Prenatal exposure to polycyclic aromatic hydrocarbons is not associated with behavior problems in preschool and early school-aged children: A prospective multi-cohort study.

BACKGROUND: Epidemiological study findings are inconsistent regarding associations between prenatal polycyclic aromatic hydrocarbon (PAH) exposures and childhood behavior. This study examined associations of prenatal PAH exposure with behavior at age 4-6 years in a large, diverse, multi-region prospective cohort. Secondary aims included examination of PAH mixtures and effect modification by child sex, breastfeeding, and child neighborhood opportunity. METHODS: The ECHO PATHWAYS Consortium pooled 1118 mother-child dyads from three prospective pregnancy cohorts in six U.S. cities. Seven PAH metabolites were measured in prenatal urine. Child behavior was assessed at age 4-6 using the Total Problems score from the Child Behavior Checklist (CBCL). Neighborhood opportunity was assessed using the socioeconomic and educational scales of the Child Opportunity Index. Multivariable linear regression was used to estimate associations per 2-fold increase in each PAH metabolite, adjusted for demographic, prenatal, and maternal factors and using interaction terms for effect modifiers. Associations with PAH mixtures were estimated using Weighted Quantile Sum Regression (WQSR). RESULTS: The sample was racially and sociodemographically diverse (38% Black, 49% White, 7% Other; household-adjusted income range $2651-$221,102). In fully adjusted models, each 2-fold increase in 2-hydroxynaphthalene was associated with a lower Total Problems score, contrary to hypotheses (b = -0.80, 95% CI = -1.51, -0.08). Associations were notable in boys (b = -1.10, 95% CI = -2.11, -0.08) and among children breastfed 6+ months (b = -1.31, 95% CI = -2.25, -0.37), although there was no statistically significant evidence for interaction by child sex, breastfeeding, or neighborhood child opportunity. Associations were null for other PAH metabolites; there was no evidence of associations with PAH mixtures from WQSR. CONCLUSION: In this large, well-characterized, prospective study of mother-child pairs, prenatal PAH exposure was not associated with child behavior problems. Future studies characterizing the magnitude of prenatal PAH exposure and studies in older childhood are needed

Placental transcriptomic signatures of spontaneous preterm birth.

BACKGROUND: Spontaneous preterm birth accounts for most preterm births and leads to significant morbidity in the newborn and childhood period. This subtype of preterm birth represents an increasing proportion of all preterm births when compared with medically indicated preterm birth, yet it is understudied in omics analyses. The placenta is a key regulator of fetal and newborn health, and the placental transcriptome can provide insight into pathologic changes that lead to spontaneous preterm birth. OBJECTIVE: This analysis aimed to identify genes for which placental expression was associated with spontaneous preterm birth (including early preterm and late preterm birth). STUDY DESIGN: The ECHO PATHWAYS consortium extracted RNA from placental samples collected from the Conditions Affecting Neurocognitive Development and Learning in Early Childhood and the Global Alliance to Prevent Prematurity and Stillbirth studies. Placental transcriptomic data were obtained by RNA sequencing. Linear models were fit to estimate differences in placental gene expression between term birth and spontaneous preterm birth (including gestational age subgroups defined by the American College of Obstetricians and Gynecologists). Models were adjusted for numerous confounding variables, including labor status, cohort, and RNA sequencing batch. This analysis excluded patients with induced labor, chorioamnionitis, multifetal gestations, or medical indications for preterm birth. Our combined cohort contained gene expression data for 14,023 genes in 48 preterm and 540 term samples. Genes and pathways were considered statistically significantly different at false discovery rate-adjusted P value of <.05. RESULTS: In total, we identified 1728 genes for which placental expression was associated with spontaneous preterm birth with more differences in expression in early preterm samples than late preterm samples when compared with full-term samples. Of those, 9 genes were significantly decreased in both early and late spontaneous preterm birth, and the strongest associations involved placental expression of IL1B, ALPL, and CRLF1. In early and late preterm samples, we observed decreased expression of genes involved in immune signaling, signal transduction, and endocrine function. CONCLUSION: This study provides a comprehensive assessment of the differences in the placental transcriptome associated with spontaneous preterm birth with robust adjustment for confounding. Results of this study are in alignment with the known etiology of spontaneous preterm birth, because we identified multiple genes and pathways for which the placental and chorioamniotic membrane expression was previously associated with prematurity, including IL1B. We identified decreased expression in key signaling pathways that are essential for placental growth and function, which may be related to the etiology of spontaneous preterm birth. We identified increased expression of genes within metabolic pathways associated exclusively with early preterm birth. These signaling and metabolic pathways may provide clinically targetable pathways and biomarkers. The findings presented here can be used to understand underlying pathologic changes in premature placentas, which can inform and improve clinical obstetrics practice

Quantifying cancer risk from exposures to medical imaging in the Risk of Pediatric and Adolescent Cancer Associated with Medical Imaging (RIC) Study: research methods and cohort profile

PurposeThe Risk of Pediatric and Adolescent Cancer Associated with Medical Imaging (RIC) Study is quantifying the association between cumulative radiation exposure from fetal and/or childhood medical imaging and subsequent cancer risk. This manuscript describes the study cohorts and research methods.MethodsThe RIC Study is a longitudinal study of children in two retrospective cohorts from 6 U.S. healthcare systems and from Ontario, Canada over the period 1995-2017. The fetal-exposure cohort includes children whose mothers were enrolled in the healthcare system during their entire pregnancy and followed to age 20. The childhood-exposure cohort includes children born into the system and followed while continuously enrolled. Imaging utilization was determined using administrative data. Computed tomography (CT) parameters were collected to estimate individualized patient organ dosimetry. Organ dose libraries for average exposures were constructed for radiography, fluoroscopy, and angiography, while diagnostic radiopharmaceutical biokinetic models were applied to estimate organ doses received in nuclear medicine procedures. Cancers were ascertained from local and state/provincial cancer registry linkages.ResultsThe fetal-exposure cohort includes 3,474,000 children among whom 6,606 cancers (2394 leukemias) were diagnosed over 37,659,582 person-years; 0.5% had in utero exposure to CT, 4.0% radiography, 0.5% fluoroscopy, 0.04% angiography, 0.2% nuclear medicine. The childhood-exposure cohort includes 3,724,632 children in whom 6,358 cancers (2,372 leukemias) were diagnosed over 36,190,027 person-years; 5.9% were exposed to CT, 61.1% radiography, 6.0% fluoroscopy, 0.4% angiography, 1.5% nuclear medicine.ConclusionThe RIC Study is poised to be the largest study addressing risk of childhood and adolescent cancer associated with ionizing radiation from medical imaging, estimated with individualized patient organ dosimetry

Whole-exome sequence analysis of anthropometric traits illustrates challenges in identifying effects of rare genetic variants

Anthropometric traits, measuring body size and shape, are highly heritable and significant clinical risk factors for cardiometabolic disorders. These traits have been extensively studied in genome-wide association studies (GWASs), with hundreds of genome-wide significant loci identified. We performed a whole-exome sequence analysis of the genetics of height, body mass index (BMI) and waist/hip ratio (WHR). We meta-analyzed single-variant and gene-based associations of whole-exome sequence variation with height, BMI, and WHR in up to 22,004 individuals, and we assessed replication of our findings in up to 16,418 individuals from 10 independent cohorts from Trans-Omics for Precision Medicine (TOPMed). We identified four trait associations with single-nucleotide variants (SNVs; two for height and two for BMI) and replicated the LECT2 gene association with height. Our expression quantitative trait locus (eQTL) analysis within previously reported GWAS loci implicated CEP63 and RFT1 as potential functional genes for known height loci. We further assessed enrichment of SNVs, which were monogenic or syndromic variants within loci associated with our three traits. This led to the significant enrichment results for height, whereas we observed no Bonferroni-corrected significance for all SNVs. With a sample size of ∼20,000 whole-exome sequences in our discovery dataset, our findings demonstrate the importance of genomic sequencing in genetic association studies, yet they also illustrate the challenges in identifying effects of rare genetic variants

A System for Phenotype Harmonization in the NHLBI Trans-Omics for Precision Medicine (TOPMed) Program

Genotype-phenotype association studies often combine phenotype data from multiple studies to increase statistical power. Harmonization of the data usually requires substantial effort due to heterogeneity in phenotype definitions, study design, data collection procedures, and data-set organization. Here we describe a centralized system for phenotype harmonization that includes input from phenotype domain and study experts, quality control, documentation, reproducible results, and data-sharing mechanisms. This system was developed for the National Heart, Lung, and Blood Institute's Trans-Omics for Precision Medicine (TOPMed) program, which is generating genomic and other -omics data for more than 80 studies with extensive phenotype data. To date, 63 phenotypes have been harmonized across thousands of participants (recruited in 1948-2012) from up to 17 studies per phenotype. Here we discuss challenges in this undertaking and how they were addressed. The harmonized phenotype data and associated documentation have been submitted to National Institutes of Health data repositories for controlled access by the scientific community. We also provide materials to facilitate future harmonization efforts by the community, which include 1) the software code used to generate the 63 harmonized phenotypes, enabling others to reproduce, modify, or extend these harmonizations to additional studies, and 2) the results of labeling thousands of phenotype variables with controlled vocabulary terms

Whole Genome Sequence Analysis of the Plasma Proteome in Black Adults Provides Novel Insights Into Cardiovascular Disease

BackgroundPlasma proteins are critical mediators of cardiovascular processes and are the targets of many drugs. Previous efforts to characterize the genetic architecture of the plasma proteome have been limited by a focus on individuals of European descent and leveraged genotyping arrays and imputation. Here we describe whole genome sequence analysis of the plasma proteome in individuals with greater African ancestry, increasing our power to identify novel genetic determinants.MethodsProteomic profiling of 1301 proteins was performed in 1852 Black adults from the Jackson Heart Study using aptamer-based proteomics (SomaScan). Whole genome sequencing association analysis was ascertained for all variants with minor allele count ≥5. Results were validated using an alternative, antibody-based, proteomic platform (Olink) as well as replicated in the Multi-Ethnic Study of Atherosclerosis and the HERITAGE Family Study (Health, Risk Factors, Exercise Training and Genetics).ResultsWe identify 569 genetic associations between 479 proteins and 438 unique genetic regions at a Bonferroni-adjusted significance level of 3.8×10-11. These associations include 114 novel locus-protein relationships and an additional 217 novel sentinel variant-protein relationships. Novel cardiovascular findings include new protein associations at the APOE gene locus including ZAP70 (sentinel single nucleotide polymorphism [SNP] rs7412-T, β=0.61±0.05, P=3.27×10-30) and MMP-3 (β=-0.60±0.05, P=1.67×10-32), as well as a completely novel pleiotropic locus at the HPX gene, associated with 9 proteins. Further, the associations suggest new mechanisms of genetically mediated cardiovascular disease linked to African ancestry; we identify a novel association between variants linked to APOL1-associated chronic kidney and heart disease and the protein CKAP2 (rs73885319-G, β=0.34±0.04, P=1.34×10-17) as well as an association between ATTR amyloidosis and RBP4 levels in community-dwelling individuals without heart failure.ConclusionsTaken together, these results provide evidence for the functional importance of variants in non-European populations, and suggest new biological mechanisms for ancestry-specific determinants of lipids, coagulation, and myocardial function

Inherited causes of clonal haematopoiesis in 97,691 whole genomes.

Age is the dominant risk factor for most chronic human diseases, but the mechanisms through which ageing confers this risk are largely unknown1. The age-related acquisition of somatic mutations that lead to clonal expansion in regenerating haematopoietic stem cell populations has recently been associated with both haematological cancer2-4 and coronary heart disease5-this phenomenon is termed clonal haematopoiesis of indeterminate potential (CHIP)6. Simultaneous analyses of germline and somatic whole-genome sequences provide the opportunity to identify root causes of CHIP. Here we analyse high-coverage whole-genome sequences from 97,691 participants of diverse ancestries in the National Heart, Lung, and Blood Institute Trans-omics for Precision Medicine (TOPMed) programme, and identify 4,229 individuals with CHIP. We identify associations with blood cell, lipid and inflammatory traits that are specific to different CHIP driver genes. Association of a genome-wide set of germline genetic variants enabled the identification of three genetic loci associated with CHIP status, including one locus at TET2 that was specific to individuals of African ancestry. In silico-informed in vitro evaluation of the TET2 germline locus enabled the identification of a causal variant that disrupts a TET2 distal enhancer, resulting in increased self-renewal of haematopoietic stem cells. Overall, we observe that germline genetic variation shapes haematopoietic stem cell function, leading to CHIP through mechanisms that are specific to clonal haematopoiesis as well as shared mechanisms that lead to somatic mutations across tissues