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Sex hormones are negatively associated with vertebral bone marrow fat.

ABSTRACT: CONTEXT:Higher bone marrow fat (BMF)1 is associated with osteoporosis and reduced hematopoiesis. Exogenous estradiol reduces BMF in older women, but effects of endogenous sex hormones are unknown. OBJECTIVE:To determine if endogenous sex hormones are associated with BMF in older men and women. DESIGN, SETTING AND PARTICIPANTS:Cross-sectional study in the Age Gene/Environment Susceptibility (AGES) Reykjavik cohort. Participants using medications that may affect BMF were excluded. MAIN OUTCOME MEASURES:Vertebral BMF was measured with magnetic resonance spectroscopy. Estradiol, testosterone and sex hormone binding globulin were measured on archived serum. Linear regression models were adjusted for age, total percent body fat and visit window. RESULTS:Analyses included 244 men and 226 women, mean age 81.5 (SD 4.1) years. Mean BMF was 54.1% (SD 8.6) (men) and 54.7% (SD 8.1) (women). In adjusted models, per 1pg/ml increase in total estradiol, there was a statistically significant 0.26% decrease in BMF in men (95% CI: -0.41, -0.11) and a non-significant 0.20% decrease in women (95% CI: -0.55, 0.15), with no evidence of interaction by gender (p=0.88). Per 10ng/dl increase in total testosterone, there was a significant 0.10% decrease in BMF in men (95% CI: -0.17, -0.03) and a non-significant 0.13% (95% CI: -0.79, 0.53) decrease in women, with no evidence of interaction by gender (p=0.97). CONCLUSION:Higher bone marrow fat is associated with lower total estradiol and testosterone levels in older men, with a similar but statistically non-significant association in older women. Sex hormone levels appear to play a role in the regulation of bone marrow fat in older adults.

SUBMITTER: Mistry SD

PROVIDER: S-EPMC5803453 | biostudies-literature | 2018 Mar

REPOSITORIES: biostudies-literature

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Sex hormones are negatively associated with vertebral bone marrow fat.

Mistry Swaroop D SD Woods Gina N GN Sigurdsson Sigurdur S Ewing Susan K SK Hue Trisha F TF Eiriksdottir Gudny G Xu Kaipin K Hilton Joan F JF Kado Deborah M DM Gudnason Vilmundur V Harris Tamara B TB Rosen Clifford J CJ Lang Thomas F TF Li Xiaojuan X Schwartz Ann V AV

Bone 20171211

<h4>Context</h4>Higher bone marrow fat (BMF)<sup>1</sup> is associated with osteoporosis and reduced hematopoiesis. Exogenous estradiol reduces BMF in older women, but effects of endogenous sex hormones are unknown.<h4>Objective</h4>To determine if endogenous sex hormones are associated with BMF in older men and women.<h4>Design, setting and participants</h4>Cross-sectional study in the Age Gene/Environment Susceptibility (AGES) Reykjavik cohort. Participants using medications that may affect BM ...[more]

PMID: 29241825

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Project description:Background: Bone marrow fat (BMF) fraction quantification in vertebral bodies is used as a novel imaging biomarker to assess and characterize chronic lower back pain. However, manual segmentation of vertebral bodies is time consuming and laborious. Purpose: (1) Develop a deep learning pipeline for segmentation of vertebral bodies using quantitative water-fat MRI. (2) Compare BMF measurements between manual and automatic segmentation methods to assess performance. Materials and Methods: In this retrospective study, MR images using a 3D spoiled gradient-recalled echo (SPGR) sequence with Iterative Decomposition of water and fat with Echo Asymmetry and Least-squares estimation (IDEAL) reconstruction algorithm were obtained in 57 subjects (28 women, 29 men, mean age, 47.2 ± 12.6 years). An artificial network was trained for 100 epochs on a total of 165 lumbar vertebrae manually segmented from 31 subjects. Performance was assessed by analyzing the receiver operating characteristic curve, precision-recall, F1 scores, specificity, sensitivity, and similarity metrics. Bland-Altman analysis was used to assess performance of BMF fraction quantification using the predicted segmentations. Results: The deep learning segmentation method achieved an AUC of 0.92 (CI 95%: 0.9186, 0.9195) on a testing dataset (n = 24 subjects) on classification of pixels as vertebrae. A sensitivity of 0.99 and specificity of 0.80 were achieved for a testing dataset, and a mean Dice similarity coefficient of 0.849 ± 0.091. Comparing manual and automatic segmentations on fat fraction maps of lumbar vertebrae (n = 124 vertebral bodies) using Bland-Altman analysis resulted in a bias of only -0.605% (CI 95% = -0.847 to -0.363%) and agreement limits of -3.275% and +2.065%. Automatic segmentation was also feasible in 16 ± 1 s. Conclusion: Our results have demonstrated the feasibility of automated segmentation of vertebral bodies using deep learning models on water-fat MR (Dixon) images to define vertebral regions of interest with high specificity. These regions of interest can then be used to quantify BMF with comparable results as manual segmentation, providing a framework for completely automated investigation of vertebral changes in CLBP.

Project description:Bone marrow fat is a unique fat depot that may regulate bone metabolism. Marrow fat is increased in states of low bone mass, severe underweight, and diabetes. However, longitudinal effects of weight loss and improved glucose homeostasis on marrow fat are unclear, as is the relationship between marrow fat and bone mineral density (BMD) changes. We hypothesized that after Roux-en-Y gastric bypass (RYGB) surgery, marrow fat changes are associated with BMD loss. We enrolled 30 obese women, stratified by diabetes status. Before and 6 months after RYGB, we measured BMD by dual-energy X-ray absorptiometry (DXA) and quantitative computed tomography (QCT) and vertebral marrow fat content by magnetic resonance spectroscopy. At baseline, those with higher marrow fat had lower BMD. Postoperatively, total body fat declined dramatically in all participants. Effects of RYGB on marrow fat differed by diabetes status (p?=?0.03). Nondiabetic women showed no significant mean change in marrow fat (+1.8%, 95% confidence interval [CI] -1.8% to +5.4%, p?=?0.29), although those who lost more total body fat were more likely to have marrow fat increases (r?=?-0.70, p?=?0.01). In contrast, diabetic women demonstrated a mean marrow fat change of -6.5% (95% CI -13.1% to 0%, p?=?0.05). Overall, those with greater improvements in hemoglobin A1c had decreases in marrow fat (r?=?0.50, p?=?0.01). Increases in IGF-1, a potential mediator of the marrow fat-bone relationship, were associated with marrow fat declines (r?=?-0.40, p?=?0.05). Spinal volumetric BMD decreased by 6.4%?±?5.9% (p?<?0.01), and femoral neck areal BMD decreased by 4.3%?±?4.1% (p?<?0.01). Marrow fat and BMD changes were negatively associated, such that those with marrow fat increases had more BMD loss at both spine (r?=?-0.58, p?<?0.01) and femoral neck (r?=?-0.49, p?=?0.01), independent of age and menopause. Our findings suggest that glucose metabolism and weight loss may influence marrow fat behavior, and marrow fat may be a determinant of bone metabolism. © 2017 American Society for Bone and Mineral Research.

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Sex hormones are negatively associated with vertebral bone marrow fat.

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Sex hormones are negatively associated with vertebral bone marrow fat.

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