In recent years different types of structural variants (SVs) have been discovered in the human genome and their functional impact has become increasingly clear. Inversions, however, are poorly characterized and more difficult to study, especially those mediated by inverted repeats or segmental duplications. Here, we describe the results of a simple and fast inverse PCR (iPCR) protocol for high-throughput genotyping of a wide variety of inversions using a small amount of DNA. In particular, we analyzed 22 inversions predicted in humans ranging from 5.1 kb to 226 kb and mediated by inverted repeat sequences of 1.6–24 kb. First, we validated 17 of the 22 inversions in a panel of nine HapMap individuals from different populations, and we genotyped them in 68 additional individuals of European origin, with correct genetic transmission in ∼12 mother-father-child trios. Global inversion minor allele frequency varied between 1% and 49% and inversion genotypes were consistent with Hardy-Weinberg equilibrium. By analyzing the nucleotide variation and the haplotypes in these regions, we found that only four inversions have linked tag-SNPs and that in many cases there are multiple shared SNPs between standard and inverted chromosomes, suggesting an unexpected high degree of inversion recurrence during human evolution. iPCR was also used to check 16 of these inversions in four chimpanzees and two gorillas, and 10 showed both orientations either within or between species, providing additional support for their multiple origin. Finally, we have identified several inversions that include genes in the inverted or breakpoint regions, and at least one disrupts a potential coding gene. Thus, these results represent a significant advance in our understanding of inversion polymorphism in human populations and challenge the common view of a single origin of inversions, with important implications for inversion analysis in SNP-based studies.

We present new calculations of the CAT3D clumpy torus models, which now include a more physical dust sublimation model as well as AGN anisotropic emission. These new models allow graphite grains to persist at temperatures higher than the silicate dust sublimation temperature. This produces stronger near-infrared emission and bluer mid-infrared (MIR) spectral slopes. We make a statistical comparison of the CAT3D model MIR predictions with a compilation of sub-arcsecond resolution ground-based MIR spectroscopy of 52 nearby Seyfert galaxies (median distance of 36 Mpc) and 10 quasars. We focus on the AGN MIR spectral index α MIR and the strength of the 9.7 µm silicate feature S Sil . As with other clumpy torus models, the new CAT3D models do not reproduce the Seyfert galaxies with deep silicate absorption (S Sil < −1). Excluding those, we conclude that the new CAT3D models are in better agreement with the observed α MIR and S Sil of Seyfert galaxies and quasars. We find that Seyfert 2 are reproduced with models with low photon escape probabilities, while the quasars and the Seyfert 1-1.5 require generally models with higher photon escape probabilities. Quasars and Seyfert 1-1.5 tend to show steeper radial cloud distributions and fewer clouds along an equatorial line-of-sight than Seyfert 2. Introducing AGN anisotropic emission besides the more physical dust sublimation models alleviates the problem of requiring inverted radial cloud distributions (i.e., more clouds towards the outer parts of the torus) to explain the MIR spectral indices of type 2 Seyferts.

Polygenic risk scores (PRSs) have been among the leading advances in biomedicine in recent years. As a proxy of genetic liability, PRSs are utilised across multiple fields and applications. While numerous statistical and machine learning methods have been developed to optimise their predictive accuracy, these typically distil genetic liability to a single number based on aggregation of an individual’s genome-wide risk alleles. This results in a key loss of information about an individual’s genetic profile, which could be critical given the functional sub-structure of the genome and the heterogeneity of complex disease. In this manuscript, we introduce a ‘pathway polygenic’ paradigm of disease risk, in which multiple genetic liabilities underlie complex diseases, rather than a single genome-wide liability. We describe a method and accompanying software, PRSet, for computing and analysing pathway-based PRSs, in which polygenic scores are calculated across genomic pathways for each individual. We evaluate the potential of pathway PRSs in two distinct ways, creating two major sections: (1) In the first section, we benchmark PRSet as a pathway enrichment tool, evaluating its capacity to capture GWAS signal in pathways. We find that for target sample sizes of >10,000 individuals, pathway PRSs have similar power for evaluating pathway enrichment as leading methods MAGMA and LD score regression, with the distinct advantage of providing individual-level estimates of genetic liability for each pathway–opening up a range of pathway-based PRS applications, (2) In the second section, we evaluate the performance of pathway PRSs for disease stratification. We show that using a supervised disease stratification approach, pathway PRSs (computed by PRSet) outperform two standard genome-wide PRSs (computed by C+T and lassosum) for classifying disease subtypes in 20 of 21 scenarios tested. As the definition and functional annotation of pathways becomes increasingly refined, we expect pathway PRSs to offer key insights into the heterogeneity of complex disease and treatment response, to generate biologically tractable therapeutic targets from polygenic signal, and, ultimately, to provide a powerful path to precision medicine.

Objective Clinically, anorexia nervosa (AN) presents with altered body composition. We quantified these alterations and evaluated their relationships with metabolites and hormones in patients with AN longitudinally. Method In accordance with PRISMA guidelines, we conducted 94 meta‐analyses on 62 samples published during 1996–2019, comparing up to 2,319 pretreatment, posttreatment, and weight‐recovered female patients with AN with up to 1,879 controls. Primary outcomes were fat mass, fat‐free mass, body fat percentage, and their regional distribution. Secondary outcomes were bone mineral density, metabolites, and hormones. Meta‐regressions examined relationships among those measures and moderators. Results Pretreatment female patients with AN evidenced 50% lower fat mass (mean difference [MD]: −8.80 kg, 95% CI: −9.81, −7.79, Q = 1.01 × 10−63) and 4.98 kg (95% CI: −5.85, −4.12, Q = 1.99 × 10−28) lower fat‐free mass, with fat mass preferentially stored in the trunk region during early weight restoration (4.2%, 95% CI: −2.1, −6.2, Q = 2.30 × 10−4). While the majority of traits returned to levels seen in healthy controls after weight restoration, fat‐free mass (MD: −1.27 kg, 95% CI: −1.79, −0.75, Q = 5.49 × 10−6) and bone mineral density (MD: −0.10 kg, 95% CI: −0.18, −0.03, Q = 0.01) remained significantly altered. Discussion Body composition is markedly altered in AN, warranting research into these phenotypes as clinical risk or relapse predictors. Notably, the long‐term altered levels of fat‐free mass and bone mineral density suggest that these parameters should be investigated as potential AN trait markers. ResumenObjetivo Clínicamente, la anorexia nervosa (AN) se presenta con alteraciones en la composición corporal. Cuantificamos estas alteraciones y evaluamos longitudinalmente su relación con metabolitos y hormonas en pacientes con AN. Método De acuerdo con las pautas PRISMA, realizamos 94 meta‐análisis en 62 muestras publicadas entre 1996–2019, comparando hasta 2,319 pacientes mujeres en pre‐tratamiento, post‐tratamiento, y recuperadas en base al peso con hasta 1,879 controles. Las principales medidas fueron masa grasa, masa libre de grasa, porcentaje de grasa corporal y su distribución regional. Las medidas secundarias fueron densidad mineral ósea, metabolitos y hormonas. Las meta‐regresiones examinaron las relaciones entre esas medidas y moderadores. Resultados Las pacientes femeninas con AN pre‐tratamiento mostraron un 50% menos de masa grasa (MD: −8.80 kg, CI 95%: −9.81, −7.79, Q = 1.01 × 10–63) y 4.98 kg (CI 95%: −5.85, −4.12, Q = 1.99 × 10–28) menos de masa libre de grasa, con masa grasa preferentemente almacenada en la región del tronco durante la recuperación temprana del peso (4.2%, CI 95%: −2.1, −6.2, Q = 2.30 × 10–4). Aunque la mayoría de los rasgos regresaron a los niveles vistos en los controles sanos después de la restauración del peso, la masa libre de grasa (MD: −1.27 kg, CI 95%: −1.79, −0.75, Q = 5.49 × 10–6) y la densidad mineral ósea (MD: −0.10 kg, CI 95%: −0.18, −0.03, Q = 0.01) perm...

There is extensive evidence of gender inequality in research leading to insufficient representation of women in leadership positions. Numbers revealing a gender gap in research are periodically reported by national and international institutions but data on perceptions of gender equality within the research community are scarce. In the present study, a questionnaire based on the British Athena Survey of Science, Engineering and Technology (ASSET 2016) was distributed among researchers working in Spain. Consistent with the original UKbased study, women in research perceived a greater degree of gender inequality than men. This difference was consistent from junior to senior positions, within public and private universities as well as research centres, and across all research disciplines. When responses were compared with the existing UK-based questionnaire, researchers in Spain felt that women and men are treated more equally in the workplace, yet they perceived their home departments to be less supportive regarding matters of gender equality. The results of this study provide clear evidence that men and women do not share the same perceptions of gender equality in science and that their differing perceptions are relatively consistent across two major European countries. The fact that men occupy the majority of senior positions while not perceiving the same inequality as women do, may be critical when it comes to ensuring the fair ascent of women to senior positions in an academic system. These data encourage the implementation of measures to ensure that both men and women are aware of gender biases in research.PLOS ONE | https://doi.org/10.1371/journal.pone.research and innovation in Europe [2], showed that only 21% of grade A, top-level researchers were women and, strikingly, numbers have not improved much from the 20% observed in 2010. In the Spanish academic system, the representation of women is nearly identical to that of the rest of the EU (40.8% vs 41.0%), and women occupy 21.0% of senior positions in Spain vs 20.9% in the EU [2,3].Gender perceptions may influence women's ascent to senior positions [4]. Women are perceived as worse scientific leaders [5,6] and are stereotyped as not possessing the innate talent that is required in some fields [7]. These and other gender stereotypes may explain why women receive similar levels of research funding when they are judged on the quality of their research but less funding when judged on the excellence of the researcher [8], are less frequently invited to conferences [9,10], are less likely to be selected for scientific awards [11,12], are less represented on editorial boards [13], their work is less likely to be cited [14], they have less chances of being invited to participate in peer review [14,15], and they have a more restricted access to influential networks [16]. In 2015, Handley et al reported that men do not recognise the presence of gender bias in research to the same extent as women: when men and women were asked to read an abstract from a study reportin...