Non-parental Childcare During Early Childhood and Problem Behaviour Trajectories from Ages 5 to 14 Years.

Using data from the nationally representative Millennium Cohort Study, this study examined the association between age of starting and weekly hours in formal childcare between birth and 5 years with internalising and externalising behaviour trajectories from ages 5 to 14 years in England (N = 6194 children). Associations were analysed using multilevel general linear regression models, with adjustment for socio-economic position, maternal mental health, demographics, and child temperament. Later entry was associated with more internalising behaviours at age 14 years. Children who spent > 40 h per week in childcare between birth and 3 years displayed more externalising behaviour at 5 years than children who did not attend childcare. Controlling for socio-economic position and parental mental health attenuated findings.

A case report of lobular intradural extramedullary capillary hemangioma in a 14-year-old patient: resection and reconstruction.

Background: Intradural, extramedullary capillary hemangiomas of the cauda equina are exceedingly rare malformations arising from the endothelial cells of the nervous system vasculature. Roughly 20 cases have been reported in the literature, with the youngest and only pediatric case being in a 17-year-old patient. We report the youngest case of intradural extramedullary capillary hemangioma of the cauda equina in a 14-year-old patient. Case Description: A 14-year-old female presented with two-month history of low back pain with bilateral leg pain and numbness. Magnetic resonance imaging (MRI) revealed an L2 well-defined homogenous contrast-enhancing intradural, extramedullary mass causing severe spinal canal stenosis. Patient underwent laminoplasty for resection of an intradural tumor. Intraoperative hemostasis was readily achieved via early identification and coagulation of the predominate feeding vessel. Postoperatively, the patient awoke with no deficits and resolved leg pain. A 3-month postoperative MRI revealed no tumor recurrence and fully healed lamina. Conclusions: Given the benign nature, the operative goal is complete excision of the tumor without damage to surrounding neural structures. Postoperatively the goal is relief of pain and improvement in neurologic function. To our knowledge we report the first case in which laminoplasty is utilized for the treatment of this pathology in a pediatric patient. Evidence for laminoplasty in this patient population is sparse and future studies are still needed. In any case, reconstruction of the surgical site in a manner that returns the patient's normal anatomy should be strongly considered especially in younger patients.

Interaction molecular QTL mapping discovers cellular and environmental modifiers of genetic regulatory effects.

Bulk-tissue molecular quantitative trait loci (QTLs) have been the starting point for interpreting disease-associated variants, and context-specific QTLs show particular relevance for disease. Here, we present the results of mapping interaction QTLs (iQTLs) for cell type, age, and other phenotypic variables in multi-omic, longitudinal data from the blood of individuals of diverse ancestries. By modeling the interaction between genotype and estimated cell-type proportions, we demonstrate that cell-type iQTLs could be considered as proxies for cell-type-specific QTL effects, particularly for the most abundant cell type in the tissue. The interpretation of age iQTLs, however, warrants caution because the moderation effect of age on the genotype and molecular phenotype association could be mediated by changes in cell-type composition. Finally, we show that cell-type iQTLs contribute to cell-type-specific enrichment of diseases that, in combination with additional functional data, could guide future functional studies. Overall, this study highlights the use of iQTLs to gain insights into the context specificity of regulatory effects.

Trends in childhood body mass index between 1936 and 2011 showed that underweight remained more common than obesity among 398 970 Danish school children.

AIM: To examine trends in all body mass index (BMI) groups in children from 1936 to 2011. METHODS: We included 197 694 girls and 201 276 boys from the Copenhagen School Health Records Register, born between 1930 and 1996, with longitudinal weight and height measurements (6-14 years). Using International Obesity Task Force criteria, BMI was classified as underweight, normal-weight, overweight and obesity. Sex- and age-specific prevalences were calculated. RESULTS: From the 1930s, the prevalence of underweight was stable until a small increase occurred from 1950 to 1970s, and thereafter it declined into the early 2000s. Using 7-year-olds as an example, underweight changed from 10% to 7% in girls and from 9% to 6% in boys during the study period. The prevalence of overweight plateaued from 1950 to 1970s and then steeply increased from 1970s onwards and in 1990-2000s 15% girls and 11% boys at 7 years had overweight. The prevalence of obesity particularly increased from 1980s onwards and in 1990-2000s 5% girls and 4% boys at 7 years had obesity. These trends slightly differed by age. CONCLUSION: Among Danish schoolchildren, the prevalence of underweight was greater than overweight until the 1980s and greater than obesity throughout the period. Thus, monitoring the prevalence of childhood underweight remains an important public health issue.

Contaminants of Concern and Spatiotemporal Metabolomic Changes in Quagga Mussels (Dreissena bugensis rostriformis) from the Milwaukee Estuary (Wisconsin, USA).

Environmental metabolomics has emerged as a promising technique in the field of biomonitoring and as an indicator of aquatic ecosystem health. In the Milwaukee Estuary (Wisconsin, USA), previous studies have used a nontargeted metabolomic approach to distinguish between zebra mussels (Dreissena polymorpha) collected from sites of varying contamination. To further elucidate the potential effects of contaminants on bivalve health in the Milwaukee Estuary, the present study adopted a caging approach to study the metabolome of quagga mussels (Dreissena bugensis rostriformis) deployed in six sites of varying contamination for 2, 5, or 55 days. Caged mussels were co-deployed with two types of passive sampler (polar organic chemical integrative samplers and semipermeable membrane devices) and data loggers. In conjunction, in situ quagga mussels were collected from the four sites studied previously and analyzed for residues of contaminants and metabolomics using a targeted approach. For the caging study, temporal differences in the metabolomic response were observed with few significant changes observed after 2 and 5 days, but larger differences (up to 97 significantly different metabolites) to the metabolome in all sites after 55 days. A suite of metabolic pathways were altered, including biosynthesis and metabolism of amino acids, and upmodulation of phospholipids at all sites, suggesting a potential biological influence such as gametogenesis. In the caging study, average temperatures appeared to have a greater effect on the metabolome than contaminants, despite a large concentration gradient in polycyclic aromatic hydrocarbons residues measured in passive samplers and mussel tissue. Conversely, significant differences between the metabolome of mussels collected in situ from all three contaminated sites and the offshore reference site were observed. Overall, these findings highlight the importance of contextualizing the effects of environmental conditions and reproductive processes on the metabolome of model organisms to facilitate the wider use of this technique for biomonitoring and environmental health assessments. Environ Toxicol Chem 2024;43:307-323. © 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

Psychosocial stressors and breast cancer gene expression in the Black Women's Health Study.

PURPOSE: Prior studies indicate that the physiologic response to stress can affect gene expression. We evaluated differential gene expression in breast cancers collected from Black women with high versus low exposure to psychosocial stressors. METHODS: We analyzed tumor RNA sequencing data from 417 Black Women's Health Study breast cancer cases with data on early life trauma and neighborhood disadvantage. We conducted age-adjusted differential gene expression analyses and pathway analyses. We also evaluated Conserved Transcriptional Response to Adversity (CTRA) contrast scores, relative fractions of immune cell types, T cell exhaustion, and adrenergic signaling. Analyses were run separately for estrogen receptor positive (ER+; n = 299) and ER- (n = 118) cases. RESULTS: Among ER+ cases, the top differentially expressed pathways by stress exposure were related to RNA and protein metabolism. Among ER- cases, they were related to developmental biology, signal transduction, metabolism, and the immune system. Targeted analyses indicated greater immune pathway enrichment with stress exposure for ER- cases, and possible relevance of adrenergic signaling for ER+ cases. CTRA contrast scores did not differ by stress exposure, but in analyses of the CTRA components, ER- breast cancer cases with high neighborhood disadvantage had higher pro-inflammatory gene expression (p = 0.039) and higher antibody gene expression (p = 0.006) compared to those with low neighborhood disadvantage. CONCLUSION: There are multiple pathways through which psychosocial stress exposure may influence breast tumor biology. Given the present findings on inflammation and immune response in ER- tumors, further research to identify stress-induced changes in the etiology and progression of ER- breast cancer is warranted.

Untargeted Metabolomics Analyses and Contaminant Chemistry of Dreissenid Mussels at the Maumee River Area of Concern in the Great Lakes.

Bivalves serve as an ideal ecological indicator; hence, their use by the NOAA Mussel Watch Program to monitor environmental health. This study aimed to expand the baseline knowledge of using metabolic end points in environmental monitoring by investigating the dreissenid mussel metabolome in the field. Dreissenids were caged at four locations along the Maumee River for 30 days. The mussel metabolome was measured using nuclear magnetic resonance spectroscopy, and mussel tissue chemical contaminants were analyzed using gas or liquid chromatography coupled with mass spectrometry. All Maumee River sites had a distinct mussel metabolome compared to the reference site and revealed changes in the energy metabolism and amino acids. Data also highlighted the importance of considering seasonality or handling effects on the metabolome at the time of sampling. The furthest upstream site presented a specific mussel tissue chemical signature of pesticides (atrazine and metolachlor), while a downstream site, located at Toledo's wastewater treatment plant, was characterized by polycyclic aromatic hydrocarbons and other organic contaminants. Further research into the dreissenid mussel's natural metabolic cycle and metabolic response to specific anthropogenic stressors is necessary before successful implementation of metabolomics in a biomonitoring program.

Multi-ancestry epigenome-wide analyses identify methylated sites associated with aortic augmentation index in TOPMed MESA.

Despite the prognostic value of arterial stiffness (AS) and pulsatile hemodynamics (PH) for cardiovascular morbidity and mortality, epigenetic modifications that contribute to AS/PH remain unknown. To gain a better understanding of the link between epigenetics (DNA methylation) and AS/PH, we examined the relationship of eight measures of AS/PH with CpG sites and co-methylated regions using multi-ancestry participants from Trans-Omics for Precision Medicine (TOPMed) Multi-Ethnic Study of Atherosclerosis (MESA) with sample sizes ranging from 438 to 874. Epigenome-wide association analysis identified one genome-wide significant CpG (cg20711926-CYP1B1) associated with aortic augmentation index (AIx). Follow-up analyses, including gene set enrichment analysis, expression quantitative trait methylation analysis, and functional enrichment analysis on differentially methylated positions and regions, further prioritized three CpGs and their annotated genes (cg23800023-ETS1, cg08426368-TGFB3, and cg17350632-HLA-DPB1) for AIx. Among these, ETS1 and TGFB3 have been previously prioritized as candidate genes. Furthermore, both ETS1 and HLA-DPB1 have significant tissue correlations between Whole Blood and Aorta in GTEx, which suggests ETS1 and HLA-DPB1 could be potential biomarkers in understanding pathophysiology of AS/PH. Overall, our findings support the possible role of epigenetic regulation via DNA methylation of specific genes associated with AIx as well as identifying potential targets for regulation of AS/PH.

The functional impact of rare variation across the regulatory cascade.

Each human genome has tens of thousands of rare genetic variants; however, identifying impactful rare variants remains a major challenge. We demonstrate how use of personal multi-omics can enable identification of impactful rare variants by using the Multi-Ethnic Study of Atherosclerosis, which included several hundred individuals, with whole-genome sequencing, transcriptomes, methylomes, and proteomes collected across two time points, 10 years apart. We evaluated each multi-omics phenotype's ability to separately and jointly inform functional rare variation. By combining expression and protein data, we observed rare stop variants 62 times and rare frameshift variants 216 times as frequently as controls, compared to 13-27 times as frequently for expression or protein effects alone. We extended a Bayesian hierarchical model, "Watershed," to prioritize specific rare variants underlying multi-omics signals across the regulatory cascade. With this approach, we identified rare variants that exhibited large effect sizes on multiple complex traits including height, schizophrenia, and Alzheimer's disease.

Analysis of nasopharyngeal microbiome patterns in Zambian infants with fatal acute febrile illness.

Introduction: Associative connections have previously been identified between nasopharyngeal infections and infant mortality. The nasopharyngeal microbiome may potentially influence the severity of these infections. Methods: We conducted an analysis of a longitudinal prospective cohort study of 1,981 infants who underwent nasopharyngeal sampling from 1 week through 14 weeks of age at 2-3-week intervals. In all, 27 microbiome samples from 9 of the infants in the cohort who developed fatal acute febrile illness (fAFI) were analyzed in pooled comparisons with 69 samples from 10 healthy comparator infants. We completed 16S rRNA amplicon gene sequencing all infant NP samples and characterized the maturation of the infant NP microbiome among the fAFI(+) and fAFI(-) infant cohorts. Results: Beta diversity measures of fAFI(-) infants were markedly higher than those of fAFI(+) infants. The fAFI(+) infant NP microbiome was marked by higher abundances of Escherichia, Pseudomonas, Leuconostoc, and Weissella, with low relative presence of Alkalibacterium, Dolosigranulum, Moraxella, and Streptococcus. Conclusions: Our results suggest that nasopharyngeal microbiome dysbiosis precedes fAFI in young infants. Early dysbiosis, involving microbes such as Escherichia, may play a role in the causal pathway leading to fAFI or could be a marker of other pathogenic forces that directly lead to fAFI.

Proteome-Wide Association Studies for Blood Lipids and Comparison with Transcriptome-Wide Association Studies.

Blood lipid traits are treatable and heritable risk factors for heart disease, a leading cause of mortality worldwide. Although genome-wide association studies (GWAS) have discovered hundreds of variants associated with lipids in humans, most of the causal mechanisms of lipids remain unknown. To better understand the biological processes underlying lipid metabolism, we investigated the associations of plasma protein levels with total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL), and low-density lipoprotein cholesterol (LDL) in blood. We trained protein prediction models based on samples in the Multi-Ethnic Study of Atherosclerosis (MESA) and applied them to conduct proteome-wide association studies (PWAS) for lipids using the Global Lipids Genetics Consortium (GLGC) data. Of the 749 proteins tested, 42 were significantly associated with at least one lipid trait. Furthermore, we performed transcriptome-wide association studies (TWAS) for lipids using 9,714 gene expression prediction models trained on samples from peripheral blood mononuclear cells (PBMCs) in MESA and 49 tissues in the Genotype-Tissue Expression (GTEx) project. We found that although PWAS and TWAS can show different directions of associations in an individual gene, 40 out of 49 tissues showed a positive correlation between PWAS and TWAS signed p-values across all the genes, which suggests a high-level consistency between proteome-lipid associations and transcriptome-lipid associations.

Multiset correlation and factor analysis enables exploration of multi-omics data.

Multi-omics datasets are becoming more common, necessitating better integration methods to realize their revolutionary potential. Here, we introduce multi-set correlation and factor analysis (MCFA), an unsupervised integration method tailored to the unique challenges of high-dimensional genomics data that enables fast inference of shared and private factors. We used MCFA to integrate methylation markers, protein expression, RNA expression, and metabolite levels in 614 diverse samples from the Trans-Omics for Precision Medicine/Multi-Ethnic Study of Atherosclerosis multi-omics pilot. Samples cluster strongly by ancestry in the shared space, even in the absence of genetic information, while private spaces frequently capture dataset-specific technical variation. Finally, we integrated genetic data by conducting a genome-wide association study (GWAS) of our inferred factors, observing that several factors are enriched for GWAS hits and trans-expression quantitative trait loci. Two of these factors appear to be related to metabolic disease. Our study provides a foundation and framework for further integrative analysis of ever larger multi-modal genomic datasets.

Interactive analysis of single-cell data using flexible workflows with SCTK2.

Analysis of single-cell RNA sequencing (scRNA-seq) data can reveal novel insights into the heterogeneity of complex biological systems. Many tools and workflows have been developed to perform different types of analyses. However, these tools are spread across different packages or programming environments, rely on different underlying data structures, and can only be utilized by people with knowledge of programming languages. In the Single-Cell Toolkit 2 (SCTK2), we have integrated a variety of popular tools and workflows to perform various aspects of scRNA-seq analysis. All tools and workflows can be run in the R console or using an intuitive graphical user interface built with R/Shiny. HTML reports generated with Rmarkdown can be used to document and recapitulate individual steps or entire analysis workflows. We show that the toolkit offers more features when compared with existing tools and allows for a seamless analysis of scRNA-seq data for non-computational users.

Protein-metabolite association studies identify novel proteomic determinants of metabolite levels in human plasma.

Although many novel gene-metabolite and gene-protein associations have been identified using high-throughput biochemical profiling, systematic studies that leverage human genetics to illuminate causal relationships between circulating proteins and metabolites are lacking. Here, we performed protein-metabolite association studies in 3,626 plasma samples from three human cohorts. We detected 171,800 significant protein-metabolite pairwise correlations between 1,265 proteins and 365 metabolites, including established relationships in metabolic and signaling pathways such as the protein thyroxine-binding globulin and the metabolite thyroxine, as well as thousands of new findings. In Mendelian randomization (MR) analyses, we identified putative causal protein-to-metabolite associations. We experimentally validated top MR associations in proof-of-concept plasma metabolomics studies in three murine knockout strains of key protein regulators. These analyses identified previously unrecognized associations between bioactive proteins and metabolites in human plasma. We provide publicly available data to be leveraged for studies in human metabolism and disease.

Metagenomic profiling pipelines improve taxonomic classification for 16S amplicon sequencing data.

Most experiments studying bacterial microbiomes rely on the PCR amplification of all or part of the gene for the 16S rRNA subunit, which serves as a biomarker for identifying and quantifying the various taxa present in a microbiome sample. Several computational methods exist for analyzing 16S amplicon sequencing. However, the most-used bioinformatics tools cannot produce high quality genus-level or species-level taxonomic calls and may underestimate the potential accuracy of these calls. We used 16S sequencing data from mock bacterial communities to evaluate the sensitivity and specificity of several bioinformatics pipelines and genomic reference libraries used for microbiome analyses, concentrating on measuring the accuracy of species-level taxonomic assignments of 16S amplicon reads. We evaluated the tools DADA2, QIIME 2, Mothur, PathoScope 2, and Kraken 2 in conjunction with reference libraries from Greengenes, SILVA, Kraken 2, and RefSeq. Profiling tools were compared using publicly available mock community data from several sources, comprising 136 samples with varied species richness and evenness, several different amplified regions within the 16S rRNA gene, and both DNA spike-ins and cDNA from collections of plated cells. PathoScope 2 and Kraken 2, both tools designed for whole-genome metagenomics, outperformed DADA2, QIIME 2 using the DADA2 plugin, and Mothur, which are theoretically specialized for 16S analyses. Evaluations of reference libraries identified the SILVA and RefSeq/Kraken 2 Standard libraries as superior in accuracy compared to Greengenes. These findings support PathoScope and Kraken 2 as fully capable, competitive options for genus- and species-level 16S amplicon sequencing data analysis, whole genome sequencing, and metagenomics data tools.

Interaction molecular QTL mapping discovers cellular and environmental modifiers of genetic regulatory effects.

Bulk tissue molecular quantitative trait loci (QTLs) have been the starting point for interpreting disease-associated variants, while context-specific QTLs show particular relevance for disease. Here, we present the results of mapping interaction QTLs (iQTLs) for cell type, age, and other phenotypic variables in multi-omic, longitudinal data from blood of individuals of diverse ancestries. By modeling the interaction between genotype and estimated cell type proportions, we demonstrate that cell type iQTLs could be considered as proxies for cell type-specific QTL effects. The interpretation of age iQTLs, however, warrants caution as the moderation effect of age on the genotype and molecular phenotype association may be mediated by changes in cell type composition. Finally, we show that cell type iQTLs contribute to cell type-specific enrichment of diseases that, in combination with additional functional data, may guide future functional studies. Overall, this study highlights iQTLs to gain insights into the context-specificity of regulatory effects.

Systemic Markers of Lung Function and Forced Expiratory Volume in 1 Second Decline across Diverse Cohorts.

Rationale: Chronic obstructive pulmonary disease (COPD) is a complex disease characterized by airway obstruction and accelerated lung function decline. Our understanding of systemic protein biomarkers associated with COPD remains incomplete. Objectives: To determine what proteins and pathways are associated with impaired pulmonary function in a diverse population. Methods: We studied 6,722 participants across six cohort studies with both aptamer-based proteomic and spirometry data (4,566 predominantly White participants in a discovery analysis and 2,156 African American cohort participants in a validation). In linear regression models, we examined protein associations with baseline forced expiratory volume in 1 second (FEV1) and FEV1/forced vital capacity (FVC). In linear mixed effects models, we investigated the associations of baseline protein levels with rate of FEV1 decline (ml/yr) in 2,777 participants with up to 7 years of follow-up spirometry. Results: We identified 254 proteins associated with FEV1 in our discovery analyses, with 80 proteins validated in the Jackson Heart Study. Novel validated protein associations include kallistatin serine protease inhibitor, growth differentiation factor 2, and tumor necrosis factor-like weak inducer of apoptosis (discovery ß = 0.0561, Q = 4.05 × 10-10; ß = 0.0421, Q = 1.12 × 10-3; and ß = 0.0358, Q = 1.67 × 10-3, respectively). In longitudinal analyses within cohorts with follow-up spirometry, we identified 15 proteins associated with FEV1 decline (Q < 0.05), including elafin leukocyte elastase inhibitor and mucin-associated TFF2 (trefoil factor 2; ß = -4.3 ml/yr, Q = 0.049; ß = -6.1 ml/yr, Q = 0.032, respectively). Pathways and processes highlighted by our study include aberrant extracellular matrix remodeling, enhanced innate immune response, dysregulation of angiogenesis, and coagulation. Conclusions: In this study, we identify and validate novel biomarkers and pathways associated with lung function traits in a racially diverse population. In addition, we identify novel protein markers associated with FEV1 decline. Several protein findings are supported by previously reported genetic signals, highlighting the plausibility of certain biologic pathways. These novel proteins might represent markers for risk stratification, as well as novel molecular targets for treatment of COPD.

Psyllium is a natural nonfermented gel-forming fiber that is effective for weight loss: A comprehensive review and meta-analysis.

BACKGROUND: Psyllium is a natural, predominantly soluble fiber that forms a viscous gel when hydrated and is not digested or fermented. In the small intestine, psyllium gel increases chyme viscosity, slowing the degradation and absorption of nutrients. Psyllium has a significant effect in patients with metabolic syndrome and type-2 diabetes on glycemic control, while lowering serum cholesterol in hypercholesterolemic patients. Some randomized controlled studies have shown that psyllium also facilitates weight loss in overweight and obese participants. OBJECTIVES: A comprehensive review and meta-analysis assessing psyllium's impact on body weight, body mass index (BMI), and waist circumference in overweight and obese participants. DATA SOURCES: A comprehensive search was performed (Medline, Scopus, Cochrane Database) through March 21, 2022, using search terms to identify randomized, controlled, clinical studies designed to assess weight loss in overweight and obese participants over at least 2 months. Data were analyzed using the inverse variance method with random effects models. CONCLUSIONS: Six studies meeting inclusion criteria were identified (total n = 354). The meta-analysis showed that psyllium, dosed just before meals (mean dose 10.8 g/day, mean duration 4.8 months), was effective for decreasing body weight (MD = -2.1 kg [95% confidence interval [CI]: -2.6 to -1.6]; p < .001), BMI (MD = -0.8 kg/m 2 [95% CI: -1.0 to -0.6]; p < .001) and waist circumference (MD = -2.2 cm [95% CI: -2.9 to -1.4]; p < .001) in overweight and obese populations. IMPLICATIONS FOR PRACTICE: Gel-forming nonfermented psyllium fiber, dosed just before meals, is effective in facilitating weight loss in overweight and obese participants.

Genetic characterization of the zoonotic parasite Ancylostoma caninum in the central and eastern United States.

Ancylostoma caninum is the most common nematode parasite of dogs in the United States. The present study aimed to describe the molecular epidemiology of A. caninum isolates from the central and eastern states of the United States using the partial mitochondrial cytochrome oxidase (cox1) gene and to compare them with those reported globally. We isolated eggs from faecal samples of dogs and characterized each isolate based on cox1 sequences. A total of 60 samples originating from Kansas, Iowa, New York, Florida and Massachusetts were included. 25 haplotypes were identified in the United States dataset with high haplotype diversity (0.904). Sequence data were compared to sequences from other world regions available in GenBank. Global haplotype analysis demonstrated 35 haplotypes with a haplotype diversity of 0.931. Phylogenetic and network analysis provide evidence for the existence of moderate geographical structuring of A. caninum haplotypes. Our results provide an updated summary of A. caninum haplotypes and data for neutral genetic markers with utility for tracking hookworm populations. Sequences have been deposited in GenBank (ON980650-ON980674). Further studies of isolates from other regions are essential to understand the genetic diversity of this parasite.