Childhood vascular phenotypes have differing associations with pre- and postnatal growth

Objective: In children aged 8--9 years, we examined the associations of linear and abdominal circumference growth during critical stages of prenatal and postnatal development with six vascular measurements commonly used as early markers of atherosclerosis and later cardiovascular disease (CVD) risk. Methods: In 724 children from the UK Southampton Women's Survey mother--offspring cohort, offspring length/height and abdominal circumference measurements were collected at 10 ages between 11 weeks’ gestation and age 8--9 years. Using residual growth modelling and linear regression, we examined the independent associations between growth and detailed vascular measures made at 8--9 years. Results: Postnatal linear and abdominal circumference growth were associated with higher childhood SBP and carotid--femoral pulse wave velocity, whereas prenatal growth was not. For example, 1SD faster abdominal circumference gain between ages 3 and 6 years was associated with 2.27 [95% confidence interval (CI): 1.56--2.98] mmHg higher SBP. In contrast, faster abdominal circumference gain before 19 weeks’ gestation was associated with greater carotid intima--media thickness [0.009 mm (0.004--0.015) per 1SD larger 19-week abdominal circumference), whereas later growth was not. We found no strong associations between prenatal or postnatal growth and DBP or measures of endothelial function. Conclusion: Higher postnatal linear growth and adiposity gain are related to higher SBP and carotid--femoral pulse wave velocity in childhood. In contrast, faster growth in early gestation is associated with greater childhood carotid intima--media thickness, perhaps resulting from subtle changes in vascular structure that reflect physiological adaptations rather than subclinical atherosclerosis

Childhood fat and lean mass: differing relations to vascular structure and function at age 8-9-years

OBJECTIVE— Childhood body mass index (BMI) has been related to vascular structure and function. However, little is known about the differing contributions of fat and lean mass to this relationship. Our objectives were to relate the fat and lean mass (bone excluded) components of BMI (fat mass index and lean mass index; mass [kg]/height [m]2) to vascular measures in prepubertal children. APPROACH AND RESULTS— In the UK Southampton Women’s Survey mother-offspring cohort, 983 children had dual x-ray absorptiometry and vascular measurements at 8 to 9 years. Using linear regression analyses, we found that most vascular measures were related to BMI, but fat and lean mass contributed differently. Systolic blood pressure was positively associated with both fat mass index (β=0.91 [95% CI, 0.52–1.30] mm Hg) and lean mass index (β=2.16 [95% CI, 1.47–2.85] mm Hg), whereas pulse rate was positively associated with fat mass index (β=0.93 [95% CI, 0.48–1.38] b/min) but negatively associated with lean mass index (β=−1.79 [95% CI, −2.59 to −0.99] b/min). The positive relation between BMI and carotid intima-media thickness was mainly due to a positive association with lean mass index (β=0.013 [95% CI, 0.008–0.019] mm). Carotid-femoral pulse wave velocity, but not carotid-radial pulse wave velocity, was positively associated with fat mass index (β=0.06 [95% CI, 0.03–0.09] m/s). For systolic blood pressure, carotid-femoral pulse wave velocity and reactive hyperemia significant interactions indicated that the association with fat mass depended on the amount of lean mass. CONCLUSIONS— In prepubertal children, differences in vascular structure and function in relation to BMI probably represent combinations of adverse effects of fat mass, adaptive effects of body size, and relatively protective effects of lean mass

Impact of ethnicity on gestational diabetes identified with the WHO and the modified International Association of Diabetes and Pregnancy Study Groups criteria: a population-based cohort study

Objective The International Association of Diabetes and Pregnancy Study Groups (IADPSG) recently proposed new criteria for diagnosing gestational diabetes mellitus (GDM). We compared prevalence rates, risk factors, and the effect of ethnicity using the World Health Organization (WHO) and modified IADPSG criteria. Methods This was a population-based cohort study of 823 (74% of eligible) healthy pregnant women, of whom 59% were from ethnic minorities. Universal screening was performed at 28±2 weeks of gestation with the 75 g oral glucose tolerance test (OGTT). Venous plasma glucose (PG) was measured on site. GDM was diagnosed as per the definition of WHO criteria as fasting PG (FPG) ≥7.0 or 2-h PG ≥7.8 mmol/l; and as per the modified IADPSG criteria as FPG ≥5.1 or 2-h PG ≥8.5 mmol/l. Results OGTT was performed in 759 women. Crude GDM prevalence was 13.0% with WHO (Western Europeans 11%, ethnic minorities 15%, P=0.14) and 31.5% with modified IADPSG criteria (Western Europeans 24%, ethnic minorities 37%, P< 0.001). Using the WHO criteria, ethnic minority origin was an independent predictor (South Asians, odds ratio (OR) 2.24 (95% confidence interval (CI) 1.26–3.97); Middle Easterners, OR 2.13 (1.12–4.08)) after adjustments for age, parity, and prepregnant body mass index (BMI). This increased OR was unapparent after further adjustments for body height (proxy for early life socioeconomic status), education and family history of diabetes. Using the modified IADPSG criteria, prepregnant BMI (1.09 (1.05–1.13)) and ethnic minority origin (South Asians, 2.54 (1.56–4.13)) were independent predictors, while education, body height and family history had little impact. Conclusion GDM prevalence was overall 2.4-times higher with the modified IADPSG criteria compared with the WHO criteria. The new criteria identified many subjects with a relatively mild increase in FPG, strongly associated with South Asian origin and prepregnant overweigh

External validation of prognostic models to predict stillbirth using the International Prediction of Pregnancy Complications (IPPIC) Network database: an individual participant data meta-analysis

Objective Stillbirth is a potentially preventable complication of pregnancy. Identifying women at high risk of stillbirth can guide decisions on the need for closer surveillance and timing of delivery in order to prevent fetal death. Prognostic models have been developed to predict the risk of stillbirth, but none has yet been validated externally. In this study, we externally validated published prediction models for stillbirth using individual participant data (IPD) meta-analysis to assess their predictive performance. Methods MEDLINE, EMBASE, DH-DATA and AMED databases were searched from inception to December 2020 to identify studies reporting stillbirth prediction models. Studies that developed or updated prediction models for stillbirth for use at any time during pregnancy were included. IPD from cohorts within the International Prediction of Pregnancy Complications (IPPIC) Network were used to validate externally the identified prediction models whose individual variables were available in the IPD. The risk of bias of the models and cohorts was assessed using the Prediction study Risk Of Bias ASsessment Tool (PROBAST). The discriminative performance of the models was evaluated using the C-statistic, and calibration was assessed using calibration plots, calibration slope and calibration-in-the-large. Performance measures were estimated separately in each cohort, as well as summarized across cohorts using random-effects meta-analysis. Clinical utility was assessed using net benefit. Results Seventeen studies reporting the development of 40 prognostic models for stillbirth were identified. None of the models had been previously validated externally, and the full model equation was reported for only one-fifth (20%, 8/40) of the models. External validation was possible for three of these models, using IPD from 19 cohorts (491 201 pregnant women) within the IPPIC Network database. Based on evaluation of the model development studies, all three models had an overall high risk of bias, according to PROBAST. In the IPD meta-analysis, the models had summary C-statistics ranging from 0.53 to 0.65 and summary calibration slopes ranging from 0.40 to 0.88, with risk predictions that were generally too extreme compared with the observed risks. The models had little to no clinical utility, as assessed by net benefit. However, there remained uncertainty in the performance of some models due to small available sample sizes. Conclusions The three validated stillbirth prediction models showed generally poor and uncertain predictive performance in new data, with limited evidence to support their clinical application. The findings suggest methodological shortcomings in their development, including overfitting. Further research is needed to further validate these and other models, identify stronger prognostic factors and develop more robust prediction models. (c) 2021 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.Peer reviewe

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

This is the final version. Available from Nature Research via the DOI in this record. Data availability: Cohorts should be contacted individually for access to raw genotype and phenotype data, as each cohort has different data access policies. Summary statistics from the meta-analysis, excluding 23andMe, are available at the EGG website (https://egg-consortium.org/), and access to the weights for constructing the polygenic score of gestational duration excluding 23andMe are available at the PGS Catalog (https://www.pgscatalog.org/, score ID: PGS002806). Access to the full set, including 23andMe results, can be obtained after approval from 23andMe is presented to the corresponding author or by completion of a Data Transfer Agreement (https://research.23andme.com/dataset-access/), which exists to protect the privacy of 23andMe participants. Access to the Danish National Birth Cohort (phs000103.v1.p1), Hyperglycemia and Adverse Pregnancy Outcome (phs000096.v4.p1) and Genomic and Proteomic Network (phs000714.v1.p1) individual-level phenotype and genetic data can be obtained through dbGaP Authorized Access portal (https://dbgap.ncbi.nlm.nih.gov/dbgap/aa/wga.cgi?page=login). The informed consent under which the data or samples were collected is the basis for determining the appropriateness of sharing data through unrestricted-access databases or NIH-designated controlled-access data repositories. The summary statistics used in this publication other than the one generated are available at the following links: fetal GWAS of gestational duration (http://egg-consortium.org/gestational-duration-2019.html), fetal and maternal GWAS of birth weight (http://egg-consortium.org/birth-weight-2019.html), miscarriage (http://www.geenivaramu.ee/tools/misc_sumstats.zip), age at first birth, estradiol (women), endometriosis, number of live births and age at menarche (http://www.nealelab.is), age at menopause (https://www.reprogen.org), testosterone (women)58, SHBG, testosterone and CBAT (https://doi.org/10.6084/m9.figshare.c.5304500.v1), pelvic organ prolapse and leiomyoma of the uterus (https://www.finngen.fi/fi), polycystic ovary syndrome (https://www.repository.cam.ac.uk/handle/1810/283491 and https://www.finngen.fi/fi) and pre-eclampsia (European Genome-phenome Archive, https://ega-archive.org, EGAD00010001984). Pan-UK Biobank data are available at https://pan.ukbb.broadinstitute.org/. Precomputed LD scores for European populations (https://data.broadinstitute.org/alkesgroup/LDSCORE/eur_w_ld_chr.tar.bz2) and multi-tissue gene expression precomputed stratified LD scores (https://alkesgroup.broadinstitute.org/LDSCORE/LDSC_SEG_ldscores/Multi_tissue_gene_expr_1000Gv3_ldscores.tgz) are available. eQTL data from GTEx are available at https://gtexportal.org/home/ and from endometrium at http://reproductivegenomics.com.au/shiny/endo_eqtl_rna/. Protein QTL data were obtained from https://www.omicscience.org/apps/pgwas/. Genome Reference Consortium Human Build 37 (hg19) available at https://www.ncbi.nlm.nih.gov/data-hub/genome/GCF_000001405.13/.Code availability: Code for this project has been structured using a Snakemake workflow65 and is available at https://github.com/PerinatalLab/metaGWAS. A public release of it has been deposited in Zenodo (https://doi.org/10.5281/zenodo.7311977).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.Swedish Research CouncilSwedish Research CouncilResearch Council of NorwayResearch Council of NorwayMarch of Dimesunice Kennedy Shriver National Institute Of Child Health & Human Development of the National Institutes of HealthNorwegian Diabetes AssociationNils Normans minnegaveNorwegian Research CouncilMedical Research CouncilBritish Heart FoundationResearch Council of NorwayBritish Heart FoundationDaniel B. Burke Chair for Diabetes Research and NIHCHOPEuropean Regional Development Fund and the programme Mobilitas PlussWellcome Trust and Royal Society Sir Henry Dale FellowshipWellcome TrustOak FoundationFonds de la recherche du Québec en santéUS National Institutes of HealthNovo Nordisk FoundationNovo Nordisk FoundationNovo Nordisk Foundatio

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

BackgroundEpigenetic 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 (450K) 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.ResultsWe 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 59years), 2) an extended ABEC (eABEC) trained on DNAm data from MoBa and GEO (n=2227, age-span: 18 to 88years), and 3) a common ABEC (cABEC) trained on the same training set as eABEC but restricted to CpGs common to 450K 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.ConclusionsOur 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.Peer reviewe