Bone Microarchitecture Phenotypes Identified in Older Adults Are Associated With Different Levels of Osteoporotic Fracture Risk

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).     

Greater Visceral Fat but No Difference in Measures of Total Body Fat in Ambulatory Children With Spastic Cerebral Palsy Compared to Typically Developing Children

Background: Individuals with cerebral palsy (CP) are at increased risk for obesity and obesity-related complications. Studies of total body fat in those with CP are inconsistent and studies of abdominal fat are lacking in children with CP. The objective of this study was to determine if ambulatory children with spastic CP have greater central adiposity compared to typically developing children. Methodology: Eighteen ambulatory children with spastic CP (n = 5 girls; 8.6 ± 2.9 yr) and 18 age-, sex-, and race-matched typically developing children (controls; 8.9 ± 2.1 yr) participated in this cross-sectional study. Children with CP were classified as I or II using the Gross Motor Function Classification System. Dual-energy X-ray absorptiometry assessed body composition, including total body, trunk and abdominal fat mass, fat-free mass, fat mass index (FMI), and fat-free mass index (FFMI). Results: There were no group differences in fat mass, fat-free mass, FMI, and FFMI in the total body, fat mass, fat-free mass, and FFMI in the trunk, or fat mass, visceral fat mass, and subcutaneous fat mass in the abdomen (p > 0.05). Compared to controls, children with CP had higher trunk FMI, abdominal FMI, and visceral FMI (p < 0.05). Although marginally insignificant (p = 0.088), children with CP had higher subcutaneous FMI. Conclusions: Ambulatory children with spastic CP have elevated central adiposity, especially in the visceral region, despite no differences in measures of total body fat. How this relates to cardiometabolic disease progression in those with CP requires further investigation.     

Effect of gamma aminobutyric acid (GABA) or GABA with glutamic acid decarboxylase (GAD) on the progression of type 1 diabetes mellitus in children: Trial design and methodology

BackgroundEvidence suggests that GABA may reduce pancreatic inflammation, protect β-cells from autoimmune destruction, and potentiate the regeneration of new β-cells in the setting of type 1 diabetes mellitus (T1DM). The enzyme GAD, also expressed in human pancreatic β-cells, is an antigenic target of reactive T cells. We hypothesized that treatment of children with recent onset T1DM with GABA or combination GABA with GAD will preserve β-cell function and ameliorate autoimmune dysregulation.MethodsThis is a one-year, prospective, randomized, double-blind, placebo-controlled trial. Ninety-nine patients aged 4–18 years with newly diagnosed T1DM are randomized into three treatment groups: 1) oral GABA twice daily in addition to two injections of recombinant GAD enzyme, 2) oral GABA plus placebo GAD injections, or 3) placebo GABA and placebo GAD. Patients are evaluated at baseline and months 1, 5, 8 and 12. Mixed meal tolerance testing is performed at all but the 8-month visit. Laboratory studies will assess indices of beta and alpha cell function, glycemic control, immunophenotyping, and diabetes-related autoantibodies.ResultsThe primary outcome is the effect on pancreatic β-cell function as measured by meal-stimulated c-peptide secretion compared between the treatment groups before and after one year of treatment. Secondary outcomes include: 1) fasting and meal stimulated glucagon and proinsulin levels, 2) response in insulin usage by participants, 3) indices of immune cell function, and 4) effect on autoantibodies GAD65, ICA512, and ZnT8.Conclusions: This trial will determine the safety and efficacy of GABA and combination GABA/GAD therapy to delay T1DM progression in children.     

Cardiovascular risk assessment tools: A scoping review

ObjectivesThe objective of this review was to describe cardiovascular risk (CVR) assessment methods and to identify evidence-based practice recommendations when dealing with population at risk of developing cardiovascular diseases.Review methods and data sourcesA literature review following the Arksey and O'Malley scoping review methodology was conducted. By using appropriate key terms, literature searches were conducted in PubMed, SciELO, Cochrane Library, Dialnet, ENFISPO, Medigraphic, ScienceDirect, Cuiden, and Lilacs databases. A complementary search on websites related to the area of interest was conducted. Articles published in English or Spanish in peer-review journals between 2010 and 2017. Critical appraisal for methodological quality was conducted. Data was extracted using ad-hoc tables and qualitatively synthesized.ResultsAfter eliminating duplicates, 55 325 records remained, and 1432 records were selected for screening. Out of these, 88 full-text articles were selected for eligibility criteria, and finally, 67 studies were selected for this review, and 25 studies were selected for evidence synthesis. In total, 23 CVR assessment tools have been identified, pioneered by the Framingham study. Qualitative findings were grouped into four thematic areas: assessment tools and scores, CVR indicators, comparative models, and evidence-based recommendations.ConclusionsIt is necessary to adapt the instruments to the epidemiological reality of the population. The most appropriate way to estimate CVR is to choose the assessment tool that best suits individual conditions, accompanied by a comprehensive assessment of the patient. More research is required to determine a single, adequate, and reliable tool.