DNA methylation risk score for type 2 diabetes is associated with gestational diabetes.

BACKGROUND: Gestational diabetes mellitus (GDM) and type 2 diabetes mellitus (T2DM) share many pathophysiological factors including genetics, but whether epigenetic marks are shared is unknown. We aimed to test whether a DNA methylation risk score (MRS) for T2DM was associated with GDM across ancestry and GDM criteria. METHODS: In two independent pregnancy cohorts, EPIPREG (n = 480) and EPIDG (n = 32), DNA methylation in peripheral blood leukocytes was measured at a gestational age of 28 ± 2. We constructed an MRS in EPIPREG and EPIDG based on CpG hits from a published epigenome-wide association study (EWAS) of T2DM. RESULTS: With mixed models logistic regression of EPIPREG and EPIDG, MRS for T2DM was associated with GDM: odd ratio (OR)[95% CI]: 1.3 [1.1-1.8], P = 0.002 for the unadjusted model, and 1.4 [1.1-1.7], P = 0.00014 for a model adjusted by age, pre-pregnant BMI, family history of diabetes and smoking status. Also, we found 6 CpGs through a meta-analysis (cg14020176, cg22650271, cg14870271, cg27243685, cg06378491, cg25130381) associated with GDM, and some of their methylation quantitative loci (mQTLs) were related to T2DM and GDM. CONCLUSION: For the first time, we show that DNA methylation marks for T2DM are also associated with GDM, suggesting shared epigenetic mechanisms between GDM and T2DM.

Intrauterine Growth and Offspring Neurodevelopmental Traits: A Mendelian Randomization Analysis of the Norwegian Mother, Father and Child Cohort Study (MoBa).

Importance: Conventional epidemiological analyses have suggested that lower birth weight is associated with later neurodevelopmental difficulties; however, it is unclear whether this association is causal. Objective: To investigate the relationship between intrauterine growth and offspring neurodevelopmental difficulties. Design, Setting, and Participants: MoBa is a population-based pregnancy cohort that recruited pregnant women from June 1999 to December 2008 included approximately 114 500 children, 95 200 mothers, and 75 200 fathers. Observational associations between birth weight and neurodevelopmental difficulties were assessed with a conventional epidemiological approach. Mendelian randomization analyses were performed to investigate the potential causal association between maternal allele scores for birth weight and offspring neurodevelopmental difficulties conditional on offspring allele scores. Exposures: Birth weight and maternal allele scores for birth weight (derived from genetic variants robustly associated with birth weight) were the exposures in the observational and mendelian randomization analyses, respectively. Main Outcomes and Measures: Clinically relevant maternal ratings of offspring neurodevelopmental difficulties at 6 months, 18 months, 3 years, 5 years, and 8 years of age assessing language and motor difficulties, inattention and hyperactivity-impulsivity, social communication difficulties, and repetitive behaviors. Results: The conventional epidemiological sample included up to 46 970 offspring, whereas the mendelian randomization sample included up to 44 134 offspring (median offspring birth year, 2005 [range, 1999-2009]; mean [SD] maternal age at birth, 30.1 [4.5] years; mean [SD] paternal age at birth, 32.5 [5.1] years). The conventional epidemiological analyses found evidence that birth weight was negatively associated with several domains at multiple offspring ages (outcome of autism-related trait scores: Social Communication Questionnaire [SCQ]-full at 3 years, ß = -0.046 [95% CI, -0.057 to -0.034]; SCQ-Restricted and Repetitive Behaviors subscale at 3 years, ß = -0.049 [95% CI, -0.060 to -0.038]; attention-deficit/hyperactivity disorder [ADHD] trait scores: Child Behavior Checklist [CBCL]-ADHD subscale at 18 months, ß = -0.035 [95% CI, -0.045 to -0.024]; CBCL-ADHD at 3 years, ß = -0.032 [95% CI, -0.043 to -0.021]; CBCL-ADHD at 5 years, ß = -0.050 [95% CI, -0.064 to -0.037]; Rating Scale for Disruptive Behavior Disorders [RS-DBD]-ADHD at 8 years, ß = -0.036 [95% CI, -0.049 to -0.023]; RS-DBD-Inattention at 8 years, ß = -0.037 [95% CI, -0.050 to -0.024]; RS-DBD-Hyperactive-Impulsive Behavior at 8 years, ß = -0.027 [95% CI, -0.040 to -0.014]; Conners Parent Rating Scale-Revised [Short Form] at 5 years, ß = -0.041 [95% CI, -0.054 to -0.028]; motor scores: Ages and Stages Questionnaire-Motor Difficulty [ASQ-MOTOR] at 18 months, ß = -0.025 [95% CI, -0.035 to -0.015]; ASQ-MOTOR at 3 years, ß = -0.029 [95% CI, -0.040 to -0.018]; and Child Development Inventory-Gross and Fine Motor Skills at 5 years, ß = -0.028 [95% CI, -0.042 to -0.015]). Mendelian randomization analyses did not find any evidence for an association between maternal allele scores for birth weight and offspring neurodevelopmental difficulties. Conclusions and Relevance: This study found that the maternal intrauterine environment, as proxied by maternal birth weight genetic variants, is unlikely to be a major determinant of offspring neurodevelopmental outcomes.

Genome-wide association study of placental weight identifies distinct and shared genetic influences between placental and fetal growth.

A well-functioning placenta is essential for fetal and maternal health throughout pregnancy. Using placental weight as a proxy for placental growth, we report genome-wide association analyses in the fetal (n = 65,405), maternal (n = 61,228) and paternal (n = 52,392) genomes, yielding 40 independent association signals. Twenty-six signals are classified as fetal, four maternal and three fetal and maternal. A maternal parent-of-origin effect is seen near KCNQ1. Genetic correlation and colocalization analyses reveal overlap with birth weight genetics, but 12 loci are classified as predominantly or only affecting placental weight, with connections to placental development and morphology, and transport of antibodies and amino acids. Mendelian randomization analyses indicate that fetal genetically mediated higher placental weight is causally associated with preeclampsia risk and shorter gestational duration. Moreover, these analyses support the role of fetal insulin in regulating placental weight, providing a key link between fetal and placental growth.

Direct and INdirect effects analysis of Genetic lOci (DINGO): A software package to increase the power of locus discovery in GWAS meta-analyses of perinatal phenotypes and traits influenced by indirect genetic effects.

Perinatal traits are influenced by genetic variants from both fetal and maternal genomes. Genome-wide association studies (GWAS) of these phenotypes have typically involved separate fetal and maternal scans, however, this approach may be inefficient as it does not utilize the information shared across the individual GWAS. In this manuscript we investigate the performance of three strategies to detect loci in maternal and fetal GWAS of the same trait: (i) the traditional strategy of analysing maternal and fetal GWAS separately; (ii) a novel two degree of freedom test which combines information from maternal and fetal GWAS; and (iii) a novel one degree of freedom test where signals from maternal and fetal GWAS are meta-analysed together conditional on the estimated sample overlap. We demonstrate through a combination of analytical formulae and data simulation that the optimal strategy depends on the extent of sample overlap/relatedness between the maternal and fetal GWAS, the correlation between own and offspring phenotypes, whether loci jointly exhibit fetal and maternal effects, and if so, whether these effects are directionally concordant. We apply our methods to summary results statistics from a recent GWAS meta-analysis of birth weight from deCODE, the UK Biobank and the Early Growth Genetics (EGG) consortium. Both the two degree of freedom (213 loci) and meta-analytic approach (226 loci) dramatically increase the number of robustly associated genetic loci for birth weight relative to separately analysing the scans (183 loci). Our best strategy identifies an additional 62 novel loci compared to the most recent published meta-analysis of birth weight and implicates both known and new biological pathways in the aetiology of the trait. We implement our methods in the online DINGO (Direct and INdirect effects analysis of Genetic lOci) software package, which allows users to perform one and/or two degree of freedom tests easily and computationally efficiently across the genome. We conclude that whilst the novel two degree of freedom test may be particularly useful for the analysis of certain perinatal phenotypes where many loci exhibit discordant maternal and fetal genetic effects, for most phenotypes, a simple meta-analytic strategy is likely to perform best, particularly in situations where maternal and fetal GWAS only partially overlap.

Genetic effects on the timing of parturition and links to fetal birth weight.

The timing of parturition is crucial for neonatal survival and infant health. Yet, its genetic basis remains largely unresolved. We present a maternal genome-wide meta-analysis of gestational duration (n = 195,555), identifying 22 associated loci (24 independent variants) and an enrichment in genes differentially expressed during labor. A meta-analysis of preterm delivery (18,797 cases, 260,246 controls) revealed six associated loci and large genetic similarities with gestational duration. Analysis of the parental transmitted and nontransmitted alleles (n = 136,833) shows that 15 of the gestational duration genetic variants act through the maternal genome, whereas 7 act both through the maternal and fetal genomes and 2 act only via the fetal genome. Finally, the maternal effects on gestational duration show signs of antagonistic pleiotropy with the fetal effects on birth weight: maternal alleles that increase gestational duration have negative fetal effects on birth weight. The present study provides insights into the genetic effects on the timing of parturition and the complex maternal-fetal relationship between gestational duration and birth weight.

Epigenome-wide association study of serum folate in maternal peripheral blood leukocytes.

Aim: To perform an epigenome-wide association study (EWAS) of serum folate in maternal blood. Methods: Cross-ancestry (Europeans = 302, South Asians = 161) and ancestry-specific EWAS in the EPIPREG cohort were performed, followed by methyl quantitative trait loci analysis and association with cardiometabolic phenotypes. Replication was attempted using maternal folate intake and blood methylation data from the MoBa study and verified if the findings were significant in a previous EWAS of maternal serum folate in cord blood. Results & conclusion: cg19888088 (cross-ancestry) in EBF3, cg01952260 (Europeans) and cg07077240 (South Asians) in HERC3 were associated with serum folate. cg19888088 and cg01952260 were associated with diastolic blood pressure. cg07077240 was associated with variants in CASC15. The findings were not replicated and were not significant in cord blood.

Cross-Ancestry DNA Methylation Marks of Insulin Resistance in Pregnancy: An Integrative Epigenome-Wide Association Study.

Although there are some epigenome-wide association studies (EWAS) of insulin resistance, for most of them authors did not replicate their findings, and most are focused on populations of European ancestry, limiting the generalizability. In the Epigenetics in Pregnancy (EPIPREG; n = 294 Europeans and 162 South Asians) study, we conducted an EWAS of insulin resistance in maternal peripheral blood leukocytes, with replication in the Born in Bradford (n = 879; n = 430 Europeans and 449 South Asians), Methyl Epigenome Network Association (MENA) (n = 320), and Botnia (n = 56) cohorts. In EPIPREG, we identified six CpG sites inversely associated with insulin resistance across ancestry, of which five were replicated in independent cohorts (cg02988288, cg19693031, and cg26974062 in TXNIP; cg06690548 in SLC7A11; and cg04861640 in ZSCAN26). From methylation quantitative trait loci analysis in EPIPREG, we identified gene variants related to all five replicated cross-ancestry CpG sites, which were associated with several cardiometabolic phenotypes. Mediation analyses suggested that the gene variants regulate insulin resistance through DNA methylation. To conclude, our cross-ancestry EWAS identified five CpG sites related to lower insulin resistance.

Using Genomic Structural Equation Modeling to Partition the Genetic Covariance Between Birthweight and Cardiometabolic Risk Factors into Maternal and Offspring Components in the Norwegian HUNT Study.

The Barker Hypothesis posits that adverse intrauterine environments result in fetal growth restriction and increased risk of cardiometabolic disease through developmental compensations. Here we introduce a new statistical model using the genomic SEM software that is capable of simultaneously partitioning the genetic covariation between birthweight and cardiometabolic traits into maternally mediated and offspring mediated contributions. We model the covariance between birthweight and later life outcomes, such as blood pressure, non-fasting glucose, blood lipids and body mass index in the Norwegian HUNT study, consisting of 15,261 mother-eldest offspring pairs with genetic and phenotypic data. Application of this model showed some evidence for maternally mediated effects of systolic blood pressure on offspring birthweight, and pleiotropy between birthweight and non-fasting glucose mediated through the offspring genome. This underscores the importance of genetic links between birthweight and cardiometabolic phenotypes and offer alternative explanations to environmentally based hypotheses for the phenotypic correlation between these variables.

Mendelian randomization study of maternal coffee consumption and its influence on birthweight, stillbirth, miscarriage, gestational age and pre-term birth.

BACKGROUND: Coffee consumption has been associated with several adverse pregnancy outcomes, although data from randomized-controlled trials are lacking. We investigate whether there is a causal relationship between coffee consumption and miscarriage, stillbirth, birthweight, gestational age and pre-term birth using Mendelian randomization (MR). METHODS: A two-sample MR study was performed using summary results data from a genome-wide association meta-analysis of coffee consumption (N = 91 462) from the Coffee and Caffeine Genetics Consortium. Outcomes included self-reported miscarriage (N = 49 996 cases and 174 109 controls from a large meta-analysis); the number of stillbirths [N = 60 453 from UK Biobank (UKBB)]; gestational age and pre-term birth (N = 43 568 from the 23andMe, Inc cohort) and birthweight (N = 297 356 reporting own birthweight and N = 210 248 reporting offspring's birthweight from UKBB and the Early Growth Genetics Consortium). Additionally, a one-sample genetic risk score (GRS) analysis of coffee consumption in UKBB women (N up to 194 196) and the Avon Longitudinal Study of Parents and Children (N up to 6845 mothers and 4510 children) and its relationship with offspring outcomes was performed. RESULTS: Both the two-sample MR and one-sample GRS analyses showed no change in risk of sporadic miscarriages, stillbirths, pre-term birth or effect on gestational age connected to coffee consumption. Although both analyses showed an association between increased coffee consumption and higher birthweight, the magnitude of the effect was inconsistent. CONCLUSION: Our results suggest that coffee consumption during pregnancy might not itself contribute to adverse outcomes such as stillbirth, sporadic miscarriages and pre-term birth or lower gestational age or birthweight of the offspring.

Insulin and Body Mass Index Decrease Serum Soluble Leptin Receptor Levels in Humans.

CONTEXT: Serum soluble leptin receptor (sOb-R) may protect against future type 2 diabetes or serve as a marker for protective features, but how sOb-R is regulated is largely unknown. OBJECTIVE: This work aimed to test how serum sOb-R is influenced by glucose, insulin, body fat, body mass index (BMI), food intake, and physical activity. METHODS: We performed an epidemiological triangulation combining cross-sectional, interventional, and Mendelian randomization study designs. In 5 independent clinical studies (n = 24-823), sOb-R was quantified in serum or plasma by commercial enzyme-linked immunosorbent assay kits using monoclonal antibodies. We performed mixed-model regression and 2-sample Mendelian randomization. RESULTS: In pooled, cross-sectional data, leveling by study, sOb-R was associated inversely with BMI (ß [95% CI] -0.19 [-0.21 to -0.17]), body fat (-0.12 [-0.14 to -0.10), and fasting C-peptide (-2.04 [-2.46 to -1.62]). sOb-R decreased in response to acute hyperinsulinemia during euglycemic glucose clamp in 2 independent clinical studies (-0.5 [-0.7 to -0.4] and -0.5 [-0.6 to -0.3]), and immediately increased in response to intensive exercise (0.18 [0.04 to 0.31]) and food intake (0.20 [0.06 to 0.34]). In 2-sample Mendelian randomization, higher fasting insulin and higher BMI were causally linked to lower sOb-R levels (inverse variance weighted, -1.72 [-2.86 to -0.58], and -0.20 [-0.36 to -0.04], respectively). The relationship between hyperglycemia and sOb-R was inconsistent in cross-sectional studies and nonsignificant in intervention studies, and 2-sample Mendelian randomization suggested no causal effect of fasting glucose on sOb-R. CONCLUSION: BMI and insulin both causally decreased serum sOb-R levels. Conversely, intensive exercise and food intake acutely increased sOb-R. Our results suggest that sOb-R is involved in short-term regulation of leptin signaling, either directly or indirectly, and that hyperinsulinemia may reduce leptin signaling.

Mendelian randomization analysis of factors related to ovulation and reproductive function and endometrial cancer risk.

BACKGROUND: Observational epidemiological studies suggest a link between several factors related to ovulation and reproductive function and endometrial cancer (EC) risk; however, it is not clear whether these relationships are causal, and whether the risk factors act independently of each other. The aim of this study was to investigate putative causal relationships between the number of live births, age at last live birth, and years ovulating and EC risk.  METHODS: We conducted a series of observational analyses to investigate various risk factors and EC risk in the UK Biobank (UKBB). Additionally, multivariate analysis was performed to elucidate the relationship between the number of live births, age at last live birth, and years ovulating and other related factors such as age at natural menopause, age at menarche, and body mass index (BMI). Secondly, we used Mendelian randomization (MR) to assess if these observed relationships were causal. Genome-wide significant single nucleotide polymorphisms (SNPs) were extracted from previous studies of woman's number of live births, age at menopause and menarche, and BMI. We conducted a genome-wide association analysis using the UKBB to identify SNPs associated with years ovulating, years using the contraceptive pill, and age at last live birth. RESULTS: We found evidence for a causal effect of the number of live births (inverse variance weighted (IVW) odds ratio (OR): 0.537, p = 0.006), the number of years ovulating (IVW OR: 1.051, p = 0.014), in addition to the known risk factors BMI, age at menarche, and age at menopause on EC risk in the univariate MR analyses. Due to the close relationships between these factors, we followed up with multivariable MR (MVMR) analysis. Results from the MVMR analysis showed that number of live births had a causal effect on EC risk (OR: 0.783, p = 0.036) independent of BMI, age at menarche and age at menopause. CONCLUSIONS: MVMR analysis showed that the number of live births causally reduced the risk of EC.

Using adopted individuals to partition indirect maternal genetic effects into prenatal and postnatal effects on offspring phenotypes.

Maternal genetic effects can be defined as the effect of a mother's genotype on the phenotype of her offspring, independent of the offspring's genotype. Maternal genetic effects can act via the intrauterine environment during pregnancy and/or via the postnatal environment. In this manuscript, we present a simple extension to the basic adoption design that uses structural equation modelling (SEM) to partition maternal genetic effects into prenatal and postnatal effects. We examine the power, utility and type I error rate of our model using simulations and asymptotic power calculations. We apply our model to polygenic scores of educational attainment and birth weight associated variants, in up to 5,178 adopted singletons, 943 trios, 2687 mother-offspring pairs, 712 father-offspring pairs and 347,980 singletons from the UK Biobank. Our results show the expected pattern of maternal genetic effects on offspring birth weight, but unexpectedly large prenatal maternal genetic effects on offspring educational attainment. Sensitivity and simulation analyses suggest this result may be at least partially due to adopted individuals in the UK Biobank being raised by their biological relatives. We show that accurate modelling of these sorts of cryptic relationships is sufficient to bring type I error rate under control and produce asymptotically unbiased estimates of prenatal and postnatal maternal genetic effects. We conclude that there would be considerable value in following up adopted individuals in the UK Biobank to determine whether they were raised by their biological relatives, and if so, to precisely ascertain the nature of these relationships. These adopted individuals could then be incorporated into informative statistical genetics models like the one described in our manuscript to further elucidate the genetic architecture of complex traits and diseases.

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.

Investigating a Potential Causal Relationship Between Maternal Blood Pressure During Pregnancy and Future Offspring Cardiometabolic Health.

Observational epidemiological studies have reported that higher maternal blood pressure (BP) during pregnancy is associated with increased future risk of offspring cardiometabolic disease. However, it is unclear whether this association represents a causal relationship through intrauterine mechanisms. We used a Mendelian randomization (MR) framework to examine the relationship between unweighted maternal genetic scores for systolic BP and diastolic BP and a range of cardiometabolic risk factors in the offspring of up to 29 708 genotyped mother-offspring pairs from the UKB study (UK Biobank) and the HUNT study (Trøndelag Health). We conducted similar analyses in up to 21 423 father-offspring pairs from the same cohorts. We confirmed that the BP-associated genetic variants from the general population sample also had similar effects on maternal BP during pregnancy in independent cohorts. We did not detect any association between maternal (or paternal) unweighted genetic scores and cardiometabolic offspring outcomes in the meta-analysis of UKB and HUNT after adjusting for offspring genotypes at the same loci. We find little evidence to support the notion that maternal BP is a major causal risk factor for adverse offspring cardiometabolic outcomes in later life.

Cohort profile: Epigenetics in Pregnancy (EPIPREG) - population-based sample of European and South Asian pregnant women with epigenome-wide DNA methylation (850k) in peripheral blood leukocytes.

Pregnancy is a valuable model to study the association between DNA methylation and several cardiometabolic traits, due to its direct potential to influence mother's and child's health. Epigenetics in Pregnancy (EPIPREG) is a population-based sample with the aim to study associations between DNA-methylation in pregnancy and cardiometabolic traits in South Asian and European pregnant women and their offspring. This cohort profile paper aims to present our sample with genetic and epigenetic data and invite researchers with similar cohorts to collaborative projects, such as replication of ours or their results and meta-analysis. In EPIPREG we have quantified epigenome-wide DNA methylation in maternal peripheral blood leukocytes in gestational week 28±1 in Europeans (n = 312) and South Asians (n = 168) that participated in the population-based cohort STORK Groruddalen, in Norway. DNA methylation was measured with Infinium MethylationEPIC BeadChip (850k sites), with technical validation of four CpG sites using bisulphite pyrosequencing in a subset (n = 30). The sample is well characterized with few missing data on e.g. genotype, universal screening for gestational diabetes, objectively measured physical activity, bioelectrical impedance, anthropometrics, biochemical measurements, and a biobank with maternal serum and plasma, urine, placenta tissue. In the offspring, we have repeated ultrasounds during pregnancy, cord blood, and anthropometrics up to 4 years of age. We have quantified DNA methylation in peripheral blood leukocytes in nearly all eligible women from the STORK Groruddalen study, to minimize the risk of selection bias. Genetic principal components distinctly separated Europeans and South Asian women, which fully corresponded with the self-reported ethnicity. Technical validation of 4 CpG sites from the methylation bead chip showed good agreement with bisulfite pyrosequencing. We plan to study associations between DNA methylation and cardiometabolic traits and outcomes.

Epigenetic signatures associated with maternal body mass index or gestational weight gain: a systematic review.

Maternal body mass index (BMI) and gestational weight gain (GWG) impacts both the mother's and the child's health, and epigenetic modifications have been suggested to mediate some of these effects in offspring. This systematic review aimed to summarize the current literature on associations between maternal BMI and GWG and epigenetic marks. We performed systematic searches in PubMed and EMBASE and manual searches of reference lists. We included 49 studies exploring the association between maternal BMI and/or GWG and DNA methylation or miRNA; 7 performed in maternal tissues, 13 in placental tissue and 38 in different offspring tissues. The most consistent findings were reported for the relationship between maternal BMI, in particular pre-pregnant BMI, and expression of miRNA Let-7d in both maternal blood and placental tissue, methylation of the gene HIF3A in umbilical cord blood and umbilical tissue, and with expression in the miR-210 target gene, BDNF in placental tissue and cord blood. Correspondingly, methylation of BDNF was also found in placental tissue and cord blood. The current evidence suggests that maternal BMI is associated with some epigenetic signatures in the mother, the placenta and her offspring, which could indicate that some of the effects proposed by the Developmental Origins of Health and Disease-hypothesis may be mediated by epigenetic marks. In conclusion, there is a need for large, well-designed studies and meta-analyses that can clarify the relationship between BMI, GWG and epigenetic changes.

A cautionary note on using Mendelian randomization to examine the Barker hypothesis and Developmental Origins of Health and Disease (DOHaD).

Recent studies have used Mendelian randomization (MR) to investigate the observational association between low birth weight (BW) and increased risk of cardiometabolic outcomes, specifically cardiovascular disease, glycemic traits, and type 2 diabetes (T2D), and inform on the validity of the Barker hypothesis. We used simulations to assess the validity of these previous MR studies, and to determine whether a better formulated model can be used in this context. Genetic and phenotypic data were simulated under a model of no direct causal effect of offspring BW on cardiometabolic outcomes and no effect of maternal genotype on offspring cardiometabolic risk through intrauterine mechanisms; where the observational relationship between BW and cardiometabolic risk was driven entirely by horizontal genetic pleiotropy in the offspring (i.e. offspring genetic variants affecting both BW and cardiometabolic disease simultaneously rather than a mechanism consistent with the Barker hypothesis). We investigated the performance of four commonly used MR analysis methods (weighted allele score MR (WAS-MR), inverse variance weighted MR (IVW-MR), weighted median MR (WM-MR), and MR-Egger) and a new approach, which tests the association between maternal genotypes related to offspring BW and offspring cardiometabolic risk after conditioning on offspring genotype at the same loci. We caution against using traditional MR analyses, which do not take into account the relationship between maternal and offspring genotypes, to assess the validity of the Barker hypothesis, as results are biased in favor of a causal relationship. In contrast, we recommend the aforementioned conditional analysis framework utilizing maternal and offspring genotypes as a valid test of not only the Barker hypothesis, but also to investigate hypotheses relating to the Developmental Origins of Health and Disease more broadly.

Investigating the causal effect of maternal vitamin B12 and folate levels on offspring birthweight.

BACKGROUND: Lower maternal serum vitamin B12 (B12) and folate levels have been associated with lower offspring birthweight, in observational studies. The aim of this study was to investigate whether this relationship is causal. METHODS: We performed two-sample Mendelian randomization (MR) using summary data on associations between genotype-B12 (10 genetic variants) or genotype-folate (four genetic variants) levels from: a genome-wide association study of 45 576 individuals (sample 1); and both maternal- and fetal-specific genetic effects on offspring birthweight from the latest Early Growth Genetics consortium meta-analysis with 297 356 individuals reporting their own birthweight and 210 248 women reporting their offspring's birthweight (sample 2). We used the inverse variance weighted method, and sensitivity analyses to account for pleiotropy, in addition to excluding a potentially pleiotropic variant in the FUT2 gene for B12 levels. RESULTS: We did not find evidence for a causal effect of maternal or fetal B12 levels on offspring birthweight. The results were consistent across the different methods. We found a positive causal effect of maternal folate levels on offspring birthweight [0.146 (0.065, 0.227), which corresponds to an increase in birthweight of 71 g per 1 standard deviation higher folate]. We found some evidence for a small inverse effect of fetal folate levels on their own birthweight [-0.051 (-0.100, -0.003)]. CONCLUSIONS: Our results are consistent with evidence from randomized controlled trials that higher maternal folate levels increase offspring birthweight. We did not find evidence for a causal effect of B12 levels on offspring birthweight, suggesting previous observational studies may have been confounded.

Blood-based epigenetic estimators of chronological age in human adults using DNA methylation data from the Illumina MethylationEPIC array.

BACKGROUND: Epigenetic clocks have been recognized for their precise prediction of chronological age, age-related diseases, and all-cause mortality. Existing epigenetic clocks are based on CpGs from the Illumina HumanMethylation450 BeadChip (450 K) which has now been replaced by the latest platform, Illumina MethylationEPIC BeadChip (EPIC). Thus, it remains unclear to what extent EPIC contributes to increased precision and accuracy in the prediction of chronological age. RESULTS: We developed three blood-based epigenetic clocks for human adults using EPIC-based DNA methylation (DNAm) data from the Norwegian Mother, Father and Child Cohort Study (MoBa) and the Gene Expression Omnibus (GEO) public repository: 1) an Adult Blood-based EPIC Clock (ABEC) trained on DNAm data from MoBa (n = 1592, age-span: 19 to 59 years), 2) an extended ABEC (eABEC) trained on DNAm data from MoBa and GEO (n = 2227, age-span: 18 to 88 years), and 3) a common ABEC (cABEC) trained on the same training set as eABEC but restricted to CpGs common to 450 K and EPIC. Our clocks showed high precision (Pearson correlation between chronological and epigenetic age (r) > 0.94) in independent cohorts, including GSE111165 (n = 15), GSE115278 (n = 108), GSE132203 (n = 795), and the Epigenetics in Pregnancy (EPIPREG) study of the STORK Groruddalen Cohort (n = 470). This high precision is unlikely due to the use of EPIC, but rather due to the large sample size of the training set. CONCLUSIONS: Our ABECs predicted adults' chronological age precisely in independent cohorts. As EPIC is now the dominant platform for measuring DNAm, these clocks will be useful in further predictions of chronological age, age-related diseases, and mortality.