Associations between genetic obesity susceptibility and early postnatal fat and lean mass: an individual participant meta-analysis

IMPORTANCE: Patterns of body size and body composition associated with genetic obesity susceptibility inform the mechanisms that increase obesity risk. OBJECTIVE: To test associations between genetic obesity susceptibility, represented by a combined obesity risk-allele score, and body size or body composition at birth to age 5 years. DESIGN, SETTING, AND PARTICIPANTS: A total of 3031 children from 4 birth cohort studies in England, France, and Spain were included in a meta-analysis. EXPOSURES: A combined obesity risk-allele score was calculated from genotypes at 16 variants identified by genome-wide association studies of adult body mass index (BMI). MAIN OUTCOMES AND MEASURES: Outcomes were age- and sex-adjusted SD scores (SDS) for weight, length/height, BMI, fat mass, lean mass, and percentage of body fat at birth as well as at ages 1, 2 to 3, and 4 to 5 years. RESULTS: The obesity risk-allele score was not associated with infant size at birth; at age 1 year it was positively associated with weight (β [SE], 0.020 [0.008] SDS per allele; P = .009) and length (β [SE], 0.020 [0.008] SDS per allele; P = .01), but not with BMI (β [SE], 0.013 [0.008] SDS per allele; P = .11). At age 2 to 3 years these associations were stronger (weight: β [SE], 0.033 [0.008] SDS per allele; P  .15 at all ages). CONCLUSIONS AND RELEVANCE: Genetic obesity susceptibility appears to promote a normally partitioned increase in early postnatal, but not prenatal, growth. These findings suggest that symmetrical rapid growth may identify infants with high life-long susceptibility for obesity

Quantitative lipoprotein subclass and low molecular weight metabolite analysis in human serum and plasma by 1H NMR spectroscopy in a multilaboratory trial

We report an extensive 600 MHz NMR trial of a quantitative lipoprotein and small molecule measurements in human blood serum and plasma. Five centers with eleven 600 MHz NMR spectrometers were used to analyze 98 samples including: 20 QCs, 37 commercially sourced, paired serum and plasma samples and 2 National Institute of Science and Technology, NIST, reference material 1951c replicates. Samples were analyzed using rigorous protocols for sample preparation and experimental acquisition. A commercial lipoprotein subclass analysis was used to quantify 105 lipoprotein subclasses and 24 low molecular weight metabolites from the nuclear magnetic resonance, NMR, spectra. For all spectrometers, the instrument specific variance in measuring internal quality controls, QCs, was lower than the percentage described by the National Cholesterol Education Program, NCEP, criteria for lipid testing (triglycerides<2.7%, cholesterol<2.8%; LDL-cholesterol<2.8%; HDL-cholesterol<2.3%), showing exceptional reproducibility for direct quantitation of lipoproteins in both matrices. The average RSD for the 105 lipoprotein parameters in the 11 instruments was 4.6% and 3.9% for the two NIST samples while it was 38% and 40% for the 37 commercially sourced plasmas and sera, respectively, showing negligible analytical compared to biological variation. The coefficient of variance, CV, obtained for the quantification of the small molecules across the 11 spectrometers was below 15% for 20 out of the 24 metabolites analyzed. This study provides further evidence of the suitability of NMR for high-throughput lipoprotein subcomponent analysis and small molecule quantitation with the exceptional reproducibility required for clinical and other regulatory settings

Srs2 removes deadly recombination intermediates independently of its interaction with SUMO-modified PCNA

Saccharomyces cerevisiae Srs2 helicase plays at least two distinct functions. One is to prevent recombinational repair through its recruitment by sumoylated Proliferating Cell Nuclear Antigen (PCNA), evidenced in postreplication-repair deficient cells, and a second one is to eliminate potentially lethal intermediates formed by recombination proteins. Both actions are believed to involve the capacity of Srs2 to displace Rad51 upon translocation on single-stranded DNA (ssDNA), though a role of its helicase activity may be important to remove some toxic recombination structures. Here, we described two new mutants, srs2R1 and srs2R3, that have lost the ability to hinder recombinational repair in postreplication-repair mutants, but are still able to remove toxic recombination structures. Although the mutants present very similar phenotypes, the mutated proteins are differently affected in their biochemical activities. Srs2R1 has lost its capacity to interact with sumoylated PCNA while the biochemical activities of Srs2R3 are attenuated (ATPase, helicase, DNA binding and ability to displace Rad51 from ssDNA). In addition, crossover (CO) frequencies are increased in both mutants. The different roles of Srs2, in relation to its eventual recruitment by sumoylated PCNA, are discussed

BMI Changes During Childhood and Adolescence as Predictors of Amount of Adult Subcutaneous and Visceral Adipose Tissue in Men: The GOOD Study

Objective. The amount of visceral adipose tissue is a risk factor for the metabolic syndrome. It is unclear how body mass index (BMI) changes during childhood and adolescence predict adult fat distribution. We hypothesized that there are critical periods during development for the prediction of adult subcutaneous and visceral fat mass by BMI changes during childhood and adolescence. Research Design and Methods. Detailed growth charts were retrieved for the men participating in the population-based Gothenburg Osteoporosis and Obesity Determinants (GOOD) study (n=612). Body composition was analysed using Dual X-Ray Absorptiometry and adipose tissue areas using abdominal computed tomography at 18-20 years of age. Results. The main finding in the present study was that subjects with increases in BMI Z-score of >1 SD during adolescence had, independent of prepubertal BMI, both larger subcutaneous (+138%; p1 SD during late childhood had larger amount adult subcutaneous adipose tissue (+83%;

Gestational age at birth and body size from infancy through adolescence: An individual participant data meta-analysis on 253,810 singletons in 16 birth cohort studies

Background Preterm birth is the leading cause of perinatal morbidity and mortality and is associated with adverse developmental and long-term health outcomes, including several cardiometabolic risk factors and outcomes. However, evidence about the association of preterm birth with later body size derives mainly from studies using birth weight as a proxy of prematurity rather than an actual length of gestation. We investigated the association of gestational age (GA) at birth with body size from infancy through adolescence. Methods and findings We conducted a two-stage individual participant data (IPD) meta-analysis using data from 253,810 mother-child dyads from 16 general population-based cohort studies in Europe (Denmark, Finland, France, Italy, Norway, Portugal, Spain, the Netherlands, United Kingdom), North America (Canada), and Australasia (Australia) to estimate the association of GA with body mass index (BMI) and overweight (including obesity) adjusted for the following maternal characteristics as potential confounders: education, height, prepregnancy BMI, ethnic background, parity, smoking during pregnancy, age at child's birth, gestational diabetes and hypertension, and preeclampsia. Pregnancy and birth cohort studies from the LifeCycle and the EUCAN-Connect projects were invited and were eligible for inclusion if they had information on GA and minimum one measurement of BMI between infancy and adolescence. Using a federated analytical tool (DataSHIELD), we fitted linear and logistic regression models in each cohort separately with a complete-case approach and combined the regression estimates and standard errors through random-effects study-level meta-analysis providing an overall effect estimate at early infancy (>0.0 to 0.5 years), late infancy (>0.5 to 2.0 years), early childhood (>2.0 to 5.0 years), mid-childhood (>5.0 to 9.0 years), late childhood (>9.0 to 14.0 years), and adolescence (>14.0 to 19.0 years). GA was positively associated with BMI in the first decade of life, with the greatest increase in mean BMI z-score during early infancy (0.02, 95% confidence interval (CI): 0.00; 0.05, p < 0.05) per week of increase in GA, while in adolescence, preterm individuals reached similar levels of BMI (0.00, 95% CI: -0.01; 0.01, p 0.9) as term counterparts. The association between GA and overweight revealed a similar pattern of association with an increase in odds ratio (OR) of overweight from late infancy through mid-childhood (OR 1.01 to 1.02) per week increase in GA. By adolescence, however, GA was slightly negatively associated with the risk of overweight (OR 0.98 [95% CI: 0.97; 1.00], p 0.1) per week of increase in GA. Although based on only four cohorts (n = 32,089) that reached the age of adolescence, data suggest that individuals born very preterm may be at increased odds of overweight (OR 1.46 [95% CI: 1.03; 2.08], p < 0.05) compared with term counterparts. Findings were consistent across cohorts and sensitivity analyses despite considerable heterogeneity in cohort characteristics. However, residual confounding may be a limitation in this study, while findings may be less generalisable to settings in low- and middle-income countries. Conclusions This study based on data from infancy through adolescence from 16 cohort studies found that GA may be important for body size in infancy, but the strength of association attenuates consistently with age. By adolescence, preterm individuals have on average a similar mean BMI to peers born at term.This collaborative project received funding from the European Union's Horizon 2020 research and innovation programme (Grant Agreement No. 733206 LifeCycle, Grand Recipient VWVJ; Grant Agreement No. 824989 EUCAN-Connect, Grand Recipient AMNA). Please, see S1 Appendix for list of cohort-specific funding/support. DAL is supported by the UK Medical Research Council (MC_UU_00011/6) and British Heart Foundation (CH/F/20/90003 and AA/18/7/34219). RCW is supported by UKRI Innovation Fellowship with Health Data Research UK [MR/S003959/1]. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

Gestational Weight Gain and Body Mass Index in Children: Results from Three German Cohort Studies

Previous studies suggested potential priming effects of gestational weight gain (GWG) on offspring's body composition in later life. However, consistency of these effects in normal weight, overweight and obese mothers is less clear. We combined the individual data of three German cohorts and assessed associations of total and excessive GWG (as defined by criteria of the Institute of Medicine) with offspring's mean body mass index (BMI) standard deviation scores (SDS) and overweight at the age of 5-6 years (total: n = 6,254). Quantile regression was used to examine potentially different effects on different parts of the BMI SDS distribution. All models were adjusted for birth weight, maternal age and maternal smoking during pregnancy and stratified by maternal pre-pregnancy weight status. In adjusted models, positive associations of total and excessive GWG with mean BMI SDS and overweight were observed only in children of non- overweight mothers. For example, excessive GWG was associated with a mean increase of 0.08 (95% CI: 0.01, 0.15) units of BMI SDS (0.13 (0.02, 0.24) kg/m(2) of 'real' BMI) in children of normal-weight mothers. The effects of total and excessive GWG on BMI SDS increased for higher- BMI children of normal-weight mothers. Increased GWG is likely to be associated with overweight in offspring of non-overweight mothers

Measurement error adjustment in essential fatty acid intake from a food frequency questionnaire: alternative approaches and methods

<p>Abstract</p> <p>Background</p> <p>We aimed at assessing the degree of measurement error in essential fatty acid intakes from a food frequency questionnaire and the impact of correcting for such an error on precision and bias of odds ratios in logistic models. To assess these impacts, and for illustrative purposes, alternative approaches and methods were used with the binary outcome of cognitive decline in verbal fluency.</p> <p>Methods</p> <p>Using the Atherosclerosis Risk in Communities (ARIC) study, we conducted a sensitivity analysis. The error-prone exposure – visit 1 fatty acid intake (1987–89) – was available for 7,814 subjects 50 years or older at baseline with complete data on cognitive decline between visits 2 (1990–92) and 4 (1996–98). Our binary outcome of interest was clinically significant decline in verbal fluency. Point estimates and 95% confidence intervals were compared between naïve and measurement-error adjusted odds ratios of decline with every SD increase in fatty acid intake as % of energy. Two approaches were explored for adjustment: (A) External validation against biomarkers (plasma fatty acids in cholesteryl esters and phospholipids) and (B) Internal repeat measurements at visits 2 and 3. The main difference between the two is that Approach B makes a stronger assumption regarding lack of error correlations in the structural model. Additionally, we compared results from regression calibration (RCAL) to those from simulation extrapolation (SIMEX). Finally, using structural equations modeling, we estimated attenuation factors associated with each dietary exposure to assess degree of measurement error in a bivariate scenario for regression calibration of logistic regression model.</p> <p>Results and conclusion</p> <p>Attenuation factors for Approach A were smaller than B, suggesting a larger amount of measurement error in the dietary exposure. Replicate measures (Approach B) unlike concentration biomarkers (Approach A) may lead to imprecise odds ratios due to larger standard errors. Using SIMEX rather than RCAL models tends to preserve precision of odds ratios. We found in many cases that bias in naïve odds ratios was towards the null. RCAL tended to correct for a larger amount of effect bias than SIMEX, particularly for Approach A.</p