Transcriptome analysis reveals key genes modulated by ALK5 inhibition in a bleomycin model of systemic sclerosis.

OBJECTIVE: SSc is a rheumatic autoimmune disease affecting roughly 20 000 people worldwide and characterized by excessive collagen accumulation in the skin and internal organs. Despite the high morbidity and mortality associated with SSc, there are no approved disease-modifying agents. Our objective in this study was to explore transcriptomic and model-based drug discovery approaches for SSc. METHODS: In this study, we explored the molecular basis for SSc pathogenesis in a well-studied mouse model of scleroderma. We profiled the skin and lung transcriptomes of mice at multiple timepoints, analysing the differential gene expression that underscores the development and resolution of bleomycin-induced fibrosis. RESULTS: We observed shared expression signatures of upregulation and downregulation in fibrotic skin and lung tissue, and observed significant upregulation of key pro-fibrotic genes including GDF15, Saa3, Cxcl10, Spp1 and Timp1. To identify changes in gene expression in responses to anti-fibrotic therapy, we assessed the effect of TGF-ß pathway inhibition via oral ALK5 (TGF-ß receptor I) inhibitor SB525334 and observed a time-lagged response in the lung relative to skin. We also implemented a machine learning algorithm that showed promise at predicting lung function using transcriptome data from both skin and lung biopsies. CONCLUSION: This study provides the most comprehensive look at the gene expression dynamics of an animal model of SSc to date, provides a rich dataset for future comparative fibrotic disease research, and helps refine our understanding of pathways at work during SSc pathogenesis and intervention.

Use of copula to model within-study association in bivariate meta-analysis of binomial data at the aggregate level: A Bayesian approach and application to surrogate endpoint evaluation.

Bivariate meta-analysis provides a useful framework for combining information across related studies and has been utilized to combine evidence from clinical studies to evaluate treatment efficacy on two outcomes. It has also been used to investigate surrogacy patterns between treatment effects on the surrogate endpoint and the final outcome. Surrogate endpoints play an important role in drug development when they can be used to measure treatment effect early compared to the final outcome and to predict clinical benefit or harm. The standard bivariate meta-analytic approach models the observed treatment effects on the surrogate and the final outcome outcomes jointly, at both the within-study and between-studies levels, using a bivariate normal distribution. For binomial data, a normal approximation on log odds ratio scale can be used. However, this method may lead to biased results when the proportions of events are close to one or zero, affecting the validation of surrogate endpoints. In this article, we explore modeling the two outcomes on the original binomial scale. First, we present a method that uses independent binomial likelihoods to model the within-study variability avoiding to approximate the observed treatment effects. However, the method ignores the within-study association. To overcome this issue, we propose a method using a bivariate copula with binomial marginals, which allows the model to account for the within-study association. We applied the methods to an illustrative example in chronic myeloid leukemia to investigate the surrogate relationship between complete cytogenetic response and event-free-survival.

Resolving a Half-Century-Long Controversy between (Magneto)optical and EPR Spectra of Single-Electron-Reduced [PcFe]-, [PcFeL]-, and [PcFeX]2- Complexes: Story of a Double Flip.

The reduction of iron(II) phthalocyanine (Pc(2-)FeII) or its bisaxially coordinated complexes results in the formation of the purple/red [PcFe]-, [PcFeL]-, and [PcFeX]2- (L is neutral and X is anionic ligand) species. The X-ray structure of the [K(DME)4][PcFe] complex exhibits a square-planar [PcFe]- anion. 1H NMR spectra of the reduced species have one or two phthalocyanine broad peaks between 15 and 17 ppm. Solution magnetic moments are consistent with the presence of a single unpaired electron. A solid-state Mössbauer spectrum of [K(DME)4][PcFe] is consistent with an early report [Taube, R. Pure Appl. Chem.1974, 38, 427-438]. The solid-state EPR spectrum of the [PcFe]- anion is close to that recorded by Konarev et al. [ Dalton Trans.2012, 41, 13841-13847]. Solution EPR spectra of reduced species have axial symmetry (g⊥ ∼ 2.08-2.17 and g|| ∼ 1.95-1.96) and correlate well with spectra reported by Lever and Wilshire in 1978 [ Inorg. Chem.1978, 17, 1145-1151]. The UV-vis spectra of pentacoordinated [PcFeL]- and [PcFeX]2- anions consist of the characteristic bands around 810, 690, and 515 nm. These bands correlate well with the set of MCD pseudo A-terms and resemble transitions in the [Pc(3-)M]- and [Pc(3-)ML]- compounds. The UV-vis and MCD spectra of [PcFeL]- and [PcFeX]2- complexes are in stark contrast to the crystallographically characterized reference [Pc(2-)CoI]- anion, which is EPR silent, has a regular diamagnetic 1H NMR spectrum, and has an intense Q-band at 699 nm, which correlates well with the strong MCD A-term. The DFT and TDDFT calculations are suggestive of the iron(II) center in a (dxy)2(dxz,yz)3(dz2)1 (s = 1) electronic configuration that is antiferromagnetically coupled with the one-electron-reduced Pc(3-) ligand (i.e., [Pc(3-)FeII]-, [Pc(3-)FeIIL]-, and [Pc(3-)FeIIX]2-). The calculated EPR, Mössbauer, and UV-vis spectra of [PcFe]-, [PcFeL]-, and [PcFeX]2- complexes are in excellent agreement with the experimental data, thus resolving the controversy between axial s = 1/2 like EPR and Pc(3-)-like UV-vis spectra of these compounds.

Polygenic risk scores in cardiovascular risk prediction: A cohort study and modelling analyses.

BACKGROUND: Polygenic risk scores (PRSs) can stratify populations into cardiovascular disease (CVD) risk groups. We aimed to quantify the potential advantage of adding information on PRSs to conventional risk factors in the primary prevention of CVD. METHODS AND FINDINGS: Using data from UK Biobank on 306,654 individuals without a history of CVD and not on lipid-lowering treatments (mean age [SD]: 56.0 [8.0] years; females: 57%; median follow-up: 8.1 years), we calculated measures of risk discrimination and reclassification upon addition of PRSs to risk factors in a conventional risk prediction model (i.e., age, sex, systolic blood pressure, smoking status, history of diabetes, and total and high-density lipoprotein cholesterol). We then modelled the implications of initiating guideline-recommended statin therapy in a primary care setting using incidence rates from 2.1 million individuals from the Clinical Practice Research Datalink. The C-index, a measure of risk discrimination, was 0.710 (95% CI 0.703-0.717) for a CVD prediction model containing conventional risk predictors alone. Addition of information on PRSs increased the C-index by 0.012 (95% CI 0.009-0.015), and resulted in continuous net reclassification improvements of about 10% and 12% in cases and non-cases, respectively. If a PRS were assessed in the entire UK primary care population aged 40-75 years, assuming that statin therapy would be initiated in accordance with the UK National Institute for Health and Care Excellence guidelines (i.e., for persons with a predicted risk of ≥10% and for those with certain other risk factors, such as diabetes, irrespective of their 10-year predicted risk), then it could help prevent 1 additional CVD event for approximately every 5,750 individuals screened. By contrast, targeted assessment only among people at intermediate (i.e., 5% to <10%) 10-year CVD risk could help prevent 1 additional CVD event for approximately every 340 individuals screened. Such a targeted strategy could help prevent 7% more CVD events than conventional risk prediction alone. Potential gains afforded by assessment of PRSs on top of conventional risk factors would be about 1.5-fold greater than those provided by assessment of C-reactive protein, a plasma biomarker included in some risk prediction guidelines. Potential limitations of this study include its restriction to European ancestry participants and a lack of health economic evaluation. CONCLUSIONS: Our results suggest that addition of PRSs to conventional risk factors can modestly enhance prediction of first-onset CVD and could translate into population health benefits if used at scale.

Bayesian hierarchical meta-analytic methods for modeling surrogate relationships that vary across treatment classes using aggregate data.

Surrogate endpoints play an important role in drug development when they can be used to measure treatment effect early compared to the final clinical outcome and to predict clinical benefit or harm. Such endpoints are assessed for their predictive value of clinical benefit by investigating the surrogate relationship between treatment effects on the surrogate and final outcomes using meta-analytic methods. When surrogate relationships vary across treatment classes, such validation may fail due to limited data within each treatment class. In this paper, two alternative Bayesian meta-analytic methods are introduced which allow for borrowing of information from other treatment classes when exploring the surrogacy in a particular class. The first approach extends a standard model for the evaluation of surrogate endpoints to a hierarchical meta-analysis model assuming full exchangeability of surrogate relationships across all the treatment classes, thus facilitating borrowing of information across the classes. The second method is able to relax this assumption by allowing for partial exchangeability of surrogate relationships across treatment classes to avoid excessive borrowing of information from distinctly different classes. We carried out a simulation study to assess the proposed methods in nine data scenarios and compared them with subgroup analysis using the standard model within each treatment class. We also applied the methods to an illustrative example in colorectal cancer which led to obtaining the parameters describing the surrogate relationships with higher precision.

Age at menopause and lung function: a Mendelian randomisation study.

In observational studies, early menopause is associated with lower forced vital capacity (FVC) and a higher risk of spirometric restriction, but not airflow obstruction. It is, however, unclear if this association is causal. We therefore used a Mendelian randomisation (MR) approach, which is not affected by classical confounding, to assess the effect of age at natural menopause on lung function.We included 94 742 naturally post-menopausal women from the UK Biobank and performed MR analyses on the effect of age at menopause on forced expiratory volume in 1 s (FEV1), FVC, FEV1/FVC, spirometric restriction (FVC

A Bayesian approach to Mendelian randomisation with dependent instruments.

Mendelian randomisation (MR) is a method for establishing causality between a risk factor and an outcome by using genetic variants as instrumental variables. In practice, the association between individual genetic variants and the risk factor is often weak, which may lead to a lack of precision in the MR and even biased MR estimates. Usually, the most significant variant within a genetic region is selected to represent the association with the risk factor, but there is no guarantee that this variant will be causal or that it will capture all of the genetic association within the region. It may be advantageous to use extra variants selected from the same region in the MR. The problem is to decide which variants to select. Rather than selecting a specific set of variants, we investigate the use of Bayesian model averaging (BMA) to average the MR over all possible combinations of genetic variants. Our simulations demonstrate that the BMA version of MR outperforms classical estimation with many dependent variants and performs much better than an MR based on variants selected by penalised regression. In further simulations, we investigate robustness to violations in the model assumptions and demonstrate sensitivity to the inclusion of invalid instruments. The method is illustrated by applying it to an MR of the effect of body mass index on blood pressure using SNPs in the FTO gene.

Bivariate network meta-analysis for surrogate endpoint evaluation.

Surrogate endpoints are very important in regulatory decision making in healthcare, in particular if they can be measured early compared to the long-term final clinical outcome and act as good predictors of clinical benefit. Bivariate meta-analysis methods can be used to evaluate surrogate endpoints and to predict the treatment effect on the final outcome from the treatment effect measured on a surrogate endpoint. However, candidate surrogate endpoints are often imperfect, and the level of association between the treatment effects on the surrogate and final outcomes may vary between treatments. This imposes a limitation on methods which do not differentiate between the treatments. We develop bivariate network meta-analysis (bvNMA) methods, which combine data on treatment effects on the surrogate and final outcomes, from trials investigating multiple treatment contrasts. The bvNMA methods estimate the effects on both outcomes for all treatment contrasts individually in a single analysis. At the same time, they allow us to model the trial-level surrogacy patterns within each treatment contrast and treatment-level surrogacy, thus enabling predictions of the treatment effect on the final outcome either for a new study in a new population or for a new treatment. Modelling assumptions about the between-studies heterogeneity and the network consistency, and their impact on predictions, are investigated using an illustrative example in advanced colorectal cancer and in a simulation study. When the strength of the surrogate relationships varies across treatment contrasts, bvNMA has the advantage of identifying treatment comparisons for which surrogacy holds, thus leading to better predictions.

Competing forces in the self-assembly of amide-functionalized discotic mesogens.

The effect of incorporating a single amide group on the self-assembly of discotic mesogens was examined. Two series of tetraalkoxydibenzophenazines amides were prepared: tertiary diethyl amides, dEt(n) incapable of hydrogen bonding, and secondary amides HBu(n) that can act as both H-bond donors and acceptors. These compounds exhibit markedly different behavior in solution; NMR studies of dEt(n) show no evidence of self-association, whereas HBu(n) strongly associate via H-bonding and π-stacking. Compounds HBu(n) also act as small molecule gelators in a range of solvents, a property not observed for the corresponding tertiary amides. All compounds were found to form Colh liquid crystal phases; variable temperature XRD experiments indicate that each column has a diameter approximately equal to that of a single molecule. A comparison of the phase behavior of HBu(n) and dEt(n) suggests that the columnar phases of the former are stabilized by hydrogen bonding, likely at the expense of local parallel alignment of these molecules. Single crystal X-ray diffraction studies revealed that dEt(6) adopts an antiparallel arrangement in the solid state, in keeping with previous theories of packing within columnar LC phases. These studies highlight the interplay between competing factors, such as hydrogen bonding, π-stacking and dipole-dipole interactions that affect the stability of the LC phases.

Inclusion of biological knowledge in a Bayesian shrinkage model for joint estimation of SNP effects.

With the aim of improving detection of novel single-nucleotide polymorphisms (SNPs) in genetic association studies, we propose a method of including prior biological information in a Bayesian shrinkage model that jointly estimates SNP effects. We assume that the SNP effects follow a normal distribution centered at zero with variance controlled by a shrinkage hyperparameter. We use biological information to define the amount of shrinkage applied on the SNP effects distribution, so that the effects of SNPs with more biological support are less shrunk toward zero, thus being more likely detected. The performance of the method was tested in a simulation study (1,000 datasets, 500 subjects with ∼200 SNPs in 10 linkage disequilibrium (LD) blocks) using a continuous and a binary outcome. It was further tested in an empirical example on body mass index (continuous) and overweight (binary) in a dataset of 1,829 subjects and 2,614 SNPs from 30 blocks. Biological knowledge was retrieved using the bioinformatics tool Dintor, which queried various databases. The joint Bayesian model with inclusion of prior information outperformed the standard analysis: in the simulation study, the mean ranking of the true LD block was 2.8 for the Bayesian model versus 3.6 for the standard analysis of individual SNPs; in the empirical example, the mean ranking of the six true blocks was 8.5 versus 9.3 in the standard analysis. These results suggest that our method is more powerful than the standard analysis. We expect its performance to improve further as more biological information about SNPs becomes available.

Runs of Homozygosity: Association with Coronary Artery Disease and Gene Expression in Monocytes and Macrophages.

Runs of homozygosity (ROHs) are recognized signature of recessive inheritance. Contributions of ROHs to the genetic architecture of coronary artery disease and regulation of gene expression in cells relevant to atherosclerosis are not known. Our combined analysis of 24,320 individuals from 11 populations of white European ethnicity showed an association between coronary artery disease and both the count and the size of ROHs. Individuals with coronary artery disease had approximately 0.63 (95% CI: 0.4-0.8) excess of ROHs when compared to coronary-artery-disease-free control subjects (p = 1.49 × 10(-9)). The average total length of ROHs was approximately 1,046.92 (95% CI: 634.4-1,459.5) kb greater in individuals with coronary artery disease than control subjects (p = 6.61 × 10(-7)). None of the identified individual ROHs was associated with coronary artery disease after correction for multiple testing. However, in aggregate burden analysis, ROHs favoring increased risk of coronary artery disease were much more common than those showing the opposite direction of association with coronary artery disease (p = 2.69 × 10(-33)). Individual ROHs showed significant associations with monocyte and macrophage expression of genes in their close proximity-subjects with several individual ROHs showed significant differences in the expression of 44 mRNAs in monocytes and 17 mRNAs in macrophages when compared to subjects without those ROHs. This study provides evidence for an excess of homozygosity in coronary artery disease in outbred populations and suggest the potential biological relevance of ROHs in cells of importance to the pathogenesis of atherosclerosis.

Adult height and risk of 50 diseases: a combined epidemiological and genetic analysis.

BACKGROUND: Adult height is associated with risk of several diseases, but the breadth of such associations and whether these associations are primary or due to confounding are unclear. We examined the association of adult height with 50 diseases spanning multiple body systems using both epidemiological and genetic approaches, the latter to identify un-confounded associations and possible underlying mechanisms. METHODS: We examined the associations for adult height (using logistic regression adjusted for potential confounders) and genetically determined height (using a two-sample Mendelian randomisation approach with height-associated genetic variants as instrumental variables) in 417,434 individuals of white ethnic background participating in the UK Biobank. We undertook pathway analysis of height-associated genes to identify biological processes that could link height and specific diseases. RESULTS: Height was associated with 32 diseases and genetically determined height associated with 12 diseases. Of these, 11 diseases showed a concordant association in both analyses, with taller height associated with reduced risks of coronary artery disease (odds ratio per standard deviation (SD) increase in height ORepi = 0.80, 95% CI 0.78-0.81; OR per SD increase in genetically determined height ORgen = 0.86, 95% CI 0.82-0.90), hypertension (ORepi = 0.83, 95% CI 0.82-0.84; ORgen = 0.88, 95% CI 0.85-0.91), gastro-oesophageal reflux disease (ORepi = 0.85, 95% CI 0.84-0.86; ORgen = 0.94, 95% CI 0.92-0.97), diaphragmatic hernia (ORepi = 0.81, 95% CI 0.79-0.82; ORgen = 0.91, 95% CI 0.88-0.94), but increased risks of atrial fibrillation (ORepi = 1.42, 95% CI 1.38-1.45; ORgen = 1.33, 95% CI 1.26-1.40), venous thromboembolism (ORepi = 1.18, 95% CI 1.16-1.21; ORgen = 1.15, 95% CI 1.11-1.19), intervertebral disc disorder (ORepi = 1.15, 95% CI 1.13-1.18; ORgen = 1.14, 95% CI 1.09-1.20), hip fracture (ORepi = 1.19, 95% CI 1.12-1.26; ORgen = 1.27, 95% CI 1.17-1.39), vasculitis (ORepi = 1.15, 95% CI 1.11-1.19; ORgen = 1.20, 95% CI 1.14-1.28), cancer overall (ORepi = 1.09, 95% CI 1.08-1.11; ORgen = 1.06, 95% CI 1.04-1.08) and breast cancer (ORepi = 1.08, 95% CI 1.06-1.10; ORgen = 1.07, 95% CI 1.03-1.11). Pathway analysis showed multiple height-associated pathways associating with individual diseases. CONCLUSIONS: Adult height is associated with risk of a range of diseases. We confirmed previously reported height associations for coronary artery disease, atrial fibrillation, venous thromboembolism, intervertebral disc disorder, hip fracture and cancer and identified potential novel associations for gastro-oesophageal reflux disease, diaphragmatic hernia and vasculitis. Multiple biological mechanisms affecting height may affect the risks of these diseases.

Activation by Oxidation: Ferrocene-Functionalized Ru(II)-Arene Complexes with Anticancer, Antibacterial, and Antioxidant Properties.

Organometallic Ru(II)-cymene complexes linked to ferrocene (Fc) via nitrogen heterocycles have been synthesized and studied as cytotoxic agents. These compounds are analogues of Ru(II)-arene piano-stool anticancer complexes such as RAPTA-C. The Ru center was coordinated by pyridine, imidazole, and piperidine with 0-, 1-, or 2-carbon bridges to Fc to give six bimetallic, dinuclear compounds, and the properties of these complexes were compared with their non-Fc-functionalized parent compounds. Crystal structures for five of the compounds, their Ru-cymene parent compounds, and an unusual trinuclear compound were determined. Cyclic voltammetry was used to determine the formal MIII/II potentials of each metal center of the Ru-cymene-Fc complexes, with distinct one-electron waves observed in each case. The Fc-functionalized complexes were found to exhibit good cytotoxicity against HT29 human colon adenocarcinoma cells, whereas the parent compounds were inactive. Similarly, antibacterial activity from the Ru-cymene-Fc compounds was observed against Bacillus subtilis, but not from the unfunctionalized complexes. In both cases, the IC50 values correlated quantitatively with the Fc+/0 reduction potentials. This is consistent with more facile oxidation to give ferrocenium, and subsequent generation of toxic reactive oxygen species, leading to greater cytotoxicity. The antioxidant properties of the complexes were quantified by a 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging assay. EC50 values indicate that linking of the Ru and Fc centers promotes antioxidant activity.

The Redox-Active Chromium Phthalocyanine System: Isolation of Five Oxidation States from Pc4- CrI to Pc2- CrIII.

The preparation and structural characterization of a series of chromium phthalocyanine complexes with multiple metal and ring oxidation states were achieved using PcCrII (1) (Pc=phthalocyanine) or PcCrII (THF)2 (1⋅THF2 ) as starting materials. The reaction of soluble 1⋅THF2 with Br2 or I2 gave the PcCrIII halide complexes PcCrX(THF) (X=I/I3 , Br; 3, 4, respectively). Treatment of 1 with 0.5 equivalent of PhIO or air generated the dinuclear [PcCr(THF)]2 (µ-O) (5), whereas the addition of one equivalent of AgSbF6 to 1 resulted in oxidation to THF-solvated octahedral [PcCrIII (THF)2 ]SbF6 (6). The reduction of 1 with three sequential equivalents of KEt3 BH resulted in the isolation of [K(DME)4 ][Pc3- CrII ] (7), [K(DME)4 ]2 [Pc4- CrII ] (8) and [K6 (DME)4 ][Pc4- CrI ]2 (9), respectively. The reduced products are deep purple in colour, with visible absorption maxima between 500-580 nm. The ring-reduced complexes 7 and 8 are monomeric, whereas 9 is a 1D chain of dinuclear [PcCr]2 units with intercalated K+ cations and supported by Cr-Cr interactions of 2.988(2) Å. Addition of four equivalents of KC8 resulted in the demetallated product PcK2 (DME)4 (10), which has a 1D chain structure. The isolation and structural characterization of new PcCr complexes spanning five oxidation states, including rare examples of crystalline reduced Pc-ring species emphasizes the broad redox activity and stability of phthalocyanine-based complexes.

Serum iron level and kidney function: a Mendelian randomization study.

Background: Iron depletion is a known consequence of chronic kidney disease (CKD), but there is contradicting epidemiological evidence on whether iron itself affects kidney function and whether its effect is protective or detrimental in the general population. While epidemiological studies tend to be affected by confounding and reverse causation, Mendelian randomization (MR) can provide unconfounded estimates of causal effects by using genes as instruments. Methods: We performed an MR study of the effect of serum iron levels on estimated glomerular filtration rate (eGFR), using genetic variants known to be associated with iron. MR estimates of the effect of iron on eGFR were derived based on the association of each variant with iron and eGFR from two large genome-wide meta-analyses on 48 978 and 74 354 individuals. We performed a similar MR analysis for ferritin, which measures iron stored in the body, using variants associated with ferritin. Results: A combined MR estimate across all variants showed a 1.3% increase in eGFR per standard deviation increase in iron (95% confidence interval 0.4­2.1%; P = 0.004). The results for ferritin were consistent with those for iron. Secondary MR analyses of the effects of iron and ferritin on CKD did not show significant associations but had very low statistical power. Conclusions: Our study suggests a protective effect of iron on kidney function in the general population. Further research is required to confirm this causal association, investigate it in study populations at higher risk of CKD and explore its underlying mechanism of action.

Mendelian randomization incorporating uncertainty about pleiotropy.

Mendelian randomization (MR) requires strong assumptions about the genetic instruments, of which the most difficult to justify relate to pleiotropy. In a two-sample MR, different methods of analysis are available if we are able to assume, M1 : no pleiotropy (fixed effects meta-analysis), M2 : that there may be pleiotropy but that the average pleiotropic effect is zero (random effects meta-analysis), and M3 : that the average pleiotropic effect is nonzero (MR-Egger). In the latter 2 cases, we also require that the size of the pleiotropy is independent of the size of the effect on the exposure. Selecting one of these models without good reason would run the risk of misrepresenting the evidence for causality. The most conservative strategy would be to use M3 in all analyses as this makes the weakest assumptions, but such an analysis gives much less precise estimates and so should be avoided whenever stronger assumptions are credible. We consider the situation of a two-sample design when we are unsure which of these 3 pleiotropy models is appropriate. The analysis is placed within a Bayesian framework and Bayesian model averaging is used. We demonstrate that even large samples of the scale used in genome-wide meta-analysis may be insufficient to distinguish the pleiotropy models based on the data alone. Our simulations show that Bayesian model averaging provides a reasonable trade-off between bias and precision. Bayesian model averaging is recommended whenever there is uncertainty about the nature of the pleiotropy.

Observation of a Tricyclic[4.1.0.02,4]heptane During a Michael Addition-Ring Closure Reaction and a Computational Study on Its Mechanism of Formation.

We describe the formation of a bis-cyclopropane product, a tricyclic[4.1.0.02,4]heptane, that is formed during a Johnson-Corey-Chaykovsky reaction on a cyclopentenone. Two (of four possible) bicyclic products are selectively formed by addition of a COOEt-stabilized sulfur ylide onto the Michael acceptor. The tricyclic product is formed subsequently via a retro Michael elimination of a hindered ether followed by addition of a further cyclopropyl moiety, affecting only one of the two bicyclic products initially formed. The experimental reaction outcome was rationalized using density functional theory (DFT), investigating the different Michael-addition approaches of the sulfur ylide, the transition state (TS) energies for the formation of possible zwitterionic intermediates and subsequent reactions that give rise to cyclopropanation. Selective formation of only two of the four possible products occurs due to the epimerization of unreactive intermediates from the other two pathways, as revealed by energy barrier calculations. The formation of the tricyclic product was rationalized by evaluation of energy barriers for proton abstraction required to form the intermediate undergoing the second cyclopropanation. The selectivity-guiding factors discussed for the single and double cyclopropanation of this functionalized Michael-acceptor will be useful guidelines for the synthesis of future singly and doubly cyclopropanated compounds.

Age at menarche and lung function: a Mendelian randomization study.

A trend towards earlier menarche in women has been associated with childhood factors (e.g. obesity) and hypothesised environmental exposures (e.g. endocrine disruptors present in household products). Observational evidence has shown detrimental effects of early menarche on various health outcomes including adult lung function, but these might represent spurious associations due to confounding. To address this we used Mendelian randomization where genetic variants are used as proxies for age at menarche, since genetic associations are not affected by classical confounding. We estimated the effects of age at menarche on forced vital capacity (FVC), a proxy for restrictive lung impairment, and ratio of forced expiratory volume in one second to FVC (FEV1/FVC), a measure of airway obstruction, in both adulthood and adolescence. We derived SNP-age at menarche association estimates for 122 variants from a published genome-wide meta-analysis (N = 182,416), with SNP-lung function estimates obtained by meta-analysing three studies of adult women (N = 46,944) and two of adolescent girls (N = 3025). We investigated the impact of departures from the assumption of no pleiotropy through sensitivity analyses. In adult women, in line with previous evidence, we found an effect on restrictive lung impairment with a 24.8 mL increase in FVC per year increase in age at menarche (95% CI 1.8-47.9; p = 0.035); evidence was stronger after excluding potential pleiotropic variants (43.6 mL; 17.2-69.9; p = 0.001). In adolescent girls we found an opposite effect (-56.5 mL; -108.3 to -4.7; p = 0.033), suggesting that the detrimental effect in adulthood may be preceded by a short-term post-pubertal benefit. Our secondary analyses showing results in the same direction in men and boys, in whom age at menarche SNPs have also shown association with sexual development, suggest a role for pubertal timing in general rather than menarche specifically. We found no effect on airway obstruction (FEV1/FVC).

Bayesian meta-analytical methods to incorporate multiple surrogate endpoints in drug development process.

A number of meta-analytical methods have been proposed that aim to evaluate surrogate endpoints. Bivariate meta-analytical methods can be used to predict the treatment effect for the final outcome from the treatment effect estimate measured on the surrogate endpoint while taking into account the uncertainty around the effect estimate for the surrogate endpoint. In this paper, extensions to multivariate models are developed aiming to include multiple surrogate endpoints with the potential benefit of reducing the uncertainty when making predictions. In this Bayesian multivariate meta-analytic framework, the between-study variability is modelled in a formulation of a product of normal univariate distributions. This formulation is particularly convenient for including multiple surrogate endpoints and flexible for modelling the outcomes which can be surrogate endpoints to the final outcome and potentially to one another. Two models are proposed, first, using an unstructured between-study covariance matrix by assuming the treatment effects on all outcomes are correlated and second, using a structured between-study covariance matrix by assuming treatment effects on some of the outcomes are conditionally independent. While the two models are developed for the summary data on a study level, the individual-level association is taken into account by the use of the Prentice's criteria (obtained from individual patient data) to inform the within study correlations in the models. The modelling techniques are investigated using an example in relapsing remitting multiple sclerosis where the disability worsening is the final outcome, while relapse rate and MRI lesions are potential surrogates to the disability progression.

Synthesis of Iron and Cobalt Complexes of a Ferrocene-Linked Diphosphinoamide Ligand and Characterization of a Weak Iron-Cobalt Interaction.

A ferrocene-based bis(phosphinoamine) fc(NHP(i)Pr2)2 has been deprotonated and used in salt metathesis reactions to form dimeric complexes ([fc(NP(i)Pr2)2]M)2 (M = Fe, Co). A novel coordination environment for Co(II) is observed including a weak but significant Fe-Co interaction, which was characterized using X-ray crystallography, Mössbauer spectroscopy, and VT-magnetometry. Density functional theory (DFT) calculations including natural bond order analysis provides further support for the interaction and suggests a combination of Fe → Co and Co → Fe interactions.