Analysis of Escherichia coli RNase E and RNase III activity in vivo using tiling microarrays

Tiling microarrays have proven to be a valuable tool for gaining insights into the transcriptomes of microbial organisms grown under various nutritional or stress conditions. Here, we describe the use of such an array, constructed at the level of 20 nt resolution for the Escherichia coli MG1655 genome, to observe genome-wide changes in the steady-state RNA levels in mutants defective in either RNase E or RNase III. The array data were validated by comparison to previously published results for a variety of specific transcripts as well as independent northern analysis of additional mRNAs and sRNAs. In the absence of RNase E, 60% of the annotated coding sequences showed either increases or decreases in their steady-state levels. In contrast, only 12% of the coding sequences were affected in the absence of RNase III. Unexpectedly, many coding sequences showed decreased abundance in the RNase E mutant, while more than half of the annotated sRNAs showed changes in abundance. Furthermore, the steady-state levels of many transcripts showed overlapping effects of both ribonucleases. Data are also presented demonstrating how the arrays were used to identify potential new genes, RNase III cleavage sites and the direct or indirect control of specific biological pathways

The PedAL/EuPAL Project:A Global Initiative to Address the Unmet Medical Needs of Pediatric Patients with Relapsed or Refractory Acute Myeloid Leukemia

The prognosis of children with acute myeloid leukemia (AML) has improved incrementally over the last few decades. However, at relapse, overall survival (OS) is approximately 40–50% and is even lower for patients with chemo-refractory disease. Effective and less toxic therapies are urgently needed for these children. The Pediatric Acute Leukemia (PedAL) program is a strategic global initiative that aims to overcome the obstacles in treating children with relapsed/refractory acute leukemia and is supported by the Leukemia and Lymphoma Society in collaboration with the Children’s Oncology Group, the Innovative Therapies for Children with Cancer consortium, and the European Pediatric Acute Leukemia (EuPAL) foundation, amongst others. In Europe, the study is set up as a complex clinical trial with a stratification approach to allocate patients to sub-trials of targeted inhibitors at relapse and employing harmonized response and safety definitions across sub-trials. The PedAL/EuPAL international collaboration aims to determine new standards of care for AML in a first and second relapse, using biology-based selection markers for treatment stratification, and deliver essential data to move drugs to front-line pediatric AML studies. An overview of potential treatment targets in pediatric AML, focused on drugs that are planned to be included in the PedAL/EuPAL project, is provided in this manuscript.</p

The PedAL/EuPAL Project:A Global Initiative to Address the Unmet Medical Needs of Pediatric Patients with Relapsed or Refractory Acute Myeloid Leukemia

The prognosis of children with acute myeloid leukemia (AML) has improved incrementally over the last few decades. However, at relapse, overall survival (OS) is approximately 40–50% and is even lower for patients with chemo-refractory disease. Effective and less toxic therapies are urgently needed for these children. The Pediatric Acute Leukemia (PedAL) program is a strategic global initiative that aims to overcome the obstacles in treating children with relapsed/refractory acute leukemia and is supported by the Leukemia and Lymphoma Society in collaboration with the Children’s Oncology Group, the Innovative Therapies for Children with Cancer consortium, and the European Pediatric Acute Leukemia (EuPAL) foundation, amongst others. In Europe, the study is set up as a complex clinical trial with a stratification approach to allocate patients to sub-trials of targeted inhibitors at relapse and employing harmonized response and safety definitions across sub-trials. The PedAL/EuPAL international collaboration aims to determine new standards of care for AML in a first and second relapse, using biology-based selection markers for treatment stratification, and deliver essential data to move drugs to front-line pediatric AML studies. An overview of potential treatment targets in pediatric AML, focused on drugs that are planned to be included in the PedAL/EuPAL project, is provided in this manuscript.</p

High density genetic mapping identifies new susceptibility loci for rheumatoid arthritis

Summary Using the Immunochip custom single nucleotide polymorphism (SNP) array, designed for dense genotyping of 186 genome wide association study (GWAS) confirmed loci we analysed 11,475 rheumatoid arthritis cases of European ancestry and 15,870 controls for 129,464 markers. The data were combined in meta-analysis with GWAS data from additional independent cases (n=2,363) and controls (n=17,872). We identified fourteen novel loci; nine were associated with rheumatoid arthritis overall and 5 specifically in anti-citrillunated peptide antibody positive disease, bringing the number of confirmed European ancestry rheumatoid arthritis loci to 46. We refined the peak of association to a single gene for 19 loci, identified secondary independent effects at six loci and association to low frequency variants (minor allele frequency <0.05) at 4 loci. Bioinformatic analysis of the data generated strong hypotheses for the causal SNP at seven loci. This study illustrates the advantages of dense SNP mapping analysis to inform subsequent functional investigations

High-density genetic mapping identifies new susceptibility loci for rheumatoid arthritis.

Using the Immunochip custom SNP array, which was designed for dense genotyping of 186 loci identified through genome-wide association studies (GWAS), we analyzed 11,475 individuals with rheumatoid arthritis (cases) of European ancestry and 15,870 controls for 129,464 markers. We combined these data in a meta-analysis with GWAS data from additional independent cases (n = 2,363) and controls (n = 17,872). We identified 14 new susceptibility loci, 9 of which were associated with rheumatoid arthritis overall and five of which were specifically associated with disease that was positive for anticitrullinated peptide antibodies, bringing the number of confirmed rheumatoid arthritis risk loci in individuals of European ancestry to 46. We refined the peak of association to a single gene for 19 loci, identified secondary independent effects at 6 loci and identified association to low-frequency variants at 4 loci. Bioinformatic analyses generated strong hypotheses for the causal SNP at seven loci. This study illustrates the advantages of dense SNP mapping analysis to inform subsequent functional investigations

Serious adverse events reported in placebo randomised controlled trials of oral naltrexone: a systematic review and meta-analysis

Background Naltrexone is an opioid antagonist used in many different conditions, both licensed and unlicensed. It is used at widely varying doses from 3 - 250 mg. The aim of this review was to evaluate the safety of oral naltrexone by examining the risk of serious adverse events (SAEs) in randomised controlled trials (RCTs) of naltrexone compared to placebo. Methods A systematic search of Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, EMBASE, other databases and clinical trials registries was undertaken up to March 2018. Parallel placebo-controlled RCTs longer than 4 weeks published after 1/1/2001, of oral naltrexone at any dose were selected. Any condition and age group were included, excluding only studies for opioid or ex-opioid users, due to possible opioid/opioid antagonist interactions. The systematic review used the guidance of the Cochrane Handbook throughout. Numerical data was independently extracted by two people and cross-checked. Risk of bias was assessed with the Cochrane Risk of Bias Tool. Meta-analyses were performed using Stata 15 and R, using random and fixed effects models throughout. Results Eighty-nine RCTs with 11194 participants were found, studying alcohol use disorders, various psychiatric disorders, impulse control disorders, other addictions, obesity, Crohn’s disease, fibromyalgia and cancers. Twenty-six studies (4,960 participants) recorded SAEs occurring by arm of study. There was no evidence of increased risk of SAEs for naltrexone compared to placebo, relative risk (RR) 0.84 (95% CI: 0.66 to 1.06). Sensitivity analyses pooling risk differences supported this conclusion (RD = -0.01 (-0.02, 0.00)) and subgroup analyses showed that results were consistent across different doses and disease groups. The quality of evidence for this outcome was judged high using the GRADE criteria. Conclusions Naltrexone does not appear to increase the risk of SAEs over placebo. These findings confirm the safety of naltrexone when used in licensed indications and encourage investments to undertake efficacy studies in unlicensed indications

Genomic and drug target evaluation of 90 cardiovascular proteins in 30,931 individuals.

Circulating proteins are vital in human health and disease and are frequently used as biomarkers for clinical decision-making or as targets for pharmacological intervention. Here, we map and replicate protein quantitative trait loci (pQTL) for 90 cardiovascular proteins in over 30,000 individuals, resulting in 451 pQTLs for 85 proteins. For each protein, we further perform pathway mapping to obtain trans-pQTL gene and regulatory designations. We substantiate these regulatory findings with orthogonal evidence for trans-pQTLs using mouse knockdown experiments (ABCA1 and TRIB1) and clinical trial results (chemokine receptors CCR2 and CCR5), with consistent regulation. Finally, we evaluate known drug targets, and suggest new target candidates or repositioning opportunities using Mendelian randomization. This identifies 11 proteins with causal evidence of involvement in human disease that have not previously been targeted, including EGF, IL-16, PAPPA, SPON1, F3, ADM, CASP-8, CHI3L1, CXCL16, GDF15 and MMP-12. Taken together, these findings demonstrate the utility of large-scale mapping of the genetics of the proteome and provide a resource for future precision studies of circulating proteins in human health

Genomic and drug target evaluation of 90 cardiovascular proteins in 30,931 individuals.

Circulating proteins are vital in human health and disease and are frequently used as biomarkers for clinical decision-making or as targets for pharmacological intervention. Here, we map and replicate protein quantitative trait loci (pQTL) for 90 cardiovascular proteins in over 30,000 individuals, resulting in 451 pQTLs for 85 proteins. For each protein, we further perform pathway mapping to obtain trans-pQTL gene and regulatory designations. We substantiate these regulatory findings with orthogonal evidence for trans-pQTLs using mouse knockdown experiments (ABCA1 and TRIB1) and clinical trial results (chemokine receptors CCR2 and CCR5), with consistent regulation. Finally, we evaluate known drug targets, and suggest new target candidates or repositioning opportunities using Mendelian randomization. This identifies 11 proteins with causal evidence of involvement in human disease that have not previously been targeted, including EGF, IL-16, PAPPA, SPON1, F3, ADM, CASP-8, CHI3L1, CXCL16, GDF15 and MMP-12. Taken together, these findings demonstrate the utility of large-scale mapping of the genetics of the proteome and provide a resource for future precision studies of circulating proteins in human health

Linking Symptom Inventories using Semantic Textual Similarity

An extensive library of symptom inventories has been developed over time to measure clinical symptoms, but this variety has led to several long standing issues. Most notably, results drawn from different settings and studies are not comparable, which limits reproducibility. Here, we present an artificial intelligence (AI) approach using semantic textual similarity (STS) to link symptoms and scores across previously incongruous symptom inventories. We tested the ability of four pre-trained STS models to screen thousands of symptom description pairs for related content - a challenging task typically requiring expert panels. Models were tasked to predict symptom severity across four different inventories for 6,607 participants drawn from 16 international data sources. The STS approach achieved 74.8% accuracy across five tasks, outperforming other models tested. This work suggests that incorporating contextual, semantic information can assist expert decision-making processes, yielding gains for both general and disease-specific clinical assessment