Exome-wide association study of pancreatic cancer risk

We conducted a case-control exome-wide association study to discover germline variants in coding regions that affect risk for pancreatic cancer, combining data from 5 studies. We analyzed exome and genome sequencing data from 437 patients with pancreatic cancer (cases) and 1922 individuals not known to have cancer (controls). In the primary analysis, BRCA2 had the strongest enrichment for rare inactivating variants (17/437 cases vs 3/1922 controls) (P=3.27x10(-6); exome-wide statistical significance threshold P<2.5x10(-6)). Cases had more rare inactivating variants in DNA repair genes than controls, even after excluding 13 genes known to predispose to pancreatic cancer (adjusted odds ratio, 1.35, P=.045). At the suggestive threshold (P<.001), 6 genes were enriched for rare damaging variants (UHMK1, AP1G2, DNTA, CHST6, FGFR3, and EPHA1) and 7 genes had associations with pancreatic cancer risk, based on the sequence-kernel association test. We confirmed variants in BRCA2 as the most common high-penetrant genetic factor associated with pancreatic cancer and we also identified candidate pancreatic cancer genes. Large collaborations and novel approaches are needed to overcome the genetic heterogeneity of pancreatic cancer predisposition

Validity, practical utility, and reliability of the activPAL in preschool children

<p>Purpose: With the increasing global prevalence of childhood obesity, it is important to have appropriate measurement tools for investigating factors (e.g. sedentary time) contributing to positive energy balance in early childhood. For pre-school children, single unit monitors such as the activPALTM are promising. However, validation is required as activity patterns differ from adults.</p> <p>Methods: Thirty pre-school children participated in a validation study. Children were videoed for one hour undertaking usual nursery activity while wearing an activPALTM. Video (criterion method) was analyzed on a second-by-second basis to categorise posture and activity. This was compared with the corresponding activPALTM output. In a subsequent sub-study investigating practical utility and reliability, 20 children wore an activPALTM for seven consecutive 24-hour periods.</p> <p>Results: A total of 97,750 seconds of direct observation from 30 children were categorized as sit/lie (46%), stand (35%), walk (16%); with 3% of time in nonsit/lie/upright postures (e.g. crawl/crouch/kneel-up). Sensitivity for the overall total time matched seconds detected as activPALTM ‘sit/lie’ was 86.7%, specificity 97.1%, and positive predictive value (PPV) 96.3%. For individual children, the median (interquartile range) sensitivity for activPALTM sit/lie was 92.8% (76.1-97.4), specificity 97.3% (94.9-99.2), PPV 97.0% (91.5-99.1). The activPALTM underestimated total time spent sitting (mean difference -4.4%, p<0.01), and overestimated time standing (mean difference 7.1%, p<0.01). There was no difference in overall % time categorised as ‘walk’ (p=0.2). The monitors were well tolerated by children during a seven day period of free-living activity. In the reliability study, at least five days of monitoring were required to obtain an intraclass correlation coefficient of ≥0.8 for time spent sit/lie according to activPALTM output.</p> <p>Conclusion: The activPAL had acceptable validity, practical utility, and reliability for the measurement of posture and activity during freeliving activities in pre-school children.</p&gt

Real-world Independent Testing of e-ASPECTS Software (RITeS): statistical analysis plan

Background: Artificial intelligence-based software may automatically detect ischaemic stroke lesions and provide an Alberta Stroke Program Early CT score (ASPECTS) on CT, and identify arterial occlusion and provide a collateral score on CTA. Large-scale independent testing will inform clinical use, but is lacking. We aim to test e-ASPECTS and e-CTA (Brainomix, Oxford UK) using CT scans obtained from a range of clinical studies.Methods: Using prospectively collected baseline CT and CTA scans from 10 national/international clinical stroke trials or registries (total >6600 patients), we will select a large clinically representative sample for testing e-ASPECTS and e-CTA compared to previously acquired independent expert human interpretation (reference standard). Our primary aims are to test agreement between software-derived and masked human expert ASPECTS, and the diagnostic accuracy of e-ASPECTS for identifying all causes of stroke symptoms using follow-up imaging and final clinical opinion as diagnostic ground truth. Our secondary aims are to test when and why e-ASPECTS is more or less accurate, or succeeds/fails to produce results, agreement between e-CTA and human expert CTA interpretation, and repeatability of e-ASPECTS/e-CTA results. All testing will be conducted on an intention-to-analyse basis. We will assess agreement between software and expert-human ratings and test the diagnostic accuracy of software. Conclusions: RITeS will provide comprehensive, robust and representative testing of e-ASPECTS and e-CTA against the current gold-standard, expert-human interpretation

Identification of the first ATRIP-deficient patient and novel mutations in ATR define a clinical spectrum for ATR-ATRIP Seckel Syndrome

A homozygous mutational change in the Ataxia-Telangiectasia and RAD3 related (ATR) gene was previously reported in two related families displaying Seckel Syndrome (SS). Here, we provide the first identification of a Seckel Syndrome patient with mutations in ATRIP, the gene encoding ATR-Interacting Protein (ATRIP), the partner protein of ATR required for ATR stability and recruitment to the site of DNA damage. The patient has compound heterozygous mutations in ATRIP resulting in reduced ATRIP and ATR expression. A nonsense mutational change in one ATRIP allele results in a C-terminal truncated protein, which impairs ATR-ATRIP interaction; the other allele is abnormally spliced. We additionally describe two further unrelated patients native to the UK with the same novel, heterozygous mutations in ATR, which cause dramatically reduced ATR expression. All patient-derived cells showed defective DNA damage responses that can be attributed to impaired ATR-ATRIP function. Seckel Syndrome is characterised by microcephaly and growth delay, features also displayed by several related disorders including Majewski (microcephalic) osteodysplastic primordial dwarfism (MOPD) type II and Meier-Gorlin Syndrome (MGS). The identification of an ATRIP-deficient patient provides a novel genetic defect for Seckel Syndrome. Coupled with the identification of further ATR-deficient patients, our findings allow a spectrum of clinical features that can be ascribed to the ATR-ATRIP deficient sub-class of Seckel Syndrome. ATR-ATRIP patients are characterised by extremely severe microcephaly and growth delay, microtia (small ears), micrognathia (small and receding chin), and dental crowding. While aberrant bone development was mild in the original ATR-SS patient, some of the patients described here display skeletal abnormalities including, in one patient, small patellae, a feature characteristically observed in Meier-Gorlin Syndrome. Collectively, our analysis exposes an overlapping clinical manifestation between the disorders but allows an expanded spectrum of clinical features for ATR-ATRIP Seckel Syndrome to be define

“Lest we forget” : An overview of Australia’s response to the recovery and identification of unrecovered historic military remains

Peer reviewedPostprin

Analysis of SARS-CoV-2 in Nasopharyngeal Samples from Patients with COVID-19 Illustrates Population Variation and Diverse Phenotypes, Placing the Growth Properties of Variants of Concern in Context with Other Lineages

New variants of SARS-CoV-2 are continuing to emerge and dominate the global sequence landscapes. Several variants have been labeled variants of concern (VOCs) because they may have a transmission advantage, increased risk of morbidity and/or mortality, or immune evasion upon a background of prior infection or vaccination. Placing the VOCs in context with the underlying variability of SARS-CoV-2 is essential in understanding virus evolution and selection pressures. Dominant genome sequences and the population genetics of SARS-CoV-2 in nasopharyngeal swabs from hospitalized patients were characterized. Nonsynonymous changes at a minor variant level were identified. These populations were generally preserved when isolates were amplified in cell culture. To place the Alpha, Beta, Delta, and Omicron VOCs in context, their growth was compared to clinical isolates of different lineages from earlier in the pandemic. The data indicated that the growth in cell culture of the Beta variant was more than that of the other variants in Vero E6 cells but not in hACE2-A549 cells. Looking at each time point, Beta grew more than the other VOCs in hACE2-A549 cells at 24 to 48 h postinfection. At 72 h postinfection there was no difference in the growth of any of the variants in either cell line. Overall, this work suggested that exploring the biology of SARS-CoV-2 is complicated by population dynamics and that these need to be considered with new variants. In the context of variation seen in other coronaviruses, the variants currently observed for SARS-CoV-2 are very similar in terms of their clinical spectrum of disease. IMPORTANCE SARS-CoV-2 is the causative agent of COVID-19. The virus has spread across the planet, causing a global pandemic. In common with other coronaviruses, SARS-CoV-2 genomes can become quite diverse as a consequence of replicating inside cells. This has given rise to multiple variants from the original virus that infected humans. These variants may have different properties and in the context of a widespread vaccination program may render vaccines less effective. Our research confirms the degree of genetic diversity of SARS-CoV-2 in patients. By comparing the growth of previous variants to the pattern seen with four variants of concern (VOCs) (Alpha, Beta, Delta, and Omicron), we show that, at least in cells, Beta variant growth exceeds that of Alpha, Delta, and Omicron VOCs at 24 to 48 h in both Vero E6 and hACE2-A549 cells, but by 72 h postinfection, the amount of virus is not different from that of the other VOCs

Accuracy of artificial intelligence software for CT angiography in stroke

Objective: Software developed using artificial intelligence may automatically identify arterial occlusion and provide collateral vessel scoring on CT angiography (CTA) performed acutely for ischemic stroke. We aimed to assess the diagnostic accuracy of e‐CTA by Brainomix™ Ltd by large‐scale independent testing using expert reading as the reference standard. Methods: We identified a large clinically representative sample of baseline CTA from 6 studies that recruited patients with acute stroke symptoms involving any arterial territory. We compared e‐CTA results with masked expert interpretation of the same scans for the presence and location of laterality‐matched arterial occlusion and/or abnormal collateral score combined into a single measure of arterial abnormality. We tested the diagnostic accuracy of e‐CTA for identifying any arterial abnormality (and in a sensitivity analysis compliant with the manufacturer's guidance that software only be used to assess the anterior circulation). Results: We include CTA from 668 patients (50% female; median: age 71 years, NIHSS 9, 2.3 h from stroke onset). Experts identified arterial occlusion in 365 patients (55%); most (343, 94%) involved the anterior circulation. Software successfully processed 545/668 (82%) CTAs. The sensitivity, specificity and diagnostic accuracy of e‐CTA for detecting arterial abnormality were each 72% (95% CI = 66–77%). Diagnostic accuracy was non‐significantly improved in a sensitivity analysis excluding occlusions from outside the anterior circulation (76%, 95% CI = 72–80%). Interpretation: Compared to experts, the diagnostic accuracy of e‐CTA for identifying acute arterial abnormality was 72–76%. Users of e‐CTA should be competent in CTA interpretation to ensure all potential thrombectomy candidates are identified

Expedition inspiration consensus 2001

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/44209/1/10549_2004_Article_357949.pd

Likely Health Outcomes for Untreated Acute Febrile Illness in the Tropics in Decision and Economic Models; A Delphi Survey

BACKGROUND: Modelling is widely used to inform decisions about management of malaria and acute febrile illnesses. Most models depend on estimates of the probability that untreated patients with malaria or bacterial illnesses will progress to severe disease or death. However, data on these key parameters are lacking and assumptions are frequently made based on expert opinion. Widely diverse opinions can lead to conflicting outcomes in models they inform. METHODS AND FINDINGS: A Delphi survey was conducted with malaria experts aiming to reach consensus on key parameters for public health and economic models, relating to the outcome of untreated febrile illnesses. Survey questions were stratified by malaria transmission intensity, patient age, and HIV prevalence. The impact of the variability in opinion on decision models is illustrated with a model previously used to assess the cost-effectiveness of malaria rapid diagnostic tests. Some consensus was reached around the probability that patients from higher transmission settings with untreated malaria would progress to severe disease (median 3%, inter-quartile range (IQR) 1-5%), and the probability that a non-malaria illness required antibiotics in areas of low HIV prevalence (median 20%). Children living in low transmission areas were considered to be at higher risk of progressing to severe malaria (median 30%, IQR 10-58%) than those from higher transmission areas (median 13%, IQR 7-30%). Estimates of the probability of dying from severe malaria were high in all settings (medians 60-73%). However, opinions varied widely for most parameters, and did not converge on resurveying. CONCLUSIONS: This study highlights the uncertainty around potential consequences of untreated malaria and bacterial illnesses. The lack of consensus on most parameters, the wide range of estimates, and the impact of variability in estimates on model outputs, demonstrate the importance of sensitivity analysis for decision models employing expert opinion. Results of such models should be interpreted cautiously. The diversity of expert opinion should be recognised when policy options are debated