Taxanorm: a novel taxa-specific normalization approach for microbiome data

BACKGROUND

In high-throughput sequencing studies, sequencing depth, which quantifies the total number of reads, varies across samples. Unequal sequencing depth can obscure true biological signals of interest and prevent direct comparisons between samples. To remove variability due to differential sequencing depth, taxa counts are usually normalized before downstream analysis. However, most existing normalization methods scale counts using size factors that are sample specific but not taxa specific, which can result in over- or under-correction for some taxa.

RESULTS

We developed TaxaNorm, a novel normalization method based on a zero-inflated negative binomial model. This method assumes the effects of sequencing depth on mean and dispersion vary across taxa. Incorporating the zero-inflation part can better capture the nature of microbiome data. We also propose two corresponding diagnosis tests on the varying sequencing depth effect for validation. We find that TaxaNorm achieves comparable performance to existing methods in most simulation scenarios in downstream analysis and reaches a higher power for some cases. Specifically, it balances power and false discovery control well. When applying the method in a real dataset, TaxaNorm has improved performance when correcting technical bias.

CONCLUSION

TaxaNorm both sample- and taxon- specific bias by introducing an appropriate regression framework in the microbiome data, which aids in data interpretation and visualization. The 'TaxaNorm' R package is freely available through the CRAN repository https://CRAN.R-project.org/package=TaxaNorm and the source code can be downloaded at https://github.com/wangziyue57/TaxaNorm .

Interactive data sharing for multiple questionnaire-based exposome-wide association studies and exposome correlations in the Personalized Environment and Genes Study

The correlations among individual exposures in the exposome, which refers to all exposures an individual encounters throughout life, are important for understanding the landscape of how exposures co-occur, and how this impacts health and disease. Exposome-wide association studies (ExWAS), which are analogous to genome-wide association studies (GWAS), are increasingly being used to elucidate links between the exposome and disease. Despite increased interest in the exposome, tools and publications that characterize exposure correlations and their relationships with human disease are limited, and there is a lack of data and results sharing in resources like the GWAS catalog. To address these gaps, we developed the PEGS Explorer web application to explore exposure correlations in data from the diverse North Carolina-based Personalized Environment and Genes Study (PEGS) that were rigorously calculated to account for differing data types and previously published results from ExWAS. Through globe visualizations, PEGS Explorer allows users to explore correlations between exposures found to be associated with complex diseases. The exposome data used for analysis includes not only standard environmental exposures such as point source pollution and ozone levels but also exposures from diet, medication, lifestyle factors, stress, and occupation. The web application addresses the lack of accessible data and results sharing, a major challenge in the field, and enables users to put results in context, generate hypotheses, and, importantly, replicate findings in other cohorts. PEGS Explorer will be updated with additional results as they become available, ensuring it is an up-to-date resource in exposome science.

Questionnaire-based exposome-wide association studies for common diseases in the Personalized Environment and Genes Study

The exposome collectively refers to all exposures, beginning in utero and continuing throughout life, and comprises not only standard environmental exposures such as point source pollution and ozone levels but also exposures from diet, medication, lifestyle factors, stress, and occupation. The exposome interacts with individual genetic and epigenetic characteristics to affect human health and disease, but large-scale studies that characterize the exposome and its relationships with human disease are limited. To address this gap, we used extensive questionnaire data from the diverse North Carolina-based Personalized Environment and Genes Study (PEGS, n = 9, 429) to evaluate exposure associations in relation to common diseases. We performed an exposome-wide association study (ExWAS) to examine single exposure models and their associations with 11 common complex diseases, namely allergic rhinitis, asthma, bone loss, fibroids, high cholesterol, hypertension, iron-deficient anemia, ovarian cysts, lower GI polyps, migraines, and type 2 diabetes. Across diseases, we found associations with lifestyle factors and socioeconomic status as well as asbestos, various dust types, biohazardous material, and textile-related exposures. We also found disease-specific associations such as fishing with lead weights and migraines. To differentiate between a replicated result and a novel finding, we used an AI-based literature search and database tool that allowed us to examine the current literature. We found both replicated findings, especially for lifestyle factors such as sleep and smoking across diseases, and novel findings, especially for occupational exposures and multiple diseases.

Recombinant inbred lines derived from wide crosses in Pisum

Genomic resources are becoming available for Pisum but to link these to phenotypic diversity requires well marked populations segregating for relevant traits. Here we describe two such resources. Two recombinant inbred populations, derived from wide crosses in Pisum are described. One high resolution mapping population involves cv Caméor, for which the first pea whole genome assembly was obtained, crossed to JI0281, a basally divergent P. sativum sativum landrace from Ethiopia. The other is an inter sub-specific cross between P. s. sativum and the independently domesticated P. s. abyssinicum. The corresponding genetic maps provide information on chromosome level sequence assemblies and identify structural differences between the genomes of these two Pisum subspecies. In order to visualise chromosomal translocations that distinguish the mapping parents, we created a simplified version of Threadmapper to optimise it for interactive 3-dimensional display of multiple linkage groups. The genetic mapping of traits affecting seed coat roughness and colour, plant height, axil ring pigmentation, leaflet number and leaflet indentation enabled the definition of their corresponding genomic regions. The consequence of structural rearrangement for trait analysis is illustrated by leaf serration. These analyses pave the way for identification of the underlying genes and illustrate the utility of these publicly available resources. Segregating inbred populations derived from wide crosses in Pisum, together with the associated marker data, are made publicly available for trait dissection. Genetic analysis of these populations is informative about chromosome scale assemblies, structural diversity in the pea genome and has been useful for the fine mapping of several discrete and quantitative traits.

Questionnaire-Based Polyexposure Assessment Outperforms Polygenic Scores for Classification of Type 2 Diabetes in a Multiancestry Cohort

OBJECTIVE

Environmental exposures may have greater predictive power for type 2 diabetes than polygenic scores (PGS). Studies examining environmental risk factors, however, have included only individuals with European ancestry, limiting the applicability of results. We conducted an exposome-wide association study in the multiancestry Personalized Environment and Genes Study to assess the effects of environmental factors on type 2 diabetes.

RESEARCH DESIGN AND METHODS

Using logistic regression for single-exposure analysis, we identified exposures associated with type 2 diabetes, adjusting for age, BMI, household income, and self-reported sex and race. To compare cumulative genetic and environmental effects, we computed an overall clinical score (OCS) as a weighted sum of BMI and prediabetes, hypertension, and high cholesterol status and a polyexposure score (PXS) as a weighted sum of 13 environmental variables. Using UK Biobank data, we developed a multiancestry PGS and calculated it for participants.

RESULTS

We found 76 significant associations with type 2 diabetes, including novel associations of asbestos and coal dust exposure. OCS, PXS, and PGS were significantly associated with type 2 diabetes. PXS had moderate power to determine associations, with larger effect size and greater power and reclassification improvement than PGS. For all scores, the results differed by race.

CONCLUSIONS

Our findings in a multiancestry cohort elucidate how type 2 diabetes odds can be attributed to clinical, genetic, and environmental factors and emphasize the need for exposome data in disease-risk association studies. Race-based differences in predictive scores highlight the need for genetic and exposome-wide studies in diverse populations.

A dynamically coherent pattern of rhythms that matches between distant species across the evolutionary scale

We address the temporal organization of circadian and ultradian rhythms, crucial for understanding biological timekeeping in behavior, physiology, metabolism, and alignment with geophysical time. Using a newly developed five-steps wavelet-based approach to analyze high-resolution time series of metabolism in yeast cultures and spontaneous movement, metabolism, and feeding behavior in mice, rats, and quails, we describe a dynamically coherent pattern of rhythms spanning over a broad range of temporal scales (hours to minutes). The dynamic pattern found shares key features among the four, evolutionary distant, species analyzed. Specifically, a branching appearance given by splitting periods from 24 h into 12 h, 8 h and below in mammalian and avian species, or from 14 h down to 0.07 h in yeast. Scale-free fluctuations with long-range correlations prevail below ~ 4 h. Synthetic time series modeling support a scenario of coexisting behavioral rhythms, with circadian and ultradian rhythms at the center of the emergent pattern observed.

Sex-specific DNA methylation and associations with in utero tobacco smoke exposure at nuclear-encoded mitochondrial genes

Sex-linked differences in mitochondrial ATP production, enzyme activities, and reactive oxygen species generation have been reported in multiple tissue and cell types. While the effects of reproductive hormones underlie many of these differences, regulation of sexually dimorphic mitochondrial function has not been fully characterized. We hypothesized that sex-specific DNA methylation contributes to sex-specific expression of nuclear genes that influence mitochondrial function. Herein, we analysed DNA methylation data specifically focused on nuclear-encoded mitochondrial genes in 191 males and 190 females. We found 596 differentially methylated sites (DMSs) (FDR p < 0.05), corresponding to 324 genes, with at least a 1% difference in methylation between sexes. To investigate the potential functional significance, we utilized gene expression microarray data. Of the 324 genes containing DMSs, 17 showed differences in gene expression by sex. Particularly striking was that ATP5G2, encoding subunit C of ATP synthase, contains seven DMSs and exhibits a sex difference in expression (p = 0.04). Finally, we also found that alterations in DNA methylation associated with in utero tobacco smoke exposure were sex-specific in these nuclear-encoded mitochondrial genes. Interestingly, the level of sex differences in DNA methylation at nuclear-encoded mitochondrial genes and the level of methylation changes associated with smoke exposure were less prominent than that of other genes. This suggests more conservative regulation of DNA methylation at these nuclear-encoded mitochondrial genes as compared to others. Overall, our findings suggest that sex-specific DNA methylation may help establish sex differences in expression and function and that sex-specific alterations in DNA methylation in response to exposures could contribute to sex-variable toxicological responses.

542 Laparoscopic Division of a Congenital Splenogonadal Portosystemic Shunt: A Case Report

We describe a rare congenital portosystemic shunt. A 37-year-old woman was found to have a previously unreported congenital shunt following investigations into secondary causes of hypertension. The abnormal venous shunt connected the splenic vein to the left ovarian vein. The patient underwent a laparoscopic procedure to successfully divide the shunt. She made a full recovery without complications. To our knowledge, this is the first presentation of a congenital portosystemic shunt involving the splenic and ovarian veins to be reported. This case demonstrates that such a shunt can be amenable for laparoscopic management. The case report shows preoperative scans and intraoperative images.

Environmental impacts of Hurricane Florence flooding in eastern North Carolina: temporal analysis of contaminant distribution and potential human health risks

BACKGROUND

Hurricane Florence made landfall in North Carolina in September 2018 causing extensive flooding. Several potential point sources of hazardous substances and Superfund sites sustained water damage and contaminants may have been released into the environment.

OBJECTIVE

This study conducted temporal analysis of contaminant distribution and potential human health risks from Hurricane Florence-associated flooding.

METHODS

Soil samples were collected from 12 sites across four counties in North Carolina in September 2018, January and May 2019. Chemical analyses were performed for organics by gas chromatography-mass spectrometry. Metals were analyzed using inductively coupled plasma mass spectrometry. Hazard index and cancer risk were calculated using EPA Regional Screening Level Soil Screening Levels for residential soils.

RESULTS

PAH and metals detected downstream from the coal ash storage pond that leaked were detected and were indicative of a pyrogenic source of contamination. PAH at these sites were of human health concern because cancer risk values exceeded 1 × 10^-6 threshold. Other contaminants measured across sampling sites, or corresponding hazard index and cancer risk, did not exhibit spatial or temporal differences or were of concern.

SIGNIFICANCE

This work shows the importance of rapid exposure assessment following natural disasters. It also establishes baseline levels of contaminants for future comparisons.

Risk Characterization of Environmental Samples Using In Vitro Bioactivity and Polycyclic Aromatic Hydrocarbon Concentrations Data

Methods to assess environmental exposure to hazardous chemicals have primarily focused on quantification of individual chemicals, although chemicals often occur in mixtures, presenting challenges to the traditional risk characterization framework. Sampling sites in a defined geographic region provide an opportunity to characterize chemical contaminants, with spatial interpolation as a tool to provide estimates for non-sampled sites. At the same time, the use of in vitro bioactivity measurements has been shown to be informative for rapid risk-based decisions. In this study, we measured in vitro bioactivity in 39 surface soil samples collected immediately after flooding associated with Hurricane Harvey in Texas in a residential area known to be inundated with polycyclic aromatic hydrocarbon (PAH) contaminants. Bioactivity data were from a number of functional and toxicity assays in 5 human cell types, such as induced pluripotent stem cell-derived hepatocytes, cardiomyocytes, neurons, and endothelial cells, as well as human umbilical vein endothelial cells. Data on concentrations of PAH in these samples were also available and the combination of data sources offered a unique opportunity to assess the joint spatial variation of PAH components and bioactivity. We found significant evidence of spatial correlation of a subset of PAH contaminants and of cell-based phenotypes. In addition, we show that the cell-based bioactivity data can be used to predict environmental concentrations for several PAH contaminants, as well as overall PAH summaries and cancer risk. This study's impact lies in its demonstration that cell-based profiling can be used for rapid hazard screening of environmental samples by anchoring the bioassays to concentrations of PAH. This work sets the stage for identification of the areas of concern and direct quantitative risk characterization based on bioactivity data, thereby providing an important supplement to traditional individual chemical analyses by shedding light on constituents that may be missed from targeted chemical monitoring.

Waterlow score for risk assessment in surgical patients: a systematic review

INTRODUCTION

The Waterlow score (WS) is used routinely in clinical practice to assess risk of pressure sore development. Recent studies have also suggested its use in preoperative risk stratification. The primary aim of this systematic review was to evaluate the current evidence on the WS in predicting morbidity and mortality in surgical patients.

METHODS

A systematic review was carried out in accordance with PRISMA and SWiM guidelines. A search strategy was conducted on the MEDLINE and EMBASE databases. Quality was assessed using the Newcastle-Ottawa scale.

FINDINGS

Overall, 72 papers were identified, of which 7 met inclusion criteria for full text review, and 4 were included for analysis. All studies were cohort in nature and published between 2013 and 2016, encompassing a total of 505 surgical patients. The studies included general, vascular, transplant and orthopaedic surgery. A high WS was demonstrated to have statistically significant association with increased morbidity and mortality as well as need for intensive care unit admission and length of stay. Furthermore, this was a more accurate predictor compared with the P-POSSUM and ASA scoring systems used currently in routine practice.

CONCLUSIONS

The WS is a promising tool for risk stratification of surgical patients. It is already collected routinely by nursing staff throughout hospitals in the UK and would therefore be easy to implement. However, further large prospective studies are required in order to validate these findings prior to its establishment for this role in everyday surgical practice.

Classification of estrogenic compounds by coupling high content analysis and machine learning algorithms

Environmental toxicants affect human health in various ways. Of the thousands of chemicals present in the environment, those with adverse effects on the endocrine system are referred to as endocrine-disrupting chemicals (EDCs). Here, we focused on a subclass of EDCs that impacts the estrogen receptor (ER), a pivotal transcriptional regulator in health and disease. Estrogenic activity of compounds can be measured by many in vitro or cell-based high throughput assays that record various endpoints from large pools of cells, and increasingly at the single-cell level. To simultaneously capture multiple mechanistic ER endpoints in individual cells that are affected by EDCs, we previously developed a sensitive high throughput/high content imaging assay that is based upon a stable cell line harboring a visible multicopy ER responsive transcription unit and expressing a green fluorescent protein (GFP) fusion of ER. High content analysis generates voluminous multiplex data comprised of minable features that describe numerous mechanistic endpoints. In this study, we present a machine learning pipeline for rapid, accurate, and sensitive assessment of the endocrine-disrupting potential of benchmark chemicals based on data generated from high content analysis. The multidimensional imaging data was used to train a classification model to ultimately predict the impact of unknown compounds on the ER, either as agonists or antagonists. To this end, both linear logistic regression and nonlinear Random Forest classifiers were benchmarked and evaluated for predicting the estrogenic activity of unknown compounds. Furthermore, through feature selection, data visualization, and model discrimination, the most informative features were identified for the classification of ER agonists/antagonists. The results of this data-driven study showed that highly accurate and generalized classification models with a minimum number of features can be constructed without loss of generality, where these machine learning models serve as a means for rapid mechanistic/phenotypic evaluation of the estrogenic potential of many chemicals.

Chemical contaminants or toxicants pose environmental and health-related risks for exposure. The ability to rapidly understand their biological impact, specifically on a key modulator of important physiological and pathological states in the human body is essential for diagnosing and avoiding undesirable health outcomes during environmental emergencies. In this study, we use advanced data analytics for creating statistical models that can accurately predict the endocrinological activity of toxic chemicals based on high throughput/high content image analysis data. We focus on a subclass of chemicals that affect the estrogen receptor (ER), which is a pivotal transcriptional regulator in health and disease. The multidimensional imaging data of these benchmark chemicals are used to train a classification model to ultimately predict the impact of unknown compounds on the ER, either as agonists or antagonists. To this end, we evaluate linear and nonlinear classifiers for predicting the estrogenic activity of unknown compounds and use feature selection, data visualization, and model discrimination methodologies to identify the most informative features for the classification of ER agonists/antagonists.

BEVA primary care clinical guidelines: Analgesia

Primary care guidelines provide a reference point to guide clinicians based on a systematic review of the literature, contextualised by expert clinical opinion. These guidelines develop a modification of the GRADE framework for assessment of research evidence (vetGRADE) and applied this to a range of clinical scenarios regarding use of analgesic agents. Key guidelines produced by the panel included recommendations that horses undergoing routine castration should receive intratesticular local anaesthesia irrespective of methods adopted and that horses should receive NSAIDs prior to surgery (overall certainty levels high). Butorphanol and buprenorphine should not be considered appropriate as sole analgesic for such procedures (high certainty). The panel recommend the continuation of analgesia for 3 days following castration (moderate certainty) and conclude that phenylbutazone provided superior analgesia to meloxicam and firocoxib for hoof pain/laminitis (moderate certainty), but that enhanced efficacy has not been demonstrated for joint pain. In horses with colic, flunixin and firocoxib are considered to provide more effective analgesia than meloxicam or phenylbutazone (moderate certainty). Given the risk of adverse events of all classes of analgesic, these agents should be used only under the control of a veterinary surgeon who has fully evaluated a horse and developed a therapeutic, analgesic plan that includes ongoing monitoring for such adverse events such as the development of right dorsal colitis with all classes of NSAID and spontaneous locomotor activity and potentially ileus with opiates. Finally, the panel call for the development of a single properly validated composite pain score for horses to allow accurate comparisons between medications in a robust manner.

Chondromalacia of the cranial medial femoral condyle; its occurrence and association with clinical outcome in a population of adult horses with stifle lameness

BACKGROUND

Chondromalacia of the cranial medial femoral condyle (CMFC) is a potential cause of stifle lameness in adult horses. However, there is scant published evidence of either its occurrence or its clinical significance.

OBJECTIVES

To document the occurrence of CMFC seen during diagnostic arthroscopy in adult horses with stifle lameness and to investigate its prognostic significance.

STUDY DESIGN

Retrospective cohort study.

METHODS

The records were reviewed of all horses with unilateral or bilateral lameness localised to the stifle that underwent diagnostic arthroscopy of the cranial medial femorotibial joint at a UK equine hospital. The surgical findings were noted from each. Case outcomes were determined by unstructured telephone discussions with owners. A satisfactory outcome was defined as a horse that was in ridden work without ongoing anti-inflammatory medication. Multivariable logistic regression was used to create a model with an outcome time point at 12-month post-operatively.

RESULTS

One hundred and four horses were included in the study. CMFC was found in 79. In 25 CMFC was the only finding, 54 horses had CMFC plus other pathology and 25 had other pathology, but no CMFC. At 12 months, horses with CMFC were 9.9 (95% CI 2.2-45.0, P<0.01) times more likely to have an unsatisfactory outcome than horses without CMFC.

MAIN LIMITATIONS

The study relied on retrospective analysis of clinical notes and archived arthroscopy videos. Assessment of outcome was determined by unstructured telephone interview and therefore there is potential for reporting errors to exist.

CONCLUSIONS

CMFC is a common arthroscopic finding in horses with stifle lameness and is significantly associated with an increased likelihood of the horse not being in ridden work at long-term follow-up.

BIODOSIMETRY AND BIODOSIMETRY NETWORKS FOR MANAGING RADIATION EMERGENCY

Biological dosimetry enables individual dose reconstruction in the case of unclear or inconsistent radiation exposure situations, especially when a direct measurement of ionizing radiation is not or is no longer possible. To be prepared for large-scale radiological incidents, networking between well-trained laboratories has been identified as a useful approach for provision of the fast and trustworthy dose assessments needed in such circumstances. To this end, various biodosimetry laboratories worldwide have joined forces and set up regional and/or nationwide networks either on a formal or informal basis. Many of these laboratories are also a part of global networks such as those organized by World Health Organization, International Atomic Energy Agency or Global Health Security Initiative. In the present report, biodosimetry networks from different parts of the world are presented, and the partners, activities and cooperation actions are detailed. Moreover, guidance for situational application of tools used for individual dosimetry is given.

Population-based cohort study of variation in the use of emergency cholecystectomy for benign gallbladder diseases

Background

The aims of this prospective population-based cohort study were to identify the patient and hospital characteristics associated with emergency cholecystectomy, and the influences of these in determining variations between hospitals.

Methods

Data were collected for consecutive patients undergoing cholecystectomy in acute UK and Irish hospitals between 1 March and 1 May 2014. Potential explanatory variables influencing the performance of emergency cholecystectomy were analysed by means of multilevel, multivariable logistic regression modelling using a two-level hierarchical structure with patients (level 1) nested within hospitals (level 2).

Results

Data were collected on 4744 cholecystectomies from 165 hospitals. Increasing age, lower ASA fitness grade, biliary colic, the need for further imaging (magnetic retrograde cholangiopancreatography), endoscopic interventions (endoscopic retrograde cholangiopancreatography) and admission to a non-biliary centre significantly reduced the likelihood of an emergency cholecystectomy being performed. The multilevel model was used to calculate the probability of receiving an emergency cholecystectomy for a woman aged 40 years or over with an ASA grade of I or II and a BMI of at least 25·0 kg/m2, who presented with acute cholecystitis with an ultrasound scan showing a thick-walled gallbladder and a normal common bile duct. The mean predicted probability of receiving an emergency cholecystectomy was 0·52 (95 per cent c.i. 0·45 to 0·57). The predicted probabilities ranged from 0·02 to 0·95 across the 165 hospitals, demonstrating significant variation between hospitals.

Conclusion

Patients with similar characteristics presenting to different hospitals with acute gallbladder pathology do not receive comparable care.

Multiscale musculoskeletal modelling, data-model fusion and electromyography-informed modelling

This paper proposes methods and technologies that advance the state of the art for modelling the musculoskeletal system across the spatial and temporal scales; and storing these using efficient ontologies and tools. We present population-based modelling as an efficient method to rapidly generate individual morphology from only a few measurements and to learn from the ever-increasing supply of imaging data available. We present multiscale methods for continuum muscle and bone models; and efficient mechanostatistical methods, both continuum and particle-based, to bridge the scales. Finally, we examine both the importance that muscles play in bone remodelling stimuli and the latest muscle force prediction methods that use electromyography-assisted modelling techniques to compute musculoskeletal forces that best reflect the underlying neuromuscular activity. Our proposal is that, in order to have a clinically relevant virtual physiological human, (i) bone and muscle mechanics must be considered together; (ii) models should be trained on population data to permit rapid generation and use underlying principal modes that describe both muscle patterns and morphology; and (iii) these tools need to be available in an open-source repository so that the scientific community may use, personalize and contribute to the database of models.