Multi-ancestry genome-wide association study of gestational diabetes mellitus highlights genetic links with type 2 diabetes.

Gestational diabetes mellitus (GDM) is associated with increased risk of pregnancy complications and adverse perinatal outcomes. GDM often reoccurs and is associated with increased risk of subsequent diagnosis of type 2 diabetes (T2D). To improve our understanding of the aetiological factors and molecular processes driving the occurrence of GDM, including the extent to which these overlap with T2D pathophysiology, the GENetics of Diabetes In Pregnancy Consortium assembled genome-wide association studies of diverse ancestry in a total of 5485 women with GDM and 347 856 without GDM. Through multi-ancestry meta-analysis, we identified five loci with genome-wide significant association (P < 5 × 10-8) with GDM, mapping to/near MTNR1B (P = 4.3 × 10-54), TCF7L2 (P = 4.0 × 10-16), CDKAL1 (P = 1.6 × 10-14), CDKN2A-CDKN2B (P = 4.1 × 10-9) and HKDC1 (P = 2.9 × 10-8). Multiple lines of evidence pointed to the shared pathophysiology of GDM and T2D: (i) four of the five GDM loci (not HKDC1) have been previously reported at genome-wide significance for T2D; (ii) significant enrichment for associations with GDM at previously reported T2D loci; (iii) strong genetic correlation between GDM and T2D and (iv) enrichment of GDM associations mapping to genomic annotations in diabetes-relevant tissues and transcription factor binding sites. Mendelian randomization analyses demonstrated significant causal association (5% false discovery rate) of higher body mass index on increased GDM risk. Our results provide support for the hypothesis that GDM and T2D are part of the same underlying pathology but that, as exemplified by the HKDC1 locus, there are genetic determinants of GDM that are specific to glucose regulation in pregnancy.

Integrating multiple lines of evidence to assess the effects of maternal BMI on pregnancy and perinatal outcomes.

BACKGROUND: Higher maternal pre-pregnancy body mass index (BMI) is associated with adverse pregnancy and perinatal outcomes. However, whether these associations are causal remains unclear. METHODS: We explored the relation of maternal pre-/early-pregnancy BMI with 20 pregnancy and perinatal outcomes by integrating evidence from three different approaches (i.e. multivariable regression, Mendelian randomisation, and paternal negative control analyses), including data from over 400,000 women. RESULTS: All three analytical approaches supported associations of higher maternal BMI with lower odds of maternal anaemia, delivering a small-for-gestational-age baby and initiating breastfeeding, but higher odds of hypertensive disorders of pregnancy, gestational hypertension, preeclampsia, gestational diabetes, pre-labour membrane rupture, induction of labour, caesarean section, large-for-gestational age, high birthweight, low Apgar score at 1 min, and neonatal intensive care unit admission. For example, higher maternal BMI was associated with higher risk of gestational hypertension in multivariable regression (OR = 1.67; 95% CI = 1.63, 1.70 per standard unit in BMI) and Mendelian randomisation (OR = 1.59; 95% CI = 1.38, 1.83), which was not seen for paternal BMI (OR = 1.01; 95% CI = 0.98, 1.04). Findings did not support a relation between maternal BMI and perinatal depression. For other outcomes, evidence was inconclusive due to inconsistencies across the applied approaches or substantial imprecision in effect estimates from Mendelian randomisation. CONCLUSIONS: Our findings support a causal role for maternal pre-/early-pregnancy BMI on 14 out of 20 adverse pregnancy and perinatal outcomes. Pre-conception interventions to support women maintaining a healthy BMI may reduce the burden of obstetric and neonatal complications. FUNDING: Medical Research Council, British Heart Foundation, European Research Council, National Institutes of Health, National Institute for Health Research, Research Council of Norway, Wellcome Trust.

Pre-pregnancy body mass index and gut microbiota of mothers and children 5 years postpartum.

BACKGROUND: Maternal pre-pregnancy body mass index (BMI) has been linked to altered gut microbiota in women shortly after delivery and in their offspring in the first few years of life. But little is known about how long these differences persist. METHODS: We followed 180 mothers and children from pregnancy until 5-year postpartum in the Gen3G cohort (Canada, enrolled 2010-2013). At 5 years postpartum we collected stool samples from mothers and children and estimated the gut microbiota by 16 S rRNA sequencing (V4 region) using Illumina MiSeq, and assigning amplicon sequence variants (ASV). We examined whether overall microbiota composition (as measured by microbiota ß diversity) was more similar between mother-child pairs compared to between mothers or between children. We also assessed whether mother-child pair sharing of overall microbiota composition differed by the weight status of mothers before pregnancy and of children at 5-year. Furthermore, in mothers, we examined whether pre-pregnancy BMI, BMI 5-year postpartum, and change in BMI between time points was associated with maternal gut microbiota 5-year postpartum. In children, we further examined associations of maternal pre-pregnancy BMI and child 5-year BMI z-score with child 5-year gut microbiota. RESULTS: Mother-child pairs had greater similarity in overall microbiome composition compared to between mothers and between children. In mothers, higher pre-pregnancy BMI and 5-year postpartum BMI were associated with lower microbiota observed ASV richness and Chao 1 index; in children's gut microbiota, higher maternal pre-pregnancy BMI was weakly associated with lower microbiota Shannon index, whereas child's 5-year BMI z-score was associated with higher observed ASV richness. Pre-pregnancy BMI was also linked to differential abundances of several microbial ASVs in the Ruminococcaceae and Lachnospiraceae families, but no specific ASV had overlapping associations with BMI measures in both mothers and children. CONCLUSIONS: Pre-pregnancy BMI was associated with gut microbiota diversity and composition of mothers and children 5 years after birth, however, the nature and direction of most associations differed for mothers and children. Future studies are encouraged to confirm our findings and look into potential mechanisms or factors that may drive these associations.

Portrait of autosomal recessive diseases in the French-Canadian founder population of Saguenay-Lac-Saint-Jean.

The population of the Saguenay-Lac-Saint-Jean (SLSJ) region, located in the province of Quebec, Canada, is recognized as a founder population, where some rare autosomal recessive diseases show a high prevalence. Through the clinical and molecular study of 82 affected individuals from 60 families, this study outlines 12 diseases identified as recurrent in SLSJ. Their carrier frequency was estimated with the contribution of 1059 healthy individuals, increasing the number of autosomal recessive diseases with known carrier frequency in this region from 14 to 25. We review the main clinical and molecular features previously reported for these disorders. Five of the studied diseases have a potential lethal effect and three are associated with intellectual deficiency. Therefore, we believe that the provincial program for carrier screening should be extended to include these eight disorders. The high-carrier frequency, together with the absence of consanguinity in most of these unrelated families, suggest a founder effect and genetic drift for the 12 recurrent variants. We recommend further studies to validate this hypothesis, as well as to extend the present study to other regions in the province of Quebec, since some of these disorders could also be present in other French-Canadian families.

Maternal Hyperglycemia in Pregnancy and Offspring Internalizing and Externalizing Behaviors.

OBJECTIVE: To examine the associations between exposure to gestational diabetes mellitus (GDM) and maternal glycemic markers during pregnancy and offspring behaviors at 3 and 5 years. We hypothesized that exposure to maternal hyperglycemia would be associated with more behavioral problems in offspring. METHODS: We included 548 mother-child pairs from the prospective pre-birth Gen3G cohort (Canada). Glycemic markers were measured during a 75 g oral glucose tolerance test (OGTT) in the second trimester of pregnancy. Based on OGTT, we classified 59 women (10.8%) as having GDM according to international diagnostic criteria. Mothers reported offspring behavior using the Strengths and Difficulties Questionnaire (SDQ) at 3 and 5 years, and the Child Behavior Checklist (CBCL) at 5 years. We used linear mixed models and multivariate regression to assess the associations between GDM or glycemic markers and children's behavior, adjusted for child sex and age, and maternal demographic factors, body mass index and family history of diabetes. RESULTS: Exposure to GDM was associated with higher SDQ externalizing scores at 3 and 5 years [B = 1.12, 95% CI (0.14, 2.10)] in fully adjusted linear mixed models. These results were supported by the CBCL at 5 years. Higher levels of maternal glucose at 1 h and 2 h during OGTT were associated with greater SDQ externalizing scores. Fasting glucose levels were not associated with child behavior scores. We did not observe associations between glycemic markers and internalizing behaviors. CONCLUSIONS: Exposure to higher levels of maternal glycemia during pregnancy was associated with more externalizing behaviors in children at 3 and 5 years.

What is already known on this subject? Prenatal exposure to gestational diabetes mellitus (GDM) has been linked to a higher risk of long-term consequences in offspring including metabolic problems and cognitive difficulties. However, prior studies examining associations between GDM and behavior in children reported mixed results. What this study adds? We reported associations between exposure to maternal GDM and post-OGTT hyperglycemia during pregnancy and greater levels of externalizing behaviors in children at 3 and 5 years of age. Our results underscore the importance of early detection of behavioral problems in children.

Human plasma pregnancy-associated miRNAs and their temporal variation within the first trimester of pregnancy.

BACKGROUND: During pregnancy, maternal metabolism undergoes substantial changes to support the developing fetus. Such changes are finely regulated by different mechanisms carried out by effectors such as microRNAs (miRNAs). These small non-coding RNAs regulate numerous biological functions, mostly through post-transcriptional repression of gene expression. miRNAs are also secreted in circulation by numerous organs, such as the placenta. However, the complete plasmatic microtranscriptome of pregnant women has still not been fully described, although some miRNA clusters from the chromosome 14 (C14MC) and the chromosome 19 (C19MC and miR-371-3 cluster) have been proposed as being specific to pregnancy. Our aims were thus to describe the plasma microtranscriptome during the first trimester of pregnancy, by assessing the differences with non-pregnant women, and how it varies between the 4th and the 16th week of pregnancy. METHODS: Plasmatic miRNAs from 436 pregnant (gestational week 4 to 16) and 15 non-pregnant women were quantified using Illumina HiSeq next-generation sequencing platform. Differentially abundant miRNAs were identified using DESeq2 package (FDR q-value ≤ 0.05) and their targeted biological pathways were assessed with DIANA-miRpath. RESULTS: A total of 2101 miRNAs were detected, of which 191 were differentially abundant (fold change < 0.05 or > 2, FDR q-value ≤ 0.05) between pregnant and non-pregnant women. Of these, 100 miRNAs were less and 91 miRNAs were more abundant in pregnant women. Additionally, the abundance of 57 miRNAs varied according to gestational age at first trimester, of which 47 were positively and 10 were negatively associated with advancing gestational age. miRNAs from the C19MC were positively associated with both pregnancy and gestational age variation during the first trimester. Biological pathway analysis revealed that these 191 (pregnancy-specific) and 57 (gestational age markers) miRNAs targeted genes involved in fatty acid metabolism, ECM-receptor interaction and TGF-beta signaling pathways. CONCLUSION: We have identified circulating miRNAs specific to pregnancy and/or that varied with gestational age in first trimester. These miRNAs target biological pathways involved in lipid metabolism as well as placenta and embryo development, suggesting a contribution to the maternal metabolic adaptation to pregnancy and fetal growth.

Genetic burden linked to founder effects in Saguenay-Lac-Saint-Jean illustrates the importance of genetic screening test availability.

The Saguenay-Lac-Saint-Jean (SLSJ) region located in the province of Quebec was settled in the 19th century by pioneers issued from successive migration waves starting in France in the 17th century and continuing within Quebec until the beginning of the 20th century. The genetic structure of the SLSJ population is considered to be the product of a triple founder effect and is characterised by a higher prevalence of some rare genetic diseases. Several studies were performed to elucidate the historical, demographic and genetic background of current SLSJ inhabitants to assess the origins of these rare disorders and their distribution in the population. Thanks to the development of new sequencing technologies, the genes and the variants responsible for the most prevalent conditions were identified. Combined with other resources such as the BALSAC population database, identifying the causal genes and the pathogenic variants allowed to assess the impacts of some of these founder mutations on the population health and to design precision medicine public health strategies based on carrier testing. Furthermore, it stimulated the establishment of many public programmes.We report here a review and an update of a subset of inherited disorders and founder mutations in the SLSJ region. Data were collected from published scientific sources. This work expands the knowledge about the current frequencies of these rare disorders, the frequencies of other rare genetic diseases in this population, the relevance of the carrier tests offered to the population, as well as the current available treatments and research about future therapeutic avenues for these inherited disorders.

SERPINE1 DNA Methylation Levels Quantified in Blood Cells at Five Years of Age Are Associated with Adiposity and Plasma PAI-1 Levels at Five Years of Age.

Plasminogen activator inhibitor (PAI-1) expression has been associated with a higher risk of development of obesity. DNA methylation (DNAm) is an epigenetic mechanism regulating gene transcription and likely involved in the fetal programming of childhood obesity. Our study aimed to assess the associations between PAI-1 gene (SERPINE1) DNAm, plasma PAI-1 levels, and adiposity at five years of age. We analyzed DNAm and anthropometric data from 146 girls and 177 boys from the Gen3G prospective birth cohort. We assessed adiposity using BMI z-scores, waist circumference, total skinfolds, and percentages of total, android, and trunk fat measured by dual-energy radiography (DXA). We estimated blood cell DNAm levels at 15 CpG sites within SERPINE1 using the methylationEPIC array. After correction for multiple testing, we found that lower DNAm in SERPINE1 intron 3 (cg11353706) was associated with greater adiposity levels in girls (waist circumference: r = −0.258, p = 0.002; skinfolds: r = −0.212, p = 0. 013; android fat: r = −0.215, p = 0.015; BMI z-score: r = −0.278, p < 0.001) and that lower DNAm in the SERPINE1 promoter (cg19722814) was associated with higher plasma PAI-1 levels in boys (r = −0.178, p = 0.021). Our study suggests that DNAm levels at the SERPINE1 gene locus are negatively correlated with adiposity, but not with plasma PAI-1 levels, in young girls only.

Allele length of the DMPK CTG repeat is a predictor of progressive myotonic dystrophy type 1 phenotypes.

Myotonic dystrophy type 1 (DM1) is an autosomal dominant inherited disorder caused by expansion of a germline and somatically unstable CTG repeat in the DMPK gene. Previously, CTG repeat length at birth has been correlated to patient age at symptom onset. Attempts to correlate CTG repeat length with progressive DM1 phenotypes, such as muscle power, have proven difficult. To better correlate genotype with progressive phenotypes, we have measured CTG repeat tract length and screened for interrupting variant repeats in 192 study participants from a well-characterized Canadian cohort. We have assessed genotype-phenotype correlations with nine progressive measures of skeletal muscle power and respiratory function. We have built statistical models that include confounding factors such as sex, age, height and weight to further explain variation in muscle power. Our analysis reveals a strong correlation between DM1 genotype and respiratory function and skeletal muscle power, as part of a complex model that includes additional modulators such as sex, age, height, weight and the presence or absence of interrupting variant repeats. Distal skeletal muscle measurements, such as hand pinch and grip strength, show the strongest correlation with disease genotype. Detailed analysis of CTG repeat length, and incorporation of confounding factors, greatly improves the predictive ability of these models. They reveal a greater genetic influence on individual progressive phenotypes than on age at symptom onset and for clinical trials will help optimize stratification and explain patient variability. They will also help practitioners prioritize assessment of the muscular power measurements that correlate best with disease severity.

A prospective study of maternal adiposity and glycemic traits across pregnancy and mid-childhood metabolomic profiles.

BACKGROUND: Fetal exposure to maternal excess adiposity and hyperglycemia is risk factors for childhood adverse metabolic outcomes. Using data from a prospective pre-birth cohort, we aimed to further understand the prenatal determinants of fetal metabolic programming based on analyses of maternal adiposity and glycemic traits across pregnancy with childhood metabolomic profiles. METHODS: This study included 330 mother-child pairs from the Gen3G cohort with information on maternal adiposity and glycemic markers at 5-16 (visit 1) and 24-30 (visit 2) weeks of pregnancy. At mid-childhood (4.8-7.2 years old), we collected fasting plasma and measured 1116 metabolites using an untargeted approach. We constructed networks of interconnected metabolites using a weighted-correlation network analysis algorithm. We estimated Spearman's partial correlation coefficients of maternal adiposity and glycemic traits across pregnancy with metabolite networks and individual metabolites, adjusting for maternal age, gravidity, race/ethnicity, history of smoking, and child's sex and age at blood collection for metabolite measurement. RESULTS: We identified a network of 16 metabolites, primarily glycero-3-phosphoethanolamines (GPE) at mid-childhood that showed consistent negative correlations with maternal body mass index, waist circumference, and body-fat percentage at visits 1 and 2 (ρadjusted = -0.14 to -0.21) and post-challenge glucose levels at visit 2 (ρadjusted = -0.10 to -0.13), while positive correlations with Matsuda index (ρadjusted = 0.13). Within this identified network, 1-palmitoyl-2-decosahexaenoyl-GPE and 1-stearoyl-2-decosahexaenoyl-GPE appeared to be driving the associations. In addition, a network of 89 metabolites, primarily phosphatidylcholines, plasmalogens, sphingomyelins, and ceramides showed consistent negative correlations with insulin at visit 1 and post-challenge glucose at visit 2, while positive correlation with adiponectin at visit 2. CONCLUSIONS: Prenatal exposure to maternal higher adiposity and hyperglycemic traits and lower insulin sensitivity markers were associated with a unique metabolomic pattern characterized by low serum phospho- and sphingolipids in mid-childhood.

Associations of maternal insulin resistance during pregnancy and offspring inflammation at birth and at 5 years of age: A prospective study in the Gen3G cohort.

BACKGROUND: Maternal insulin resistance is associated with greater maternal inflammation during pregnancy, but its relation to inflammation in offspring remains unclear. The goal of this study was to assess the relationship of gestational insulin resistance and other glycemic markers with offspring inflammation at birth and at 5 years of age. METHODS: We included 653 mother-child pairs from the prospective pre-birth Gen3G cohort. We examined maternal insulin and glucose levels measured during the second trimester of pregnancy, from which we derived the homeostatic model of assessment of insulin resistance (HOMA-IR) and the Matsuda index. We assessed offspring inflammation at birth and at 5 years of age by measuring plasma tumor necrosis factor-α (TNFα) concentrations. We conducted multivariable regression models to evaluate associations of each insulin and glucose marker with offspring inflammation adjusting for confounding variables. RESULTS: Higher levels of fasting insulin were associated with lower TNFα levels at birth (-0.78, 95% CI [-1.45, -0.11]), in the fully adjusted model. We observed similar associations with the HOMA-IR and opposite direction with the Matsuda index. We did not find persistence of the association between maternal fasting insulin and offspring TNFα at 5 years of age. CONCLUSIONS: Greater maternal insulin resistance during pregnancy was associated with lower cord blood TNFα levels in newborns. The mechanisms by which maternal insulin resistance may promote lower inflammatory levels in newborns are not fully understood and more research is needed to deepen our understanding of these mechanisms.

Individuals with self-determined motivation for eating have better overall diet quality: Results from the PREDISE study.

The study aimed at documenting motivational orientations for the regulation of eating as defined by self-determination theory and their association with sociodemographic characteristics and overall diet quality. As part of the PREDISE study, French-speaking women (n = 550) and men (n = 547), aged 18-65 years, living in the Province of Québec, Canada, completed online validated questionnaires. The Regulation of Eating Behavior Scale, based on the self-determination theory, assessed self-determined and non-self-determined motivation to regulate one's eating behavior. Three web-based 24-h food recalls were completed and used to compute the Canadian Healthy Eating Index 2007 (C-HEI), an indicator of the overall adherence to Canadian guidelines for healthy eating. Multiple linear regressions were performed to assess how regulation styles are associated with the C-HEI. Model 1 included no covariate, model 2 included sociodemographic covariates, and fully adjusted model 3 included as covariates sociodemographic variables as well as variables that were previously associated with diet quality, namely nutrition knowledge and social support for healthy eating. Women (p < 0.0001), older individuals (p = 0.0002), those with a higher education level (p < 0.0001), and non-smokers (p < 0.0001) reported higher self-determined motivation score than their counterparts. Self-determined motivation was positively (model 1: B = 4.67, p < 0.0001; model 2: B = 3.82, p < 0.0001; model 3: B = 3.61, p < 0.0001) and non-self-determined motivation was negatively (model 1: B = -1.62, p = 0.0009; model 2: B = -1.63, p = 0.0006; model 2: B = -1.49, p = 0.0022) associated with C-HEI. The present study suggests that some subgroups of the general adult population show more self-determined motivation for eating, which is associated with a better diet quality independently of individual characteristics and other individual and social determinants of healthy eating. Strategies to help individuals internalize the regulation of eating should be further investigated.

Genome-wide association study of offspring birth weight in 86 577 women identifies five novel loci and highlights maternal genetic effects that are independent of fetal genetics.

Genome-wide association studies of birth weight have focused on fetal genetics, whereas relatively little is known about the role of maternal genetic variation. We aimed to identify maternal genetic variants associated with birth weight that could highlight potentially relevant maternal determinants of fetal growth. We meta-analysed data on up to 8.7 million SNPs in up to 86 577 women of European descent from the Early Growth Genetics (EGG) Consortium and the UK Biobank. We used structural equation modelling (SEM) and analyses of mother-child pairs to quantify the separate maternal and fetal genetic effects. Maternal SNPs at 10 loci (MTNR1B, HMGA2, SH2B3, KCNAB1, L3MBTL3, GCK, EBF1, TCF7L2, ACTL9, CYP3A7) were associated with offspring birth weight at P < 5 × 10-8. In SEM analyses, at least 7 of the 10 associations were consistent with effects of the maternal genotype acting via the intrauterine environment, rather than via effects of shared alleles with the fetus. Variants, or correlated proxies, at many of the loci had been previously associated with adult traits, including fasting glucose (MTNR1B, GCK and TCF7L2) and sex hormone levels (CYP3A7), and one (EBF1) with gestational duration. The identified associations indicate that genetic effects on maternal glucose, cytochrome P450 activity and gestational duration, and potentially on maternal blood pressure and immune function, are relevant for fetal growth. Further characterization of these associations in mechanistic and causal analyses will enhance understanding of the potentially modifiable maternal determinants of fetal growth, with the goal of reducing the morbidity and mortality associated with low and high birth weights.

Mediation Analysis Supports a Causal Relationship between Maternal Hyperglycemia and Placental DNA Methylation Variations at the Leptin Gene Locus and Cord Blood Leptin Levels.

Changes in fetal DNA methylation (DNAm) of the leptin (LEP) gene have been associated with exposure to maternal hyperglycemia, but their links with childhood obesity risk are still unclear. We investigated the association between maternal hyperglycemia, placental LEP DNAm (25 5'-C-phosphate-G-3' (CpG) sites), neonatal leptinemia, and adiposity (i.e., BMI and skinfold thickness (ST) (subscapular (SS) + triceps (TR) skinfold measures, and the ratio of SS:TR) at 3-years-old, in 259 mother-child dyads, from Gen3G birth cohort. We conducted multivariate linear analyses adjusted for gestational age at birth, sex of the child, age at follow-up, and cellular heterogeneity. We assessed the causal role of DNAm in the association between maternal glycemia and childhood outcomes, using mediation analysis. We found three CpGs associated with neonatal leptinemia (p ≤ 0.002). Of these, cg05136031 and cg15758240 were also associated with BMI (ß = -2.69, p = 0.05) and fat distribution (ß = -0.581, p = 0.05) at 3-years-old, respectively. Maternal glycemia was associated with DNAm at cg15758240 (ß = -0.01, p = 0.04) and neonatal leptinemia (ß = 0.19, p = 0.004). DNAm levels at cg15758240 mediates 0.8% of the association between maternal glycemia and neonatal leptinemia (p < 0.001). Our results support that DNAm regulation of the leptin pathway in response to maternal glycemia might be involved in programming adiposity in childhood.

Placental Epigenome-Wide Association Study Identified Loci Associated with Childhood Adiposity at 3 Years of Age.

The aim of this study was to identify placental DNA methylation (DNAm) variations associated with adiposity at 3 years of age. We quantified placental DNAm using the Infinium MethylationEPIC BeadChips. We assessed associations between DNAm at single-CpGs and skinfold thickness using robust linear regression models adjusted for gestational age, child's sex, age at follow-up and cellular heterogeneity. We sought replication of DNAm association with child adiposity in an independent cohort. We quantified placental mRNA levels for annotated gene using qRT-PCR and tested for correlation with DNAm. Lower DNAm at cg22593959 and cg22436429 was associated with higher adiposity (ß = -1.18, q = 0.002 and ß = -0.82, q = 0.04). The cg22593959 is located in an intergenic region (chr7q31.3), whereas cg22436429 is within the TFAP2E gene (1p34.3). DNAm at cg22593959 and cg22436429 was correlated with mRNA levels at FAM3C (rs = -0.279, p = 0.005) and TFAP2E (rs = 0.216, p = 0.03). In an independent cohort, the association between placental DNAm at cg22593959 and childhood adiposity was of similar strength and direction (ß = -3.8 ± 4.1, p = 0.36), yet non-significant. Four genomic regions were also associated with skinfold thickness within FMN1, MAGI2, SKAP2 and BMPR1B genes. We identified placental epigenetic variations associated with adiposity at 3 years of age suggesting that childhood fat accretion patterns might be established during fetal life.

An analytic approach for interpretable predictive models in high-dimensional data in the presence of interactions with exposures.

Predicting a phenotype and understanding which variables improve that prediction are two very challenging and overlapping problems in the analysis of high-dimensional (HD) data such as those arising from genomic and brain imaging studies. It is often believed that the number of truly important predictors is small relative to the total number of variables, making computational approaches to variable selection and dimension reduction extremely important. To reduce dimensionality, commonly used two-step methods first cluster the data in some way, and build models using cluster summaries to predict the phenotype. It is known that important exposure variables can alter correlation patterns between clusters of HD variables, that is, alter network properties of the variables. However, it is not well understood whether such altered clustering is informative in prediction. Here, assuming there is a binary exposure with such network-altering effects, we explore whether the use of exposure-dependent clustering relationships in dimension reduction can improve predictive modeling in a two-step framework. Hence, we propose a modeling framework called ECLUST to test this hypothesis, and evaluate its performance through extensive simulations. With ECLUST, we found improved prediction and variable selection performance compared to methods that do not consider the environment in the clustering step, or to methods that use the original data as features. We further illustrate this modeling framework through the analysis of three data sets from very different fields, each with HD data, a binary exposure, and a phenotype of interest. Our method is available in the eclust CRAN package.

Mediation by Placental DNA Methylation of the Association of Prenatal Maternal Smoking and Birth Weight.

Prenatal maternal smoking is a risk factor for lower birth weight. We performed epigenome-wide association analyses of placental DNA methylation (DNAm) at 720,077 cytosine-phosphate-guanine (CpG) sites and prenatal maternal smoking among 441 mother-infant pairs (2010-2014) and evaluated whether DNAm mediates the association between smoking and birth weight using mediation analysis. Mean birth weight was 3,443 (standard deviation, 423) g, and 38 mothers (8.6%) reported smoking at a mean of 9.4 weeks of gestation. Prenatal maternal smoking was associated with a 175-g lower birth weight (95% confidence interval (CI): -305.5, -44.8) and with differential DNAm of 71 CpGs in placenta, robust to latent-factor adjustment reflecting cell types (Bonferroni-adjusted P < 6.94 × 10-8). Of the 71 CpG sites, 7 mediated the association between prenatal smoking and birth weight (on MDS2, PBX1, CYP1A2, VPRBP, WBP1L, CD28, and CDK6 genes), and prenatal smoking × DNAm interactions on birth weight were observed for 5 CpG sites. The strongest mediator, cg22638236, was annotated to the PBX1 gene body involved in skeletal patterning and programming, with a mediated effect of 301-g lower birth weight (95% CI: -543, -86) among smokers but no mediated effect for nonsmokers (ß = -38 g; 95% CI: -88, 9). Prenatal maternal smoking might interact with placental DNAm at specific loci, mediating the association with lower infant birth weight.

Prenatal determinants of childhood obesity: a review of risk factors 1.

Childhood obesity is a predictor of adult obesity and has its roots in the pre-pregnancy or pregnancy period. This review presents an overview of the prenatal risk factors for childhood obesity, which were categorized into 2 groups: biological risk factors (maternal pre-pregnancy body mass index, gestational weight gain, diabetes in pregnancy, and caesarean section), and environmental and behavioural risk factors (maternal smoking and exposure to obesogens, maternal dietary patterns, maternal intestinal microbiome and antibiotics exposure, and maternal psychosocial stress). Identifying modifiable predisposing prenatal factors for obesity will inform further development of inventions to prevent obesity over the life course, and future directions for research and intervention are discussed.

Altered DNA Methylation of Long Noncoding RNA H19 in Calcific Aortic Valve Disease Promotes Mineralization by Silencing NOTCH1.

BACKGROUND: Calcific aortic valve disease is characterized by an abnormal mineralization of the aortic valve. Osteogenic activity in the aortic valve is under the control of NOTCH1, which regulates the expression of key pro-osteogenic genes such as RUNX2 and BMP2. Long noncoding RNAs (lncRNAs) may reprogram cells by altering the gene expression pattern. METHODS: Multidimensional genomic profiling was performed in human aortic valves to document the expression of lncRNAs and the DNA methylation pattern in calcific aortic valve disease. In-depth functional assays were carried out to document the impact of lncRNA on the mineralization of the aortic valve. RESULTS: We documented that lncRNA H19 (H19) was increased in calcific aortic valve disease. Hypomethylation of the promoter region was observed in mineralized aortic valves and was inversely associated with H19 expression. Knockdown and overexpression experiments showed that H19 induces a strong osteogenic phenotype by altering the NOTCH1 pathway. Gene promoter analyses showed that H19 silenced NOTCH1 by preventing the recruitment of p53 to its promoter. A knockdown of H19 in valve interstitial cells (VICs) increased the expression of NOTCH1 and decreased the level of RUNX2 and BMP2, 2 downstream targets repressed by NOTCH1. In rescue experiments, the transfection of a vector encoding for the active Notch intracellular domain prevented H19-induced mineralization of valve interstitial cells. CONCLUSIONS: These findings indicate that a dysregulation of DNA methylation in the promoter of H19 during calcific aortic valve disease is associated with a higher expression of this lncRNA, which promotes an osteogenic program by interfering with the expression of NOTCH1.

Layered genetic control of DNA methylation and gene expression: a locus of multiple sclerosis in healthy individuals.

DNA methylation may contribute to the etiology of complex genetic disorders through its impact on genome integrity and gene expression; it is modulated by DNA-sequence variants, named methylation quantitative trait loci (meQTLs). Most meQTLs influence methylation of a few CpG dinucleotides within short genomic regions (<3 kb). Here, we identified a layered genetic control of DNA methylation at numerous CpGs across a long 300 kb genomic region. This control involved a single long-range meQTL and multiple local meQTLs. The long-range meQTL explained up to 75% of variance in methylation of CpGs located over extended areas of the 300 kb region. The meQTL was identified in four samples (P = 2.8 × 10(-17), 3.1 × 10(-31), 4.0 × 10(-71) and 5.2 × 10(-199)), comprising a total of 2796 individuals. The long-range meQTL was strongly associated not only with DNA methylation but also with mRNA expression of several genes within the 300 kb region (P = 7.1 × 10(-18)-1.0 × 10(-123)). The associations of the meQTL with gene expression became attenuated when adjusted for DNA methylation (causal inference test: P = 2.4 × 10(-13)-7.1 × 10(-20)), indicating coordinated regulation of DNA methylation and gene expression. Further, the long-range meQTL was found to be in linkage disequilibrium with the most replicated locus of multiple sclerosis, a disease affecting primarily the brain white matter. In middle-aged adults free of the disease, we observed that the risk allele was associated with subtle structural properties of the brain white matter found in multiple sclerosis (P = 0.02). In summary, we identified a long-range meQTL that controls methylation and expression of several genes and may be involved in increasing brain vulnerability to multiple sclerosis.