PASI: A novel pathway method to identify delicate group effects

Pathway analysis is a common approach in diverse biomedical studies, yet the currently-available pathway tools do not typically support the increasingly popular personalized analyses. Another weakness of the currently-available pathway methods is their inability to handle challenging data with only modest group-based effects compared to natural individual variation. In an effort to address these issues, this study presents a novel pathway method PASI (Pathway Analysis for Sample-level Information) and demonstrates its performance on complex diseases with different levels of group-based differences in gene expression. PASI is freely available as an R package

Systematic evaluation of differential splicing tools for RNA-seq studies

Differential splicing (DS) is a post-transcriptional biological process with critical, wide-ranging effects on a plethora of cellular activities and disease processes. To date, a number of computational approaches have been developed to identify and quantify differentially spliced genes from RNA-seq data, but a comprehensive intercomparison and appraisal of these approaches is currently lacking. In this study, we systematically evaluated 10 DS analysis tools for consistency and reproducibility, precision, recall and false discovery rate, agreement upon reported differentially spliced genes and functional enrichment. The tools were selected to represent the three different methodological categories: exon-based (DEXSeq, edgeR, JunctionSeq, limma), isoform-based (cuffdiff2, DiffSplice) and event-based methods (dSpliceType, MAJIQ, rMATS, SUPPA). Overall, all the exon-based methods and two event-based methods (MAJIQ and rMATS) scored well on the selected measures. Of the 10 tools tested, the exon-based methods performed generally better than the isoform-based and event-based methods. However, overall, the different data analysis tools performed strikingly differently across different data sets or numbers of samples

In utero exposures to perfluoroalkyl substances and the human fetal liver metabolome in Scotland : a cross-sectional study

The Fetal Human study was funded by the UK Medical Research Council (MR/L010011/1) to PAF, PJO’S, JPI, DCH, and AD, by the Seventh Framework Programme of the European Union under Grant Agreement 212885, and by NHS Grampian Endowments grants (08/02, 09/12, 13/56, and 15/1/010) to PAF. The metabolomics and exposomics study was supported by the Swedish Research Council (to TH and MO; grants 2016-05176 and 2020-03674), Formas (to TH and MO; grant 2019-00869), Novo Nordisk Foundation (to TH; grant NNF20OC0063971), Research Council of Finland (to MO; grant 333981), the Inflammation in human early life: targeting impacts on life-course health consortium funded by the Horizon Europe Program of the European Union (Grant Agreement 101094099 to MO, TH, and PAF), and the framework of the European Partnership for the Assessment of Risks from Chemicals, and has received funding from the European Union's Horizon Europe research and innovation programme (grant agreement 101057014). Views and opinions expressed are, however, those of the author(s) only and do not necessarily reflect those of the European Union or the Health and Digital Executive Agency. Neither the European Union nor the granting authority can be held responsible for them. The authors would like to thank (1) the Fowler team members, NHS Grampian research nurses, and staff at the Pregnancy Counselling Service for their essential work in recruiting, collecting, and processing fetuses; and (2) the Centre for Genome Enabled Biology and Medicine, University of Aberdeen, for carrying out the RNA-Seq. The RNA-Seq data analysis was supported by use of the University of Aberdeen Maxwell High Performance Computer Cluster.Peer reviewedPublisher PD

Exposure to environmental contaminants is associated with altered hepatic lipid metabolism in non-alcoholic fatty liver disease

Background & aims: Recent experimental models and epidemiological studies suggest that specific environmental contaminants (ECs) contribute to the initiation and pathology of nonalcoholic fatty liver disease (NAFLD). However, the underlying mechanisms linking EC exposure with NAFLD remain poorly understood and there is no data on their impact on the human liver metabolome. Herein, we hypothesized that exposure to ECs, particularly perfluorinated alkyl substances (PFAS), impacts liver metabolism, specifically bile acid metabolism. Methods: In a well-characterized human NAFLD cohort of 105 individuals, we investigated the effects of EC exposure on liver metabolism. We characterized the liver (via biopsy) and circulating metabolomes using 4 mass spectrometry-based analytical platforms, and measured PFAS and other ECs in serum. We subsequently compared these results with an exposure study in a PPARa-humanized mouse model. Results: PFAS exposure appears associated with perturbation of key hepatic metabolic pathways previously found altered in NAFLD, particularly those related to bile acid and lipid metabolism. We identified stronger associations between the liver metabolome, chemical exposure and NAFLD-associated clinical variables (liver fat content, HOMA-IR), in females than males. Specifically, we observed PFAS-associated upregulation of bile acids, triacylglycerols and ceramides, and association between chemical exposure and dysregulated glucose metabolism in females. The murine exposure study further corroborated our findings, vis-a-vis a sex-specific association between PFAS exposure and NAFLD-associated lipid changes. Conclusions: Females may be more sensitive to the harmful impacts of PFAS. Lipid-related changes subsequent to PFAS exposure may be secondary to the interplay between PFAS and bile acid metabolism. Lay summary: There is increasing evidence that specific environmental contaminants, such as perfluorinated alkyl substances (PFAS), contribute to the progression of non-alcoholic fatty liver disease (NAFLD). However, it is poorly understood how these chemicals impact human liver metabolism. Here we show that human exposure to PFAS impacts metabolic processes associated with NAFLD, and that the effect is different in females and males. (C) 2021 The Author(s). Published by Elsevier B.V. on behalf of European Association for the Study of the Liver.Peer reviewe

Metabolic signatures across the full spectrum of non-alcoholic fatty liver disease

Background & AimsNon-alcoholic fatty liver disease (NAFLD) is a progressive liver disease with potentially severe complications including cirrhosis and hepatocellular carcinoma. Previously, we have identified circulating lipid signatures associating with liver fat content and non-alcoholic steatohepatitis (NASH). Here, we develop a metabolomic map across the NAFLD spectrum, defining interconnected metabolic signatures of steatosis (non-alcoholic fatty liver, NASH, and fibrosis).MethodsWe performed mass spectrometry analysis of molecular lipids and polar metabolites in serum samples from the European NAFLD Registry patients (n = 627), representing the full spectrum of NAFLD. Using various univariate, multivariate, and machine learning statistical approaches, we interrogated metabolites across 3 clinical perspectives: steatosis, NASH, and fibrosis.ResultsFollowing generation of the NAFLD metabolic network, we identify 15 metabolites unique to steatosis, 18 to NASH, and 15 to fibrosis, with 27 common to all. We identified that progression from F2 to F3 fibrosis coincides with a key pathophysiological transition point in disease natural history, with n = 73 metabolites altered.ConclusionsAnalysis of circulating metabolites provides important insights into the metabolic changes during NAFLD progression, revealing metabolic signatures across the NAFLD spectrum and features that are specific to NAFL, NASH, and fibrosis. The F2–F3 transition marks a critical metabolic transition point in NAFLD pathogenesis, with the data pointing to the pathophysiological importance of metabolic stress and specifically oxidative stress.</p

Increased serum miR-193a-5p during non-alcoholic fatty liver disease progression: diagnostic and mechanistic relevance

Background & Aims: Serum microRNAs (miRNAs) levels are known to change in non-alcoholic fatty liver disease (NAFLD) and may serve as useful biomarkers. This study aimed to profile miRNAs comprehensively at all NAFLD stages.Methods: We profiled 2,083 serum miRNAs in a discovery cohort (183 NAFLD cases representing the complete NAFLD spectrum and 10 population controls). MiRNA libraries generated by HTG EdgeSeq were sequenced by Illumina NextSeq. Selected serum miRNAs were profiled in 372 additional NAFLD cases and 15 population controls by quantitative reverse transcriptase-polymerase chain reaction.Results: Levels of 275 miRNAs differed between cases and population controls. Fewer differences were seen within individual NAFLD stages but miR-193a-5p consistently the showed increased levels in all comparisons. Relative to NAFL/NASH with mild fibrosis (stage 0/1), three miRNAs (miR-193a-5p, miR-378d and miR378d) were increased in cases with NASH and clinically significant fibrosis (stage 2-4), seven (miR193a-5p, miR-378d, miR-378e, miR-320b, c, d & e) increased in cases with NAFLD Activity Score (NAS) 5-8 compared with lower NAS, and three (miR-193a-5p, miR-378d, miR-378e) increased but one (miR-19b-3p) decreased in steatosis, activity, and fibrosis "activity" (SAF-A) score 2-4 compared with lower SAF-A. The significant findings for miR-193a-5p were replicated in the additional NAFLD cohort. Studies in Hep G2 cells showed that following palmitic acid treatment, miR-193a-5p expression decreased significantly. Gene targets for miR-193a-5p were investigated in liver RNAseq data for a case subgroup (n=80); liver GPX8 levels correlated positively with serum miR-193a-5p. Conclusions: Serum miR-193a-5p levels correlate strongly with NAFLD activity grade and fibrosis stage. MiR-193a-5p may have a role in the hepatic response to oxidative stress and is a potential clinically tractable circulating biomarker for progressive NAFLD

Gene values and pathway scores.

<p>Representative example of (A) gene- and (B) pathway-level results on dataset T1D_1. Columns are samples and rows are (A) genes or (B) pathways. The gene expression values for the gene-level analysis were scaled as in PASI. The pathway scores were calculated with PASI. Blue colour indicates a low value and red colour a high value.</p

PASI: A novel pathway method to identify delicate group effects

<div><p>Pathway analysis is a common approach in diverse biomedical studies, yet the currently-available pathway tools do not typically support the increasingly popular personalized analyses. Another weakness of the currently-available pathway methods is their inability to handle challenging data with only modest group-based effects compared to natural individual variation. In an effort to address these issues, this study presents a novel pathway method PASI (Pathway Analysis for Sample-level Information) and demonstrates its performance on complex diseases with different levels of group-based differences in gene expression. PASI is freely available as an R package.</p></div

Comparison of PASI, Pathifier and PerPAS.

<p>Comparison of PASI, Pathifier and PerPAS.</p

Workflow of the pathway analysis for sample-level information PASI.

<p>The method involves four steps described briefly above and in more detail in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0199991#pone.0199991.s003" target="_blank">S1 Appendix</a>.</p