Aims: The heterogeneity in Gestational Diabetes Mellitus (GDM) risk factors among different populations impose challenges in developing a generic prediction model. This study evaluates the predictive ability of existing UK NICE guidelines for assessing GDM risk in Singaporean women, and used machine learning to develop a non-invasive predictive model. Methods: Data from 909 pregnancies in Singapore's most deeply phenotyped mother-offspring cohort study, Growing Up in Singapore Towards healthy Outcomes (GUSTO), was used for predictive modeling. We used a CatBoost gradient boosting algorithm, and the Shapley feature attribution framework for model building and interpretation of GDM risk attributes. Results: UK NICE guidelines showed poor predictability in Singaporean women [AUC:0.60 (95% CI 0.51, 0.70)]. The non-invasive predictive model comprising of 4 non-invasive factors: mean arterial blood pressure in first trimester, age, ethnicity and previous history of GDM, greatly outperformed [AUC:0.82 (95% CI 0.71, 0.93)] the UK NICE guidelines. Conclusions: The UK NICE guidelines may be insufficient to assess GDM risk in Asian women. Our non-invasive predictive model outperforms the current state-of-the-art machine learning models to predict GDM, is easily accessible and can be an effective approach to minimize the economic burden of universal testing & GDM associated healthcare in Asian populations.

Background The increasing prevalence of gestational diabetes mellitus (GDM) is concerning as women with GDM are at high risk of type 2 diabetes (T2D) later in life. The magnitude of this risk highlights the importance of early intervention to prevent the progression of GDM to T2D. Rates of postpartum screening are suboptimal, often as low as 13% in Asian countries. The lack of preventive care through structured postpartum screening in several health care systems and low public awareness are key barriers to postpartum diabetes screening. Objective In this study, we developed a machine learning model for early prediction of postpartum T2D following routine antenatal GDM screening. The early prediction of postpartum T2D during prenatal care would enable the implementation of effective strategies for diabetes prevention interventions. To our best knowledge, this is the first study that uses machine learning for postpartum T2D risk assessment in antenatal populations of Asian origin. Methods Prospective multiethnic data (Chinese, Malay, and Indian ethnicities) from 561 pregnancies in Singapore’s most deeply phenotyped mother-offspring cohort study—Growing Up in Singapore Towards healthy Outcomes—were used for predictive modeling. The feature variables included were demographics, medical or obstetric history, physical measures, lifestyle information, and GDM diagnosis. Shapley values were combined with CatBoost tree ensembles to perform feature selection. Our game theoretical approach for predictive analytics enables population subtyping and pattern discovery for data-driven precision care. The predictive models were trained using 4 machine learning algorithms: logistic regression, support vector machine, CatBoost gradient boosting, and artificial neural network. We used 5-fold stratified cross-validation to preserve the same proportion of T2D cases in each fold. Grid search pipelines were built to evaluate the best performing hyperparameters. Results A high performance prediction model for postpartum T2D comprising of 2 midgestation features—midpregnancy BMI after gestational weight gain and diagnosis of GDM—was developed (BMI_GDM CatBoost model: AUC=0.86, 95% CI 0.72-0.99). Prepregnancy BMI alone was inadequate in predicting postpartum T2D risk (ppBMI CatBoost model: AUC=0.62, 95% CI 0.39-0.86). A 2-hour postprandial glucose test (BMI_2hour CatBoost model: AUC=0.86, 95% CI 0.76-0.96) showed a stronger postpartum T2D risk prediction effect compared to fasting glucose test (BMI_Fasting CatBoost model: AUC=0.76, 95% CI 0.61-0.91). The BMI_GDM model was also robust when using a modified 2-point International Association of the Diabetes and Pregnancy Study Groups (IADPSG) 2018 criteria for GDM diagnosis (BMI_GDM2 CatBoost model: AUC=0.84, 95% CI 0.72-0.97). Total gestational weight gain was inversely associated with postpartum T2D outcome, independent of prepregnancy BMI and diagnosis of GDM (P=.02; OR 0.88, 95% CI 0.79-0.98). Conclusions Midgestation weight gain effects, combined with the metabolic derangements underlying GDM during pregnancy, signal future T2D risk in Singaporean women. Further studies will be required to examine the influence of metabolic adaptations in pregnancy on postpartum maternal metabolic health outcomes. The state-of-the-art machine learning model can be leveraged as a rapid risk stratification tool during prenatal care. Trial Registration ClinicalTrials.gov NCT01174875; https://clinicaltrials.gov/ct2/show/NCT01174875

We examined the associations of gestational diabetes mellitus (GDM) and women’s weight status from pre-pregnancy through post-delivery with the risk of developing dysglycaemia [impaired fasting glucose, impaired glucose tolerance, and type 2 diabetes (T2D)] 4–6 years post-delivery. Using Poisson regression with confounder adjustments, we assessed associations of standard categorisations of prospectively ascertained pre-pregnancy overweight and obesity (OWOB), gestational weight gain (GWG) and substantial post-delivery weight retention (PDWR) with post-delivery dysglycaemia ( n = 692). Women with GDM had a higher risk of later T2D [relative risk (95% CI) 12.07 (4.55, 32.02)] and dysglycaemia [3.02 (2.19, 4.16)] compared with non-GDM women. Independent of GDM, women with pre-pregnancy OWOB also had a higher risk of post-delivery dysglycaemia. Women with GDM who were OWOB pre-pregnancy and had subsequent PDWR (≥ 5 kg) had 2.38 times (1.29, 4.41) the risk of post-delivery dysglycaemia compared with pre-pregnancy lean GDM women without PDWR. No consistent associations were observed between GWG and later dysglycaemia risk. In conclusion, women with GDM have a higher risk of T2D 4–6 years after the index pregnancy. Pre-pregnancy OWOB and PDWR exacerbate the risk of post-delivery dysglycaemia. Weight management during preconception and post-delivery represent early windows of opportunity for improving long-term health, especially in those with GDM.

Aims: To explore the glucose-overload hypothesis of artefactual gestational diabetes (GDM) diagnosis in shorter women during oral glucose tolerance testing (OGTT), by investigating associations between height and maternal glycemia; and GDM and pregnancy complications in height-groups. Methods: Women from GUSTO (n = 1100, 2009-2010) and NUH (n = 4068, 2017-2018) cohorts underwent a mid-gestation two and three time-point 75 g 2-hour OGTT, respectively. GDMrelated complications (hypertensive disorders of pregnancy, preterm delivery, emergency cesarean section, neonatal intensive care unit admission, macrosomia, birthweight) were compared within shorter and taller groups, dichotomized by ethnic-specific median height. Results: Using WHO-1999 criteria, 18.8% (GUSTO) to 22.9% (NUH) of women were diagnosed with GDM-1999; and by WHO-2013 criteria, 21.9% (NUH) had GDM-2013. Each 5-cm height increment was inversely associated with GDM-1999 (adjusted odds ratio [aOR, 95% CI] = 0.81 [0.76-0.87], 2-h glycemia (adjusted 13 [a13, 95% CI] =-0.171 mmol/L [-0.208,-0.135]) and 1-h glycemia (a13 =-0.160 mmol/L [-0.207,-0.112]). The inverse association between height and 2-h glycemia was most marked in "Other" ethnicities (Eurasians/Cau casians/mixed/other Asians) and Indians, followed by Chinese, then Malays. Compared with non-GDM, GDM-1999 was associated with preterm delivery (aOR = 1.76 [1.19-2.61]) and higher birthweight (a13 = 57.16 g [20.95, 93.38]) only among taller but not shorter women. Conclusions: Only taller women had an increased odds of GDM-related pregnancy complica- tions. An artefactual GDM diagnosis due to glucose-overload among shorter women is plausible. (c) 2021 Elsevier B.V. All rights reserved.

Background Nausea and vomiting of pregnancy (NVP) is common and underlying mechanisms are poorly understood. Longer-term offspring outcomes are also not well documented. This study aimed to determine if NVP, even in milder forms, is associated with adverse pregnancy and childhood growth outcomes. Methods In the GUSTO prospective mother-offspring cohort, women with singleton pregnancies ( n = 1172) recruited in first trimester responded to interviewer-administered questions at 26–28 weeks’ gestation about earlier episodes of NVP since becoming pregnant. Pregnancy outcomes were obtained from medical records. Offspring height and weight measured at 15 time-points between birth to 72 months (m) were standardised for age and sex. Results 58.5% ( n = 686) reported mild-moderate vomiting (mNVP), 10.5% ( n = 123) severe vomiting (sNVP) and 5.7% ( n = 67) severe vomiting with hospitalisation (shNVP). There was no difference in odds of gestational diabetes, hypertensive disorders of pregnancy, labour induction or caesarean section after adjustment for covariates. sNVP was associated with late preterm delivery [34 + 0 –36 + 6 weeks’, adjusted OR = 3.04 (95% CI 1.39,6.68)], without increased odds of neonatal unit admission. Compared with no NVP, boys born to mothers with sNVP were longer at birth [adjusted β = 0.38 standard deviations (SDs) (95% CI 0.02,0.73)], remained taller [0.64 SDs (0.23,1.04) at 72 m] and heavier [0.57 SDs (0.05,1.08) at 60 m] without differences in BMI. Conversely, girls born to mothers with shNVP were lighter from 48 m [− 0.52 SDs (− 1.00, − 0.03)] onwards with lower BMI [− 0.61 SDs (− 1.12,-0.09)]. Conditional growth modelling revealed significant sex-divergence in weight-gain at birth-3 m, 6-9 m and 4–5 years. Conclusions Severe NVP was associated with late preterm delivery, and both mild-moderate and severe NVP associated with sex-dependent differences in early childhood growth. Boys whose mothers had NVP were taller and heavier from birth with faster growth in the first year, whereas, girls had poorer weight gain and were lighter by 48 m. As even milder severities of NVP could have long-term impact on offspring growth, further research is needed to determine mechanisms involved and implications on future health. Trial registration Clinicaltrials.gov identifier NCT01174875 .

(1) Background: Breastfeeding has been shown to support glucose homeostasis in women after a pregnancy complicated by gestational diabetes mellitus (GDM) and is potentially effective at reducing long-term diabetes risk. (2) Methods: Data from the Growing Up in Singapore Towards healthy Outcomes (GUSTO) study were analyzed to understand the influence of breastfeeding duration on long-term dysglycemia (prediabetes and diabetes) risk in women who had GDM in the index pregnancy. GDM and dysglycemia four to seven years postpartum were determined by the oral glucose tolerance test (OGTT). A Poisson regression model with a robust error variance was used to estimate incidence rate ratios (IRRs) for dysglycemia four to seven years post-delivery according to groupings of the duration of any breastfeeding (<1, ≥1 to <6, and ≥6 months). (3) Results: Women who had GDM during the index pregnancy and complete breastfeeding information and OGTT four to seven years postpartum were included in this study (n = 116). Fifty-one women (44%) had postpartum dysglycemia. Unadjusted IRRs showed an inverse association between dysglycemia risk and ≥1 month to <6 months (IRR 0.91; 95% confidence interval [CI] 0.57, 1.43; p = 0.68) and ≥6 months (IRR 0.50; 95% CI 0.27, 0.91; p = 0.02) breastfeeding compared to <1 month of any breastfeeding. After adjusting for key confounders, the IRR for the ≥6 months group remained significant (IRR 0.42; 95% CI 0.22, 0.80; p = 0.008). (4) Conclusions: Our results suggest that any breastfeeding of six months or longer may reduce long-term dysglycemia risk in women with a history of GDM in an Asian setting. Breastfeeding has benefits for mothers beyond weight loss, particularly for those with GDM.

Background Gestational diabetes mellitus (GDM) has been associated with adverse health outcomes for mothers and offspring. Prevalence of GDM differs by country/region due to ethnicity, lifestyle and diagnostic criteria. We compared GDM rates and risk factors in two Asian cohorts using the 1999 WHO and the International Association of Diabetes and Pregnancy Study Groups (IADPSG) criteria. Methods The Shanghai Birth Cohort (SBC) and the Growing Up in Singapore Towards healthy Outcomes (GUSTO) cohort are prospective birth cohorts. Information on sociodemographic characteristics and medical history were collected from interviewer-administered questionnaires. Participants underwent a 2-h 75-g oral glucose tolerance test at 24–28 weeks gestation. Logistic regressions were performed. Results Using the 1999 WHO criteria, the prevalence of GDM was higher in GUSTO (20.8%) compared to SBC (16.6%) ( p = 0.046). Family history of hypertension and alcohol consumption were associated with higher odds of GDM in SBC than in GUSTO cohort while obesity was associated with higher odds of GDM in GUSTO. Using the IADPSG criteria, the prevalence of GDM was 14.3% in SBC versus 12.0% in GUSTO. A history of GDM was associated with higher odds of GDM in GUSTO than in SBC, while being overweight, alcohol consumption and family history of diabetes were associated with higher odds of GDM in SBC. Conclusions We observed several differential risk factors of GDM among ethnic Chinese women living in Shanghai and Singapore. These findings might be due to heterogeneity of GDM reflected in diagnostic criteria as well as in unmeasured genetic, lifestyle and environmental factors.

The Singapore Preconception Study of Long-Term Maternal and Child Outcomes (S-PRESTO) is a preconception, longitudinal cohort study that aims to study the effects of nutrition, lifestyle, and maternal mood prior to and during pregnancy on the epigenome of the offspring and clinically important outcomes including duration of gestation, fetal growth, metabolic and neural phenotypes in the offspring. Between February 2015 and October 2017, the S-PRESTO study recruited 1039 Chinese, Malay or Indian (or any combinations thereof) women aged 18-45 years and who intended to get pregnant and deliver in Singapore, resulting in 1032 unique participants and 373 children born in the cohort. The participants were followed up for 3 visits during the preconception phase and censored at 12 months of follow up if pregnancy was not achieved (N = 557 censored). Women who successfully conceived (N = 475) were characterised at gestational weeks 6-8, 11-13, 18-21, 24-26, 27-28 and 34-36. Follow up of their index offspring (N = 373 singletons) is on-going at birth, 1, 3 and 6 weeks, 3, 6, 12, 18, 24 and 36 months and beyond. Women are also being followed up post-delivery. Data is collected via interviewer-administered questionnaires, metabolic imaging (magnetic resonance imaging), standardized anthropometric measurements and collection of diverse specimens, i.e. blood, urine, buccal smear, stool, skin tapes, epithelial swabs at numerous timepoints. S-PRESTO has extensive repeated data collected which include genetic and epigenetic sampling from preconception which is unique in mother-offspring epidemiological cohorts. This enables prospective assessment of a wide array of potential determinants of future health outcomes in women from preconception to post-delivery and in their offspring across the earliest development from embryonic stages into early childhood. In addition, the S-PRESTO study draws from the three major Asian ethnic groups that represent 50% of the global population, increasing the relevance of its findings to global efforts to address non-communicable diseases.

In animal studies early life antibiotic exposure causes metabolic abnormalities including obesity through microbiota disruption, but evidence from human studies is scarce. We examined involvement of gut microbiota in the associations between infant antibiotic exposure and childhood adiposity. Infant antibiotic exposure in the first year of life was ascertained using parental reports during interviewer-administered questionnaires. Primary outcomes were childhood obesity [body mass index (BMI) z-score > 95th percentile] and adiposity [abdominal circumference (AC) and skinfold (triceps + subscapular (SST)) measurements] determined from ages 15–60 months. At age 24 months, when the gut microbiota are more stable, stool samples (n = 392) were collected for the gut microbiota profiling using co-abundancy networks. Associations of antibiotic exposure with obesity and adiposity (n = 1016) were assessed using multiple logistic and linear mixed effects regressions. Key bacteria associated with antibiotics exposure were identified by partial redundancy analysis and multivariate association with linear models. Antibiotic exposure was reported in 38% of study infants. In a fully adjusted model, a higher odds of obesity from 15–60 months of age was observed for any antibiotic exposure [OR(95% CI) = 1.45(1.001, 2.14)] and exposure to ≥3 courses of antibiotics [2.78(1.12, 6.87)]. For continuous adiposity indicators, any antibiotic exposure was associated with higher BMI z-score in boys [β = 0.15(0.01, 0.28)] but not girls [β = −0.04(−0.19, 0.11)] (P interaction = 0.026). Similarly, exposure to ≥3 courses of antibiotics was associated with higher AC in boys [1.15(0.05, 2.26) cm] but not girls [0.57(−1.32, 2.45) cm] (P interaction not significant). Repeated exposure to antibiotics was associated with a significant reduction (FDR-corrected P values < 0.05) in a microbial co-abundant group (CAG) represented by Eubacterium hallii, whose proportion was negatively correlated with childhood adiposity. Meanwhile, a CAG represented by Tyzzerella 4 was positively correlated with the repeated use of antibiotics and childhood adiposity. Infant antibiotic exposure was associated with disruption of the gut microbiota and the higher risks of childhood obesity and increased adiposity.

BACKGROUND Gestational diabetes is associated with unfavorable body fat distribution in offspring. However, less is known about the effects across the range of maternal gestational glycemia on offspring abdominal adiposity (AA) in infancy and early childhood. OBJECTIVES This study determined the association between gestational glycemia and offspring AA measured by MRI in the neonatal period and during the preschool years. METHODS Participants were mother-offspring pairs from the GUSTO (Growing Up in Singapore Towards healthy Outcomes) prospective cohort study. Children who underwent MRI within 2 wk postdelivery (n = 305) and/or at preschool age, 4.5 y (n = 273), and whose mothers had a 2-h 75-g oral-glucose-tolerance test (OGTT) at 26-28 weeks of gestation were included. AA measured by adipose tissue compartment volumes-abdominal superficial (sSAT), deep subcutaneous (dSAT), and internal (IAT) adipose tissue-was quantified from MRI images. RESULTS Adjusting for potential confounders including maternal prepregnancy BMI, each 1-mmol/L increase in maternal fasting glucose was associated with higher SD scores for sSAT (0.66; 95% CI: 0.45, 0.86), dSAT (0.65; 95% CI: 0.44, 0.87), and IAT (0.64; 95% CI: 0.42, 0.86) in neonates. Similarly, each 1-mmol/L increase in 2-h OGTT glucose was associated with higher neonatal sSAT (0.11; 95% CI: 0.03, 0.19) and dSAT (0.09; 95% CI: 0.00, 0.17). These associations were stronger in female neonates but only persisted in girls between fasting glucose, and sSAT and dSAT at 4.5 y. CONCLUSIONS A positive association between maternal glycemia and neonatal AA was observed across the whole range of maternal mid-gestation glucose concentrations. These findings may lend further support to efforts toward optimizing maternal hyperglycemia during pregnancy. The study also provides suggestive evidence on sex differences in the impact of maternal glycemia, which merits further confirmation in other studies.This trial was registered at clinicaltrials.gov as NCT01174875.

Studies investigating timeliness for childhood vaccination are limited especially in Asia. We examined the timeliness of vaccine administration and associated factors among infant and young children in Singapore. A total of 782 children born between November 2009 and July 2011 from a prospective cohort in Singapore were studied. Vaccination records from birth to 24 months of age were obtained from the National Immunization Registry of Singapore. Multivariable logistic regression models were performed. By 2 years of age, 92.8% of children in our cohort experienced a delay in receiving 1 or more vaccine doses according to the recommended national immunization schedule. When vaccinations were reviewed by series for each vaccine, 15.6% received all vaccine series outside the recommended age ranges. Factors associated with receiving vaccination series outside the recommended ages included maternal aged ≤ 35 years (OR 2.00; 95% CI 1.09, 3.66), Malay (1.71; 1.01, 2.89) or Indian ethnicity (2.06; 1.19, 3.59), low monthly household income (1.91; 1.14, 3.18), having at least four children (3.46; 1.62, 7.38) and private (3.42; 1.80, 6.48) and multiple vaccination providers (3.91; 1.23, 12.48). These findings show an unacceptably high proportion of children experienced a delay in the receipt of their vaccinations. The identification of several demographic, socioeconomic, health-seeking behavioural and vaccine provider factors provides opportunities for targeted interventions to enhance the timeliness of childhood vaccination in Singapore.

To examine the associations of energy, macronutrient and food intakes with GWG on 960 pregnant women from the Growing Up in Singapore Towards healthy Outcomes (GUSTO) mother-offspring cohort.

Prenatal exposure to air pollution is associated with childhood respiratory health; however, no previous studies have examined maternal pre-pregnancy body mass index (BMI) as a potential effect modifier. We investigated whether maternal pre-pregnancy BMI modified the association of trimester-specific air pollution divided into quartiles of exposure (Q1⁻4) on respiratory health in the Growing Up in Singapore towards healthy Outcomes (GUSTO) study (n = 953) in 2-year-old children. For episodes of wheezing, children of overweight/obese mothers and who were exposed to particulate matter less than 2.5 μm (PM2.5) in the first trimester had an adjusted incidence rate ratio (IRR) (95% confidence interval (CI)) of 1.85 (1.23⁻2.78), 1.76 (1.08⁻2.85) and 1.90 (1.10⁻3.27) in quartile (Q) 2⁻4, with reference to Q1. This association is seen in the second trimester for bronchiolitis/bronchitis. The risk of ear infection in the first year of life was associated with exposure to PM2.5 in the first trimester with adjusted Odds Ratio (adjOR) (95% CI) = 7.64 (1.18⁻49.37), 11.37 (1.47⁻87.97) and 8.26 (1.13⁻60.29) for Q2⁻4, and similarly in the second year with adjOR (95% CI) = 3.28 (1.00⁻10.73) and 4.15 (1.05⁻16.36) for Q2⁻3. Prenatal exposure to air pollution has an enhanced impact on childhood respiratory health, and differs according to maternal pre-pregnancy BMI.

Background: In randomized trials, supplementation of n-3 (omega-3) long-chain polyunsaturated fatty acids (LC-PUFAs) during pregnancy has resulted in increased size at birth, which is attributable to longer gestation. Objective: We examined this finding by using a Mendelian randomization approach utilizing fatty acid desaturase (FADS) gene variants affecting LC-PUFA metabolism. Design: As part of a tri-ethnic mother-offspring cohort in Singapore, 35 genetic variants in FADS1, FADS2, and FADS3 were genotyped in 898 mothers and 1103 offspring. Maternal plasma n-3 and n-6 PUFA concentrations at 26-28 wk of gestation were measured. Gestation duration was derived from an ultrasound dating scan in early pregnancy and from birth date. Birth length and weight were measured. Eight FADS variants were selected through a tagging-SNP approach and examined in association with PUFA concentrations, gestation duration among spontaneous labors, and birth size with the use of ethnicity-adjusted linear regressions and survival models that accounted for the competing risks of induced and prelabor cesarean delivery. Results: Maternal FADS1 variant rs174546, tagging for 8 other variants located on FADS1 and FADS2, was strongly related to plasma n-6 but not n-3 LC-PUFA concentrations. Offspring and maternal FADS3 variants were associated with gestation duration among women who had spontaneous labor: each copy of rs174450 minor allele C was associated with a shorter gestation by 2.2 d (95% CI: 0.9, 3.4 d) and 1.9 d (0.7, 3.0 d) for maternal and offspring variants, respectively. In survival models, rs174450 minor allele homozygotes had reduced time to delivery after spontaneous labor compared with major allele homozygotes [HR (95% CI): 1.51 (1.18, 1.95) and 1.51 (1.20, 1.89) for mothers and offspring, respectively]. Conclusions: With the use of a Mendelian randomization approach, we observed associations between FADS variants and gestation duration. This suggests a potential role of LC-PUFAs in gestation duration.

The gut microbiome harbors antibiotic resistance genes (ARGs), known as the resistome, that has the potential to spread and contribute to the global crisis of antibacterial resistance. Little is known about the genomic traits of the infant resistome, especially in areas with high endemic antibacterial resistance. We analyzed ARGs among a subset of infants from the Growing Up in Singapore Towards Healthy Outcomes (GUSTO) birth cohort. The subset included 75 mostly term, healthy Singaporean infants born from November 2009 to May 2011. Stool samples collected at Week 3 (W3), months 3 (M3), 6 (M6) and 12 (M12) were analyzed using shotgun metagenomics. Sequencing reads were assembled into contigs using MEGAHIT. ARGs were identified using ResFinder 2.1. Demographic, perinatal factors, pre- and postnatal antibiotic exposure were collected. One hundred and eighty-eight stool samples from 75 infants were studied. Of the 169 ARGs detected, the four commonest ARGs were blaZ, fosA, tet(M) and mef(A), conferring resistance to β-lactams, fosfomycin, tetracyclines, and macrolides respectively. The number of ARGs per infant increased over time (median: W3 = 18.0, M12 = 22.0, P < 0.05). At W3, 118 ARGs were detected among 28 infants. The most prevalent ARGs were fos(A) and blaZ (both 96.4%) at W3. Among the 22 infants who had samples at W3 and M12, only six of 118 ARGs detected at W3 were also present at M12. These were mef(A), msr(D), tet(W), erm(B), tet(M) and fosA, conferring macrolide and tetracycline resistance. Their prevalence among at M12 was 100%, 93.3%, 90.9%, 84.6%, 68.8% and 52.4%, respectively. ARGs were not associated with gender, race, delivery mode, peripartum or postnatal antibiotics in infancy. Of note, longitudinal analysis showed that only the cfxA gene, which confers β-lactam resistance, was more prevalent in infants whose mothers received antibiotics in pregnancy than those whose mothers did not (adjusted P < 0.05). In regions with high endemic antimicrobial resistance such as Singapore, the infant gut harbors a diversity of ARGs as early as 3 weeks of age. Few ARGs persisted through infancy, implying the dynamic nature of the infant resistome. The lack of association of ARGs with most clinical variables evaluated here suggests that other unrecognized factors may contribute to the plasticity of ARGs in the infant gut resistome. R. Banerjee, Accelerate Diagnostics, Biomerieux, BioFire: Grant Investigator, Research grant and Research support.

The Growing Up in Singapore Towards Healthy Outcomes (GUSTO) cohort study was established in 2009 and recruited 1247 Chinese, Malay, and Indian families to precisely define the critical developmental pathways and mechanisms of the origins of obesity, metabolic disease, and neurodevelopmental disorders that have major public health and economic importance in Asia and globally, with the goal to develop precision medicine approaches (biomarkers and interventions) for families at risk of future noncommunicable diseases. Our studies have already had major academic and translational impact and attracted significant media attention and policymakers’ interest. Some examples of the translation of our science into public health activities are in the area of gestational diabetes mellitus, maternal emotional well-being, and preconception and antenatal nutritional intervention to develop better nutrition guidelines for prospective parents, pregnant women, infants, and children.

We assessed the impact of adopting the 2013 World Health Organization (WHO) diagnostic criteria on the rates of gestational diabetes (GDM), pregnancy outcomes and identification of women at future risk of type 2 diabetes.

7 ES P E Poster presented at: Early BMI Trajectory Classes are Linked to Distinct Body Fat Partitioning Later in Childhood Navin Michael1 , Ong Yi Ying5, Suresh Anand Sadananthan1, Izzuddin Iris15, Mya Thway Tint2, Yuan We Lun5, Pang Wei Wei2, Loy See Ling3,4, Shu-E Soh1, Lynette Pei-Chi Shek5, Fabian Kok Peng Yap4,6,7, Kok Hian Tan4,8, Keith M. Godfrey11 , Peter D. Gluckman1,12, Yap Seng Chong1,2, Neerja Karnani1, Michael S. Kramer2,9, Johan G. Eriksson2,10,Marielle Valerie Fortier1,13, S. Sendhil Velan1,14 and Yung Seng Lee1,5 1Singapore Institute for Clinical Sciences, A*STAR, Singapore. 2Department of Obstetrics & Gynaecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore. 3Department of Reproductive Medicine, KK Women’s and Children’s Hospital, Singapore. 4Duke-NUS Graduate Medical School, Singapore. 5Department of Paediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore. 6Department of Paediatric Endocrinology, KK Women’s and Children’s Hospital, Singapore. 7Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore. 8Department of Maternal Fetal Medicine, KK Women’s and Children’s Hospital, Singapore. 9Departments of Pediatrics and of Epidemiology, Biostatistics and Occupational Health, Faculty of Medicine, McGill University, Montreal, Canada. 10Department of General Practice and Primary Health Care, University of Helsinki, Finland. 11MRC Lifecourse Epidemiology Unit & NIHR Southampton Biomedical Research Centre, University of Southampton & University Hospital Southampton NHS Foundation Trust, Southampton, United Kingdom. 12Liggins Institute, University of Auckland, Auckland, New Zealand. 13Department of Diagnostic and Interventional Imaging, KK Women’s and Children’s Hospital, Singapore. 14Singapore BioImaging Consortium, Agency for Science Technology and Research, Singapore., 15Division of Chronic Disease Research Across the Lifecourse, Harvard Medical School and Harvard Pilgrim Health Care Institute (EO), Boston, USA Fat, metabolism and obesity 4: Poster NumberP2-P153