The gut microbiome plays an essential role in regulating lipid metabolism. However, little is known about how gut microbiome modulates sex differences in lipid metabolism. The present study aims to determine whether gut microbiota modulates sexual dimorphism of lipid metabolism in mice fed a high-fat diet (HFD). Conventional and germ-free male and female mice were fed an HFD for four weeks, and lipid absorption, plasma lipid profiles, and apolipoprotein levels were then evaluated. The gut microbiota was analyzed by 16S rRNA gene sequencing. After 4-week HFD consumption, the females exhibited less body weight gain and body fat composition and significantly lower triglyceride levels in very-low-density lipoprotein (VLDL) and cholesterol levels in high-density lipoprotein (HDL) compared to male mice. The fecal microbiota analysis revealed that the male mice were associated with reduced gut microbial diversity. The female mice had considerably different microbiota composition compared to males, e.g., enriched growth of beneficial microbes (e.g., Akkermansia) and depleted growth of Adlercreutzia and Enterococcus. Correlation analyses suggested that the different compositions of the gut microbiota were associated with sexual dimorphism in body weight, fat mass, and lipid metabolism in mice fed an HFD. Our findings demonstrated significant sex differences in lipid metabolism and the microbiota composition at baseline (during LFD), along with sex-dependent responses to HFD. A comprehensive understanding of sexual dimorphism in lipid metabolism modulated by microbiota will help to develop more sex-specific effective treatment options for dyslipidemia and metabolic disorders in females.

Study Objective: To determine if baseline cytokines and their changes over postoperative days 0-2 (POD0-2) predict acute and chronic postsurgical pain (CPSP) after major surgery. Design: Prospective, observational, longitudinal nested study. Setting: University-affiliated quaternary children’s hospital. Patients: Subjects (≥8 years old) with idiopathic scoliosis undergoing spine fusion or pectus excavatum undergoing Nuss procedure. Measurements: Demographics, surgical, psychosocial measures, pain scores, and opioid use over POD0-2 were collected. Cytokine concentrations were analyzed in serial blood samples collected before and after (up to two weeks) surgery, using Luminex bead arrays. After data preparation, relationships between pre- and post-surgical cytokine concentrations with acute (% time in moderate-severe pain over POD0-2) and chronic (pain score>3/10 beyond 3 months post-surgery) pain were analyzed. After adjusting for covariates, univariate/multivariate regression analyses were conducted to associate baseline cytokine concentrations with postoperative pain, and mixed effects models were used to associate longitudinal cytokine concentrations with pain outcomes. Main Results: Analyses included 3,164 measures of 16 cytokines from 112 subjects (median age 15.3, IQR 13.5-17.0, 54.5% female, 59.8% pectus). Acute postsurgical pain was associated with higher baseline concentrations of GM-CSF (β=0.95, SE 0.31; p =.003), IL-1β (β=0.84, SE 0.36; p =.02), IL-2 (β=0.78, SE 0.34; p =.03), and IL-12 p70 (β=0.88, SE 0.40; p =.03) and longitudinal postoperative elevations in GM-CSF (β=1.38, SE 0.57; p =.03), IFNγ (β=1.36, SE 0.6; p =.03), IL-1β (β=1.25, SE 0.59; p =.03), IL-7 (β=1.65, SE 0.7, p =.02), and IL-12 p70 (β=1.17, SE 0.58; p =.04). In contrast, CPSP was associated with lower baseline concentration of IL-8 (β= -0.39, SE 0.17; p =.02), and the risk of developing CPSP was elevated in patients with lower longitudinal postoperative concentrations of IL-6 (β= -0.57, SE 0.26; p =.03), IL-8 (β= - 0.68, SE 0.24; p =.006), and IL-13 (β= -0.48, SE 0.22; p =.03). Furthermore, higher odds for CPSP were found for females ( vs. males) for IL-2, IL-4, IL-5, IL-6, IL-8, IL-10, and TNFα, and for pectus ( vs. spine) surgery for IL-8 and IL-10. Conclusion: We identified pro-inflammatory cytokines associated with increased acute postoperative pain and anti-inflammatory cytokines associated with lower CPSP risk, with potential to serve as predictive and prognostic biomarkers.

To study the relationship between genetic variants and phenotypes, association testing is adopted; however, most association studies are conducted by genotype-based testing. Testing methods based on next-generation sequencing (NGS) data without genotype calling demonstrate an advantage over testing methods based on genotypes in the scenarios when genotype estimation is not accurate. Our objective was to develop NGS data-based methods for association studies to fill the gap in the literature. Single-variant testing methods based on NGS data have been proposed, including our previously proposed single-variant NGS data-based testing method, i.e., UNC combo method. The NGS data-based group testing method has been proposed by us using a linear model framework which can handle continuous responses. In this paper, we extend our linear model-based framework to a generalized linear model-based framework so that the methods can handle other types of responses especially binary responses which is a common problem in association studies. To evaluate the performance of various estimators and compare them we performed simulation studies. We found that all methods have Type I errors controlled, and our NGS data-based methods have better performance than genotype-based methods for other types of responses, including binary responses (logistics regression) and count responses (Poisson regression), especially when sequencing depth is low. We have extended our previous linear model (LM) framework to a generalized linear model (GLM) framework and derived NGS data-based methods for a group of genetic variables. Compared with our previously proposed LM-based methods, the new GLM-based methods can handle more complex responses (for example, binary responses and count responses) in addition to continuous responses. Our methods have filled the literature gap and shown advantage over their corresponding genotype-based methods in the literature.

Objectives: Preterm infants confront multiple coexistent health risks and may not receive human milk (HM), which contains human milk oligosaccharides (HMOs), among other biologically active, beneficial components. 2′-Fucosyllactose (2′-FL) is the most abundant HMO in most HM. Interventional studies of formula with added HMOs have demonstrated multiple beneficial outcomes in healthy, term infants. Methods: This double-blind, randomized, placebo-controlled pilot study (NCT03306316) evaluated the effect of a 2′-FL supplement on growth, tolerance, and neurobehavior, as assessed by the Neonatal Intensive Care Unit (NICU) Network Neurobehavioral Scale (NNNS), in preterm infants. Eligible neonates born between 26 0/7 and 31 6/7 weeks gestational age (GA) were enrolled from three NICUs in the United States. Preterm infants consuming mother’s own milk or donor human milk were randomized to receive a supplement of 0.135 g/mL of 2′-FL or 0.05 g/mL dextrose (placebo) twice daily until 36 weeks corrected GA, NNNS assessment, or hospital discharge, whichever came first. Results: Of 42 participating preterm infants, 23 (55%) received 2′-FL and demonstrated no significant differences in growth in weight, length, or head circumference over 5 weeks. There were also no differences in stool frequency, adverse (AEs) or serious adverse events (SAEs), or neurobehavior (NNNS) between groups. Conclusions: This pilot study found that 2′-FL supplementation in preterm infants through 36 weeks corrected GA was safe and well-tolerated and supported adequate growth and neurobehavior.

OBJECTIVES: Public insurance reduces financial barriers to healthcare but may not fully mitigate the influence of neighborhood opportunity on pediatric critical care utilization. We examined the association between neighborhood opportunity and PICU utilization, including costs, and assessed whether public insurance modified these relationships. DESIGN: Population-level retrospective observational study. SETTING: A single, free-standing quaternary children’s hospital in southwestern Ohio. PATIENTS: Children 18 years or younger admitted to the PICU between January 1, 2016, and December 31, 2022, residing within the hospital’s primary service area. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Primary outcomes were census tract (CT) level PICU admission rates and median PICU costs. Very low opportunity neighborhoods had the highest PICU admission rates (3.41 vs. 1.76 admissions per 1000 children in very high opportunity neighborhoods; p < 0.001). Overall CT level median PICU costs did not differ by Child Opportunity Index (COI; p = 0.582). Publicly insured children were more likely to reside in very low opportunity neighborhoods (44% vs. 10%; p < 0.001). Within very low opportunity neighborhoods, publicly insured children had lower median PICU costs than children with other insurance ($16,693 vs. $22,585; p = 0.008); costs were similar across insurance groups in other COI quintiles. In multivariable analyses, the interaction between insurance status and neighborhood opportunity was not statistically significant ( p = 0.099). CONCLUSIONS: Children from low opportunity neighborhoods experienced higher PICU admission rates, while neighborhood opportunity and public insurance jointly influenced patterns of PICU resource utilization. Expanding insurance coverage alone is unlikely to eliminate disparities; improving neighborhood conditions and implementing place-based strategies may help mitigate PICU utilization.