Evaluating the Utility of Multiple Trait Methods for Estimating Polygenic Risk Scores

Polygenic risk score (PRS) is a method that utilizes the effect sizes of genetic variants on a particular disease or trait to evaluate an overall genetic risk for a certain individual. Such effect sizes are often estimated using traditional genome-wide association study (GWAS) for the trait of interest. There are methods developed that aim to improve the predictive power of PRS by incorporating the genetic information from multiple related traits. One existing popular method is MTAG, which requires GWAS summary statistics from multiple traits and is based on strong assumptions about genetic correlation across traits. We developed some variations of MTAG and evaluated their performance for computing PRS against GWAS, using a variety of trait data from UK Biobank as well as simulated data

An Approach to Carbon Emissions Prediction Using Generalized Regression Neural Network Improved by Genetic Algorithm

The study on scientific analysis and prediction of China’s future carbonemissions is conducive to balancing the relationship between economicdevelopment and carbon emissions in the new era, and actively respondingto climate change policy. Through the analysis of the application of thegeneralized regression neural network (GRNN) in prediction, this paperimproved the prediction method of GRNN. Genetic algorithm (GA) wasadopted to search the optimal smooth factor as the only factor of GRNN,which was then used for prediction in GRNN. During the prediction of carbon dioxide emissions using the improved method, the increments of datawere taken into account. The target values were obtained after the calculation of the predicted results. Finally, compared with the results of GRNN,the improved method realized higher prediction accuracy. It thus offers anew way of predicting total carbon dioxide emissions, and the predictionresults can provide macroscopic guidance and decision-making referencefor China’s environmental protection and trading of carbon emissions

The role of the gut microbiome in graft fibrosis after pediatric liver transplantation

Liver transplantation (LT) is a life-saving option for children with end-stage liver disease. However, about 50% of patients develop graft fibrosis in 1 year after LT, with normal liver function. Graft fibrosis may progress to cirrhosis, resulting in graft dysfunction and ultimately the need for re-transplantation. Previous studies have identified various risk factors for the post-LT fibrogenesis, however, to date, neither of the factors seems to fully explain the cause of graft fibrosis. Recently, evidence has accumulated on the important role of the gut microbiome in outcomes after solid organ transplantation. As an altered microbiome is present in pediatric patients with end-stage liver diseases, we hypothesize that the persisting alterations in microbial composition or function contribute to the development of graft fibrosis, for example by bacteria translocation due to increased intestinal permeability, imbalanced bile acids metabolism, and/or decreased production of short-chain fatty acids (SCFAs). Subsequently, an immune response can be activated in the graft, together with the stimulation of fibrogenesis. Here we review current knowledge about the potential mechanisms by which alterations in microbial composition or function may lead to graft fibrosis in pediatric LT and we provide prospective views on the efficacy of gut microbiome manipulation as a therapeutic target to alleviate the graft fibrosis and to improve long-term survival after LT

Interaction between drugs and the gut microbiome

The human gut microbiome is a complex ecosystem that can mediate the interaction of the human host with their environment. The interaction between gut microbes and commonly used non-antibiotic drugs is complex and bidirectional: gut microbiome composition can be influenced by drugs, but, vice versa, the gut microbiome can also influence an individual's response to a drug by enzymatically transforming the drug's structure and altering its bioavailability, bioactivity or toxicity (pharmacomicrobiomics). The gut microbiome can also indirectly impact an individual's response to immunotherapy in cancer treatment. In this review we discuss the bidirectional interactions between microbes and drugs, describe the changes in gut microbiota induced by commonly used non-antibiotic drugs, and their potential clinical consequences and summarise how the microbiome impacts drug effectiveness and its role in immunotherapy. Understanding how the microbiome metabolises drugs and reduces treatment efficacy will unlock the possibility of modulating the gut microbiome to improve treatment

Multi-ethnic studies in complex traits

The successes of genome-wide association (GWA) studies have mainly come from studies performed in populations of European descent. Since complex traits are characterized by marked genetic heterogeneity, the findings so far may provide an incomplete picture of the genetic architecture of complex traits. However, the recent GWA studies performed on East Asian populations now allow us to globally assess the heterogeneity of association signals between populations of European ancestry and East Asians, and the possible obstacles for multi-ethnic GWA studies. We focused on four different traits that represent a broad range of complex phenotypes, which have been studied in both Europeans and East Asians: type 2 diabetes, systemic lupus erythematosus, ulcerative colitis and height. For each trait, we observed that most of the risk loci identified in East Asians were shared with Europeans. However, we also observed that a significant part of the association signals at these shared loci seems to be independent between populations. This suggests that disease aetiology is common between populations, but that risk variants are often population specific. These variants could be truly population specific and result from natural selection, genetic drift and recent mutations, or they could be spurious, caused by the limitations of the method of analysis employed in the GWA studies. We therefore propose a three-stage framework for multi-ethnic GWA analyses, starting with the commonly used single-nucleotide polymorphism-based analysis, and followed by a gene-based approach and a pathway-based analysis, which will take into account the heterogeneity of association between populations at different levels

Gut microbiome and bile acids in obesity-related diseases

Dysbiosis has been implemented in the etiologies of obesity-related chronic diseases such as type 2 diabetes, NAFLD and cardiovascular diseases. Bile acids, a class of amphipathic steroids produced in the liver and extensively modified by the microbiome, are increasingly recognized as actors in onset and progression of these diseases. Indeed, human obesity is associated with altered bile acid metabolism. Bile acids facilitate intestinal fat absorption but also exert hormone-like functions through activation of nuclear and membrane-bound receptors and thereby modulate glucose, lipid and energy metabolism, intestinal integrity and immunity. Bile acid signaling pathways have thus been identified as potential pharmacological targets for obesity-related diseases. Interfering with micro biome composition may also be considered, as liver-and microbiomederived bile acid species have different signaling functions. This review summarizes recent developments in this rapidly expanding field of research and addresses potential clinical prospects of interference with bile acid signaling pathways in human diseases. (c) 2021 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons. org/licenses/by/4.0/)

Human induced pluripotent stem cell–derived liver-on-a-chip for studying drug metabolism:the challenge of the cytochrome P450 family

The liver is the primary organ responsible for the detoxification and metabolism of drugs. To date, a lack of preclinical models that accurately emulate drug metabolism by the human liver presents a significant challenge in the drug development pipeline, particularly for predicting drug efficacy and toxicity. In recent years, emerging microfluidic-based organ-on-a-chip (OoC) technologies, combined with human induced pluripotent stem cell (hiPSC) technology, present a promising avenue for the complete recapitulation of human organ biology in a patient-specific manner. However, hiPSC-derived organoids and liver-on-a-chip models have so far failed to sufficiently express cytochrome P450 monooxygenase (CYP450) enzymes, the key enzymes involved in first-pass metabolism, which limits the effectiveness and translatability of these models in drug metabolism studies. This review explores the potential of innovative organoid and OoC technologies for studying drug metabolism and discusses their existing drawbacks, such as low expression of CYP450 genes. Finally, we postulate potential approaches for enhancing CYP450 expression in the hope of paving the way toward developing novel, fully representative liver drug-metabolism models.</p

Human induced pluripotent stem cell–derived liver-on-a-chip for studying drug metabolism:the challenge of the cytochrome P450 family

The liver is the primary organ responsible for the detoxification and metabolism of drugs. To date, a lack of preclinical models that accurately emulate drug metabolism by the human liver presents a significant challenge in the drug development pipeline, particularly for predicting drug efficacy and toxicity. In recent years, emerging microfluidic-based organ-on-a-chip (OoC) technologies, combined with human induced pluripotent stem cell (hiPSC) technology, present a promising avenue for the complete recapitulation of human organ biology in a patient-specific manner. However, hiPSC-derived organoids and liver-on-a-chip models have so far failed to sufficiently express cytochrome P450 monooxygenase (CYP450) enzymes, the key enzymes involved in first-pass metabolism, which limits the effectiveness and translatability of these models in drug metabolism studies. This review explores the potential of innovative organoid and OoC technologies for studying drug metabolism and discusses their existing drawbacks, such as low expression of CYP450 genes. Finally, we postulate potential approaches for enhancing CYP450 expression in the hope of paving the way toward developing novel, fully representative liver drug-metabolism models.</p