Does prenylation predict progression in NAFLD?

Non-alcoholic fatty liver disease (NAFLD) often develops in concert with related metabolic diseases, such as obesity, dyslipidemia and insulin resistance. Prolonged lipid accumulation and inflammation can progress to non-alcoholic steatohepatitis (NASH). Although factors associated with the development of NAFLD are known, triggers for the progression of NAFLD to NASH are poorly understood. Recent findings published in The Journal of Pathology reveal the possible regulation of NASH progression by metabolites of the mevalonate pathway. Mevalonate can be converted into the isoprenoids farnesyldiphosphate (FPP) and geranylgeranyl diphosphate (GGPP). GGPP synthase (GGPPS), the enzyme that converts FPP to GGPP, is dysregulated in humans and mice during NASH. Both FPP and GGPP can be conjugated to proteins through prenylation, modifying protein function and localization. Deletion or knockdown of GGPPS favors FPP prenylation (farnesylation) and augments the function of liver kinase B1, an upstream kinase of AMP-activated protein kinase (AMPK). Despite increased AMPK activation, livers in Ggpps-deficient mice on a high-fat diet poorly oxidize lipids due to mitochondrial dysfunction. Although work from Liu et al provides evidence as to the potential importance of the prenylation portion of the mevalonate pathway during NAFLD, future studies are necessary to fully grasp any therapeutic or diagnostic potential. Copyright © 2018 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.     

GeneYenta: A Phenotype­Based Rare Disease Case Matching Tool Based on Online Dating Algorithms for the Acceleration of Exome Interpretation

Advances in next‐generation sequencing (NGS) technologies have helped reveal causal variants for genetic diseases. In order to establish causality, it is often necessary to compare genomes of unrelated individuals with similar disease phenotypes to identify common disrupted genes. When working with cases of rare genetic disorders, finding similar individuals can be extremely difficult. We introduce a web tool, GeneYenta, which facilitates the matchmaking process, allowing clinicians to coordinate detailed comparisons for phenotypically similar cases. Importantly, the system is focused on phenotype annotation, with explicit limitations on highly confidential data that create barriers to participation. The procedure for matching of patient phenotypes, inspired by online dating services, uses an ontology­based semantic case matching algorithm with attribute weighting. We evaluate the capacity of the system using a curated reference data set and 19 clinician entered cases comparing four matching algorithms. We find that the inclusion of clinician weights can augment phenotype matching.     

Influence of conduction disturbances on clinical outcome in patients with acute myocardial infarction receiving thrombolysis (results from the ARGAMI-2 study)

Right bundle branch block and complete atrioventricular (AV) block are conduction disorders (CDs) that have been observed in 14% of patients admitted with ST-elevation acute myocardial infarction. CDs carry a poor prognosis, with a threefold increase in the mortality rate, mainly due to cardiogenic shock and recurrent fatal myocardial infarction at 1-year follow-up. According to multivariable analysis, CD was the second strongest predictor of death, after high Killip class. Compared with patients without CD, the 1-year outcome of patients with CD was identically worse, irrespective of whether CD appeared during admission, disappeared, or remained constant. Similar adverse outcomes were seen in patients with complete AV block and right bundle branch block.