A Frameshift Mutation in Golden Retriever Dogs with Progressive Retinal Atrophy Endorses SLC4A3 as a Candidate Gene for Human Retinal Degenerations

Progressive retinal atrophy (PRA) in dogs, the canine equivalent of retinitis pigmentosa (RP) in humans, is characterised by vision loss due to degeneration of the photoreceptor cells in the retina, eventually leading to complete blindness. It affects more than 100 dog breeds, and is caused by numerous mutations. RP affects 1 in 4000 people in the Western world and 70% of causal mutations remain unknown. Canine diseases are natural models for the study of human diseases and are becoming increasingly useful for the development of therapies in humans. One variant, prcd-PRA, only accounts for a small proportion of PRA cases in the Golden Retriever (GR) breed. Using genome-wide association with 27 cases and 19 controls we identified a novel PRA locus on CFA37 (praw = 1.94×10−10, pgenome = 1.0×10−5), where a 644 kb region was homozygous within cases. A frameshift mutation was identified in a solute carrier anion exchanger gene (SLC4A3) located within this region. This variant was present in 56% of PRA cases and 87% of obligate carriers, and displayed a recessive mode of inheritance with full penetrance within those lineages in which it segregated. Allele frequencies are approximately 4% in the UK, 6% in Sweden and 2% in France, but the variant has not been found in GRs from the US. A large proportion of cases (approximately 44%) remain unexplained, indicating that PRA in this breed is genetically heterogeneous and caused by at least three mutations. SLC4A3 is important for retinal function and has not previously been associated with spontaneously occurring retinal degenerations in any other species, including humans

Patient-specific cancer genes contribute to recurrently perturbed pathways and establish therapeutic vulnerabilities in esophageal adenocarcinoma

Abstract: The identification of cancer-promoting genetic alterations is challenging particularly in highly unstable and heterogeneous cancers, such as esophageal adenocarcinoma (EAC). Here we describe a machine learning algorithm to identify cancer genes in individual patients considering all types of damaging alterations simultaneously. Analysing 261 EACs from the OCCAMS Consortium, we discover helper genes that, alongside well-known drivers, promote cancer. We confirm the robustness of our approach in 107 additional EACs. Unlike recurrent alterations of known drivers, these cancer helper genes are rare or patient-specific. However, they converge towards perturbations of well-known cancer processes. Recurrence of the same process perturbations, rather than individual genes, divides EACs into six clusters differing in their molecular and clinical features. Experimentally mimicking the alterations of predicted helper genes in cancer and pre-cancer cells validates their contribution to disease progression, while reverting their alterations reveals EAC acquired dependencies that can be exploited in therapy

Evaluating the Effects of SARS-CoV-2 Spike Mutation D614G on Transmissibility and Pathogenicity.

Global dispersal and increasing frequency of the SARS-CoV-2 spike protein variant D614G are suggestive of a selective advantage but may also be due to a random founder effect. We investigate the hypothesis for positive selection of spike D614G in the United Kingdom using more than 25,000 whole genome SARS-CoV-2 sequences. Despite the availability of a large dataset, well represented by both spike 614 variants, not all approaches showed a conclusive signal of positive selection. Population genetic analysis indicates that 614G increases in frequency relative to 614D in a manner consistent with a selective advantage. We do not find any indication that patients infected with the spike 614G variant have higher COVID-19 mortality or clinical severity, but 614G is associated with higher viral load and younger age of patients. Significant differences in growth and size of 614G phylogenetic clusters indicate a need for continued study of this variant

Evaluating the Effects of SARS-CoV-2 Spike Mutation D614G on Transmissibility and Pathogenicity

Global dispersal and increasing frequency of the SARS-CoV-2 spike protein variant D614G are suggestive of a selective advantage but may also be due to a random founder effect. We investigate the hypothesis for positive selection of spike D614G in the United Kingdom using more than 25,000 whole genome SARS-CoV-2 sequences. Despite the availability of a large dataset, well represented by both spike 614 variants, not all approaches showed a conclusive signal of positive selection. Population genetic analysis indicates that 614G increases in frequency relative to 614D in a manner consistent with a selective advantage. We do not find any indication that patients infected with the spike 614G variant have higher COVID-19 mortality or clinical severity, but 614G is associated with higher viral load and younger age of patients. Significant differences in growth and size of 614G phylogenetic clusters indicate a need for continued study of this variant

Multiorgan MRI findings after hospitalisation with COVID-19 in the UK (C-MORE): a prospective, multicentre, observational cohort study

Introduction: The multiorgan impact of moderate to severe coronavirus infections in the post-acute phase is still poorly understood. We aimed to evaluate the excess burden of multiorgan abnormalities after hospitalisation with COVID-19, evaluate their determinants, and explore associations with patient-related outcome measures. Methods: In a prospective, UK-wide, multicentre MRI follow-up study (C-MORE), adults (aged ≥18 years) discharged from hospital following COVID-19 who were included in Tier 2 of the Post-hospitalisation COVID-19 study (PHOSP-COVID) and contemporary controls with no evidence of previous COVID-19 (SARS-CoV-2 nucleocapsid antibody negative) underwent multiorgan MRI (lungs, heart, brain, liver, and kidneys) with quantitative and qualitative assessment of images and clinical adjudication when relevant. Individuals with end-stage renal failure or contraindications to MRI were excluded. Participants also underwent detailed recording of symptoms, and physiological and biochemical tests. The primary outcome was the excess burden of multiorgan abnormalities (two or more organs) relative to controls, with further adjustments for potential confounders. The C-MORE study is ongoing and is registered with ClinicalTrials.gov, NCT04510025. Findings: Of 2710 participants in Tier 2 of PHOSP-COVID, 531 were recruited across 13 UK-wide C-MORE sites. After exclusions, 259 C-MORE patients (mean age 57 years [SD 12]; 158 [61%] male and 101 [39%] female) who were discharged from hospital with PCR-confirmed or clinically diagnosed COVID-19 between March 1, 2020, and Nov 1, 2021, and 52 non-COVID-19 controls from the community (mean age 49 years [SD 14]; 30 [58%] male and 22 [42%] female) were included in the analysis. Patients were assessed at a median of 5·0 months (IQR 4·2–6·3) after hospital discharge. Compared with non-COVID-19 controls, patients were older, living with more obesity, and had more comorbidities. Multiorgan abnormalities on MRI were more frequent in patients than in controls (157 [61%] of 259 vs 14 [27%] of 52; p<0·0001) and independently associated with COVID-19 status (odds ratio [OR] 2·9 [95% CI 1·5–5·8]; padjusted=0·0023) after adjusting for relevant confounders. Compared with controls, patients were more likely to have MRI evidence of lung abnormalities (p=0·0001; parenchymal abnormalities), brain abnormalities (p<0·0001; more white matter hyperintensities and regional brain volume reduction), and kidney abnormalities (p=0·014; lower medullary T1 and loss of corticomedullary differentiation), whereas cardiac and liver MRI abnormalities were similar between patients and controls. Patients with multiorgan abnormalities were older (difference in mean age 7 years [95% CI 4–10]; mean age of 59·8 years [SD 11·7] with multiorgan abnormalities vs mean age of 52·8 years [11·9] without multiorgan abnormalities; p<0·0001), more likely to have three or more comorbidities (OR 2·47 [1·32–4·82]; padjusted=0·0059), and more likely to have a more severe acute infection (acute CRP >5mg/L, OR 3·55 [1·23–11·88]; padjusted=0·025) than those without multiorgan abnormalities. Presence of lung MRI abnormalities was associated with a two-fold higher risk of chest tightness, and multiorgan MRI abnormalities were associated with severe and very severe persistent physical and mental health impairment (PHOSP-COVID symptom clusters) after hospitalisation. Interpretation: After hospitalisation for COVID-19, people are at risk of multiorgan abnormalities in the medium term. Our findings emphasise the need for proactive multidisciplinary care pathways, with the potential for imaging to guide surveillance frequency and therapeutic stratification

A video analysis framework for the rugby league tackle

Rugby league tackle video analysis research typically uses technical criteria from coaching cues or tackle variables from rugby union. As such, content validity and relevance could be questioned. A video analysis framework that establishes appropriate variables for rugby league is therefore required. The study aimed to adopt a 5-stage process to establish a video analysis framework for the rugby league tackle, which was content valid, relevant and reliable.The 5-stage process included 1) creation of draft video analysis framework, using available rugby tackle research, 2) expert group recruitment and critique, 3) refinement of framework to establish content validity, 4) response process validity task and agreement within expert group, 5) intra- and inter-reliability testing using Kappa statistics.The agreed framework comprised six phases including; tackle event, defensive start point, pre-contact, initial contact, post-contact and play-the-ball. Within the identified phases, 63 variables were established. The intra- and inter-reliability testing resulted in strong agreement within all phases.The video analysis framework can be used in rugby league tackle research, categorising complex tackle events, such as injurious or optimal tackles, improving both player welfare and performance. The application of the framework to future rugby league research will increase coherence and usefulness of research findings

Quantifying dissolved organic carbon concentrations in upland catchments using phenolic proxy measurements

Concentrations of dissolved organic carbon (DOC) in soil and stream waters in upland catchments are widely monitored, in part due to the potential of DOC to form harmful by-products when chlorinated during treatment of water for public supply. DOC can be measured directly, though this is expensive and time-consuming. Light absorbance in the UV–vis spectrum is often used as a surrogate measurement from which a colour-carbon relationship between absorbance and DOC can be derived, but this relationship can be confounded by numerous variables. Through the analysis of data from eight sites in England and Wales we investigate the possibility of using the concentration of phenolic compounds in water samples as a proxy for DOC concentration. A general model using data from all the sites allowed DOC to be calculated from phenolics at an accuracy of 81–86%. A detailed analysis at one site revealed that a site-specific calibration was more accurate than the general model, and that this compared favourably with a colour-carbon calibration. We therefore recommend this method for use where estimates of DOC concentration are needed, but where time and money are limiting factors, or as an additional method to calculate DOC alongside colour-carbon calibrations. Tests demonstrated only small amounts of phenolic degradation over time; a loss of 0.92 mg L−1 after 8 months in storage, and so this method can be used on older samples with limited loss of accuracy

Analytical validation of a novel multi-analyte plasma test for lung nodule characterization.

BackgroundIn the National Lung Screening Trial, 96.4% of nodules had benign etiology. To avoid unnecessary actions and exposure to harm, individuals with benign disease must be identified. We describe herein the analytical validation of a multi-analyte immunoassay for characterizing the risk that a lung nodule found on CT is malignant. Those at lower risk may be considered for serial surveillance to avoid unnecessary and potentially harmful procedures. While those nodules characterized at higher risk may be appropriate for more aggressive actions.ObjectiveTo validate the analytical performance of multiplexed plasma protein assays used in a novel test for lung nodule characterization.MethodsA multiplexed immunoassay panel for the measurement of plasma proteins in current smokers who present with a lung nodule on CT scan was evaluated in a clinical testing laboratory. Assay analytical sensitivity, reproducibility, precision, and recovery of Epidermal Growth Factor Receptor (EGFR), Prosurfactant protein B (ProSB), and Tissue Inhibitor of Metalloproteinases 1 (TIMP1) from human EDTA plasma samples were evaluated across multiple runs, lots, and technicians. Interfering substances and sample pre-analytical storage conditions were evaluated for their effect on analyte recovery. The lung nodule risk score reproducibility was assessed across multiple lots.ResultsThe assay sensitivities were 0.10 ng/mL EGFR, 0.02 ng/mL ProSB, and 0.29 ng/mL TIMP1 with over three orders of magnitude in the assay dynamic ranges. The assays and analytes are robust to pre-analytical sample handling and the plasma can be stored for up to 4 days at 4°C either when freshy collected or thawed after long-term storage at -80°C. Total imprecision after 20 days of testing remained under 9% for all three assays. Risk score variability remained within a ± 10% risk score range.ConclusionsThe three protein assays comprising the multi-analyte plasma test for lung nodule characterization performed quite acceptably in a clinical laboratory

Analytical validation of a novel multi-analyte plasma test for lung nodule characterization.

In the National Lung Screening Trial, 96.4% of nodules had benign etiology. To avoid unnecessary actions and exposure to harm, individuals with benign disease must be identified. We describe herein the analytical validation of a multi-analyte immunoassay for characterizing the risk that a lung nodule found on CT is malignant. Those at lower risk may be considered for serial surveillance to avoid unnecessary and potentially harmful procedures. While those nodules characterized at higher risk may be appropriate for more aggressive actions. To validate the analytical performance of multiplexed plasma protein assays used in a novel test for lung nodule characterization. A multiplexed immunoassay panel for the measurement of plasma proteins in current smokers who present with a lung nodule on CT scan was evaluated in a clinical testing laboratory. Assay analytical sensitivity, reproducibility, precision, and recovery of Epidermal Growth Factor Receptor (EGFR), Prosurfactant protein B (ProSB), and Tissue Inhibitor of Metalloproteinases 1 (TIMP1) from human EDTA plasma samples were evaluated across multiple runs, lots, and technicians. Interfering substances and sample pre-analytical storage conditions were evaluated for their effect on analyte recovery. The lung nodule risk score reproducibility was assessed across multiple lots. The assay sensitivities were 0.10 ng/mL EGFR, 0.02 ng/mL ProSB, and 0.29 ng/mL TIMP1 with over three orders of magnitude in the assay dynamic ranges. The assays and analytes are robust to pre-analytical sample handling and the plasma can be stored for up to 4 days at 4°C either when freshy collected or thawed after long-term storage at -80°C. Total imprecision after 20 days of testing remained under 9% for all three assays. Risk score variability remained within a ± 10% risk score range. The three protein assays comprising the multi-analyte plasma test for lung nodule characterization performed quite acceptably in a clinical laboratory

Risk assessment for indeterminate pulmonary nodules using a novel, plasma-protein based biomarker assay.

BackgroundThe increase in lung cancer screening is intensifying the need for a noninvasive test to characterize the many indeterminate pulmonary nodules (IPN) discovered. Correctly identifying non-cancerous nodules is needed to reduce overdiagnosis and overtreatment. Alternatively, early identification of malignant nodules may represent a potentially curable form of lung cancer.ObjectiveTo develop and validate a plasma-based multiplexed protein assay for classifying IPN by discriminating between those with a lung cancer diagnosis established pathologically and those found to be clinically and radiographically stable for at least one year.MethodsUsing a novel technology, we developed assays for plasma proteins associated with lung cancer into a panel for characterizing the risk that an IPN found on chest imaging is malignant. The assay panel was evaluated with a cohort of 277 samples, all from current smokers with an IPN 4-30 mm. Subjects were divided into training and test sets to identify a Support Vector Machine (SVM) model for risk classification containing those proteins and clinical factors that added discriminatory information to the Veteran's Affairs (VA) Clinical Factors Model. The algorithm was then evaluated in an independent validation cohort.ResultsAmong the 97 validation study subjects, 68 were grouped as having intermediate risk by the VA model of which the SVM model correctly identified 44 (65%) of these intermediate-risk samples as low (n=16) or high risk (n=28). The SVM model negative predictive value (NPV) was 94% and its sensitivity was 94%.ConclusionThe performance of the novel plasma protein biomarker assay supports its use as a noninvasive risk assessment aid for characterizing IPN. The high NPV of the SVM model suggests its application as a rule-out test to increase the confidence of providers to avoid aggressive interventions for their patients for whom the VA model result is an inconclusive, intermediate risk