64 research outputs found

    Assessment of the EarlyCDT-Lung test as an early biomarker of lung cancer in ever-smokers: A retrospective nested case-control study in two prospective cohorts

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    The EarlyCDT-Lung test is a blood-based autoantibody assay intended to identify high-risk individuals for low-dose computed tomography lung cancer screening. However, there is a paucity of evidence on the performance of the EarlyCDT-Lung test in ever-smokers. We conducted a nested case-control study within two prospective cohorts to evaluate the risk-discriminatory performance of the EarlyCDT-Lung test using prediagnostic blood samples from 154 future lung cancer cases and 154 matched controls. Cases were selected from those who had ever smoked and had a prediagnostic blood sample <3 years prior to diagnosis. Conditional logistic regression was used to estimate the association between EarlyCDT-Lung test results and lung cancer risk. Sensitivity and specificity of the EarlyCDT-Lung test were calculated in all subjects and subgroups based on age, smoking history, lung cancer stage, sample collection time before diagnosis and year of sample collection. The overall lung cancer odds ratios were 0.89 (95% CI: 0.34-2.30) for a moderate risk EarlyCDT-Lung test result and 1.09 (95% CI: 0.48-2.47) for a high-risk test result compared to no significant test result. The overall sensitivity was 8.4% (95% CI: 4.6-14) and overall specificity was 92% (95% CI: 87-96) when considering a high-risk result as positive. Stratified analysis indicated higher sensitivity (17%, 95% CI: 7.2-32.1) in subjects with blood drawn up to 1 year prior to diagnosis. In conclusion, our study does not support a role of the EarlyCDT-Lung test in identifying the high-risk subjects in ever-smokers for lung cancer screening in the EPIC and NSHDS cohorts

    New genetic loci link adipose and insulin biology to body fat distribution.

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    Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms

    Finishing the euchromatic sequence of the human genome

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    The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

    Design and baseline characteristics of the finerenone in reducing cardiovascular mortality and morbidity in diabetic kidney disease trial

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    Background: Among people with diabetes, those with kidney disease have exceptionally high rates of cardiovascular (CV) morbidity and mortality and progression of their underlying kidney disease. Finerenone is a novel, nonsteroidal, selective mineralocorticoid receptor antagonist that has shown to reduce albuminuria in type 2 diabetes (T2D) patients with chronic kidney disease (CKD) while revealing only a low risk of hyperkalemia. However, the effect of finerenone on CV and renal outcomes has not yet been investigated in long-term trials. Patients and Methods: The Finerenone in Reducing CV Mortality and Morbidity in Diabetic Kidney Disease (FIGARO-DKD) trial aims to assess the efficacy and safety of finerenone compared to placebo at reducing clinically important CV and renal outcomes in T2D patients with CKD. FIGARO-DKD is a randomized, double-blind, placebo-controlled, parallel-group, event-driven trial running in 47 countries with an expected duration of approximately 6 years. FIGARO-DKD randomized 7,437 patients with an estimated glomerular filtration rate >= 25 mL/min/1.73 m(2) and albuminuria (urinary albumin-to-creatinine ratio >= 30 to <= 5,000 mg/g). The study has at least 90% power to detect a 20% reduction in the risk of the primary outcome (overall two-sided significance level alpha = 0.05), the composite of time to first occurrence of CV death, nonfatal myocardial infarction, nonfatal stroke, or hospitalization for heart failure. Conclusions: FIGARO-DKD will determine whether an optimally treated cohort of T2D patients with CKD at high risk of CV and renal events will experience cardiorenal benefits with the addition of finerenone to their treatment regimen. Trial Registration: EudraCT number: 2015-000950-39; ClinicalTrials.gov identifier: NCT02545049

    Search for dark matter produced in association with bottom or top quarks in √s = 13 TeV pp collisions with the ATLAS detector

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    A search for weakly interacting massive particle dark matter produced in association with bottom or top quarks is presented. Final states containing third-generation quarks and miss- ing transverse momentum are considered. The analysis uses 36.1 fb−1 of proton–proton collision data recorded by the ATLAS experiment at √s = 13 TeV in 2015 and 2016. No significant excess of events above the estimated backgrounds is observed. The results are in- terpreted in the framework of simplified models of spin-0 dark-matter mediators. For colour- neutral spin-0 mediators produced in association with top quarks and decaying into a pair of dark-matter particles, mediator masses below 50 GeV are excluded assuming a dark-matter candidate mass of 1 GeV and unitary couplings. For scalar and pseudoscalar mediators produced in association with bottom quarks, the search sets limits on the production cross- section of 300 times the predicted rate for mediators with masses between 10 and 50 GeV and assuming a dark-matter mass of 1 GeV and unitary coupling. Constraints on colour- charged scalar simplified models are also presented. Assuming a dark-matter particle mass of 35 GeV, mediator particles with mass below 1.1 TeV are excluded for couplings yielding a dark-matter relic density consistent with measurements

    Large expert-curated database for benchmarking document similarity detection in biomedical literature search

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    Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

    Genetic associations at 53 loci highlight cell types and biological pathways relevant for kidney function.

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    Reduced glomerular filtration rate defines chronic kidney disease and is associated with cardiovascular and all-cause mortality. We conducted a meta-analysis of genome-wide association studies for estimated glomerular filtration rate (eGFR), combining data across 133,413 individuals with replication in up to 42,166 individuals. We identify 24 new and confirm 29 previously identified loci. Of these 53 loci, 19 associate with eGFR among individuals with diabetes. Using bioinformatics, we show that identified genes at eGFR loci are enriched for expression in kidney tissues and in pathways relevant for kidney development and transmembrane transporter activity, kidney structure, and regulation of glucose metabolism. Chromatin state mapping and DNase I hypersensitivity analyses across adult tissues demonstrate preferential mapping of associated variants to regulatory regions in kidney but not extra-renal tissues. These findings suggest that genetic determinants of eGFR are mediated largely through direct effects within the kidney and highlight important cell types and biological pathways

    The Genetic Architecture of Gliomagenesis–Genetic Risk Variants Linked to Specific Molecular Subtypes

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    Genome-wide association studies have identified 25 germline genetic loci that increase the risk of glioma. The somatic tumor molecular alterations, including IDH-mutation status and 1p/19q co-deletion, have been included into the WHO 2016 classification system for glioma. To investigate how the germline genetic risk variants correlate with the somatic molecular subtypes put forward by WHO, we performed a meta-analysis that combined findings from 330 Swedish cases and 876 controls with two other recent studies. In total, 5,103 cases and 10,915 controls were included. Three categories of associations were found. First, variants in TERT and TP53 were associated with increased risk of all glioma subtypes. Second, variants in CDKN2B-AS1, EGFR, and RTEL1 were associated with IDH-wildtype glioma. Third, variants in CCDC26 (the 8q24 locus), C2orf80 (close to IDH), LRIG1, PHLDB1, ETFA, MAML2 and ZBTB16 were associated with IDH-mutant glioma. We therefore propose three etiopathological pathways in gliomagenesis based on germline variants for future guidance of diagnosis and potential functional targets for therapies. Future prospective clinical trials of patients with suspicion of glioma diagnoses, using the genetic variants as biomarkers, are necessary to disentangle how strongly they can predict glioma diagnosis

    Progression patterns in monoclonal gammopathy of undetermined significance and multiple myeloma outcome : a cohort study in 42 patients

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    Follow-up of low-risk monoclonal gammopathy of undetermined significance (MGUS) is debated as multiple myeloma (MM) progression risk is low. Worse MM outcome was reported for patients followed for low-risk MGUS, possibly due to less optimal follow-up. However, it is unknown whether progressing low-risk MGUS is associated with aggressive tumor behavior. Understanding these patterns is crucial for MGUS management. Here, we investigated whether progression from low-risk MGUS is associated with worse MM outcome in patients who had no MGUS follow-up before myeloma diagnosis. We retrospectively determined the MGUS status in repeated pre-diagnostic blood samples prospectively collected from 42 myeloma patients in median 11.6 years (first sample) and 3.3 years (repeated sample) before myeloma diagnosis. At first pre-diagnostic blood draw, 12 had low-risk (defined by an immunoglobulin [Ig] G monoclonal [M] spike &lt; 15 g/L and a normal free light-chain ratio) and 30 had MGUS of other risk. MM bone disease was more common in patients with low-risk MGUS at first blood draw (67% vs. 30%, P = 0.041). Median survival since myeloma diagnosis was worse in low-risk than other MGUS at first blood draw (2.3 vs. 7.5 years, P = 0.004). Modest progression was observed between first and repeated blood draw for the majority of low-risk MGUS as 67% remained as low- or low-intermediate-risk MGUS at repeated blood draw. Our study, albeit limited by its small size, indicates that progression from low-risk MGUS is associated with worse MM outcome regardless of MGUS follow-up. Although further investigation is needed, progressing low-risk MGUS could belong to a group of aggressive tumors with progression that is difficult to predict
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