Diabetes Study of Children of Diverse Ethnicity and Race: Study design.

AIMS: Determining diabetes type in children has become increasingly difficult due to an overlap in typical characteristics between type 1 diabetes (T1D) and type 2 diabetes (T2D). The Diabetes Study in Children of Diverse Ethnicity and Race (DISCOVER) programme is a National Institutes of Health (NIH)-supported multicenter, prospective, observational study that enrols children and adolescents with non-secondary diabetes. The primary aim of the study was to develop improved models to differentiate between T1D and T2D in diverse youth. MATERIALS AND METHODS: The proposed models will evaluate the utility of three existing T1D genetic risk scores in combination with data on islet autoantibodies and other parameters typically available at the time of diabetes onset. Low non-fasting serum C-peptide (<0.6 nmol/L) between 3 and 10 years after diabetes diagnosis will be considered a biomarker for T1D as it reflects the loss of insulin secretion ability. Participating centres are enrolling youth (<19 years old) either with established diabetes (duration 3-10 years) for a cross-sectional evaluation or with recent onset diabetes (duration 3 weeks-15 months) for the longitudinal observation with annual visits for 3 years. Cross-sectional data will be used to develop models. Longitudinal data will be used to externally validate the best-fitting model. RESULTS: The results are expected to improve the ability to classify diabetes type in a large and growing subset of children who have an unclear form of diabetes at diagnosis. CONCLUSIONS: Accurate and timely classification of diabetes type will help establish the correct clinical management early in the course of the disease.

Sensitive periods and other timing hypotheses in developmental psychopathology: A tutorial.

Researchers often aim to assess whether repeated measures of an exposure are associated with repeated measures of an outcome. A question of particular interest is how associations between exposures and outcomes may differ over time. In other words, researchers may seek the best form of a temporal model. While several models are possible, researchers often consider a few key models. For example, researchers may hypothesize that an exposure measured during a sensitive period may be associated with repeated measures of the outcome over time. Alternatively, they may hypothesize that the exposure measured immediately before the current time period may be most strongly associated with the outcome at the current time. Finally, they may hypothesize that all prior exposures are important. Many analytic methods cannot compare and evaluate these alternative temporal models, perhaps because they make the restrictive assumption that the associations between exposures and outcomes remains constant over time. Instead, we provide a tutorial describing four temporal models that allow the associations between repeated measures of exposures and outcomes to vary, and showing how to test which temporal model is best supported by the data. By finding the best temporal model, developmental psychopathology researchers can find optimal windows for intervention.

Using Power Analysis to Choose the Unit of Randomization, Outcome, and Approach for Subgroup Analysis for a Multilevel Randomized Controlled Clinical Trial to Reduce Disparities in Cardiovascular Health.

We give examples of three features in the design of randomized controlled clinical trials which can increase power and thus decrease sample size and costs. We consider an example multilevel trial with several levels of clustering. For a fixed number of independent sampling units, we show that power can vary widely with the choice of the level of randomization. We demonstrate that power and interpretability can improve by testing a multivariate outcome rather than an unweighted composite outcome. Finally, we show that using a pooled analytic approach, which analyzes data for all subgroups in a single model, improves power for testing the intervention effect compared to a stratified analysis, which analyzes data for each subgroup in a separate model. The power results are computed for a proposed prevention research study. The trial plans to randomize adults to either telehealth (intervention) or in-person treatment (control) to reduce cardiovascular risk factors. The trial outcomes will be measures of the Essential Eight, a set of scores for cardiovascular health developed by the American Heart Association which can be combined into a single composite score. The proposed trial is a multilevel study, with outcomes measured on participants, participants treated by the same provider, providers nested within clinics, and clinics nested within hospitals. Investigators suspect that the intervention effect will be greater in rural participants, who live farther from clinics than urban participants. The results use published, exact analytic methods for power calculations with continuous outcomes. We provide example code for power analyses using validated software.

Power and sample size analysis for longitudinal mixed models of health in populations exposed to environmental contaminants: a tutorial.

BACKGROUND: When evaluating the impact of environmental exposures on human health, study designs often include a series of repeated measurements. The goal is to determine whether populations have different trajectories of the environmental exposure over time. Power analyses for longitudinal mixed models require multiple inputs, including clinically significant differences, standard deviations, and correlations of measurements. Further, methods for power analyses of longitudinal mixed models are complex and often challenging for the non-statistician. We discuss methods for extracting clinically relevant inputs from literature, and explain how to conduct a power analysis that appropriately accounts for longitudinal repeated measures. Finally, we provide careful recommendations for describing complex power analyses in a concise and clear manner. METHODS: For longitudinal studies of health outcomes from environmental exposures, we show how to [1] conduct a power analysis that aligns with the planned mixed model data analysis, [2] gather the inputs required for the power analysis, and [3] conduct repeated measures power analysis with a highly-cited, validated, free, point-and-click, web-based, open source software platform which was developed specifically for scientists. RESULTS: As an example, we describe the power analysis for a proposed study of repeated measures of per- and polyfluoroalkyl substances (PFAS) in human blood. We show how to align data analysis and power analysis plan to account for within-participant correlation across repeated measures. We illustrate how to perform a literature review to find inputs for the power analysis. We emphasize the need to examine the sensitivity of the power values by considering standard deviations and differences in means that are smaller and larger than the speculated, literature-based values. Finally, we provide an example power calculation and a summary checklist for describing power and sample size analysis. CONCLUSIONS: This paper provides a detailed roadmap for conducting and describing power analyses for longitudinal studies of environmental exposures. It provides a template and checklist for those seeking to write power analyses for grant applications.

Gestational diabetes mellitus, epigenetic age and offspring metabolism.

AIMS: No reports examine the relationship between in-utero exposure to gestational diabetes mellitus (GDM), offspring epigenetic age acceleration (EAA), and offspring insulin sensitivity. METHODS: Using data from a cohort study, we examined associations between GDM in-utero exposure and offspring EAA at approximately 10 years of age, using separate regression models adjusting for offspring chronological age and sex. We also examined associations between EAA with updated homeostasis model assessment of insulin sensitivity and secretion (HOMA2-S and HOMA2-ß) measured at approximately 10 and 16 years of age, using mixed linear regression models accounting for repeated measures after adjustment for offspring chronological age and sex. RESULTS: Compared to unexposed offspring (n = 91), offspring exposed to GDM (n = 88) had greater EAA or older extrinsic age compared to chronological age (ß-coefficient 2.00, 95% confidence interval [0.71, 3.28], p = 0.0025), but not greater intrinsic EAA (ß-coefficient -0.07, 95% CI [-0.71, 0.57], p = 0.93). Extrinsic EAA was associated with lower insulin sensitivity (ß-coefficient -0.018, 95% CI [-0.035, -0.002], p = 0.03) and greater insulin secretion (ß-coefficient 0.018, 95% CI [0.006, 0.03], p = 0.003), and these associations persisted after further adjustment for measures of maternal and child adiposity. No associations were observed between intrinsic EAA and insulin sensitivity and secretion, before or after adjustment for measures of maternal and child adiposity. CONCLUSIONS: In this study, children exposed to GDM experience greater extrinsic EAA, which is associated with lower insulin sensitivity and greater insulin secretion. Further studies are needed to determine the directionality of these associations.

A comparison of the remote food photography method and the automated self-administered 24-h dietary assessment tool for measuring full-day dietary intake among school-age children.

The limitations of self-report measures of dietary intake are well-known. Novel, technology-based measures of dietary intake may provide a more accurate, less burdensome alternative to existing tools. The first objective of this study was to compare participant burden for two technology-based measures of dietary intake among school-age children: the Automated-Self-Administered 24-hour Dietary Assessment Tool-2018 (ASA24-2018) and the Remote Food Photography Method (RFPM). The second objective was to compare reported energy intake for each method to the Estimated Energy Requirement for each child, as a benchmark for actual intake. Forty parent-child dyads participated in two, 3-d dietary assessments: a parent proxy-reported version of the ASA24 and the RFPM. A parent survey was subsequently administered to compare satisfaction, ease of use and burden with each method. A linear mixed model examined differences in total daily energy intake between assessments, and between each assessment method and the Estimated Energy Requirement (EER). Reported energy intake was 379 kcal higher with the ASA24 than the RFPM (P = 0·0002). Reported energy intake with the ASA24 was 231 kcal higher than the EER (P = 0·008). Reported energy intake with the RFPM did not differ significantly from the EER (difference in predicted means = -148 kcal, P = 0·09). Median satisfaction and ease of use scores were five out of six for both methods. A higher proportion of parents reported that the ASA24 was more time-consuming than the RFPM (74·4 % v. 25·6 %, P = 0·002). Utilisation of both methods is warranted given their high satisfaction among parents.

Adherence to index-based dietary patterns in childhood and BMI trajectory during the transition to adolescence: the EPOCH study.

BACKGROUND: In the United States, one in five adolescents are obese. Index-based dietary patterns are measures of the overall diet that have the potential to serve as valuable obesity risk stratification tools. However, little is known about the association between adherence to index-based dietary patterns in childhood and BMI during the transition from childhood to adolescence. OBJECTIVE: To prospectively examine the relationship between adherence to three index-based dietary patterns in childhood and BMI trajectory during the transition to adolescence. METHODS: The study included 581 children enrolled in a Colorado prospective cohort study conducted between 2006 and 2015. Dietary intake was assessed with the Block Kids Food Frequency Questionnaire at age 10 years. Scores were calculated for the Healthy Eating Index-2010 (HEI-2010), the alternate Mediterranean (aMED) diet, and the Dietary Approaches to Stop Hypertension (DASH) diet. Weight and height were assessed via anthropometry at two research visits (ages 10 and 16 years), with interim clinical measurements extracted from Kaiser Permanente medical records. Separate mixed models were used to assess the association between each diet index score and BMI over a 6-year period. Models were stratified by sex and adjusted for age, race/ethnicity, income, and exposure to gestational diabetes. RESULTS: Median (IQR) number of BMI assessments was 14 (10-18). Among girls, for every ten-unit increase in HEI-2010 score, there was an average 0.64 kg/m2 decrease (p = 0.007) in BMI over time, after adjustment for covariates. Among girls, there was no association between BMI and aMED (ß = -0.19, p = 0.24) or DASH (ß = 0.28, p = 0.38). Among boys, there was no statistically significant association between BMI and HEI-2010 (0.06, p = 0.83), aMED (0.07, p = 0.70), or DASH (0.42, p = 0.06). CONCLUSIONS: Efforts to prevent adolescent obesity could benefit from considering the degree of adherence to federal dietary guidance, as assessed by the HEI, in the period preceding adolescence, especially among girls.

Persistent effects of in utero overnutrition on offspring adiposity: the Exploring Perinatal Outcomes among Children (EPOCH) study.

AIMS/HYPOTHESIS: We previously showed that intrauterine exposure to gestational diabetes mellitus (GDM) increases selected markers of adiposity in pre-pubertal adolescents. In the present study, we examined these associations in adolescence, and explored whether they are strengthened as the participants transition through puberty. METHODS: Data from 597 individuals (505 unexposed, 92 exposed) participating in the longitudinal Exploring Perinatal Outcomes among Children (EPOCH) study in Colorado were collected at two research visits when the participants were, on average, 10.4 and 16.7 years old. Adiposity measures included BMI, waist/height ratio, and visceral and subcutaneous adipose tissue (as determined by MRI). Separate general linear mixed models were used to assess the longitudinal relationships between exposure to maternal GDM and each adiposity outcome. We tested whether the effect changed over time by including an interaction term between exposure and age in our models, and whether the associations were explained by postnatal behaviours. RESULTS: Compared with unexposed participants, those exposed to maternal GDM had higher BMI (ß = 1.28; 95% CI 0.35, 2.21; p < 0.007), waist/height ratio (ß = 0.03; 95% CI 0.01, 0.04; p = 0.0004), visceral adipose tissue (ß = 4.81; 95% CI 1.08, 8.54; p = 0.01) and subcutaneous adipose tissue (ß = 35.15; 95% CI 12.43, 57.87; p < 0.003). The magnitude of these differences did not change over time and the associations did not appear to be explained by postnatal behaviours. CONCLUSIONS/INTERPRETATION: Our data provide further evidence that intrauterine exposure to maternal GDM is associated with increased offspring adiposity, an effect that appears early in life and tracks throughout adolescence. Efforts to prevent childhood obesity following intrauterine exposure to maternal GDM should target the prenatal or early life periods.

Childhood adiposity and adolescent sex steroids in the Exploring Perinatal Outcomes among Children study.

OBJECTIVE: It is unclear how childhood adipose tissue deposition influences sex hormone profiles in later adolescence. DESIGN: Prospective cohort study. PARTICIPANTS: Children (n = 418) with a mean age of 10.5 (1.5) years at visit 1 and 16.7 (1.2) at visit 2 in the Exploring Perinatal Outcomes among Children (EPOCH) Study. MEASUREMENTS: We used reverse-scale Cox proportional hazard models to assess associations between pubertal dehydroepiandrosterone (DHEA), testosterone (T), and oestradiol (E2) and childhood-to-puberty rate of change in visceral (VAT) and subcutaneous adipose tissue (SAT). Models stratified by sex and adjusted for childhood adiposity, maternal factors, birthweight and pubertal onset, and then further adjusted for insulin, luteinizing hormone (LH), leptin and hepatic fat fraction. RESULTS: Among boys, more rapid accumulation of either VAT or SAT was associated with lower testosterone at visit 2 (HR 0.86, and .96, respectively, both P < .0001), independently of race/ethnicity, LH, leptin and hepatic fat fraction. Among boys, more childhood VAT was associated with lower testosterone in adolescence (HR 0.98, P = .003), but this association did not persist after adjustment for leptin or insulin. No associations were observed between either fat measure and oestradiol or DHEA in boys. In girls, no associations between childhood fat or fat accumulation and sex hormones were observed. CONCLUSIONS: More rapid accumulation of fat is associated with lower testosterone in boys. These associations suggest that fat growth influences androgen profiles in adolescent boys. Since fat accumulation is a modifiable risk factor, the study results provide a possible intervention target and time period for improving adult health.

Uncovering the liver's role in immunity through RNA co-expression networks.

Gene co-expression analysis has proven to be a powerful tool for ascertaining the organization of gene products into networks that are important for organ function. An organ, such as the liver, engages in a multitude of functions important for the survival of humans, rats, and other animals; these liver functions include energy metabolism, metabolism of xenobiotics, immune system function, and hormonal homeostasis. With the availability of organ-specific transcriptomes, we can now examine the role of RNA transcripts (both protein-coding and non-coding) in these functions. A systems genetic approach for identifying and characterizing liver gene networks within a recombinant inbred panel of rats was used to identify genetically regulated transcriptional networks (modules). For these modules, biological consensus was found between functional enrichment analysis and publicly available phenotypic quantitative trait loci (QTL). In particular, the biological function of two liver modules could be linked to immune response. The eigengene QTLs for these co-expression modules were located at genomic regions coincident with highly significant phenotypic QTLs; these phenotypes were related to rheumatoid arthritis, food preference, and basal corticosterone levels in rats. Our analysis illustrates that genetically and biologically driven RNA-based networks, such as the ones identified as part of this research, provide insight into the genetic influences on organ functions. These networks can pinpoint phenotypes that manifest through the interaction of many organs/tissues and can identify unannotated or under-annotated RNA transcripts that play a role in these phenotypes.

Epigenetic age acceleration is associated with speed of pubertal growth but not age of pubertal onset.

Using data from a longitudinal cohort of children, we examined whether epigenetic age acceleration (EAA) was associated with pubertal growth and whether these associations were mediated by adiposity. We examined associations between EAA at approximately 10 years of age with pubertal growth metrics, including age at peak height velocity (PHV), PHV, and sex steroid levels and whether these associations were mediated by measures of adiposity including body mass index (BMI) and MRI-assessed visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT). Children (n = 135) with accelerated EAA had higher PHV (ß 0.018, p = 0.0008) although the effect size was small. The association between EAA and age at PHV was not significant (ß - 0.0022, p = 0.067). Although EAA was associated with higher BMI (ß 0.16, p = 0.0041), VAT (ß 0.50, p = 0.037), and SAT (ß 3.47, p = 0.0076), BMI and VAT did not mediate associations between EAA and PHV, while SAT explained 8.4% of the association. Boys with higher EAA had lower total testosterone (ß - 12.03, p = 0.0014), but associations between EAA and other sex steroids were not significant, and EAA was not associated with sex steroid levels in girls. We conclude that EAA did not have strong associations with either age at onset of puberty or pubertal growth speed, although associations with growth speed were statistically significant. Studies with larger sample sizes are needed to confirm this pattern of associations.

Associations of infant feeding practices with abdominal and hepatic fat measures in childhood in the longitudinal Healthy Start Study.

BACKGROUND: Infant feeding patterns have been linked with obesity risk in childhood, but associations with precise measures of body fat distribution are unclear. OBJECTIVE: We examined associations of infant feeding practices with abdominal fat and hepatic fat trajectories in childhood. METHODS: This study included 356 children in the Healthy Start Study, a prospective prebirth cohort in Colorado. Infant feeding practices were assessed by postnatal interviews and categorized as any human milk <6 mo compared with ≥6 mo; complementary foods introduced ≤4 mo compared with >4 mo; soda introduced ≤18 mo compared with >18 mo. Abdominal subcutaneous (SAT) and visceral adipose tissue (VAT) areas and hepatic fat (%) were assessed by magnetic resonance imaging in early and middle childhood (median 5 and 9 y old, respectively). We examined associations of infant feeding with adiposity trajectories across childhood using linear mixed models. RESULTS: In the sample of children, 67% consumed human milk ≥6 mo, 75% were introduced to complementary foods at >4 mo, and 81% were introduced to soda at >18 mo. We did not find any associations between duration of any human milk consumption and childhood adiposity trajectories. Early introduction to complementary foods (≤4 mo) was associated with faster rates of change for SAT and VAT during childhood (Slope [95% CI]: 15.1 [10.7,19.4] cm2/y for SAT; 2.5 [1.9,2.9] cm2/y for VAT), compared with introduction at >4 mo (5.5 [3.0,8.0] cm2/y and 1.6 [1.3,1.9] cm2/y, respectively). Similarly, early introduction to soda (≤18 mo) was associated with faster rates of change for all 3 outcomes during childhood (Slope [95% CI]: 20.6 [15.0,26.1] cm2/y for SAT, 2.7 [2.0,3.3] cm2/y for VAT, 0.3 [0.1,0.5] %/year for hepatic fat) compared with delayed introduction (5.4 [2.8,8.0] cm2/y, 1.7 [1.3, 2.0] cm2/y, -0.1 [-0.2,0.0] %/y, respectively). CONCLUSIONS: The timing of introduction and quality of complementary foods in infancy was associated with rates of abdominal and hepatic fat accrual during childhood. Experimental studies are needed to assess underlying mechanisms.

The predictive utility of the in utero exposome for childhood adiposity in independent and integrated frameworks.

OBJECTIVES: To assess the predictive potential of the in utero exposome in relation to childhood adiposity as indicated by body mass index z-scores (BMIz) and the fourth versus first quartile of % fat mass (FM) at median age of 4.6 years. METHODS: We leveraged data on clinical risk factors for childhood obesity during the perinatal period, along with cord blood per/polyfluoroalkyl substances (PFAS) and cord blood DNA methylation, in 268 mother-offspring pairs. We used the sparsity ranked LASSO penalized regression framework for each outcome and assessed model performance based on % variability explained for BMIz and area under the receiver operating characteristic curve (AUC) for the fourth versus first quartile of %FM. We employed cross-validation for model tuning and split-sample validation for model evaluation. RESULTS: Mean ± SD BMIz was 0.01 ± 1.1, %FM was 19.8 ± 6.34%. The optimal model for predicting BMIz explained 19.1% of the variability in the validation set and included only clinical characteristics: maternal pre-pregnancy BMI, paternal BMI, gestational weight gain, physical activity during pregnancy and child race/ethnicity. The optimal model for fourth versus first quartiles of %FM achieved an AUC of 0.82 ± 0.01 in the validation set, with the clinical features again emerging as the strongest predictors. CONCLUSION: In this study sample, perinatal chemical exposures and the epigenome have low utility in predicting childhood adiposity, beyond known clinical risk factors.

A better performing algorithm for identification of implausible growth data from longitudinal pediatric medical records.

Tracking trajectories of body size in children provides insight into chronic disease risk. One measure of pediatric body size is body mass index (BMI), a function of height and weight. Errors in measuring height or weight may lead to incorrect assessment of BMI. Yet childhood measures of height and weight extracted from electronic medical records often include values which seem biologically implausible in the context of a growth trajectory. Removing biologically implausible values reduces noise in the data, and thus increases the ease of modeling associations between exposures and childhood BMI trajectories, or between childhood BMI trajectories and subsequent health conditions. We developed open-source algorithms (available on github) for detecting and removing biologically implausible values in pediatric trajectories of height and weight. A Monte Carlo simulation experiment compared the sensitivity, specificity and speed of our algorithms to three published algorithms. The comparator algorithms were selected because they used trajectory information, had open-source code, and had published verification studies. Simulation inputs were derived from longitudinal epidemiological cohorts. Our algorithms had higher specificity, with similar sensitivity and speed, when compared to the three published algorithms. The results suggest that our algorithms should be adopted for cleaning longitudinal pediatric growth data.

Serological profile of torque teno sus virus species 1 (TTSuV1) in pigs and antigenic relationships between two TTSuV1 genotypes (1a and 1b), between two species (TTSuV1 and -2), and between porcine and human anelloviruses.

The family Anelloviridae includes human and animal torque teno viruses (TTVs) with extensive genetic diversity. The antigenic diversity among anelloviruses has never been assessed. Using torque teno sus virus (TTSuV) as a model, we describe here the first investigation of the antigenic relationships among different anelloviruses. Using a TTSuV genotype 1a (TTSuV1a) or TTSuV1b enzyme-linked immunosorbent assay (ELISA) based on the respective putative ORF1 capsid antigen and TTSuV1-specific real-time PCR, the combined serological and virological profile of TTSuV1 infection in pigs was determined and compared with that of TTSuV2. TTSuV1 is likely not associated with porcine circovirus-associated disease (PCVAD), because both the viral loads and antibody levels were not different between affected and unaffected pigs and because there was no synergistic effect of concurrent PCV2/TTSuV1 infections. We did observe a higher correlation of IgG antibody levels between anti-TTSuV1a and -TTSuV1b than between anti-TTSuV1a or -1b and anti-TTSuV2 antibodies in these sera, implying potential antigenic cross-reactivity. To confirm this, rabbit antisera against the putative capsid proteins of TTSuV1a, TTSuV1b, or TTSuV2 were generated, and the antigenic relationships among these TTSuVs were analyzed by an ELISA and by an immunofluorescence assay (IFA) using PK-15 cells transfected with one of the three TTSuV ORF1 constructs. The results demonstrate antigenic cross-reactivity between the two genotypes TTSuV1a and TTSuV1b but not between the two species TTSuV1a or -1b and TTSuV2. Furthermore, an anti-genogroup 1 human TTV antiserum did not react with any of the three TTSuV antigens. These results have important implications for an understanding of the diversity of anelloviruses as well as for the classification and vaccine development of TTSuVs.

Rescue of a porcine anellovirus (torque teno sus virus 2) from cloned genomic DNA in pigs.

Anelloviruses are a group of single-stranded circular DNA viruses infecting humans and other animal species. Animal models combined with reverse genetic systems of anellovirus have not been developed. We report here the construction and initial characterization of full-length DNA clones of a porcine anellovirus, torque teno sus virus 2 (TTSuV2), in vitro and in vivo. We first demonstrated that five cell lines, including PK-15 cells, are free of TTSuV1 or TTSuV2 contamination, as determined by a real-time PCR and an immunofluorescence assay (IFA) using anti-TTSuV antibodies. Recombinant plasmids harboring monomeric or tandem-dimerized genomic DNA of TTSuV2 from the United States and Germany were constructed. Circular TTSuV2 genomic DNA with or without introduced genetic markers and tandem-dimerized TTSuV2 plasmids were transfected into PK-15 cells, respectively. Splicing of viral mRNAs was identified in transfected cells. Expression of TTSuV2-specific open reading frame 1 (ORF1) in cell nuclei, especially in nucleoli, was detected by IFA. However, evidence of productive TTSuV2 infection was not observed in 12 different cell lines transfected with the TTSuV2 DNA clones. Transfection with circular DNA from a TTSuV2 deletion mutant did not produce ORF1 protein, suggesting that the observed ORF1 expression is driven by TTSuV2 DNA replication in cells. Pigs inoculated with either the tandem-dimerized clones or circular genomic DNA of U.S. TTSuV2 developed viremia, and the introduced genetic markers were retained in viral DNA recovered from the sera of infected pigs. The availability of an infectious DNA clone of TTSuV2 will facilitate future study of porcine anellovirus pathogenesis and biology.

Exposure to Gestational Diabetes and BMI Trajectories Through Adolescence: The Exploring Perinatal Outcomes Among Children Study.

CONTEXT: Previous studies have shown that exposure to maternal gestational diabetes mellitus (GDM) is associated with increased offspring body mass index (BMI) and risk for overweight or obesity. OBJECTIVE: This study aimed to explore differences in BMI trajectories among youth exposed or not exposed to maternal GDM and understand whether these associations differ across life stages. METHODS: Data from 403 mother/child dyads (76 exposed; 327 not exposed) participating in the longitudinal Exploring Perinatal Outcomes among Children (EPOCH) study in Colorado were used. Participants who had 2 or more longitudinal height measurements from 27 months to a maximum of 19 years were included in the analysis. Life stages were defined using puberty related timepoints: early childhood (27 months to pre-adolescent dip [PAD, average age 5.5 years]), middle childhood (from PAD to age at peak height velocity [APHV, average age 12.2 years]), and adolescence (from APHV to 19 years). Separate general linear mixed models, stratified by life stage, were used to assess associations between GDM exposure and offspring BMI. RESULTS: There was not a significant association between exposure to GDM and BMI trajectories during early childhood (P = .27). In middle childhood, participants exposed to GDM had higher BMI trajectories compared to those not exposed (males: P = .005, females: P = .002) and adolescent (P = .02) periods. CONCLUSION: Our study indicates that children who are exposed to GDM may experience higher BMI trajectories during middle childhood and adolescence, but not during early childhood. These data suggest that efforts to prevent childhood obesity among those exposed in utero to maternal GDM should start before pubertal onset.

Infant effortful control predicts BMI trajectories from infancy to adolescence.

BACKGROUND: Effortful control, or the regulation of thoughts and behaviour, is a potential target for preventing childhood obesity. OBJECTIVES: To assess effortful control in infancy through late childhood as a predictor of repeated measures of body mass index (BMI) from infancy through adolescence, and to examine whether sex moderates the associations. METHODS: Maternal report of offspring effortful control and measurements of child BMI were obtained at 7 and 8 time points respectively from 191 gestational parent/child dyads from infancy through adolescence. General linear mixed models were used. RESULTS: Effortful control at 6 months predicted BMI trajectories from infancy through adolescence, F(5,338) = 2.75, p = 0.03. Further, when effortful control at other timepoints were included in the model, they added no additional explanatory value. Sex moderated the association between 6-month effortful control and BMI, F(4, 338) = 2.59, p = 0.03, with poorer infant effortful control predicting higher BMI in early childhood for girls, and more rapid increases in BMI in early adolescence for boys. CONCLUSIONS: Effortful control in infancy was associated with BMI over time. Specifically, poor effortful control during infancy was associated with higher BMI in childhood and adolescence. These findings support the argument that infancy may be a sensitive window for the development of later obesity.

Effects of a community gardening intervention on diet, physical activity, and anthropometry outcomes in the USA (CAPS): an observer-blind, randomised controlled trial.

BACKGROUND: Unhealthy diet, physical inactivity, and social disconnection are important modifiable risk factors for non-communicable and other chronic diseases, which might be alleviated through nature-based community interventions. We tested whether a community gardening intervention could reduce these common health risks in an adult population that is diverse in terms of age, ethnicity, and socioeconomic status. METHODS: In this observer-blind, randomised, controlled trial, we recruited individuals who were on Denver Urban Garden waiting lists for community gardens in Denver and Aurora (CO, USA), aged 18 years or older, and had not gardened in the past 2 years. Participants were randomly assigned (1:1), using a randomised block design in block sizes of two, four, or six, to receive a community garden plot (intervention group) or remain on a waiting list and not garden (control group). Researchers were masked to group allocation. Primary outcomes were diet, physical activity, and anthropometry; secondary outcomes were perceived stress and anxiety. During spring (April to early June, before randomisation; timepoint 1 [T1]), autumn (late August to October; timepoint 2 [T2]), and winter (January to March, after the intervention; timepoint 3 [T3]), participants completed three diet recalls, 7-day accelerometry, surveys, and anthropometry. Analyses were done using the intention-to-treat principle (ie, including all participants randomly assigned to groups, and assessed as randomised). We used mixed models to test time-by-intervention hypotheses at an α level of 0·04, with T2 and T3 intervention effects at an α level of 0·005 (99·5% CI). Due to potential effects of the COVID-19 pandemic on outcomes, we excluded all participant data collected after Feb 1, 2020. This study is registered with ClinicalTrials.gov, NCT03089177, and data collection is now complete. FINDINGS: Between Jan 1, 2017, and June 15, 2019, 493 adults were screened and 291 completed baseline measures and were randomly assigned to the intervention (n=145) or control (n=146) groups. Mean age was 41·5 years (SD 13·5), 238 (82%) of 291 participants were female, 52 (18%) were male, 99 (34%) identified as Hispanic, and 191 (66%) identified as non-Hispanic. 237 (81%) completed measurements before the beginning of the COVID-19 pandemic. One (<1%) participant in the intervention group had an adverse allergic event in the garden. Significant time-by-intervention effects were observed for fibre intake (p=0·034), with mean between-group difference (intervention minus control) at T2 of 1·41 g per day (99·5% CI -2·09 to 4·92), and for moderate-to-vigorous physical activity (p=0·012), with mean between-group difference of 5·80 min per day (99·5% CI -4·44 to 16·05). We found no significant time-by-intervention interactions for combined fruit and vegetable intake, Healthy Eating Index (measured using Healthy Eating Index-2010), sedentary time, BMI, and waist circumference (all p>0·04). Difference score models showed greater reductions between T1 and T2 in perceived stress and anxiety among participants in the intervention group than among those in the control group. INTERPRETATION: Community gardening can provide a nature-based solution, accessible to a diverse population including new gardeners, to improve wellbeing and important behavioural risk factors for non-communicable and chronic diseases. FUNDING: American Cancer Society, University of Colorado Cancer Centre, University of Colorado Boulder, National Institutes of Health, US Department of Agriculture National Institute of Food and Agriculture, Michigan AgBioResearch Hatch projects.

Association of Maternal BMI and Rapid Infant Weight Gain With Childhood Body Size and Composition.

OBJECTIVES: Maternal prepregnancy BMI (ppBMI) and an infant's rapid weight gain (RWG) are each associated with increased risk for childhood obesity. We hypothesized that ppBMI and RWG interact to further raise childhood obesity risk. METHODS: Mother-infant dyads (n = 414) from the Healthy Start Study, an observational prebirth cohort, were included. RWG was defined as a weight-for-age z score increase of ≥0.67 from birth to 3 to 7 months. Body composition was measured by air displacement plethysmography at age 4 to 7 years. General linear regression models were fit to characterize associations between ppBMI, RWG, and their interaction with the outcomes of childhood BMI-for-age z score and percent fat mass (%FM). RESULTS: A total of 18.6% (n = 77) of offspring experienced RWG. Maternal ppBMI and RWG were both positively associated with offspring BMI z score and %FM. RWG amplified the association between ppBMI and BMI z score, especially among females. Females exposed to maternal obesity and RWG had an average BMI at the 94th percentile (1.50 increase in childhood BMI z score) compared with those exposed to normal ppBMI and no RWG (average childhood BMI at the 51st percentile). RWG had a weaker effect on the association between ppBMI and %FM. Adjustment for breastfeeding status or childhood daily caloric intake did not significantly alter findings. CONCLUSIONS: Rapid infant weight gain interacts with maternal ppBMI to jointly exacerbate risk of childhood obesity. Pediatric providers should monitor infants for RWG, especially in the context of maternal obesity, to reduce future risk of obesity.