analyzer also at ARUP Laboratories (Siemens Medical Solutions Diagnostics, Tarrytown,NY, USA). Informed consent was provided by each participant, Measurements: bone strength and each MIDUS center obtained institutional review boardapproval.(35) During the GCRC visit, 2D projected (areal) BMD was measured in The sample for this analysis included participants in the MIDUS the lumbar spine (L1–L4) and left hip using DXA. DXA scans were II Biomarker Project with valid data on bone strength, fasting performed using GE Healthcare Lunar Prodigy (Madison site) or insulin, and fasting glucose. Of the 1255 participants in the Hologic 4500 (UCLA and Georgetown sites) technology.
MIDUS II Biomarker Project, we excluded data from 347 Reading of all DXA scans was performed centrally by participants who did not have DXA scans (mainly because physicians at the University of Wisconsin DXA center. Three Journal of Bone and Mineral Research INSULIN RESISTANCE AND BONE STRENGTH times per week, and on all days on which scans were obtained, age‐matched the oldest group of men to the postmenopausal instruments were calibrated and phantom scan data were women, because only 0.3% of occurrences of spontaneous acquired. No densitometer shift or drift occurred during menopause take place at or after 59 years of age.(41) the course of this study. For BMD cross‐calibration across thethree clinical sites, a phantom was scanned 10 times on the Statistical analyses densitometers at each of the three study sites. The linear We used multiple linear regression to examine the associations of regression equation developed from these calibration scans was HOMA‐IR (which was log‐transformed to reduce skew in the used to correct BMD values from two of the three sites to make distribution, using base 2 log transformation to facilitate the data comparable across study sites. The recalibrated BMD interpretation), prediabetes, and diabetes with bone strength values at the lumbar spine and left hip were reported in units of measures, adjusted for age, gender, menopause transition stage, grams per square centimeters(g/cm2).(38) race (black versus non‐black), and study site. We treated log‐ Femoral neck axis length (FNAL), the distance along the transformed HOMA‐IR as a continuous predictor because the femoral neck axis from the lateral margin of the base of the relationship between log HOMA‐IR and bone strength indices greater trochanter to the apex of the femoral head, and femoral has been noted to be linear.(24) To allow for age‐related changes neck width (FNW), the smallest thickness of the femoral neck in bone strength being different in men and in women, we used along any line perpendicular to the femoral neck axis, were gender‐speciﬁc coding for age. We included the categorical age measured from the hip scans using software provided by the variable for men (<50 years, 50–59 years, 60 years) as well as scanner manufacturers. Composite indices of femoral neck two continuous variables—one that tracked age in men 60 years strength relative to load were created using the following and older, and another that tracked age in women who were late perimenopausal or postmenopausal and not taking menopausalhormone therapy.
Compression strength index ðCSIÞ Bone strength measures examined as dependent variables ¼ ðBMD FNWÞ=Weight were BMD in the lumbar spine; BMD in the femoral neck; and thethree composite indices of femoral neck strength relative to load: Bending strength index ðBSIÞ CSI, BSI, and ISI. Because increased body weight is associated with insulin resistance and because body weight also inﬂuences BMD FNW2Þ=ðFNAL WeightÞ bone deposition, the models were run with and withoutadjustment for body mass index (BMI). BMI was calculated as Impact strength index ðISIÞ weight (kilograms) divided by the square of height (meters), and ¼ ðBMD FNW FNALÞ=ðHeight WeightÞ was included in the models as a three different terms: continuous(linear) term, a squared term (BMI2), and a race interaction All three indices were recorded in units of grams per kilogram term (BMI race) to allow for potentially different effects of BMI per meter (g/kg‐m). Because BMD was measured in grams per square centimeter, FNW and FNAL in centimeters, weight in We tested for effect modiﬁcation by gender, by including kilograms, and height in meters, we scaled CSI and BSI by 100 to interactions between gender and the primary predictor(s).
obtain values in units of grams per kilogram per meter (g/kg‐m).
Further, as the relationship between HOMA‐IR and bone strength CSI reﬂects the ability of the femoral neck to withstand an axial may be different in prediabetics and diabetics compared compressive load, BSI reﬂects its ability to withstand bending to nondiabetics, we included interaction terms HOMAIR forces, and ISI reﬂects the ability of the femoral neck to absorb prediabetes and HOMAIR diabetes to test for effect modiﬁca- the potential energy in a fall from standing height.
tion by diabetes and prediabetes statuses. In supplementaryanalyses aimed at shedding light on the independentroles of insulinemia and glycemia, fasting serum insulin Measurements: covariates (base 2 log transformed) and fasting serum glucose (base 2log transformed) were included together in the models in place Information regarding age and gender was obtained from self‐ of HOMA‐IR.
reports. Gender/race/ethnicity was self‐identiﬁed as white, Black/ All models accounted for within‐family correlations using African American, other, or multiracial. From self‐reported STATA's cluster option. STATA SE version 10.1 (StataCorp LP, menstrual patterns and use (in the last year) of sex steroid College Station, TX, USA) was used for all analyses.
hormones (from self‐report and examination of medicationbottles brought to the clinical research center), we classiﬁed eachfemale participant's menopause transition stage as one of the following: premenopausal (no change in regularity of menses),early perimenopausal (had menses in last 3 months with change The study sample was similar to the complete MIDUS II Biomarker in regularity of menses), late perimenopausal (last menses 3– Project sample with respect to age, BMI, HOMA‐IR, prediabetes, 12 months previously with change in regularity of menses), and diabetes prevalence (Table 1). The most common reasons for postmenopausal (no menses in prior 12 months) not taking exclusion of Biomarker Project participants from the analysis menopausal hormone therapy, and postmenopausal taking sample were missing hip DXA scans (from the UCLA and menopausal hormone therapy.(39) Georgetown sites where DXA scans were added late to the Men were categorized by age into three categories: younger protocol due to funding limitations) and unclassiﬁable meno- than 50 years, 50 to 59 years, and 60 years or older. The choice of pause transition stage in women. Therefore, compared to the age categories in men was guided by previous observations that Biomarker sample, the study sample had a smaller proportion of substantial age‐related bone loss in men does not start until age women and a larger proportion of African Americans (because 50 years.(40) Further, the age categories chosen in men also the new urban African American participants from Milwaukee SRIKANTHAN ET AL.
Journal of Bone and Mineral Research Table 1. Descriptive Statistics for the Analytic Sample and the Complete MIDUS II Biomarker Project Sample MIDUS biomarker sample University of California, Los Angeles, Los Angeles, CA, USA University of Wisconsin–Madison, Madison, WI, USA Georgetown University, Washington, DC, USA Body mass index (kg/m2) Age in men (years) Women by menopause transition stage Early perimenopausal Late perimenopausal or postmenopausal, no hormones Postmenopausal taking hormones HOMA‐IR (log2 transformed) Fasting glucose (mg/dL, log2 transformed) Fasting insulin (mIU/mL, log2 transformed) Bone mineral density Femoral neck (g/cm2) Lumbar spine (g/cm2) Femoral neck composite strength indices Compression strength index (g/kg‐m) Bending strength index (g/kg‐m) Impact strength index (g/kg‐m) Values are mean (SD) or percentage.
MIDUS ¼ Study of Midlife in the United States; HOMA‐IR ¼ Homeostasis Model of Assessment–Insulin Resistance; HbA1c ¼ glycosylated hemoglobin; g/kg‐m ¼ grams per kilogram per meter.
aMost common reasons for exclusion of MIDUS II Biomarker Project participants from the study sample were missing bone scans (n ¼ 348), use of medications known to inﬂuence bone (n ¼ 94), and unclassiﬁable menopause transition stage (n ¼ 88).
p < 0.05 for t test or chi‐square test comparing analytic sample to excluded sample.
were seen at the University of Wisconsin–Madison site, which either prediabetes or overt diabetes, mean age 52.9 years, 45.3% collected DXA scans from the start of the Biomarker Project) were men, and 9.2% were African American.
In the complete sample, median and interquartile range of The average age of study participants was 56.8 years, 38% of HOMA‐IR was 2.47 (1.47–4.40), of fasting insulin was 10.0 (6.00– men were 60 years or older and 59% of women were either late 17.0) mIU/mL, of fasting glucose was 96 (90–105) mg/dL, and of perimenopausal or postmenopausal and not taking menopausal HbA1c was 5.86 (5.60–6.24) %.
hormone therapy. The mean age (SD) of men in the analytic Adjusted for age, gender, race/ethnicity, menopause transition sample was 56.53 (11.24) years and that of women was 57.12 stage, and study site, greater insulin resistance was associated (11.38) years.
with higher BMD in the femoral neck but with lower values of Further, 54.4% of participants had prediabetes and 19.7% of each of the three composite indices of femoral neck strength participants had diabetes. Both prediabetes and overt diabetes relative to load (Table 2). With additional adjustment for BMI, were more common in older individuals and in African American greater insulin resistance was associated with lower values of all participants: among diabetics, mean age was 59.5 years, 44.4% ﬁve bone strength measures, although the association with were men, and 34.7% were African American; among predia- lower BMD in the femoral neck was not signiﬁcant (Table 2).
betics, mean age was 57.7 years, 41.8% were men, and 15.5% Every doubling of HOMA‐IR was associated with a 0.09 to 0.14 SD were African American; and among those who did not have decrement in the other four bone strength measures (Table 2).
Journal of Bone and Mineral Research INSULIN RESISTANCE AND BONE STRENGTH Table 2. Adjusted Associations of HOMA‐IR With Bone Strength Bone strength measure Effect size per doubling of HOMA‐IRa 95% confidence interval Compression strength index Bending strength index Impact strength index After additional adjustment for BMI Compression strength index Bending strength index Impact strength index Values adjusted for age, sex, race/ethnicity, menopause transition stage in women, and study site.
HOMA‐IR ¼ Homeostasis Model of Assessment–Insulin Resistance; BMD ¼ bone mineral density; BMI ¼ body mass index.
aEffect size in multiples of the SD of the outcome (strength measure).
Adjusted for age, gender, race/ethnicity, menopause transition every doubling of HOMA‐IR was associated with a 0.15 SD stage, and study site, prevalent diabetes (but not prevalent decrement in lumbar spine BMD (p ¼ 0.01); 95% conﬁdence prediabetes) was associated with lower composite indices of interval (0.27 to 0.03).
femoral neck strength relative to load, but neither diabetes nor Finally, when fasting insulin and fasting glucose were entered prediabetes were signiﬁcantly associated with BMD in either the together into the models, higher insulin (but not glucose) was femoral neck or lumbar spine (Table 3). Following additional independently associated with lower bone strength. Adjusted for adjustment for BMI, neither prediabetes nor overt diabetes was age, gender, race/ethnicity, menopause transition stage, study signiﬁcantly associated with any of the ﬁve strength measures site, BMI, and fasting glucose, every doubling of fasting insulin was associated with a 0.10 to 0.18 SD decrement in each of the Gender did not modify the associations of HOMA‐IR, with bone ﬁve bone strength measures (Table 4).
strength (all p values in tests of gender by HOMAIR interactionwere greater than 0.24). Moreover, prediabetes and diabetes status did not modify the association of HOMA‐IR with four of the ﬁve bone strength measures (all but one of the 10 p values in As hypothesized, in this national sample, increased insulin tests of prediabetes/diabetes by HOMA IR interaction were resistance, prediabetes, and overt diabetes mellitus were all greater than 0.17). The one exception was a signiﬁcant cross‐sectionally associated with lower indices of femoral neck interaction between prediabetes and HOMA‐IR in the association strength relative to load. Adjustment for BMI also unmasked an with lumbar spine BMD (interaction p value 0.05). Therefore, we association between greater insulin resistance and lower BMD in re‐ran the HOMA‐IR and lumbar spine BMD model with the the lumbar spine. Our study conﬁrms and extends the ﬁndings of analytic sample restricted to prediabetics. Among prediabetics, an inverse association between bone strength indices and insulin the association was even stronger: adjusted for age, gender, resistance, noted by Ishii and colleagues(24) in premenopausal race/ethnicity, menopause transition stage, study site, and BMI, women to a national sample, in a population with a wider age Table 3. Adjusted Associations of Prediabetes and Overt Diabetes With Bone Strength Bone strength measure Prediabetes effect size (95% CI) Diabetes effect size (95% CI) þ0.114 (0.036, þ0.264) þ0.125 (0.088, þ0.338) þ0.126 (0.028, þ0.280) þ0.022 (0.193, þ0.238) Compression strength index 0.085 (0.232, þ0.061) 0.488 (0.689, 0.288) Bending strength index 0.094 (0.269, þ0.081) 0.453 (0.680, 0.227) Impact strength index 0.145 (0.307, þ0.017) 0.544 (0.765, 0.323) After additional adjustment for BMI þ0.030 (0.111, þ0.171) 0.074 (0.281, þ0.134) þ0.082 (0.073, þ0.237) 0.066 (0.284, þ0.151) Compression strength index þ0.072 (0.057, þ0.201) 0.080 (0.243, þ0.082) Bending strength index þ0.053 (0.107, þ0.213) 0.071 (0.266, þ0.124) Impact strength index þ0.023 (0.114, þ0.161) 0.104 (0.285, þ0.076) Values adjusted for age, sex, race/ethnicity, menopause transition stage in women, and study site. Effect size in multiples of the SD of the outcome (strength measure). Reference group ¼ no diabetes.
BMD ¼ bone mineral density; CI ¼ conﬁdence interval; BMI ¼ body mass index.
p < 0.001.
SRIKANTHAN ET AL.
Journal of Bone and Mineral Research Table 4. Independent Associations of Fasting Glucose and Fasting Insulin With Bone Strength After additional adjustment for BMI Effect size in units of outcome SD per doubling of the predictor (glucose or insulin), adjusted for the other primary predictor, age, sex, race/ethnicity, menopause transition stage in women, and study site; 95% conﬁdence intervals are shown within parentheses.
BMD ¼ bone mineral density; BMI ¼ body mass index.
p < 0.001.
range that includes both men and women. Our ﬁndings are also normally stimulated by skeletal loading. Other studies have consistent with those from smaller studies in adolescents,(42) found that although BMD may be higher in T2DM, bone strength young adults,(33) bone marrow transplant patients,(32) and relative to load is not any higher.(24,59) Taken together, these diabetics(31) that have found associations between greater studies suggest that increased insulin resistance and/or hyper- insulin resistance and lower BMD. These ﬁndings and ours insulinemia may interfere with the usual anabolic response in help explain, at least partly, the increased fracture risk observed bone to skeletal loading, so that bone strength relative to load is in T2DM.(6–9,43) These ﬁndings are in contradistinction to several previous Our study has some important limitations. Foremost, it is a studies that have documented higher BMD in T2DM(44–46) cross‐sectional study; thus causal inferences cannot be conclu- despite the increased risk of fractures in T2DM.(6,8,10,12,43,47,48) Our sively drawn. We cannot for instance, infer that insulin resistance study however, suggests that hyperinsulinemia itself may in fact, leads to low bone strength. An alternate explanation for our be associated with lower bone strength, because fasting insulin ﬁndings might be that increased bone mass leads to greater levels (and not fasting glucose levels) were associated negatively insulin sensitivity, because osteoblasts and osteocalcin appear to with both BMD and composite indices of strength relative to load have a role in pancreatic function and glucose metabolism.(33,60– in the femoral neck. A deleterious role for insulin on bone is also 62) Further longitudinal studies of the temporal relationships consistent with experiments in mouse models that suggest that between changes in insulin resistance and changes in bone osteoblasts are insulin target cells(49) and that insulin signaling in strength are needed. Next, the composite indices of femoral neck osteoblasts favors bone resorption. Mice deﬁcient in osteoblast‐ strength are based on macroscopic measurements from DXA speciﬁc insulin receptors have reduced expression of genes scans, and ignore changes in microarchitecture and quality of implicated in bone resorption (CathepsinK and Tcirg1), less mineralization, both of which are thought to be adversely acidiﬁcation of bone extracellular matrix, signiﬁcantly smaller affected by T2DM.(63,64) Finally, previous studies have validated resorption pits, and markedly lower serum levels of bone femoral neck strength indices measured from Hologic machine resorption marker, cross‐linked C‐telopeptide (CTX).(50) Further, it scans; this is the ﬁrst time Lunar machine–based measurements was recently noted that in Wistar rats with an obese, insulin‐ of the strength indices have been examined in a research study.
resistant condition induced by a 12‐week high‐fat diet, there was Despite these limitations, our study conﬁrms the negative signiﬁcant impairment of osteoblastic insulin signaling and association between insulin resistance and femoral neck osteoblast proliferation, with increased osteoblastic apoptosis strength that was ﬁrst noted in the Study of Women and the culminating in osteoporosis in the jaw bone, compared to Menopausal Transition (SWAN) cohort of women by Ishii and baseline, measured using micro–computed tomography (mCT) of colleagues.(24) It suggests that obesity and hyperinsulinemia may mandibular bone.(51) not be bone‐protective, and adds to the growing body of This study also adds to the accumulating evidence that it is not evidence which points to the importance of measuring bone enough to look at BMD in isolation when assessing bone's ability strength relative to load, in assessing and understanding fracture to resist fracture. The importance of bone size and body size to risk. Further research is needed to uncover the biological fracture risk has been established.(47,52–56) The composite indices mechanisms by which insulin resistance could deleteriously of femoral neck strength relative to load combine BMD with both affect bone health.
bone size and body load and improve fracture prediction abilityin both women(25,27) and men.(26) Previous studies have alsonoted the lower spine bone volume in T2DM subjects.(57) A recent study found that bone cross‐sectional area is also lower inT2DM,(58) suggesting a deﬁcit in periosteal apposition which is All authors state that they have no conﬂicts of interest.
Journal of Bone and Mineral Research INSULIN RESISTANCE AND BONE STRENGTH 14. Beck TJ, Petit MA, Wu G, LeBoff MS, Cauley JA, Chen Z. Does obesity really make the femur stronger? BMD, geometry, and fractureincidence in the women's health initiative‐observational study.
This research was supported by National Institutes of Health J Bone Miner Res. 2009;24(8):1369–79.
grant number 1R01AG033067. The MIDUS I study (Midlife in 15. Compston JE, Watts NB, Chapurlat R, et al. Obesity is not protective the U.S.) was supported by the John D. and Catherine T.
against fracture in postmenopausal women: GLOW. Am J Med.
MacArthur Foundation Research Network on Successful Midlife Development. The MIDUS II research was supported by a grant 16. Goulding A, Grant AM, Williams SM. Bone and body composition of from the National Institute on Aging (P01‐AG020166) to conduct children and adolescents with repeated forearm fractures. J Bone a longitudinal follow‐up of the MIDUS I investigation. The Miner Res. 2005;20(12):2090–6.
research was further supported by the following grants M01‐ 17. Nielson CM, Marshall LM, Adams AL, et al. BMI and fracture risk in older men: the osteoporotic fractures in men study (MrOS). J Bone RR023942 (Georgetown), M01‐RR000865 (UCLA) from the Miner Res. 2011;26(3):496–502.
General Clinical Research Centers Program and 1UL1RR025011 18. Premaor MO, Pilbrow L, Tonkin C, Parker RA, Compston J. Obesity (UW) from the Clinical and Translational Science Award (CTSA) and fractures in postmenopausal women. J Bone Miner Res.
program of the National Center for Research Resources, National Institutes of Health. The funding sources had no role in study 19. von Muhlen D, Saﬁi S, Jassal SK, Svartberg J, Barrett‐Connor E.
design, data collection and analysis, decision to publish, or Associations between the metabolic syndrome and bone health in preparation of the manuscript.
older men and women: the Rancho Bernardo Study. Osteoporos Int.
Authors' roles: Data analysis: DMM. Data interpretation: PS, ASK, and CJC. Drafting manuscript: PS. Revising manuscript 20. Bonewald LF, Johnson ML. Osteocytes, mechanosensing and Wnt signaling. Bone. 2008;42(4):606–15.
content: PS, ASK, CJC, TES, GAG, NB, and DMM. Approving ﬁnalversion of manuscript: PS, ASK, CJC, TES, GAG, NB, and DMM.
21. Ehrlich PJ, Lanyon LE. Mechanical strain and bone cell function: a review. Osteoporos Int. 2002;13(9):688–700.
DMM, PS, and ASK take responsibility for the integrity of the data 22. de Paula FJ, Horowitz MC, Rosen CJ. Novel insights into the relationship between diabetes and osteoporosis. Diabetes Metab ResRev. 2010;26(8):622–30.
23. Yaturu S. Diabetes and skeletal health. J Diabetes. 2009;1(4):246–54.
24. Ishii S, Cauley JA, Crandall CJ, et al. Diabetes and femoral neck 1. Becker DJ, Kilgore ML, Morrisey MA. The societal burden of strength: ﬁndings from the Hip Strength Across the Menopausal osteoporosis. Curr Rheumatol Rep. 2010;12(3):186–91.
Transition Study. J Clin Endocrinol Metab. 2012;97(1):190–7.
2. Brauer CA, Coca‐Perraillon M, Cutler DM, Rosen AB. Incidence 25. Karlamangla AS, Barrett‐Connor E, Young J, Greendale GA. Hip and mortality of hip fractures in the United States. JAMA. 2009; fracture risk assessment using composite indices of femoral neck strength: the Rancho Bernardo study. Osteoporos Int. 2004;15(1):62–70.
3. Barcelo A, Gregg EW, Gerzoff RB, et al. Prevalence of diabetes and intermediate hyperglycemia among adults from the ﬁrst multina- 26. Yu N, Liu YJ, Pei Y, et al. Evaluation of compressive strength index of tional study of noncommunicable diseases in six Central American the femoral neck in Caucasians and Chinese. Calcif Tissue Int. 2010; countries: the Central America Diabetes Initiative (CAMDI). Diabetes 27. Ishii S, Greendale GA, Cauley JA, et al. Fracture risk assessment 4. Tan DA. Changing disease trends in the Asia‐Paciﬁc. Climacteric.
without race/ethnicity information. J Clin Endocrinol Metab. 2012; 5. van Dieren S, Beulens JW, van der Schouw YT, Grobbee DE, Neal B.
28. Hwang YC, Jeong IK, Ahn KJ, Chung HY. The uncarboxylated form of The global burden of diabetes and its complications: an emerging osteocalcin is associated with improved glucose tolerance and pandemic. Eur J Cardiovasc Prev Rehabil. 2010;17Suppl 1:S3–8.
enhanced beta‐cell function in middle‐aged male subjects. DiabetesMetab Res Rev. 2009;25(8):768–72.
6. Bonds DE, Larson JC, Schwartz AV, et al. Risk of fracture in women with type 2 diabetes: the Women's Health Initiative Observational 29. Weiler HA, Lowe J, Krahn J, Leslie WD. Osteocalcin and vitamin D Study. J Clin Endocrinol Metab. 2006;91(9):3404–10.
status are inversely associated with homeostatic model assessmentof insulin resistance in Canadian Aboriginal and white women: the 7. Strotmeyer ES, Cauley JA. Diabetes mellitus, bone mineral density, First Nations Bone Health Study. J Nutr Biochem. 2013 Feb;24(2): and fracture risk. Curr Opin Endocrinol Diabetes Obes. 2007;14(6): 30. Oh KW, Rhee EJ, Lee WY, et al. The relationship between circulating 8. Strotmeyer ES, Cauley JA, Schwartz AV, et al. Nontraumatic fracture osteoprotegerin levels and bone mineral metabolism in healthy risk with diabetes mellitus and impaired fasting glucose in older women. Clin Endocrinol (Oxf). 2004;61(2):244–9.
white and black adults: the health, aging, and body compositionstudy. Arch Intern Med. 2005;165(14):1612–7.
31. Arikan S, Tuzcu A, Bahceci M, Ozmen S, Gokalp D. Insulin resistance in type 2 diabetes mellitus may be related to bone mineral density.
9. Vestergaard P. Discrepancies in bone mineral density and fracture J Clin Densitom. 2012;15(2):186–90.
risk in patients with type 1 and type 2 diabetes—a meta‐analysis.
Osteoporos Int. 2007;18(4):427–44.
32. Faulhaber GA, Premaor MO, Moser Filho HL, Silla LM, Furlanetto TW.
Low bone mineral density is associated with insulin resistance in 10. de Liefde II, van der Klift M, de Laet CE, van Daele PL, Hofman A, Pols bone marrow transplant subjects. Bone Marrow Transplant. 2009; HA. Bone mineral density and fracture risk in type‐2 diabetes mellitus: the Rotterdam Study. Osteoporos Int. 2005;16(12):1713–20.
33. Lucey AJ, Paschos GK, Thorsdottir I, Martinez JA, Cashman KD, Kiely M.
11. Khalil N, Sutton‐Tyrrell K, Strotmeyer ES, et al. Menopausal bone Young overweight and obese women with lower circulating changes and incident fractures in diabetic women: a cohort study.
osteocalcin concentrations exhibit higher insulin resistance and Osteoporos Int. 2011;22(5):1367–76.
concentrations of C‐reactive protein. Nutr Res. 2013;33(1):67–75.
12. Schwartz AV, Vittinghoff E, Bauer DC, et al. Association of BMD and 34. Brim OG, Ryff CD, Kessler RC. The MIDUS national survey: an overview.
FRAX score with risk of fracture in older adults with type 2 diabetes.
In: Brim OG, Ryff CD, Kessler RC, editors. How healthy are we? A national study of well‐being at midlife. Chicago, IL: The University of 13. Robinovitch SN, Hayes WC, McMahon TA. Prediction of femoral Chicago Press; 2004. p.1–36. Available from: impact forces in falls on the hip. J Biomech Eng. 1991;113(4):366–74.
SRIKANTHAN ET AL.
Journal of Bone and Mineral Research 35. Dienberg Love G, Seeman TE, Weinstein M, Ryff CD. Bioindicators 50. Ferron M, Wei J, Yoshizawa T, et al. Insulin signaling in osteoblasts in the MIDUS national study: protocol, measures, sample, and integrates bone remodeling and energy metabolism. Cell. 2010; comparative context. J Aging Health. 2010;22(8):1059–80.
36. Radler BT, Ryff CD. Who participates? Accounting for longitudinal 51. Pramojanee SN, Phimphilai M, Kumphune S, Chattipakorn N, retention in the MIDUS national study of health and well‐being.
Chattipakorn SC. Decreased jaw bone density and osteoblastic J Aging Health. 2010;22(3):307–31.
insulin signaling in a model of obesity. J Dent Res. 2013;92(6):560–5.
37. Wallace TM, Levy JC, Matthews DR. Use and abuse of HOMA 52. Alonso CG, Curiel MD, Carranza FH, Cano RP, Perez AD. Femoral bone modeling. Diabetes Care. 2004;27(6):1487–95.
mineral density, neck‐shaft angle and mean femoral neck width as 38. Crandall CJ, Merkin SS, Seeman TE, Greendale GA, Binkley N, predictors of hip fracture in men and women. Multicenter Project for Karlamangla AS. Socioeconomic status over the life‐course and adult Research in Osteoporosis. Osteoporos Int. 2000;11(8):714–20.
bone mineral density: the Midlife in the U.S. Study. Bone. 2012; 53. Faulkner KG, Wacker WK, Barden HS, et al. Femur strength index predicts hip fracture independent of bone density and hip axis 39. Finkelstein JS, Brockwell SE, Mehta V, et al. Bone mineral density length. Osteoporos Int. 2006;17(4):593–9.
changes during the menopause transition in a multiethnic cohort of 54. Orwoll ES, Marshall LM, Nielson CM, et al. Finite element analysis of women. J Clin Endocrinol Metab. 2008;93(3):861–8.
the proximal femur and hip fracture risk in older men. J Bone Miner 40. Riggs BL, Wahner HW, Dunn WL, Mazess RB, Offord KP, Melton LJ 3rd.
Differential changes in bone mineral density of the appendicular and 55. Leslie WD, Pahlavan PS, Tsang JF, Lix LM. Prediction of hip and other axial skeleton with aging: relationship to spinal osteoporosis. J Clin osteoporotic fractures from hip geometry in a large clinical cohort.
Osteoporos Int. 2009;20(10):1767–74.
41. Treloar AE. Menstrual cyclicity and the pre‐menopause. Maturitas.
56. Allolio B. Risk factors for hip fracture not related to bone mass and their therapeutic implications. Osteoporos Int. 1999;9Suppl 2: 42. do Prado WL, de Piano A, Lazaretti‐Castro M, et al. Relationship between bone mineral density, leptin and insulin concentration in 57. Strotmeyer ES, Cauley JA, Schwartz AV, et al. Diabetes is associated Brazilian obese adolescents. J Bone Miner Metab. 2009;27(5):613–9.
independently of body composition with BMD and bone volume in 43. Dobnig H, Piswanger‐Solkner JC, Roth M, et al. Type 2 diabetes older white and black men and women: The Health, Aging, and Body mellitus in nursing home patients: effects on bone turnover, bone Composition Study. J Bone Miner Res. 2004;19(7):1084–91.
mass, and fracture risk. J Clin Endocrinol Metab. 2006;91(9):3355–63.
58. Petit MA, Paudel ML, Taylor BC, et al. Bone mass and strength in older 44. Haffner SM, Bauer RL. The association of obesity and glucose and men with type 2 diabetes: the Osteoporotic Fractures in Men Study.
insulin concentrations with bone density in premenopausal and J Bone Miner Res. 2010;25(2):285–91.
postmenopausal women. Metabolism. 1993;42(6):735–8.
59. Melton LJ III, Riggs BL, Leibson CL, et al. A bone structural basis for 45. Smythe HA. Osteoarthritis, insulin and bone density. J Rheumatol.
fracture risk in diabetes. J Clin Endocrinol Metab. 2008;93:4804–9.
1987;14 Spec No: 91–3.
60. Amelio PD, Panico A, Spertino E, Isaia GC. Energy metabolism and the 46. Meema HE, Meema S. The relationship of diabetes mellitus and body skeleton: reciprocal interplay. World J Orthop. 2012;3(11):190–8.
weight to osteoporosis in elderly females. Can Med Assoc J. 1967; 61. Schwetz V, Pieber T, Obermayer‐Pietsch B. The endocrine role of the skeleton: background and clinical evidence. Eur J Endocrinol.
47. Rivadeneira F, Zillikens MC, De Laet CE, et al. Femoral neck BMD is a strong predictor of hip fracture susceptibility in elderly men and 62. Lee NK, Sowa H, Hinoi E, et al. Endocrine regulation of energy women because it detects cortical bone instability: the Rotterdam metabolism by the skeleton. Cell. 2007;130(3):456–69.
Study. J Bone Miner Res. 2007;22(11):1781–90.
63. Burghardt AJ, Issever AS, Schwartz AV, et al. High‐resolution 48. Khazai NB, Beck GR Jr, Umpierrez GE. Diabetes and fractures: an peripheral quantitative computed tomographic imaging of cortical overshadowed association. Curr Opin Endocrinol Diabetes Obes.
and trabecular bone microarchitecture in patients with type 2 diabetes mellitus. J Clin Endocrinol Metab. 2010;95(11):5045–55.
49. Fulzele K, Riddle RC, DiGirolamo DJ, et al. Insulin receptor signaling in 64. Saito M, Marumo K. Collagen cross‐links as a determinant of bone osteoblasts regulates postnatal bone acquisition and body composi- quality: a possible explanation for bone fragility in aging, osteo- tion. Cell. 2010;142(2):309–19.
porosis, and diabetes mellitus. Osteoporos Int. 2010;21(2):195–214.
Journal of Bone and Mineral Research INSULIN RESISTANCE AND BONE STRENGTH
Am J Physiol Heart Circ Physiol279: H2994–H3002, 2000. Effects of exercise training on cardiac function,gene expression, and apoptosis in rats HONGKUI JIN,1 RENHUI YANG,1 WEI LI,1 HSIENWIE LU,1 ANNE M. RYAN,2ANNIE K. OGASAWARA,1 JOHN VAN PEBORGH,1 AND NICHOLAS F. PAONI11Department of Cardiovascular Research and 2Department of Pathology,Genentech Incorporated, South San Francisco, California 94080