Maternal Body Mass Index and Daughters’ Age at Menarche

The role of inter-generational influences on age at menarche has not been explored far beyond the association between mothers’ and daughters’ menarcheal ages. Small size at birth and childhood obesity have been associated with younger age at menarche, but the influence of maternal overweight or obesity on daughters’ age at menarche has not been thoroughly examined

Bone Health in a Nonjaundiced Population of Children with Biliary Atresia

Objectives. To assess bone health in a cohort of nonjaundiced children with biliary atresia (BA) and the effect of growth and development on bone outcomes. Methods. Children ages one to eighteen years receiving care from Children's Hospital of Philadelphia were recruited. Each child was seen once and assessed for growth, pubertal development, concurrent medications, bilirubin, ALT, albumin, vitamin D status, bone mineral density (BMD), and bone mineral content (BMC) of the lumbar spine and whole body. Results. BMD declined significantly with age, and upon further analysis with a well-phenotyped control cohort, it was found that BMC was significantly decreased for both lumbar spine and whole body, even after adjustment for confounding variables. An age interaction was identified, with older subjects having a significantly greater impairment in BMC. Conclusions. These preliminary results demonstrate that children with BA, including those without jaundice, are likely to have compromised bone health even when accounting for height and puberty, which are common confounding factors in chronic disease. Further investigation is needed to identify the determinants of poor bone mineral status and to develop strategies to prevent osteoporosis later in life

Bone metabolism and incretin hormones following glucose ingestion in young adults with pancreatic insufficient cystic fibrosis

BACKGROUND: Gut-derived incretin hormones, including glucose-dependent insulinotropic peptide (GIP) and glucagon-like peptide 1 (GLP-1), regulate post-prandial glucose metabolism by promoting insulin production. GIP, GLP-1, and insulin contribute to the acute bone anti-resorptive effect of macronutrient ingestion by modifying bone turnover. Cystic fibrosis (CF) is associated with exocrine pancreatic insufficiency (PI), which perturbs the incretin response. Cross-talk between the gut and bone ( gut-bone axis ) has not yet been studied in PI-CF. The objectives of this study were to assess changes in biomarkers of bone metabolism during oral glucose tolerance testing (OGTT) and to test associations between incretins and biomarkers of bone metabolism in individuals with PI-CF. METHODS: We performed a secondary analysis of previously acquired blood specimens from multi-sample OGTT from individuals with PI-CF ages 14-30 years (n = 23). Changes in insulin, incretins, and biomarkers of bone resorption (C-terminal telopeptide of type 1 collagen [CTX]) and formation (procollagen type I RESULTS: CTX decreased by 32% by min 120 of OGTT (P \u3c 0.001), but P1NP was unchanged. Increases in GIP from 0 to 30 mins (rho = -0.48, P = 0.03) and decreases in GIP from 30 to 120 mins (rho = 0.62, P = 0.002) correlated with decreases in CTX from mins 0-120. Changes in GLP-1 and insulin were not correlated with changes in CTX, and changes in incretins and insulin were not correlated with changes in P1NP. CONCLUSIONS: Intact GIP response was correlated with the bone anti-resorptive effect of glucose ingestion, represented by a decrease in CTX. Since incretin hormones might contribute to development of diabetes and bone disease in CF, the gut-bone axis warrants further attention in CF during the years surrounding peak bone mass attainment

Infant BMI or Weight-for-Length and Obesity Risk in Early Childhood

Weight-for-length (WFL) is currently used to assess adiposity under 2 years. We assessed WFL- versus BMI-based estimates of adiposity in healthy infants in determining risk for early obesity

Using linear and natural cubic splines, SITAR, and latent trajectory models to characterise nonlinear longitudinal growth trajectories in cohort studies

BACKGROUND: Longitudinal data analysis can improve our understanding of the influences on health trajectories across the life-course. There are a variety of statistical models which can be used, and their fitting and interpretation can be complex, particularly where there is a nonlinear trajectory. Our aim was to provide an accessible guide along with applied examples to using four sophisticated modelling procedures for describing nonlinear growth trajectories. METHODS: This expository paper provides an illustrative guide to summarising nonlinear growth trajectories for repeatedly measured continuous outcomes using (i) linear spline and (ii) natural cubic spline linear mixed-effects (LME) models, (iii) Super Imposition by Translation and Rotation (SITAR) nonlinear mixed effects models, and (iv) latent trajectory models. The underlying model for each approach, their similarities and differences, and their advantages and disadvantages are described. Their application and correct interpretation of their results is illustrated by analysing repeated bone mass measures to characterise bone growth patterns and their sex differences in three cohort studies from the UK, USA, and Canada comprising 8500 individuals and 37,000 measurements from ages 5–40 years. Recommendations for choosing a modelling approach are provided along with a discussion and signposting on further modelling extensions for analysing trajectory exposures and outcomes, and multiple cohorts. RESULTS: Linear and natural cubic spline LME models and SITAR provided similar summary of the mean bone growth trajectory and growth velocity, and the sex differences in growth patterns. Growth velocity (in grams/year) peaked during adolescence, and peaked earlier in females than males e.g., mean age at peak bone mineral content accrual from multicohort SITAR models was 12.2 years in females and 13.9 years in males. Latent trajectory models (with trajectory shapes estimated using a natural cubic spline) identified up to four subgroups of individuals with distinct trajectories throughout adolescence. CONCLUSIONS: LME models with linear and natural cubic splines, SITAR, and latent trajectory models are useful for describing nonlinear growth trajectories, and these methods can be adapted for other complex traits. Choice of method depends on the research aims, complexity of the trajectory, and available data. Scripts and synthetic datasets are provided for readers to replicate trajectory modelling and visualisation using the R statistical computing software. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12874-022-01542-8

Using linear and natural cubic splines, SITAR, and latent trajectory models to characterise nonlinear longitudinal growth trajectories in cohort studies

BACKGROUND: Longitudinal data analysis can improve our understanding of the influences on health trajectories across the life-course. There are a variety of statistical models which can be used, and their fitting and interpretation can be complex, particularly where there is a nonlinear trajectory. Our aim was to provide an accessible guide along with applied examples to using four sophisticated modelling procedures for describing nonlinear growth trajectories. METHODS: This expository paper provides an illustrative guide to summarising nonlinear growth trajectories for repeatedly measured continuous outcomes using (i) linear spline and (ii) natural cubic spline linear mixed-effects (LME) models, (iii) Super Imposition by Translation and Rotation (SITAR) nonlinear mixed effects models, and (iv) latent trajectory models. The underlying model for each approach, their similarities and differences, and their advantages and disadvantages are described. Their application and correct interpretation of their results is illustrated by analysing repeated bone mass measures to characterise bone growth patterns and their sex differences in three cohort studies from the UK, USA, and Canada comprising 8500 individuals and 37,000 measurements from ages 5-40 years. Recommendations for choosing a modelling approach are provided along with a discussion and signposting on further modelling extensions for analysing trajectory exposures and outcomes, and multiple cohorts. RESULTS: Linear and natural cubic spline LME models and SITAR provided similar summary of the mean bone growth trajectory and growth velocity, and the sex differences in growth patterns. Growth velocity (in grams/year) peaked during adolescence, and peaked earlier in females than males e.g., mean age at peak bone mineral content accrual from multicohort SITAR models was 12.2 years in females and 13.9 years in males. Latent trajectory models (with trajectory shapes estimated using a natural cubic spline) identified up to four subgroups of individuals with distinct trajectories throughout adolescence. CONCLUSIONS: LME models with linear and natural cubic splines, SITAR, and latent trajectory models are useful for describing nonlinear growth trajectories, and these methods can be adapted for other complex traits. Choice of method depends on the research aims, complexity of the trajectory, and available data. Scripts and synthetic datasets are provided for readers to replicate trajectory modelling and visualisation using the R statistical computing software

BMD loci contribute to ethnic and developmental differences in skeletal fragility across populations: Assessment of evolutionary selection pressures

Bone mineral density (BMD) is a highly heritable trait used both for the diagnosis of osteoporosis in adults and to assess bone health in children. Ethnic differences in BMD have been documented, with markedly higher levels in individuals of African descent, which partially explain disparity in osteoporosis risk across populations. To date, 63 independent genetic variants have been associated with BMD in adults of Northern-European ancestry. Here, we demonstrate that at least 61 of these variants are predictive of BMD early in life by studying their compound effect within two multiethnic pediatric cohorts. Furthermore, we show that within these cohorts and across populations worldwide the frequency of those alleles associated with increased BMD is systematically elevated in individuals of Sub-Saharan African ancestry. The amount of differentiation in the BMD genetic scores among Sub-Saharan and non-Sub-Saharan populations together with neutrality tests, suggest that these allelic differences are compatible with the hypothesis of selective pressures acting on the genetic determinants of BMD. These findings constitute an explorative contribution to the role of selection on ethnic BMD differences and likely a new example of polygenic adaptation acting on a human trait

Bivariate genome-wide association meta-analysis of pediatric musculoskeletal traits reveals pleiotropic effects at the SREBF1/TOM1L2 locus

Bone mineral density is known to be a heritable, polygenic trait whereas genetic variants contributing to lean mass variation remain largely unknown. We estimated the shared SNP heritability and performed a bivariate GWAS meta-analysis of total-body lean mass (TB-LM) and total-body less head bone mineral density (TBLH-BMD) regions in 10,414 children. The estimated SNP heritability is 43% for TBLH-BMD, and 39% for TB-LM, with a shared genetic component of 43%. We identify variants with pleiotropic effects in eight loci, including seven established bone mineral density loci: _WNT4, GALNT3, MEPE, CPED1/WNT16, TNFSF11, RIN3, and PPP6R3/LRP5_. Variants in the _TOM1L2/SREBF1_ locus exert opposing effects TB-LM and TBLH-BMD, and have a stronger association with the former trait. We show that _SREBF1_ is expressed in murine and human osteoblasts, as well as in human muscle tissue. This is the first bivariate GWAS meta-analysis to demonstrate genetic factors with pleiotropic effects on bone mineral density and lean mass

Bivariate genome-wide association meta-analysis of pediatric musculoskeletal traits reveals pleiotropic effects at the SREBF1/TOM1L2 locus

Bone mineral density is known to be a heritable, polygenic trait whereas genetic variants contributing to lean mass variation remain largely unknown. We estimated the shared SNP heritability and performed a bivariate GWAS meta-analysis of total-body lean mass (TB-LM) and total-body less head bone mineral density (TBLH-BMD) regions in 10,414 children. The estimated SNP heritability is 43% for TBLH-BMD, and 39% for TB-LM, with a shared genetic component of 43%. We identify variants with pleiotropic effects in eight loci, including seven established bone mineral density loci: _WNT4, GALNT3, MEPE, CPED1/WNT16, TNFSF11, RIN3, and PPP6R3/LRP5_. Variants in the _TOM1L2/SREBF1_ locus exert opposing effects TB-LM and TBLH-BMD, and have a stronger association with the former trait. We show that _SREBF1_ is expressed in murine and human osteoblasts, as well as in human muscle tissue. This is the first bivariate GWAS meta-analysis to demonstrate genetic factors with pleiotropic effects on bone mineral density and lean mass