Genetic determinants of metabolism in health and disease: from biochemical genetics to genome-wide associations

Increasingly sophisticated measurement technologies have allowed the fields of metabolomics and genomics to identify, in parallel, risk factors of disease; predict drug metabolism; and study metabolic and genetic diversity in large human populations. Yet the complementarity of these fields and the utility of studying genes and metabolites together is belied by the frequent separate, parallel applications of genomic and metabolomic analysis. Early attempts at identifying co-variation and interaction between genetic variants and downstream metabolic changes, including metabolic profiling of human Mendelian diseases and quantitative trait locus mapping of individual metabolite concentrations, have recently been extended by new experimental designs that search for a large number of gene-metabolite associations. These approaches, including metabolomic quantitiative trait locus mapping and metabolomic genome-wide association studies, involve the concurrent collection of both genomic and metabolomic data and a subsequent search for statistical associations between genetic polymorphisms and metabolite concentrations across a broad range of genes and metabolites. These new data-fusion techniques will have important consequences in functional genomics, microbial metagenomics and disease modeling, the early results and implications of which are reviewed

Bistability in Apoptosis by Receptor Clustering

Apoptosis is a highly regulated cell death mechanism involved in many physiological processes. A key component of extrinsically activated apoptosis is the death receptor Fas, which, on binding to its cognate ligand FasL, oligomerize to form the death-inducing signaling complex. Motivated by recent experimental data, we propose a mathematical model of death ligand-receptor dynamics where FasL acts as a clustering agent for Fas, which form locally stable signaling platforms through proximity-induced receptor interactions. Significantly, the model exhibits hysteresis, providing an upstream mechanism for bistability and robustness. At low receptor concentrations, the bistability is contingent on the trimerism of FasL. Moreover, irreversible bistability, representing a committed cell death decision, emerges at high concentrations, which may be achieved through receptor pre-association or localization onto membrane lipid rafts. Thus, our model provides a novel theory for these observed biological phenomena within the unified context of bistability. Importantly, as Fas interactions initiate the extrinsic apoptotic pathway, our model also suggests a mechanism by which cells may function as bistable life/death switches independently of any such dynamics in their downstream components. Our results highlight the role of death receptors in deciding cell fate and add to the signal processing capabilities attributed to receptor clustering.Comment: Accepted by PLoS Comput Bio

Topological Analysis of Metabolic Networks Integrating Co-Segregating Transcriptomes and Metabolomes in Type 2 Diabetic Rat Congenic Series

Background: The genetic regulation of metabolic phenotypes (i.e., metabotypes) in type 2 diabetes mellitus is caused by complex organ-specific cellular mechanisms contributing to impaired insulin secretion and insulin resistance. Methods: We used systematic metabotyping by 1H NMR spectroscopy and genome-wide gene expression in white adipose tissue to map molecular phenotypes to genomic blocks associated with obesity and insulin secretion in a series of rat congenic strains derived from spontaneously diabetic Goto-Kakizaki (GK) and normoglycemic Brown-Norway (BN) rats. We implemented a network biology strategy approach to visualise shortest paths between metabolites and genes significantly associated with each genomic block. Results: Despite strong genomic similarities (95-99%) among congenics, each strain exhibited specific patterns of gene expression and metabotypes, reflecting metabolic consequences of series of linked genetic polymorphisms in the congenic intervals. We subsequently used the congenic panel to map quantitative trait loci underlying specific metabotypes (mQTL) and genome-wide expression traits (eQTL). Variation in key metabolites like glucose, succinate, lactate or 3-hydroxybutyrate, and second messenger precursors like inositol was associated with several independent genomic intervals, indicating functional redundancy in these regions. To navigate through the complexity of these association networks we mapped candidate genes and metabolites onto metabolic pathways and implemented a shortest path strategy to highlight potential mechanistic links between metabolites and transcripts at colocalized mQTLs and eQTLs. Minimizing shortest path length drove prioritization of biological validations by gene silencing. Conclusions: These results underline the importance of network-based integration of multilevel systems genetics datasets to improve understanding of the genetic architecture of metabotype and transcriptomic regulations and to characterize novel functional roles for genes determining tissue-specific metabolism

Metabonomics and Intensive Care

This article is one of ten reviews selected from the Annual Update in Intensive Care and Emergency medicine 2016. Other selected articles can be found online at http://www.biomedcentral.com/collections/annualupdate2016. Further information about the Annual Update in Intensive Care and Emergency Medicine is available from http://www.springer.com/series/8901

Understanding and optimising patient and public involvement in trial oversight: an ethnographic study of eight clinical trials

BACKGROUND: Trial oversight is important for trial governance and conduct. Patients and/or lay members of the public are increasingly included in trial oversight committees, influenced by international patient and public involvement (PPI) initiatives to improve the quality and relevance of research. However, there is a lack of guidance on how to undertake PPI in trial oversight and tokenistic PPI remains an issue. This paper explores how PPI functions in existing trial oversight committees and provides recommendations to optimise PPI in future trials. This was part of a larger study investigating the role and function of oversight committees in trials facing challenges. METHODS: Using an ethnographic study design, we observed oversight meetings of eight UK trials and conducted semi-structured interviews with members of their trial steering committees (TSCs) and trial management groups (TMGs) including public contributors, trial sponsors and funders. Thematic analysis of data was undertaken, with findings integrated to provide a multi-perspective account of how PPI functions in trial oversight. RESULTS: Eight TSC and six TMG meetings from eight trials were observed, and 66 semi-structured interviews conducted with 52 purposively sampled oversight group members, including three public contributors. PPI was reported as beneficial in trial oversight, with public members contributing a patient voice and fulfilling a patient advocacy role. However, public contributors were not always active at oversight meetings and were sometimes felt to have a tokenistic role, with trialists reporting a lack of understanding of how to undertake PPI in trial oversight. To optimise PPI in trial oversight, the following areas were highlighted: the importance of planning effective strategies to recruit public contributors; considering the level of oversight and stage(s) of trial to include PPI; support for public contributors by the trial team between and during oversight meetings. CONCLUSIONS: We present evidence-based recommendations to inform future PPI in trial oversight. Consideration should be given at trial design stage on how to recruit and involve public contributors within trial oversight, as well as support and mentorship for both public contributors and trialists (in how to undertake PPI effectively). Findings from this study further strengthen the evidence base on facilitating meaningful PPI within clinical trials

Lack of Cetuximab induced skin toxicity in a previously irradiated field: case report and review of the literature

<p>Abstract</p> <p>Introduction</p> <p>Mutation, amplification or dysregulation of the EGFR family leads to uncontrolled division and predisposes to cancer. Inhibiting the EGFR represents a form of targeted cancer therapy.</p> <p>Case report</p> <p>We report the case of 79 year old gentlemen with a history of skin cancer involving the left ear who had radiation and surgical excision. He had presented with recurrent lymph node in the left upper neck. We treated him with radiation therapy concurrently with Cetuximab. He developed a skin rash over the face and neck area two weeks after starting Cetuximab, which however spared the previously irradiated area.</p> <p>Conclusion</p> <p>The etiology underlying the sparing of the previously irradiated skin maybe due to either decrease in the population of EGFR expressing cells or decrease in the EGFR expression.</p> <p>We raised the question that "Is it justifiable to use EGFR inhibitors for patients having recurrence in the previously irradiated field?" We may need further research to answer this question which may guide the physicians in choosing appropriate drug in this scenario.</p

Measuring perinatal complications: methodologic issues related to gestational age

<p>Abstract</p> <p>Background</p> <p>Perinatal outcomes differ by week of gestational age. However, it appears that how measures to examine these outcomes vary among various studies. The current paper explores how perinatal complications are reported and how they might differ when different denominators, numerators, and comparison groups are utilized.</p> <p>Conclusion</p> <p>One issue that can clearly affect absolute rates and trends is how groups of women are categorized by their gestational age. Since most perinatal outcomes can only occur in women and neonates who have delivered, using the number of pregnancies delivered (PD) as the denominator of outcomes is appropriate. However, for an outcome such as antepartum stillbirth, all women who are pregnant at a particular gestational age are at risk. Thus, the denominator should include all ongoing pregnancies (OP). When gestational age is used by week this means using both deliveries during a particular week plus those women who deliver beyond the particular week of gestation in the denominator. Researchers should be careful to make sure they are utilizing the appropriate measure of perinatal complications so they do not report findings that would be misleading to clinicians, patients, and policy makers.</p