Penalized linear mixed models for structured genetic data.

Many genetic studies that aim to identify genetic variants associated with complex phenotypes are subject to unobserved confounding factors arising from environmental heterogeneity. This poses a challenge to detecting associations of interest and is known to induce spurious associations when left unaccounted for. Penalized linear mixed models (LMMs) are an attractive method to correct for unobserved confounding.

Prognostic and therapeutic value of the Hippo pathway, RABL6A, and p53-MDM2 axes in sarcomas.

Additional prognostic and therapeutic biomarkers effective across different histological types of sarcoma are needed. Herein we evaluate expression of TAZ and YAP, the p53-MDM2 axis, and RABL6A, a novel oncoprotein with potential ties to both pathways, in sarcomas of different histological types. Immunohistochemical staining of a tissue microarray including 163 sarcomas and correlation with clinical data showed that elevated YAP and TAZ independently predict worse overall and progression-free survival, respectively.

Targeted Metabolomics Demonstrates Distinct and Overlapping Maternal Metabolites Associated With BMI, Glucose, and Insulin Sensitivity During Pregnancy Across Four Ancestry Groups.

Objective: We used targeted metabolomics in pregnant mothers to compare maternal metabolite associations with maternal BMI, glycemia, and insulin sensitivity.

Research Design And Methods: Targeted metabolomic assays of clinical metabolites, amino acids, and acylcarnitines were performed on fasting and 1-h postglucose serum samples from European ancestry, Afro-Caribbean, Thai, and Mexican American mothers (400 from each ancestry group) who participated in the Hyperglycemia and Adverse Pregnancy Outcome (HAPO) Study and underwent an oral glucose tolerance test at ∼28 weeks gestation.

Results: K-means clustering, which identified patterns of metabolite levels across ancestry groups, demonstrated that, at both fasting and 1-h, levels of the majority of metabolites were similar across ancestry groups.

Maternal BMI and Glycemia Impact the Fetal Metabolome.

Objective: We used targeted metabolomics to determine associations of maternal BMI and glucose levels with cord blood metabolites and associations of cord blood metabolites with newborn birth weight and adiposity in mother-offspring dyads.

Research Design And Methods: Targeted metabolomic assays were performed on cord blood serum samples from European ancestry, Afro-Caribbean, Thai, and Mexican American newborns (400 from each ancestry group) whose mothers participated in the Hyperglycemia and Adverse Pregnancy Outcome (HAPO) Study and who had anthropometric measurements at birth.

Results: Meta-analysis across the four cohorts demonstrated significant correlation of all cord blood metabolites analyzed with maternal fasting levels of the same metabolites at ∼28 weeks' gestation except for triglycerides, asparagine/aspartate, arginine, and the acylcarnitine C14-OH/C12-DC.

Mixture model normalization for non-targeted gas chromatography/mass spectrometry metabolomics data.

Background: Metabolomics offers a unique integrative perspective for health research, reflecting genetic and environmental contributions to disease-related phenotypes. Identifying robust associations in population-based or large-scale clinical studies demands large numbers of subjects and therefore sample batching for gas-chromatography/mass spectrometry (GC/MS) non-targeted assays. When run over weeks or months, technical noise due to batch and run-order threatens data interpretability.

Associations of maternal BMI and insulin resistance with the maternal metabolome and newborn outcomes.

Aims/hypothesis: Maternal obesity increases the risk for large-for-gestational-age birth and excess newborn adiposity, which are associated with adverse long-term metabolic outcomes in offspring, probably due to effects mediated through the intrauterine environment. We aimed to characterise the maternal metabolic milieu associated with maternal BMI and its relationship to newborn birthweight and adiposity.

Methods: Fasting and 1 h serum samples were collected from 400 European-ancestry mothers in the Hyperglycaemia and Adverse Pregnancy Outcome Study who underwent an OGTT at ∼28 weeks gestation and whose offspring had anthropometric measurements at birth.

Metabolic Networks and Metabolites Underlie Associations Between Maternal Glucose During Pregnancy and Newborn Size at Birth.

Maternal metabolites and metabolic networks underlying associations between maternal glucose during pregnancy and newborn birth weight and adiposity demand fuller characterization. We performed targeted and nontargeted gas chromatography/mass spectrometry metabolomics on maternal serum collected at fasting and 1 h following glucose beverage consumption during an oral glucose tolerance test (OGTT) for 400 northern European mothers at ∼28 weeks' gestation in the Hyperglycemia and Adverse Pregnancy Outcome Study. Amino acids, fatty acids, acylcarnitines, and products of lipid metabolism decreased and triglycerides increased during the OGTT.

Genetic risk score for prediction of newborn adiposity and large-for-gestational-age birth.

Context: Macrosomic infants are at increased risk for adverse metabolic outcomes. Improving prediction of large-for-gestational-age (LGA) birth may help prevent these outcomes.

Objective: This study sought to determine whether genes associated with obesity-related traits in adults are associated with newborn size, and whether a genetic risk score (GRS) predicts LGA birth.

Metabomxtr: an R package for mixture-model analysis of non-targeted metabolomics data.

Summary: Non-targeted metabolomics technologies often yield data in which abundance for any given metabolite is observed and quantified for some samples and reported as missing for other samples. Apparent missingness can be due to true absence of the metabolite in the sample or presence at a level below detectability. Mixture-model analysis can formally account for metabolite 'missingness' due to absence or undetectability, but software for this type of analysis in the high-throughput setting is limited.

Maternal short-chain fatty acids are associated with metabolic parameters in mothers and newborns.

During the course of pregnancy, dynamic remodeling of the gut microbiota occurs and contributes to maternal metabolic changes through an undefined mechanism. Because short chain fatty acids (SCFAs) are a major product of gut microbiome fermentation, we investigated whether serum SCFA levels during pregnancy are related to key metabolic parameters in mothers and newborns. In this prospective study, 20 pregnant women without gestational diabetes were evaluated at 36-38 weeks of gestation, and their newborns were assessed after parturition.

Cigarette smoking decreases global microRNA expression in human alveolar macrophages.

Human alveolar macrophages are critical components of the innate immune system. Cigarette smoking-induced changes in alveolar macrophage gene expression are linked to reduced resistance to pulmonary infections and to the development of emphysema/COPD. We hypothesized that microRNAs (miRNAs) could control, in part, the unique messenger RNA (mRNA) expression profiles found in alveolar macrophages of cigarette smokers.

Expression of human paraoxonase 1 decreases superoxide levels and alters bacterial colonization in the gut of Drosophila melanogaster.

Paraoxonases (PON) are a family of proteins (PON1, 2 and 3) with multiple enzymatic activities. PON1 interferes with homoserine lactone-mediated quorum sensing in bacteria and with reactive oxygen species (ROS) in humans and mice. PON1 gene mutations have been linked to multiple traits, including aging, and diseases of the cardiovascular, nervous and gastrointestinal system.

Induction of inflammasome-dependent pyroptosis by carbon black nanoparticles.

Inhalation of nanoparticles has been implicated in respiratory morbidity and mortality. In particular, carbon black nanoparticles are found in many different environmental exposures. Macrophages take up inhaled nanoparticles and respond via release of inflammatory mediators and in some cases cell death.