Background: Toxicant-associated steatohepatitis has been described in adults but less is known regarding the role of toxicants in liver disease of children. Perfluoroalkyl substances (PFAS) cause hepatic steatosis in rodents, but few previous studies have examined PFAS effects on severity of liver injury in children. Objectives: We aimed to examine the relationship of PFAS to histologic severity of nonalcoholic fatty liver disease (NAFLD) in children. Methods: Seventy-four children with physician-diagnosed NAFLD were recruited from Children’s Healthcare of Atlanta between 2007 and 2015. Biopsy-based liver histological features were scored for steatosis, lobular and portal inflammation, ballooning, and fibrosis. Plasma concentrations of perfluorooctanoic acid (PFOA), perfluorooctane sulfonate (PFOS) and perfluorohexane sulfonic acid (PFHxS), and untargeted plasma metabolomic profiling, were determined using liquid chromatography with high-resolution mass spectrometry. A metabolome-wide association study coupled with pathway enrichment analysis was performed to evaluate metabolic dysregulation associated with PFAS. A structural integrated analysis was applied to identify latent clusters of children with more severe form of NAFLD based on their PFAS levels and metabolite pattern. Results: Patients were 7-19 years old, mostly boys (71%), Hispanic (51%), and obese (85%). The odds of having nonalcoholic steatohepatitis (NASH), compared to children with steatosis alone, was significantly increased with each interquartile range (IQR) increase of PFOS (OR: 3.32, 95% CI: 1.40-7.87) and PFHxS (OR: 4.18, 95% CI: 1.64-10.7). Each IQR increase of PFHxS was associated with increased odds for liver fibrosis (OR: 4.44, 95% CI: 1.34-14.8), lobular inflammation (OR: 2.87, 95% CI: 1.12-7.31), and higher NAFLD activity score (β coefficient 0.46; 95% CI: 0.03, 0.89). A novel integrative analysis identified a cluster of children with NASH, characterized by increased PFAS levels and altered metabolite patterns including higher plasma levels of phosphoethanolamine, tyrosine, phenylalanine, aspartate and creatine, and decreased plasma levels of betaine. Conclusions: Higher PFAS exposure was associated with more severe disease in children with NAFLD. PFAS may be an important toxicant contributing to NAFLD progression; however larger, longitudinal studies are warranted to confirm these findings.
Objective: To examine the prospective associations between exposure to perfluoroalkyl substances (PFASs) and longitudinal measurements of glucose metabolism in high-risk overweight and obese Hispanic children. Methods: Forty overweight and obese Hispanic children (8–14 years) from urban Los Angeles underwent clinical measures and 2-hour oral glucose tolerance tests (OGTT) at baseline and a follow-up visit (range: 1–3 years after enrollment). Baseline plasma perfluorooctanoic acid (PFOA), perfluorooctane sulfonate (PFOS), perfluorohexane sulfonic acid (PFHxS), and the plasma metabolome were measured by liquid-chromatography with high-resolution mass spectrometry. Multiple linear regression models were used to assess the association between baseline PFASs and changes in glucose homeostasis over follow-up. A metabolome-wide association study coupled with pathway enrichment analysis was performed to evaluate metabolic dysregulation associated with plasma PFASs concentrations. We performed a structural integrated analysis aiming to characterize the joint impact of all factors and to identify latent clusters of children with alterations in glucose homeostasis, based on their exposure and metabolomics profile. Results: Each ln (ng/ml) increase in PFOA and PFHxS concentrations was associated with a 30.6 mg/dL (95% CI: 8.8–52.4) and 10.2 mg/dL (95% CI: 2.7–17.7) increase in 2-hour glucose levels, respectively. A ln (ng/ml) increase in PFHxS concentrations was also associated with 17.8 mg/dL increase in the glucose area under the curve (95% CI: 1.5–34.1). Pathway enrichment analysis showed significant alterations of lipids (e.g., glycosphingolipids, linoleic acid, and de novo lipogenesis), and amino acids (e.g., aspartate and asparagine, tyrosine, arginine and proline) in association to PFASs exposure. The integrated analysis identified a cluster of children with increased 2-h glucose levels over follow up, characterized by increased PFAS levels and altered metabolite patterns. Conclusions: This proof-of-concept analysis shows that higher PFAS exposure was associated with dysregulation of several lipid and amino acid pathways and longitudinal alterations in glucose homeostasis in Hispanic youth. Larger studies are needed to confirm these findings and fully elucidate the underlying biological mechanisms.
Non-coding RNAs (ncRNAs) play crucial roles in multiple fundamental biological processes, such as post-transcriptional gene regulation, and are implicated in many complex human diseases. Mostly ncRNAs function by interacting with corresponding RNA-binding proteins. The research on ncRNA–protein interaction is the key to understanding the function of ncRNA. However, the biological experiment techniques for identifying RNA–protein interactions (RPIs) are currently still expensive and time-consuming. Due to the complex molecular mechanism of ncRNA–protein interaction and the lack of conservation for ncRNA, especially for long ncRNA (lncRNA), the prediction of ncRNA–protein interaction is still a challenge. Deep learning-based models have become the state-of-the-art in a range of biological sequence analysis problems due to their strong power of feature learning. In this study, we proposed a hierarchical deep learning framework RPITER to predict RNA–protein interaction. For sequence coding, we improved the conjoint triad feature (CTF) coding method by complementing more primary sequence information and adding sequence structure information. For model design, RPITER employed two basic neural network architectures of convolution neural network (CNN) and stacked auto-encoder (SAE). Comprehensive experiments were performed on five benchmark datasets from PDB and NPInter databases to analyze and compare the performances of different sequence coding methods and prediction models. We found that CNN and SAE deep learning architectures have powerful fitting abilities for the k-mer features of RNA and protein sequence. The improved CTF coding method showed performance gain compared with the original CTF method. Moreover, our designed RPITER performed well in predicting RNA–protein interaction (RPI) and could outperform most of the previous methods. On five widely used RPI datasets, RPI369, RPI488, RPI1807, RPI2241 and NPInter, RPITER obtained A U C of 0.821, 0.911, 0.990, 0.957 and 0.985, respectively. The proposed RPITER could be a complementary method for predicting RPI and constructing RPI network, which would help push forward the related biological research on ncRNAs and lncRNAs.
Background The objective of this randomized clinical experiment was to test the influence of a mindfulness meditation practice, when delivered during one session of active chemotherapy administration, on acute salivary cortisol response as a marker of the neuroendocrine system activity in cancer patients. Methods A mindfulness, attention control, or resting exposure was assigned to N=57 English- or Spanish- speaking colorectal cancer patients at one county oncology clinic and one university oncology clinic at the start of chemotherapy. Four saliva samples were collected at the start of chemotherapy and at subsequent 20-minute intervals during the first 60 minutes of chemotherapy. Self-report on biobehavioral assessments post-chemotherapy included distress, fatigue, and mindfulness. Results Area under the curve analysis (AUCI and AUCB) denoted a relative increase in cortisol reactivity in the mindfulness group after adjusting for biological and clinical measures (β=123.21, p=.03), indicating reduced acute cortisol blunting. More than twice as many patients in the mindfulness group as compared to controls displayed a cortisol rise from baseline to 20 minutes (69% vs. 34%, p=.02). AUCi values were uncorrelated with biobehavioral measure scores although mindfulness scores were inversely correlated with fatigue (r=−.46, p<.01) and distress (r=−.54, p<.01) scores. Conclusions Findings suggest that a mindfulness practice during chemotherapy can reduce blunting of neuroendocrine profiles typically observed in cancer patients. Implications include support for the use of mindfulness practice in integrative oncology.
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