Quantifying single nucleotide variant detection sensitivity in exome sequencing

BACKGROUND: The targeted capture and sequencing of genomic regions has rapidly demonstrated its utility in genetic studies. Inherent in this technology is considerable heterogeneity of target coverage and this is expected to systematically impact our sensitivity to detect genuine polymorphisms. To fully interpret the polymorphisms identified in a genetic study it is often essential to both detect polymorphisms and to understand where and with what probability real polymorphisms may have been missed. RESULTS: Using down-sampling of 30 deeply sequenced exomes and a set of gold-standard single nucleotide variant (SNV) genotype calls for each sample, we developed an empirical model relating the read depth at a polymorphic site to the probability of calling the correct genotype at that site. We find that measured sensitivity in SNV detection is substantially worse than that predicted from the naive expectation of sampling from a binomial. This calibrated model allows us to produce single nucleotide resolution SNV sensitivity estimates which can be merged to give summary sensitivity measures for any arbitrary partition of the target sequences (nucleotide, exon, gene, pathway, exome). These metrics are directly comparable between platforms and can be combined between samples to give “power estimates” for an entire study. We estimate a local read depth of 13X is required to detect the alleles and genotype of a heterozygous SNV 95% of the time, but only 3X for a homozygous SNV. At a mean on-target read depth of 20X, commonly used for rare disease exome sequencing studies, we predict 5–15% of heterozygous and 1–4% of homozygous SNVs in the targeted regions will be missed. CONCLUSIONS: Non-reference alleles in the heterozygote state have a high chance of being missed when commonly applied read coverage thresholds are used despite the widely held assumption that there is good polymorphism detection at these coverage levels. Such alleles are likely to be of functional importance in population based studies of rare diseases, somatic mutations in cancer and explaining the “missing heritability” of quantitative traits

Measurement of D+- and D0 production in deep inelastic scattering using a lifetime tag at HERA

The production of D-+/-- and D-0-mesons has been measured with the ZEUS detector at HERA using an integrated luminosity of 133.6 pb(-1). The measurements cover the kinematic range 5 < Q(2) < 1000 GeV2, 0.02 < y < 0.7, 1.5 < p(T)(D) < 15 GeV and |eta(D)| < 1.6. Combinatorial background to the D-meson signals is reduced by using the ZEUS microvertex detector to reconstruct displaced secondary vertices. Production cross sections are compared with the predictions of next-to-leading-order QCD, which is found to describe the data well. Measurements are extrapolated to the full kinematic phase space in order to obtain the open-charm contribution, F-2(c (c) over bar), to the proton structure function, F-2

Two-pion Bose-Einstein correlations in central Pb-Pb collisions at sNN\sqrt{s_{\rm NN}} = 2.76 TeV

The first measurement of two-pion Bose-Einstein correlations in central Pb-Pb collisions at $\sqrt{s_{\rm NN}} = 2.76$ TeV at the Large Hadron Collider is presented. We observe a growing trend with energy now not only for the longitudinal and the outward but also for the sideward pion source radius. The pion homogeneity volume and the decoupling time are significantly larger than those measured at RHIC.Comment: 17 pages, 5 captioned figures, 1 table, authors from page 12, published version, figures at http://aliceinfo.cern.ch/ArtSubmission/node/388

Suppression of charged particle production at large transverse momentum in central Pb-Pb collisions at sNN=2.76\sqrt{s_{\rm NN}} = 2.76 TeV

Inclusive transverse momentum spectra of primary charged particles in Pb-Pb collisions at $\sqrt{s_{_{\rm NN}}}$ = 2.76 TeV have been measured by the ALICE Collaboration at the LHC. The data are presented for central and peripheral collisions, corresponding to 0-5% and 70-80% of the hadronic Pb-Pb cross section. The measured charged particle spectra in $|\eta|<0.8$ and $0.3 < p_T < 20$ GeV/$c$ are compared to the expectation in pp collisions at the same $\sqrt{s_{\rm NN}}$, scaled by the number of underlying nucleon-nucleon collisions. The comparison is expressed in terms of the nuclear modification factor $R_{\rm AA}$. The result indicates only weak medium effects ($R_{\rm AA} \approx$ 0.7) in peripheral collisions. In central collisions, $R_{\rm AA}$ reaches a minimum of about 0.14 at $p_{\rm T}=6$-7GeV/$c$ and increases significantly at larger $p_{\rm T}$. The measured suppression of high-$p_{\rm T}$ particles is stronger than that observed at lower collision energies, indicating that a very dense medium is formed in central Pb-Pb collisions at the LHC.Comment: 15 pages, 5 captioned figures, 3 tables, authors from page 10, published version, figures at http://aliceinfo.cern.ch/ArtSubmission/node/98

Attrition and bias in the MRC cognitive function and ageing study: an epidemiological investigation

BACKGROUND: Any hypothesis in longitudinal studies may be affected by attrition and poor response rates. The MRC Cognitive Function and Ageing study (MRC CFAS) is a population based longitudinal study in five centres with identical methodology in England and Wales each recruiting approximately 2,500 individuals. This paper aims to identify potential biases in the two-year follow-up interviews. METHODS: Initial non-response: Those not in the baseline interviews were compared in terms of mortality to those who were in the baseline interviews at the time of the second wave interviews (1993–1996). Longitudinal attrition: Logistic regression analysis was used to examine baseline differences between individuals who took part in the two-year longitudinal wave compared with those who did not. RESULTS: Initial non-response: Individuals who moved away after sampling but before baseline interview were 1.8 times more likely to die by two years (95% Confidence interval(CI) 1.3–2.4) compared to respondents, after adjusting for age. The refusers had a slightly higher, but similar mortality pattern to responders (Odds ratio 1.2, 95%CI 1.1–1.4). Longitudinal attrition: Predictors for drop out due to death were being older, male, having impaired activities of daily living, poor self-perceived health, poor cognitive ability and smoking. Similarly individuals who refused were more likely to have poor cognitive ability, but had less years of full-time education and were more often living in their own home though less likely to be living alone. There was a higher refusal rate in the rural centres. Individuals who moved away or were uncontactable were more likely to be single, smokers, demented or depressed and were less likely to have moved if in warden-controlled accommodation at baseline. CONCLUSIONS: Longitudinal estimation of factors mentioned above could be biased, particularly cognitive ability and estimates of movements from own home to residential homes. However, these differences could also affect other investigations, particularly the estimates of incidence and longitudinal effects of health and psychiatric diseases, where the factors shown here to be associated with attrition are risk factors for the diseases. All longitudinal studies should investigate attrition and this may help with aspects of design and with the analysis of specific hypotheses

Menopausia y Terapia Hormonal de la Menopausia Las recomendaciones 2018 de la Unidad de Endocrinología Ginecológica de Clínica Alemana de Santiago -Sociedad Italiana de la Menopausia y la Sociedad Chilena de Endocrinología Ginecológica

ABSTRACT In the last decade, the risk benefits ratio of MHT has been evaluated mainly in terms of cardiovascular risk. Present Consensus Statement is largely inspired by the Global Consensus on Menopausal Hormone Therapy in 2013 and 2016 by leading global menopause societies (The American Society for Reproductive Medicine, The Asia Pacific Menopause Federation, The Endocrine Society, The European Menopause and Andropause Society, The International Menopause Society, The International Osteoporosis Foundation and The North American Menopause Society). The aim of these Recommendations is to provide a simple and updated reference on postmenopausal MHT. The term MHT typically includes estrogen replacement therapy (ERT) and estrogen-progestogen therapy (EPT). EPT can be sequential (Seq) when progestogen is added to ERT for 10-14 days a month, or continuous combined (CC) when progestogen is administered continuously every day along with a fixed amount of estrogen. MHT also includes Tibolone and the Tissue Selective Estrogen Complex (TSEC)

Sensitivity and specificity of NT-proBNP to detect heart failure at post mortem examination

NT-proBNP, a marker of cardiac failure, has been shown to be stable in post mortem samples. The aim of this study was to assess the accuracy of NT-proBNP to detect heart failure in the forensic setting. One hundred sixty-eight consecutive autopsies were included in the study. NT-proBNP blood concentrations were measured using a chemiluminescent immunoassay kit. Cardiac failure was assessed by three independent forensic experts using macro- and microscopic findings complemented by information about the circumstances of body discovery and the known medical story. Area under the receiving operator curve was of 65.4% (CI 95%, from 57.1 to 73.7). Using a standard cut-off value of >220 pg/mL for NT-proBNP blood concentration, heart failure was detected with a sensitivity of 50.7% and a specificity of 72.6%. NT-proBNP vitreous humor values were well correlated to the ones measured in blood (r2 = 0.658). Our results showed that NT-proBNP can corroborate the pathological findings in cases of natural death related to heart failure, thus, keeping its diagnostic properties passing from the ante mortem to the post mortem setting. Therefore, biologically inactive polypeptides like NT-proBNP seem to be stable enough to be used in forensic medicine as markers of cardiac failure, taking into account the sensitivity and specificity of the test

Brain age predicts mortality

Age-associated disease and disability are placing a growing burden on society. However, ageing does not affect people uniformly. Hence, markers of the underlying biological ageing process are needed to help identify people at increased risk of age-associated physical and cognitive impairments and ultimately, death. Here, we present such a biomarker, ‘brain-predicted age’, derived using structural neuroimaging. Brain-predicted age was calculated using machine-learning analysis, trained on neuroimaging data from a large healthy reference sample (N = 2001), then tested in the Lothian Birth Cohort 1936 (N = 669), to determine relationships with age-associated functional measures and mortality. Having a brain-predicted age indicative of an older-appearing brain was associated with: weaker grip strength, poorer lung function, slower walking speed, lower fluid intelligence, higher allostatic load and increased mortality risk. Furthermore, while combining brain-predicted age with grey matter and cerebrospinal fluid volumes (themselves strong predictors) not did improve mortality risk prediction, the combination of brain-predicted age and DNA-methylation-predicted age did. This indicates that neuroimaging and epigenetics measures of ageing can provide complementary data regarding health outcomes. Our study introduces a clinically-relevant neuroimaging ageing biomarker and demonstrates that combining distinct measurements of biological ageing further helps to determine risk of age-related deterioration and death