Gene, Environment and Methylation (GEM): a tool suite to efficiently navigate large scale epigenome wide association studies and integrate genotype and interaction between genotype and environment

10.1186/s12859-016-1161-zBMC bioinformatics171Article number 299GUSTO (Growing up towards Healthy Outcomes

ABC multidrug transporter Cdr1p of Candida albicans has divergent nucleotide-binding domains which display functional asymmetry

In order to ascertain the molecular basis of ATP-mediated drug extrusion by Cdr1p, a multidrug transporter of Candida albicans, we recently have reported that the Walker A motif of the N-terminal nucleotide biding domain (NBD) of this protein contains an uncommon cysteine residue (C193; GXXGXGC̲S/T) which is indispensable for ATP hydrolysis. This residue is exceptionally conserved in N-terminal NBDs of fungal ABC transporters and hence makes these transporters an evolutionarily divergent group. However, the presence of a conventional lysine residue at a similar position in the Walker A motif of the C-terminal NBD warrants the individual contribution of both the NBDs in the ATP-driven efflux function of such transporters. In this study we have investigated the contribution of this divergent Walker A motif in the context of the full Cdr1p protein under in vivo conditions by swapping these two crucial amino acids (C193K in Walker A motif of N-terminal NBD and K901C in Walker A motif of C-terminal NBD) between the two NBDs. Both the native and the mutant variants of Cdr1p were integrated at the PDR5 locus as GFP-tagged fusion proteins and were hyper-expressed. Our study shows that both C193K- and K901C-expressing cells elicit a severe impairment of Cdr1p's ATPase function. However, both these mutations have distinct phenotypes with respect to other functional parameters such as substrate efflux and drug resistance profiles. In contrast to C193K, K901C mutant cells were substantially hypersensitive to the tested drugs (fluconazole, ansiomycin, miconazole and cycloheximide) and were unable to expel rhodamine 6G. Our results for the first time show that both NBDs influence the Cdr1p function asymmetrically, and that the positioning of the cysteine and lysine residues within the respective Walker A motifs is functionally not interchangeable

Molecular cloning and functional characterisation of a glucose transporter, CaHGT1, of Candida albicans

We have cloned the first glucose transporter CaHGT1 (Candida albicanshigh-affinity glucose transporter) of a pathogenic yeast, Candida albicans. The DNA sequence (GenBank accession number Y16834) analysis revealed an ORF encoding a novel protein of 545 amino acids with a predicted molecular mass of 60.67 kDa. The putative protein with 12 transmembrane domains has 51% identity with Kluyveromyces lactis high-affinity glucose transporter, HGT1. The protein signatures which are conserved and distinctive of the sugar transporters belonging to the major facilitator superfamily (MFS) were also found in CaHgt1p. When heterologously expressed, the ORF functionally complemented a mutant strain of Saccharomyces cerevisiae RE700A which was deleted in seven hexose transporter genes and thus was unable to grow or transport glucose. The expression of CaHGT1 in C. albicans showed a transcript of 1.6 kb which was enhanced in response to the human steroid hormone progesterone. Interestingly, the transcript levels were also enhanced in the presence of drugs, e.g. cycloheximide, chloramphenicol and benomyl. The results suggest that CaHGT1, which encodes a MFS protein, could be linked to the drug resistance phenomenon in C. albicans

Variability in newborn telomere length is explained by inheritance and intrauterine environment

Background: Telomere length (TL) and its attrition are important indicators of physiological stress and biological aging and hence may vary among individuals of the same age. This variation is apparent even in newborns, suggesting potential effects of parental factors and the intrauterine environment on TL of the growing fetus. Methods: Average relative TLs of newborns (cord tissue, N = 950) and mothers (buffy coat collected at 26-28 weeks of gestation, N = 892) were measured in a birth cohort. This study provides a comprehensive analysis of the effects of heritable factors, socioeconomic status, and in utero exposures linked with maternal nutrition, cardiometabolic health, and mental well-being on the newborn TL. The association between maternal TL and antenatal maternal health was also studied. Results: Longer maternal TL (beta = 0.14, P = 1.99E-05) and higher paternal age (beta = 0.10, P = 3.73E-03) were positively associated with newborn TL. Genome-wide association studies on newborn and maternal TLs identified 6 genetic variants in a strong linkage disequilibrium on chromosome 3q26.2 (Tag SNP-LRRC34-rs10936600: P-meta = 5.95E-08). Mothers with higher anxiety scores, elevated fasting blood glucose, lower plasma insulin-like growth factor-binding protein 3 and vitamin B12 levels, and active smoking status during pregnancy showed a higher risk of giving birth to offspring with shorter TL. There were sex-related differences in the factors explaining newborn TL variation. Variation in female newborn TL was best explained by maternal TL, mental health, and plasma vitamin B12 levels, while that in male newborn TL was best explained by paternal age, maternal education, and metabolic health. Mother's TL was associated with her own metabolic health and nutrient status, which may have transgenerational effects on offspring TL. Conclusions: Our findings provide a comprehensive understanding of the heritable and environmental factors and their relative contributions to the initial setting of TL and programing of longevity in early life. This study provides valuable insights for preventing in utero telomere attrition by improving the antenatal health of mothers via targeting the modifiable factors.Peer reviewe

Machine Learning-Derived Prenatal Predictive Risk Model to Guide Intervention and Prevent the Progression of Gestational Diabetes Mellitus to Type 2 Diabetes : Prediction Model Development Study

Publisher Copyright: © Mukkesh Kumar, Li Ting Ang, Cindy Ho, Shu E Soh, Kok Hian Tan, Jerry Kok Yen Chan, Keith M Godfrey, Shiao-Yng Chan, Yap Seng Chong, Johan G Eriksson, Mengling Feng, Neerja KarnaniBackground: 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.Peer reviewe

Determinants of cord blood adipokines and association with neonatal abdominal adipose tissue distribution

Background Cord blood leptin and adiponectin are adipokines known to be associated with birth weight and overall infant adiposity. However, few studies have investigated their associations with abdominal adiposity in neonates. We examined maternal factors associated with cord blood leptin and adiponectin, and the association of these adipokines with neonatal adiposity and abdominal fat distribution measured by magnetic resonance imaging (MRI) in an Asian mother-offspring cohort. Methods Growing Up in Singapore Towards healthy Outcomes (GUSTO), is a prospective mother-offspring birth cohort study in Singapore. Cord blood plasma leptin and adiponectin concentrations were measured using Luminex and Enzyme-Linked Immunosorbent Assay respectively in 816 infants. A total of 271 neonates underwent MRI within the first 2-weeks after delivery. Abdominal superficial (sSAT), deep subcutaneous (dSAT), and intra-abdominal (IAT) adipose tissue compartment volumes were quantified from MRI images. Multivariable regression analyses were performed. Results Indian or Malay ethnicity, female sex, and gestational age were positively associated with cord blood leptin and adiponectin concentrations. Maternal gestational diabetes (GDM) positively associated with cord blood leptin concentrations but inversely associated with cord blood adiponectin concentrations. Maternal pre-pregnancy body mass index (BMI) showed a positive relationship with cord blood leptin but not with adiponectin concentrations. Each SD increase in cord blood leptin was associated with higher neonatal sSAT, dSAT and IAT; differences in SD (95% CI): 0.258 (0.142, 0.374), 0.386 (0.254, 0.517) and 0.250 (0.118, 0.383), respectively. Similarly, each SD increase in cord blood adiponectin was associated with higher neonatal sSAT and dSAT; differences in SD (95% CI): 0.185 (0.096, 0.274) and 0.173 (0.067, 0.278), respectively. The association between cord blood adiponectin and neonatal adiposity was observed in neonates of obese mothers only. Conclusions Cord blood leptin and adiponectin concentrations were associated with ethnicity, maternal BMI and GDM, sex and gestational age. Both adipokines showed positive association with neonatal abdominal adiposity.Peer reviewe

Automated Machine Learning (AutoML)-Derived Preconception Predictive Risk Model to Guide Early Intervention for Gestational Diabetes Mellitus

The increasing prevalence of gestational diabetes mellitus (GDM) is contributing to the rising global burden of type 2 diabetes (T2D) and intergenerational cycle of chronic metabolic disorders. Primary lifestyle interventions to manage GDM, including second trimester dietary and exercise guidance, have met with limited success due to late implementation, poor adherence and generic guidelines. In this study, we aimed to build a preconception-based GDM predictor to enable early intervention. We also assessed the associations of top predictors with GDM and adverse birth outcomes. Our evolutionary algorithm-based automated machine learning (AutoML) model was implemented with data from 222 Asian multi-ethnic women in a preconception cohort study, Singapore Preconception Study of Long-Term Maternal and Child Outcomes (S-PRESTO). A stacked ensemble model with a gradient boosting classifier and linear support vector machine classifier (stochastic gradient descent training) was derived using genetic programming, achieving an excellent AUC of 0.93 based on four features (glycated hemoglobin A(1c) (HbA(1c)), mean arterial blood pressure, fasting insulin, triglycerides/HDL ratio). The results of multivariate logistic regression model showed that each 1 mmol/mol increase in preconception HbA(1c) was positively associated with increased risks of GDM (p = 0.001, odds ratio (95% CI) 1.34 (1.13-1.60)) and preterm birth (p = 0.011, odds ratio 1.63 (1.12-2.38)). Optimal control of preconception HbA(1c) may aid in preventing GDM and reducing the incidence of preterm birth. Our trained predictor has been deployed as a web application that can be easily employed in GDM intervention programs, prior to conception.Peer reviewe

Effects of Antenatal Maternal Depressive Symptoms and Socio-Economic Status on Neonatal Brain Development are Modulated by Genetic Risk

This study included 168 and 85 mother-infant dyads from Asian and United States of America cohorts to examine whether a genomic profile risk score for major depressive disorder (GPRSMDD) moderates the association between antenatal maternal depressive symptoms (or socio-economic status, SES) and fetal neurodevelopment, and to identify candidate biological processes underlying such association. Both cohorts showed a significant interaction between antenatal maternal depressive symptoms and infant GPRSMDD on the right amygdala volume. The Asian cohort also showed such interaction on the right hippocampal volume and shape, thickness of the orbitofrontal and ventromedial prefrontal cortex. Likewise, a significant interaction between SES and infant GPRSMDD was on the right amygdala and hippocampal volumes and shapes. After controlling for each other, the interaction effect of antenatal maternal depressive symptoms and GPRSMDD was mainly shown on the right amygdala, while the interaction effect of SES and GPRSMDD was mainly shown on the right hippocampus. Bioinformatic analyses suggested neurotransmitter/neurotrophic signaling, SNAp REceptor complex, and glutamate receptor activity as common biological processes underlying the influence of antenatal maternal depressive symptoms on fetal cortico-limbic development. These findings suggest gene-environment interdependence in the fetal development of brain regions implicated in cognitive-emotional function. Candidate biological mechanisms involve a range of brain region-specific signaling pathways that converge on common processes of synaptic development

Integrative multi-omics database (iMOMdb) of Asian pregnant women

Asians are underrepresented across many omics databases, thereby limiting the potential of precision medicine in nearly 60% of the global population. As such, there is a pressing need for multi-omics derived quantitative trait loci (QTLs) to fill the knowledge gap of complex traits in populations of Asian ancestry. Here, we provide the first blood-based multi-omics analysis of Asian pregnant women, constituting high-resolution genotyping (N= 1079), DNA methylation (N=915) and transcriptome profiling (N=238). Integrative omics analysis identified 219 154 CpGs associated with cis-DNA methylation QTLs (meQTLs) and 3703 RNAs associated with cis-RNA expression QTLs (eQTLs). Ethnicity was the largest contributor of inter-individual variation across all omics datasets, with 2561 genes identified as hotspots of this variation; 395 of these hotspot genes also contained both ethnicity-specific eQTLs and meQTLs. Gene set enrichment analysis of these ethnicity QTL hotspots showed pathways involved in lipid metabolism, adaptive immune system and carbohydrate metabolism. Pathway validation by profiling the lipidome (similar to 480 lipids) of antenatal plasma (N = 752) and placenta (N = 1042) in the same cohort showed significant lipid differences among Chinese, Malay and Indian women, validating ethnicity-QTL gene effects across different tissue types. To develop deeper insights into the complex traits and benefit future precision medicine research in Asian pregnant women, we developed iMOMdb, an open-access database.Peer reviewe

Allergic sensitization trajectories to age 8 years in the Singapore GUSTO cohort

Background: Allergic sensitization is linked to allergy development, with early sensitization often associated with worse outcomes. We aimed to identify if distinct allergic sensitization trajectories existed within a diverse and multi-ethnic Asian cohort.Methods: We administered modified ISAAC questionnaires in the first 8 years and conducted skin prick testing at ages 18 months, 3, 5 and 8 years in the Growing Up in Singapore Towards healthy Outcomes (GUSTO) cohort. We used latent class analysis to derive allergic sensitization trajectories, and adjusted odds ratios (AOR) to evaluate predictive risk factors and associations with allergic comorbidities.Results: Among 997 children, three trajectories were identified: early food and mite sensitization (16.2%), late mite sensitization (24.2%) and no/low sensitization (59.6%). Early food and mite sensitization was associated with early eczema by 6 months [AOR (95%CI) 4.67 (1.78-12.28)], increased risk of wheeze by 3-8 years (ARR 1.72-1.99) and eczema in the first 8 years of life (ARR 1.87-2.41). Late mite sensitization was associated with female sex [AOR 0.58 (0.35-0.96)], cesar-ean section [AOR 0.54 (0.30-0.98)], early eczema by 6 months [AOR 3.40 (1.38-8.42)], and increased risk of eczema by 18 months [ARR 1.47 (1.03-2.08)] and 8 years [ARR 1.35 (1.05-1.73)].Conclusion: Early onset of eczema and early allergic sensitization were strongly associated. Early sensitization, especially to house dust mites, was associated with increased risks of developing wheeze and eczema, pointing to the importance of developing preventive perinatal interventions and effective therapeutics for sensitized toddlers.Peer reviewe