Cohort profile: Andhra Pradesh Children and Parents Study (APCAPS)

The Andhra Pradesh Children and Parents Study (APCAPS) was originally established to study the long-term effects of early-life undernutrition on risk of cardiovascular disease. Its aims were subsequently expanded to include trans-generational influences of other environmental and genetic factors on chronic diseases in rural India. It builds on the Hyderabad Nutrition Trial (HNT) conducted in 1987–90 to compare the effects on birthweight of a protein-calorie supplement for pregnant women and children. The index children of HNT and their mothers were retraced and examined in 2003–05, and the children re-examined as young adults aged 18–21 years in 2009–10. The cohort was expanded to include both parents and siblings of the index children in a recently completed follow-up conducted in 2010–12 (N = ∼6225 out of 10 213 participants). Recruitment of the remaining residents of these 29 villages (N = ∼55 000) in Ranga Reddy district of Andhra Pradesh is now under way. Extensive data on socio-demographic, lifestyle, medical, anthropometric, physiological, vascular and body composition measures, DNA, stored plasma, and assays of lipids and inflammatory markers on APCAPS participants are available. Details of how to access these data are available from the corresponding author.

Life-course determinants of bone mass in young adults from a transitional rural community in India: The Andhra Pradesh Children and Parents Study (APCAPS)

Background: Undernutrition and physical inactivity are both associated with lower bone mass. Objective: This study aimed to investigate the combined effects of early-life undernutrition and urbanized lifestyles in later life on bone mass accrual in young adults from a rural community in India that is undergoing rapid socioeconomic development. Design: This was a prospective cohort study of participants of the Hyderabad Nutrition Trial (1987–1990), which offered balanced protein-calorie supplementation to pregnant women and preschool children younger than 6 y in the intervention villages. The 2009–2010 follow-up study collected data on current anthropometric measures, bone mineral density (BMD) measured by dual-energy X-ray absorptiometry, blood samples, diet, physical activity, and living standards of the trial participants (n = 1446, aged 18–23 y). Results: Participants were generally lean and had low BMD [mean hip BMD: 0.83 (women), 0.95 (men) g/cm2; lumbar spine: 0.86 (women), 0.93 (men) g/cm2]. In models adjusted for current risk factors, no strong evidence of a positive association was found between BMD and early-life supplementation. On the other hand, current lean mass and weight-bearing physical activity were positively associated with BMD. No strong evidence of an association was found between BMD and current serum 25-hydroxyvitamin D or dietary intake of calcium, protein, or calories. Conclusions: Current lean mass and weight-bearing physical activity were more important determinants of bone mass than was early-life undernutrition in this population. In transitional rural communities from low-income countries, promotion of physical activity may help to mitigate any potential adverse effects of early nutritional disadvantage.

Analysis of body composition in individuals with high bone mass reveals a marked increase in fat mass in women but not men

Context: High bone mass (HBM), detected in 0.2% of dual-energy x-ray absorptiometry (DXA) scans, is characterized by raised body mass index, the basis for which is unclear. Objective: To investigate why body mass index is elevated in individuals with HBM, we characterized body composition and examined whether differences could be explained by bone phenotypes, eg, bone mass and/or bone turnover. Design, Setting, and Participants: We conducted a case-control study of 153 cases with unexplained HBM recruited from 4 UK centers by screening 219 088 DXA scans. Atotal of 138 first-degree relatives (of whom 51 had HBM) and 39 spouses were also recruited. Unaffected individuals served as controls. Main Outcome Measures: We measured fat mass, by DXA, and bone turnover markers. Results: Amongwomen, fat mass was inversely related to age in controls (P<.01), but not in HBM cases (P<.96) in whom mean fat mass was 8.9 [95% CI 4.7, 13.0] kg higher compared with controls (fully adjusted mean difference, P<.001). Increased fat mass in male HBM cases was less marked (gender interaction P = .03). Compared with controls, lean mass was also increased in female HBM cases (by 3.3 [1.2, 5.4] kg; P<.002); however, lean mass increases wereless marked than fat mass increases, resulting in 4.5% lower percentage lean mass in HBM cases (P<.001). Osteocalcin was also lower in female HBM cases compared with controls (by 2.8 [0.1, 5.5]μg/L; P = .04). Differences in fat mass were fully attenuated after hip bone mineral density (BMD) adjustment (P = .52) but unchanged after adjustment for bone turnover (P < .001), whereas the greater hip BMD in female HBM cases was minimally attenuated by fat mass adjustment (P<.001). Conclusions: HBM is characterized by a marked increase in fat mass in females, statistically explained by their greater BMD, but not by markers of bone turnover. Copyright © 2013 by The Endocrine Society.

Elevated circulating sclerostin concentrations in individuals with high bone mass, with and without LRP5 mutations

CONTEXT: The role and importance of circulating sclerostin is poorly understood. High bone mass (HBM) caused by activating LRP5 mutations has been reported to be associated with increased plasma sclerostin concentrations; whether the same applies to HBM due to other causes is unknown. OBJECTIVE: Our objective was to determine circulating sclerostin concentrations in HBM. DESIGN AND PARTICIPANTS: In this case-control study, 406 HBM index cases were identified by screening dual-energy x-ray absorptiometry (DXA) databases from 4 United Kingdom centers (n = 219 088), excluding significant osteoarthritis/artifact. Controls comprised unaffected relatives and spouses. MAIN MEASURES: Plasma sclerostin; lumbar spine L1, total hip, and total body DXA; and radial and tibial peripheral quantitative computed tomography (subgroup only) were evaluated. RESULTS: Sclerostin concentrations were significantly higher in both LRP5 HBM and non-LRP5 HBM cases compared with controls: mean (SD) 130.1 (61.7) and 88.0 (39.3) vs 66.4 (32.3) pmol/L (both P < .001, which persisted after adjustment for a priori confounders). In combined adjusted analyses of cases and controls, sclerostin concentrations were positively related to all bone parameters found to be increased in HBM cases (ie, L1, total hip, and total body DXA bone mineral density and radial/tibial cortical area, cortical bone mineral density, and trabecular density). Although these relationships were broadly equivalent in HBM cases and controls, there was some evidence that associations between sclerostin and trabecular phenotypes were stronger in HBM cases, particularly for radial trabecular density (interaction P < .01). CONCLUSIONS: Circulating plasma sclerostin concentrations are increased in both LRP5 and non-LRP5 HBM compared with controls. In addition to the general positive relationship between sclerostin and DXA/peripheral quantitative computed tomography parameters, genetic factors predisposing to HBM may contribute to increased sclerostin levels.

Handbook of curriculum development. 'Manual de desarrollo curricular'.

Incluye índice temático. Resumen basado en el de la publicación

Genome-wide prediction of childhood asthma and related phenotypes in a longitudinal birth cohort

Childhood wheezing and asthma vary greatly in clinical presentation and time course. The extent to which phenotypic variation reflects heterogeneity in disease pathways is unclear.

STrengthening the REporting of Genetic Association studies (STREGA)--an extension of the STROBE statement

Making sense of rapidly evolving evidence on genetic associations is crucial to making genuine advances in human genomics and the eventual integration of this information in the practice of medicine and public health. Assessment of the strengths and weaknesses of this evidence, and hence the ability to synthesize it, has been limited by inadequate reporting of results. The STrengthening the REporting of Genetic Association studies (STREGA) initiative builds on the STrengthening the Reporting of OBservational Studies in Epidemiology (STROBE) Statement and provides additions to 12 of the 22 items on the STROBE checklist. The additions concern population stratification, genotyping errors, modelling haplotype variation, Hardy-Weinberg equilibrium, replication, selection of participants, rationale for choice of genes and variants, treatment effects in studying quantitative traits, statistical methods, relatedness, reporting of descriptive and outcome data and the volume of data issues that are important to consider in genetic association studies. The STREGA recommendations do not prescribe or dictate how a genetic association study should be designed, but seek to enhance the transparency of its reporting, regardless of choices made during design, conduct or analysis.

STrengthening the REporting of Genetic Association Studies (STREGA)--an extension of the STROBE statement

Making sense of rapidly evolving evidence on genetic associations is crucial to making genuine advances in human genomics and the eventual integration of this information in the practice of medicine and public health. Assessment of the strengths and weaknesses of this evidence, and hence the ability to synthesize it, has been limited by inadequate reporting of results. The STrengthening the REporting of Genetic Association studies (STREGA) initiative builds on the STrengthening the Reporting of OBservational Studies in Epidemiology (STROBE) Statement and provides additions to 12 of the 22 items on the STROBE checklist. The additions concern population stratification, genotyping errors, modelling haplotype variation, Hardy-Weinberg equilibrium, replication, selection of participants, rationale for choice of genes and variants, treatment effects in studying quantitative traits, statistical methods, relatedness, reporting of descriptive and outcome data, and the volume of data issues that are important to consider in genetic association studies. The STREGA recommendations do not prescribe or dictate how a genetic association study should be designed but seek to enhance the transparency of its reporting, regardless of choices made during design, conduct, or analysis.

Strengthening the reporting of genetic association studies (STREGA): an extension of the strengthening the reporting of observational studies in epidemiology (STROBE) statement

Making sense of rapidly evolving evidence on genetic associations is crucial to making genuine advances in human genomics and the eventual integration of this information in the practice of medicine and public health. Assessment of the strengths and weaknesses of this evidence, and hence, the ability to synthesize it, has been limited by inadequate reporting of results. The STrengthening the REporting of Genetic Association (STREGA) studies initiative builds on the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement and provides additions to 12 of the 22 items on the STROBE checklist. The additions concern population stratification, genotyping errors, modeling haplotype variation, Hardy-Weinberg equilibrium, replication, selection of participants, rationale for choice of genes and variants, treatment effects in studying quantitative traits, statistical methods, relatedness, reporting of descriptive and outcome data, and the volume of data issues that are important to consider in genetic association studies. The STREGA recommendations do not prescribe or dictate how a genetic association study should be designed, but seek to enhance the transparency of its reporting, regardless of choices made during design, conduct, or analysis.

STrengthening the REporting of Genetic Association Studies (STREGA): an extension of the STROBE statement

Making sense of rapidly evolving evidence on genetic associations is crucial to making genuine advances in human genomics and the eventual integration of this information in the practice of medicine and public health. Assessment of the strengths and weaknesses of this evidence, and hence the ability to synthesize it, has been limited by inadequate reporting of results. The STrengthening the REporting of Genetic Association studies (STREGA) initiative builds on the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement and provides additions to 12 of the 22 items on the STROBE checklist. The additions concern population stratification, genotyping errors, modelling haplotype variation, Hardy-Weinberg equilibrium, replication, selection of participants, rationale for choice of genes and variants, treatment effects in studying quantitative traits, statistical methods, relatedness, reporting of descriptive and outcome data, and the volume of data issues that are important to consider in genetic association studies. The STREGA recommendations do not prescribe or dictate how a genetic association study should be designed but seek to enhance the transparency of its reporting, regardless of choices made during design, conduct, or analysis.

STrengthening the REporting of Genetic Association studies (STREGA): an extension of the STROBE Statement

Making sense of rapidly evolving evidence on genetic associations is crucial to making genuine advances in human genomics and the eventual integration of this information into the practice of medicine and public health. Assessment of the strengths and weaknesses of this evidence, and hence the ability to synthesize it, has been limited by inadequate reporting of results. The STrengthening the REporting of Genetic Association studies (STREGA) initiative builds on the STrengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement and provides additions to 12 of the 22 items on the STROBE checklist. The additions concern population stratification, genotyping errors, modeling haplotype variation, Hardy-Weinberg equilibrium, replication, selection of participants, rationale for choice of genes and variants, treatment effects in studying quantitative traits, statistical methods, relatedness, reporting of descriptive and outcome data, and issues of data volume that are important to consider in genetic association studies. The STREGA recommendations do not prescribe or dictate how a genetic association study should be designed but seek to enhance the transparency of its reporting, regardless of choices made during design, conduct, or analysis.

Strengthening the reporting of genetic association studies (STREGA): an extension of the STROBE statement

Making sense of rapidly evolving evidence on genetic associations is crucial to making genuine advances in human genomics and the eventual integration of this information in the practice of medicine and public health. Assessment of the strengths and weaknesses of this evidence, and hence the ability to synthesize it, has been limited by inadequate reporting of results. The STrengthening the REporting of Genetic Association studies (STREGA) initiative builds on the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement and provides additions to 12 of the 22 items on the STROBE checklist. The additions concern population stratification, genotyping errors, modeling haplotype variation, Hardy-Weinberg equilibrium, replication, selection of participants, rationale for choice of genes and variants, treatment effects in studying quantitative traits, statistical methods, relatedness, reporting of descriptive and outcome data, and the volume of data issues that are important to consider in genetic association studies. The STREGA recommendations do not prescribe or dictate how a genetic association study should be designed but seek to enhance the transparency of its reporting, regardless of choices made during design, conduct, or analysis.

Strengthening the reporting of genetic association studies (STREGA): an extension of the STROBE Statement

Making sense of rapidly evolving evidence on genetic associations is crucial to making genuine advances in human genomics and the eventual integration of this information in the practice of medicine and public health. Assessment of the strengths and weaknesses of this evidence, and hence the ability to synthesize it, has been limited by inadequate reporting of results. The STrengthening the REporting of Genetic Association studies (STREGA) initiative builds on the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement and provides additions to 12 of the 22 items on the STROBE checklist. The additions concern population stratification, genotyping errors, modeling haplotype variation, Hardy-Weinberg equilibrium, replication, selection of participants, rationale for choice of genes and variants, treatment effects in studying quantitative traits, statistical methods, relatedness, reporting of descriptive and outcome data, and the volume of data issues that are important to consider in genetic association studies. The STREGA recommendations do not prescribe or dictate how a genetic association study should be designed but seek to enhance the transparency of its reporting, regardless of choices made during design, conduct, or analysis.