Solving the riddle of codon usage preferences: a test for translational selection

Translational selection is responsible for the unequal usage of synonymous codons in protein coding genes in a wide variety of organisms. It is one of the most subtle and pervasive forces of molecular evolution, yet, establishing the underlying causes for its idiosyncratic behaviour across living kingdoms has proven elusive to researchers over the past 20 years. In this study, a statistical model for measuring translational selection in any given genome is developed, and the test is applied to 126 fully sequenced genomes, ranging from archaea to eukaryotes. It is shown that tRNA gene redundancy and genome size are interacting forces that ultimately determine the action of translational selection, and that an optimal genome size exists for which this kind of selection is maximal. Accordingly, genome size also presents upper and lower boundaries beyond which selection on codon usage is not possible. We propose a model where the coevolution of genome size and tRNA genes explains the observed patterns in translational selection in all living organisms. This model finally unifies our understanding of codon usage across prokaryotes and eukaryotes. Helicobacter pylori, Saccharomyces cerevisiae and Homo sapiens are codon usage paradigms that can be better understood under the proposed model

Relationships between CYP2D6 phenotype, breast cancer and hot flushes in women at high risk of breast cancer receiving prophylactic tamoxifen: results from the IBIS-I trial

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Tamoxifen metabolism predicts drug concentrations and outcome in premenopausal patients with early breast cancer

Tamoxifen is the standard-of-care treatment for estrogen receptor-positive premenopausal breast cancer. We examined tamoxifen metabolism via blood metabolite concentrations and germline variations of CYP3A5, CYP2C9, CYP2C19 and CYP2D6 in 587 premenopausal patients (Asians, Middle Eastern Arabs, Caucasian-UK; median age 39 years) and clinical outcome in 306 patients. N-desmethyltamoxifen (DM-Tam)/(Z)-endoxifen and CYP2D6 phenotype significantly correlated across ethnicities (R2: 53%, P<10?77). CYP2C19 and CYP2C9 correlated with norendoxifen and (Z)-4-hydroxytamoxifen concentrations, respectively (P<0.001). DM-Tam was influenced by body mass index (P<0.001). Improved distant relapse-free survival (DRFS) was associated with decreasing DM-Tam/(Z)-endoxifen (P=0.036) and increasing CYP2D6 activity score (hazard ratio (HR)=0.62; 95% confidence interval (CI), 0.43–0.91; P=0.013). Low (<14?nM) compared with high (>35?nM) endoxifen concentrations were associated with shorter DRFS (univariate P=0.03; multivariate HR=1.94; 95% CI, 1.04–4.14; P=0.064). Our data indicate that endoxifen formation in premenopausal women depends on CYP2D6 irrespective of ethnicity. Low endoxifen concentration/formation and decreased CYP2D6 activity predict shorter DRFS

Obesity Alters Endoxifen Plasma Levels in Young Breast Cancer Patients: A Pharmacometric Simulation Approach

Endoxifen is the most important metabolite of the prodrug tamoxifen. High interindividual variability in endoxifen steady-state concentrations (CSS,min ENDX) is observed under tamoxifen standard dosing breast cancer patients that do not reach endoxifen concentrations above a proposed therapeutic threshold of 5.97 ng/mL may be at higher recurrence risk. In this investigation, 10 clinical tamoxifen studies were pooled (nPatients=1388) to investigate influential factors on CSS,min ENDX using nonlinear mixed-effects modelling. Age and body weight were found to significantly impact CSS,min ENDX in addition to CYP2D6 phenotype. Compared to post-menopausal patients, pre-menopausal patients had a 30% higher risk for subtarget CSS,min ENDX at tamoxifen 20 mg per day. In treatment simulations for distinct patient subpopulations, young overweight patients had a 3.1-13.8-fold higher risk for subtarget CSS,min ENDX compared to elderly low-weight patients. Considering ever-rising obesity rates and the clinical importance of tamoxifen for pre-menopausal patients, this subpopulation may benefit most from individualised tamoxifen dosing

Water

Meta-analysis can be a powerful tool for demonstrating the applicability of a concept beyond the context of individual clinical trials and observational studies, including exploration of effects across different subgroups. Meta-analysis avoids Simpson's paradox, in which a consistent effect in constituent trials is reversed when results are simply pooled. Meta-analysis in critical care medicine is made more complicated, however, by the heterogeneous nature of critically ill patients and the contexts within which they are treated. Failure to properly adjust for this heterogeneity risks missing important subgroup effects in, for example, the interaction of treatment with varying levels of baseline risk. When subgroups are defined by characteristics that vary within constituent trials (such as age) rather than features constant within each trial (such as drug dose), there is the additional risk of incorrect conclusions due to the ecological fallacy. The present review explains these problems and the strategies by which they are overcome

Alkaline-Silicate REE-HFSE Systems

This is the final version. Available on open access from the Society of Economic Geologists via the DOI in this recordDevelopment of renewable energy infrastructure requires critical raw materials, such as the rare earth elements (REEs, including scandium) and niobium, and is driving expansion and diversification in their supply chains. Although alternative sources are being explored, the majority of the world’s resources of these elements are found in alkaline-silicate rocks and carbonatites. These magmatic systems also represent major sources of fluorine and phosphorus. Exploration models for critical raw materials are comparatively less well developed than those for major and precious metals, such as iron, copper, and gold, where most of the mineral exploration industry continues to focus. The diversity of lithologic relationships and a complex nomenclature for many alkaline rock types represent further barriers to the exploration and exploitation of REE-high field strength element (HFSE) resources that will facilitate the green revolution. We used a global review of maps, cross sections, and geophysical, geochemical, and petrological observations from alkaline systems to inform our description of the alkaline-silicate REE + HFSE mineral system from continental scale (1,000s km) down to deposit scale (~1 km lateral). Continental-scale targeting criteria include a geodynamic trigger for low-degree mantle melting at high pressure and a mantle source enriched in REEs, volatile elements, and alkalies. At the province and district scales, targeting criteria relate to magmatic-system longevity and the conditions required for extensive fractional crystallization and the residual enrichment of the REEs and HFSEs. A compilation of maps and geophysical data were used to construct an interactive 3-D geologic model (25-km cube) that places mineralization within a depth and horizontal reference frame. It shows typical lithologic relationships surrounding orthomagmatic REE-Nb-Ta-Zr-Hf mineralization in layered agpaitic syenites, roof zone REE-Nb-Ta mineralization, and mineralization of REE-Nb-Zr associated with peralkaline granites and pegmatites. The resulting geologic model is presented together with recommended geophysical and geochemical approaches for exploration targeting, as well as mineral processing and environmental factors pertinent for the development of mineral resources hosted by alkaline-silicate magmatic systems.European Union Horizon 202

FGF receptor genes and breast cancer susceptibility: results from the Breast Cancer Association Consortium

Background:Breast cancer is one of the most common malignancies in women. Genome-wide association studies have identified FGFR2 as a breast cancer susceptibility gene. Common variation in other fibroblast growth factor (FGF) receptors might also modify risk. We tested this hypothesis by studying genotyped single-nucleotide polymorphisms (SNPs) and imputed SNPs in FGFR1, FGFR3, FGFR4 and FGFRL1 in the Breast Cancer Association Consortium. Methods:Data were combined from 49 studies, including 53 835 cases and 50 156 controls, of which 89 050 (46 450 cases and 42 600 controls) were of European ancestry, 12 893 (6269 cases and 6624 controls) of Asian and 2048 (1116 cases and 932 controls) of African ancestry. Associations with risk of breast cancer, overall and by disease sub-type, were assessed using unconditional logistic regression. Results:Little evidence of association with breast cancer risk was observed for SNPs in the FGF receptor genes. The strongest evidence in European women was for rs743682 in FGFR3; the estimated per-allele odds ratio was 1.05 (95 confidence interval=1.02-1.09, P=0.0020), which is substantially lower than that observed for SNPs in FGFR2. Conclusion:Our results suggest that common variants in the other FGF receptors are not associated with risk of breast cancer to the degree observed for FGFR2. © 2014 Cancer Research UK

Drug metabolizing enzyme activities versus genetic variances for drug of clinical pharmacogenomic relevance

Enzymes are critically important in the transportation, metabolism, and clearance of most therapeutic drugs used in clinical practice today. Many of these enzymes have significant genetic polymorphisms that affect the enzyme's rate kinetics. Regarding drug metabolism, specific polymorphisms to the cytochrome (CYP) P450 enzyme family are linked to phenotypes that describe reaction rates as "ultra", "intermediate", and "poor," as referenced to "extensive" metabolizers that are assigned to wildtype individuals. Activity scores is an alternate designation that provides more genotype-to-phenotype resolution. Understanding the relative change in enzyme activities or rate of clearance of specific drugs relative to an individual's genotypes is an important component in the interpretation of pharmacogenomic data for personalized medicine. Currently, the most relevant drug metabolizing enzymes are CYP 2D6, CYP 2C9, CYP 2C19, thiopurine methyltransferase (TPMT) and UDP-glucuronosyltransferase (UGT). Each of these enzymes is reactive to a host of different drug substrates. Pharmacogenomic tests that are in routine clinical practice include CYP 2C19 for clopidogrel, TPMT for thiopurine drugs, and UDP-1A1 for irinotecan. Other tests where there is considerable data but have not been widely implemented includes CYP 2C9 for warfarin, CYP 2D6 for tamoxifen and codeine, and CYP 2C19 for the proton pump inhibitors