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Prevalence of osteoporosis is more than 50% in older adults, yet current clinical methods for diagnosis that rely on areal bone mineral density (aBMD) fail to detect most individuals who have a fragility fracture. Bone fragility can manifest in different forms, and a “one-size-fits-all” approach to diagnosis and management of osteoporosis may not be suitable. High-resolution peripheral quantitative computed tomography (HR-pQCT) provides additive information by capturing information about volumetric density and microarchitecture, but interpretation is challenging because of the complex interactions between the numerous properties measured. In this study, we propose that there are common combinations of bone properties, referred to as phenotypes, that are predisposed to different levels of fracture risk. Using HR-pQCT data from a multinational cohort (n = 5873, 71% female) between 40 and 96 years of age, we employed fuzzy c-means clustering, an unsupervised machine-learning method, to identify phenotypes of bone microarchitecture. Three clusters were identified, and using partial correlation analysis of HR-pQCT parameters, we characterized the clusters as low density, low volume, and healthy bone phenotypes. Most males were associated with the healthy bone phenotype, whereas females were more often associated with the low volume or low density bone phenotypes. Each phenotype had a significantly different cumulative hazard of major osteoporotic fracture (MOF) and of any incident osteoporotic fracture (p < 0.05). After adjustment for covariates (cohort, sex, and age), the low density followed by the low volume phenotype had the highest association with MOF (hazard ratio = 2.96 and 2.35, respectively), and significant associations were maintained when additionally adjusted for femoral neck aBMD (hazard ratio = 1.69 and 1.90, respectively). Further, within each phenotype, different imaging biomarkers of fracture were identified. These findings suggest that osteoporotic fracture risk is associated with bone phenotypes that capture key features of bone deterioration that are not distinguishable by aBMD. © 2021 American Society for Bone and Mineral Research (ASBMR).  相似文献   
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The serrated pathway (SP) can be viewed as two parallel, but partially overlapping, arrays of colorectal precursor lesions, and their respective endpoint carcinomas, that are distinct from those of the conventional adenoma–carcinoma sequence (APC‐pathway). In this review we focus at the outset on the clinical impact, pathological features, molecular genetics and biological behaviours of the various SP cancers. Then we summarize the clinicopathological features, classification and molecular profiles of the two main precursor lesions that anchor the respective pathways: (i) sessile serrated adenoma/polyp (SSA/P), also called sessile serrated lesion (SSL), and (ii) traditional serrated adenoma (TSA). Activating mutations of the RAS–RAF–MAPK pathway initiate and sustain the lesions of the SP, and CpG island methylation of the promoter regions of tumour suppressor and DNA repair genes play the major role in their neoplastic progression. The SP includes microsatellite stable (MSS) carcinomas that are among the most biologically aggressive colorectal carcinomas (CRC), and also accounts for the great preponderance of sporadic hypermutated, mismatch repair (MMR)‐deficient or microsatellite instable (MSI) CRC. The identification, removal and appropriate classification of at‐risk SP precursors and surveillance of individuals who harbour these lesions present a challenge and opportunity for CRC prevention and mortality reduction.  相似文献   
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