Automated ice-core layer-counting with strong univariate signals

We present an automated process for determining the annual layer chronology of an ice-core with a strong annual signal, utilising the hydrogen peroxide record from an Antarctic Peninsula ice-core as a test signal on which to count annual cycles and explain the methods. The signal is de-trended and normalised before being split into sections with a deterministic cycle count and those that need more attention. Possible reconstructions for the uncertain sections are determined which could be used as a visual aid for manual counting, and a simple method for assigning probability measures to each reconstruction is discussed. The robustness of this process is explored by applying it to versions of two different chemistry signals from the same stretch of the NGRIP (North Greenland Ice Core Project) ice-core, which shows more variation in annual layer thickness, with and without thinning to mimic poorer quality data. An adapted version of these methods is applied to the more challenging non-sea-salt sulphur signal from the same Antarctic Peninsula core from which the hydrogen peroxide signal was taken. These methods could readily be adapted for use on much longer datasets, thereby reducing manual effort and providing a robust automated layer-counting methodology

Phase 1 study of seviteronel, a selective CYP17 lyase and androgen receptor inhibitor, in women with estrogen receptor-positive or triple-negative breast cancer

Purpose: Seviteronel (INO-464) is an oral, selective cytochrome P450c17a (CYP17) 17,20-lyase (lyase) and androgen receptor inhibitor with in vitro and in vivo anti-tumor activity. This open-label phase 1 clinical study evaluated safety, tolerability, pharmacokinetics (PK), and activity of once-daily (QD) seviteronel in women with locally advanced or metastatic TNBC or ER+ breast cancer. Methods: Seviteronel was administered in de-escalating 750, 600, and 450 mg QD 6-subject cohorts. The 750 mg QD start dose was a phase 2 dose determined for men with castration-resistant prostate cancer in (Shore et al. J Clin Oncol 34, 2016). Enrollment at lower doses was initiated in the presence of dose-limiting toxicities (DLTs). The primary objective of this study was to determine seviteronel safety, tolerability, and MTD. The secondary objectives included description of its PK in women and its initial activity, including clinical benefit rate at 4 (CBR16) and 6 months (CBR24). Results: Nineteen women were enrolled. A majority of adverse events (AEs) were Grade (Gr) 1/2, independent of relationship; the most common were tremor (42%), nausea (42%), vomiting (37%), and fatigue (37%). Four Gr 3/4 AEs (anemia, delirium, mental status change, and confusional state) deemed possibly related to seviteronel occurred in four subjects. DLTs were observed at 750 mg (Gr 3 confusional state with paranoia) and 600 mg (Gr 3 mental status change and Gr 3 delirium) QD, with none at 450 mg QD. The recommended phase 2 dose (RP2D) was 450 mg QD, and at the RP2D, 4 of 7 subjects reached at least CBR16 (2 TNBC subjects and 2 ER+ subjects achieved CBR16 and CBR24, respectively); no objective tumor responses were reported. Conclusions: Once-daily seviteronel was generally well tolerated in women with and 450 mg QD was chosen as the RP2D

Polarisation of equine pregnancy outcome associated with a maternal MHC class I allele: preliminary evidence

Identification of risk factors which are associated with severe clinical signs can assist in the management of disease outbreaks and indicate future research areas. Pregnancy loss during late gestation in the mare compromises welfare, reduces fecundity and has financial implications for horse owners. This retrospective study focussed on the identification of risk factors associated with pregnancy loss among 46 Thoroughbred mares on a single British stud farm, with some but not all losses involving equid herpesvirus-1 (EHV-1) infection. In a sub-group of 30 mares, association between pregnancy loss and the presence of five common Thoroughbred horse haplotypes of the equine Major Histocompatibility Complex (MHC) was assessed. This involved development of sequence specific, reverse transcriptase polymerase chain reactions and in several mares, measurement of cytotoxic T lymphocyte activity. Of the 46 mares, 10 suffered late gestation pregnancy loss or neonatal foal death, five of which were EHV-1 positive. Maternal factors including age, parity, number of EHV-1 specific vaccinations and the number of days between final vaccination and foaling or abortion were not significantly associated with pregnancy loss. In contrast, a statistically significant association between the presence of the MHC class I B2 allele and pregnancy loss was identified, regardless of the fetus / foal’s EHV-1 status (p=0.002). In conclusion, this study demonstrated a significantly positive association between pregnancy loss in Thoroughbred mares and a specific MHC class I allele in the mother. This association requires independent validation and further investigation of the mechanism by which the mare’s genetic background contributes to pregnancy outcome

Towards Machine Wald

The past century has seen a steady increase in the need of estimating and predicting complex systems and making (possibly critical) decisions with limited information. Although computers have made possible the numerical evaluation of sophisticated statistical models, these models are still designed \emph{by humans} because there is currently no known recipe or algorithm for dividing the design of a statistical model into a sequence of arithmetic operations. Indeed enabling computers to \emph{think} as \emph{humans} have the ability to do when faced with uncertainty is challenging in several major ways: (1) Finding optimal statistical models remains to be formulated as a well posed problem when information on the system of interest is incomplete and comes in the form of a complex combination of sample data, partial knowledge of constitutive relations and a limited description of the distribution of input random variables. (2) The space of admissible scenarios along with the space of relevant information, assumptions, and/or beliefs, tend to be infinite dimensional, whereas calculus on a computer is necessarily discrete and finite. With this purpose, this paper explores the foundations of a rigorous framework for the scientific computation of optimal statistical estimators/models and reviews their connections with Decision Theory, Machine Learning, Bayesian Inference, Stochastic Optimization, Robust Optimization, Optimal Uncertainty Quantification and Information Based Complexity.Comment: 37 page

CT-derived measures of muscle quantity and quality predict poorer outcomes from elective colorectal surgery: a UK multicentre retrospective cohort study

Purpose To assess whether preoperative radiologically defined lean muscle measures are associated with adverse clinical outcomes in patients undergoing elective surgery for colorectal cancer. Methods This retrospective UK-based multicentre data collection study identified patients having had colorectal cancer resection with curative intent between January 2013 to December 2016. Preoperative computed-tomography (CT) scans were used to measure psoas muscle characteristics. Clinical records provided postoperative morbidity and mortality data. Results This study included 1122 patients. The cohort was separated into a combined group (patients with both sarcopenia and myosteatosis) and others group (either sarcopenia or myosteatosis, or neither). For the combined group, anastomotic leak was predicted on univariate (OR 4.1, 95% CI 1.43–11.79; p = 0.009) and multivariate analysis (OR 4.37, 95% CI 1.41–13.53; p = 0.01). Also for the combined group, mortality (up to 5 years postoperatively) was predicted on univariate (HR 2.41, 95% CI 1.64–3.52; p < 0.001) and multivariate analysis (HR 1.93, 95% CI 1.28–2.89; p = 0.002). A strong correlation exists between freehand-drawn region of interest-derived psoas density measurement and using the ellipse tool (R2 = 81%; p < 0.001). Conclusion Measures of lean muscle quality and quantity, which predict important clinical outcomes, can be quickly and easily taken from routine preoperative imaging in patients being considered for colorectal cancer surgery. As poor muscle mass and quality are again shown to predict poorer clinical outcomes, these should be proactively targeted within prehabilitation, perioperative and rehabilitation phases to minimise negative impact of these pathological states

A new strategy for enhancing imputation quality of rare variants from next-generation sequencing data via combining SNP and exome chip data

Background: Rare variants have gathered increasing attention as a possible alternative source of missing heritability. Since next generation sequencing technology is not yet cost-effective for large-scale genomic studies, a widely used alternative approach is imputation. However, the imputation approach may be limited by the low accuracy of the imputed rare variants. To improve imputation accuracy of rare variants, various approaches have been suggested, including increasing the sample size of the reference panel, using sequencing data from study-specific samples (i.e., specific populations), and using local reference panels by genotyping or sequencing a subset of study samples. While these approaches mainly utilize reference panels, imputation accuracy of rare variants can also be increased by using exome chips containing rare variants. The exome chip contains 250 K rare variants selected from the discovered variants of about 12,000 sequenced samples. If exome chip data are available for previously genotyped samples, the combined approach using a genotype panel of merged data, including exome chips and SNP chips, should increase the imputation accuracy of rare variants. Results: In this study, we describe a combined imputation which uses both exome chip and SNP chip data simultaneously as a genotype panel. The effectiveness and performance of the combined approach was demonstrated using a reference panel of 848 samples constructed using exome sequencing data from the T2D-GENES consortium and 5,349 sample genotype panels consisting of an exome chip and SNP chip. As a result, the combined approach increased imputation quality up to 11 %, and genomic coverage for rare variants up to 117.7 % (MAF < 1 %), compared to imputation using the SNP chip alone. Also, we investigated the systematic effect of reference panels on imputation quality using five reference panels and three genotype panels. The best performing approach was the combination of the study specific reference panel and the genotype panel of combined data. Conclusions: Our study demonstrates that combined datasets, including SNP chips and exome chips, enhances both the imputation quality and genomic coverage of rare variants

Whole genome sequence analysis of platelet traits in the NHLBI Trans-Omics for Precision Medicine (TOPMed) initiative

Platelets play a key role in thrombosis and hemostasis. Platelet count (PLT) and mean platelet volume (MPV) are highly heritable quantitative traits, with hundreds of genetic signals previously identified, mostly in European ancestry populations. We here utilize whole genome sequencing (WGS) from NHLBI's Trans-Omics for Precision Medicine initiative (TOPMed) in a large multi-ethnic sample to further explore common and rare variation contributing to PLT (n = 61 200) and MPV (n = 23 485). We identified and replicated secondary signals at MPL (rs532784633) and PECAM1 (rs73345162), both more common in African ancestry populations. We also observed rare variation in Mendelian platelet-related disorder genes influencing variation in platelet traits in TOPMed cohorts (not enriched for blood disorders). For example, association of GP9 with lower PLT and higher MPV was partly driven by a pathogenic Bernard-Soulier syndrome variant (rs5030764, p.Asn61Ser), and the signals at TUBB1 and CD36 were partly driven by loss of function variants not annotated as pathogenic in ClinVar (rs199948010 and rs571975065). However, residual signal remained for these gene-based signals after adjusting for lead variants, suggesting that additional variants in Mendelian genes with impacts in general population cohorts remain to be identified. Gene-based signals were also identified at several genome-wide association study identified loci for genes not annotated for Mendelian platelet disorders (PTPRH, TET2, CHEK2), with somatic variation driving the result at TET2. These results highlight the value of WGS in populations of diverse genetic ancestry to identify novel regulatory and coding signals, even for well-studied traits like platelet traits