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Circulating nucleic acids (CNAs) are under investigation as a liquid biopsy in cancer. However there is wide variation in blood processing and methods for isolation of circulating free DNA (cfDNA) and microRNAs (miRNAs). Here we compare the extraction efficiency and reproducibility of 4 commercially available kits for cfDNA and 3 for miRNA using spike-in of reference templates. We also compare the effects of increasing time between venepuncture and centrifugation and differential centrifugation force on recovery of CNAs. cfDNA was quantified by TaqMan qPCR and targeted deep sequencing. miRNA profiles were assessed with TaqMan low-density arrays and assays. The QIAamp(®) DNA Blood Mini and Circulating nucleic acid kits gave the highest recovery of cfDNA and efficient recovery (>90%) of a 564bp spike-in. Moreover, targeted sequencing revealed overlapping cfDNA profiles and variant depth, including detection of HER2 gene amplification, using the Ion AmpliSeq™Cancer Hotspot Panel v2. Highest yields of miRNA and the synthetic Arabidopsis thaliana miR-159a spike-in were obtained using the miRNeasy Serum/Plasma kit, with saturation above 200 µl of plasma. miRNA profiles showed significant variation with increasing time before centrifugation (p<0.001) and increasing centrifugation force, with depletion of platelet associated miRNAs, whereas cfDNA was unaffected. However, sample replicates showed excellent reproducibility on TaqMan low density arrays (ρ = 0.96, p<0.0001). We also successfully generated miRNA profiles for plasma samples stored > 12 years, highlighting the potential for analysis of stored sample biobanks. In the era of the liquid biopsy, standardisation of methods is required to minimise variation, particularly for miRNA.

WNT ligands can activate several signalling cascades of pivotal importance during development and regenerative processes. Their de-regulation has been associated with the onset of different diseases. Here we investigated the role of the WNT/Calcium Calmodulin Kinase II (CaMKII) pathway in osteoarthritis. We identified Heme Oxygenase I (HMOX1) and Sox-9 as specific markers of the WNT/CaMKII signalling in articular chondrocytes through a microarray analysis. We showed that the expression of the activated form of CaMKII, phospho-CaMKII, was increased in human and murine osteoarthritis and the expression of HMOX1 was accordingly reduced, demonstrating the activation of the pathway during disease progression. To elucidate its function, we administered the CaMKII inhibitor KN93 to mice in which osteoarthritis was induced by resection of the anterior horn of the medial meniscus and of the medial collateral ligament in the knee joint. Pharmacological blockade of CaMKII exacerbated cartilage damage and bone remodelling. Finally, we showed that CaMKII inhibition in articular chondrocytes upregulated the expression of matrix remodelling enzymes alone and in combination with Interleukin 1. These results suggest an important homeostatic role of the WNT/CaMKII signalling in osteoarthritis which could be exploited in the future for therapeutic purposes.

Microcirculatory dysfunction occurs early in cardiovascular disease (CVD) development. Acute myocardial infarction (MI) is a late consequence of CVD. The conjunctival microcirculation is readily-accessible for quantitative assessment and has not previously been studied in MI patients. We compared the conjunctival microcirculation of acute MI patients and age/sex-matched healthy controls to determine if there were differences in microcirculatory parameters. We acquired images using an iPhone 6s and slit-lamp biomicroscope. Parameters measured included diameter, axial velocity, wall shear rate and blood volume flow. Results are for all vessels as they were not sub-classified into arterioles or venules. The conjunctival microcirculation was assessed in 56 controls and 59 inpatients with a presenting diagnosis of MI. Mean vessel diameter for the controls was 21.41 ± 7.57 μm compared to 22.32 ± 7.66 μm for the MI patients (p < 0.001). Axial velocity for the controls was 0.53 ± 0.15 mm/s compared to 0.49 ± 0.17 mm/s for the MI patients (p < 0.001). Wall shear rate was higher for controls than MI patients (162 ± 93 s −1 vs 145 ± 88 s −1 , p < 0.001). Blood volume flow did not differ significantly for the controls and MI patients (153 ± 124 pl/s vs 154 ± 125 pl/s, p = 0.84). This pilot iPhone and slit-lamp assessment of the conjunctival microcirculation found lower axial velocity and wall shear rate in patients with acute MI. Further study is required to correlate these findings further and assess long-term outcomes in this patient group with a severe CVD phenotype.

Prediction models for population-based screening need, for global usage, to be resource-driven, involving predictors that are affordably resourced. Here, we report the development and validation of three resource-driven risk models to identify people with type 2 diabetes (T2DM) at risk of stage 3 CKD defined by a decline in estimated glomerular filtration rate (eGFR) to below 60 mL/min/1.73m 2 . The observational study cohort used for model development consisted of data from a primary care dataset of 20,510 multi-ethnic individuals with T2DM from London, UK (2007–2018). Discrimination and calibration of the resulting prediction models developed using cox regression were assessed using the c-statistic and calibration slope, respectively. Models were internally validated using tenfold cross-validation and externally validated on 13,346 primary care individuals from Wales, UK. The simplest model was simplified into a risk score to enable implementation in community-based medicine. The derived full model included demographic, laboratory parameters, medication-use, cardiovascular disease history (CVD) and sight threatening retinopathy status (STDR). Two less resource-intense models were developed by excluding CVD and STDR in the second model and HbA1c and HDL in the third model. All three 5-year risk models had good internal discrimination and calibration (optimism adjusted C-statistics were each 0.85 and calibration slopes 0.999–1.002). In Wales, models achieved excellent discrimination(c-statistics ranged 0.82–0.83). Calibration slopes at 5-years suggested models over-predicted risks, however were successfully updated to accommodate reduced incidence of stage 3 CKD in Wales, which improved their alignment with the observed rates in Wales (E/O ratios near to 1). The risk score demonstrated similar model performance compared to direct evaluation of the cox model. These resource-driven risk prediction models may enable universal screening for Stage 3 CKD to enable targeted early optimisation of risk factors for CKD.

High-dimensional cytometry is an innovative tool for immune monitoring in health and disease, and it has provided novel insight into the underlying biology as well as biomarkers for a variety of diseases. However, the analysis of large multiparametric datasets usually requires specialist computational knowledge. Here, we describe ImmunoCluster ( https://github.com/kordastilab/ImmunoCluster ), an R package for immune profiling cellular heterogeneity in high-dimensional liquid and imaging mass cytometry, and flow cytometry data, designed to facilitate computational analysis by a nonspecialist. The analysis framework implemented within ImmunoCluster is readily scalable to millions of cells and provides a variety of visualization and analytical approaches, as well as a rich array of plotting tools that can be tailored to users’ needs. The protocol consists of three core computational stages: (1) data import and quality control; (2) dimensionality reduction and unsupervised clustering; and (3) annotation and differential testing, all contained within an R-based open-source framework.

ObjectiveTo evaluate the dynamics and longevity of the humoral immune response to SARS-CoV-2 infection and assess the performance of professional use of the UK-RTC AbC-19 Rapid Test lateral flow immunoassay (LFIA) for the target condition of SARS-CoV-2 spike protein IgG antibodies.DesignNationwide serological study.SettingNorthern Ireland, UK, May 2020–February 2021.ParticipantsPlasma samples were collected from a diverse cohort of individuals from the general public (n=279), Northern Ireland healthcare workers (n=195), pre-pandemic blood donations and research studies (n=223) and through a convalescent plasma programme (n=183). Plasma donors (n=101) were followed with sequential samples over 11 months post-symptom onset.Main outcome measuresSARS-CoV-2 antibody levels in plasma samples using Roche Elecsys Anti-SARS-CoV-2 IgG/IgA/IgM, Abbott SARS-CoV-2 IgG and EuroImmun IgG SARS-CoV-2 ELISA immunoassays over time. UK-RTC AbC-19 LFIA sensitivity and specificity, estimated using a three-reference standard system to establish a characterised panel of 330 positive and 488 negative SARS-CoV-2 IgG samples.ResultsWe detected persistence of SARS-CoV-2 IgG antibodies for up to 10 months post-infection, across a minimum of two laboratory immunoassays. On the known positive cohort, the UK-RTC AbC-19 LFIA showed a sensitivity of 97.58% (95.28% to 98.95%) and on known negatives, showed specificity of 99.59% (98.53 % to 99.95%).ConclusionsThrough comprehensive analysis of a cohort of pre-pandemic and pandemic individuals, we show detectable levels of IgG antibodies, lasting over 46 weeks when assessed by EuroImmun ELISA, providing insight to antibody levels at later time points post-infection. We show good laboratory validation performance metrics for the AbC-19 rapid test for SARS-CoV-2 spike protein IgG antibody detection in a laboratory-based setting.

Intratumoral heterogeneity may help drive resistance to targeted therapies in cancer. In breast cancer, the presence of nodal metastases is a key indicator of poorer overall survival. The aim of this study was to identify somatic genetic alterations in early dissemination of breast cancer by whole genome next generation sequencing (NGS) of a primary breast tumor, a matched locally-involved axillary lymph node and healthy normal DNA from blood. Whole genome NGS was performed on 12 µg (range 11.1-13.3 µg) of DNA isolated from fresh-frozen primary breast tumor, axillary lymph node and peripheral blood following the DNA nanoball sequencing protocol. Single nucleotide variants, insertions, deletions, and substitutions were identified through a bioinformatic pipeline and compared to CIN25, a key set of genes associated with tumor metastasis. Whole genome sequencing revealed overlapping variants between the tumor and node, but also variants that were unique to each. Novel mutations unique to the node included those found in two CIN25 targets, TGIF2 and CCNB2, which are related to transcription cyclin activity and chromosomal stability, respectively, and a unique frameshift in PDS5B, which is required for accurate sister chromatid segregation during cell division. We also identified dominant clonal variants that progressed from tumor to node, including SNVs in TP53 and ARAP3, which mediates rearrangements to the cytoskeleton and cell shape, and an insertion in TOP2A, the expression of which is significantly associated with tumor proliferation and can segregate breast cancers by outcome. This case study provides preliminary evidence that primary tumor and early nodal metastasis have largely overlapping somatic genetic alterations. There were very few mutations unique to the involved node. However, significant conclusions regarding early dissemination needs analysis of a larger number of patient samples.

Papillary Thyroid Carcinoma (PTC) accounts for approximately 85% of patients with thyroid cancer. Despite its indolent nature, progression to higher stages is expected in a subgroup of patients. Hence, genomic characterization of the early stages of PTC may help to identify this subgroup, leading to better clinical management. Here, we conducted a comprehensive mutational and somatic copy number alteration (SCNA) investigation on 277 stage one PTC from TCGA. SCNA analysis revealed amplification and deletion of several cancer related genes. We found amplification of 60 oncogenes (Oncs), from which 15 were recurrently observed. Deletion of 58 tumor suppressors (TSs) was also detected. MAPK, PI3K-Akt, Rap1 and Ras were the signaling pathways with large numbers of amplified Oncs. On the other hand, deleted TSs belonged mostly to cell cycle, PI3K-Akt, mTOR and cellular senescence pathways. This suggests that despite heterogeneity in SCNA events, the final results would be the activation/deactivation of a few cancer signaling pathways. Of note, despite large amounts of heterogeneity in stage one PTC, recurrent broad deletion on Chr22 was detected in 21 individuals, leading to deletion of several tumor suppressors. In parallel, the oncogenic/pathogenic mutations in the RTK-RAS and PI3k-Akt pathways were detected. However, no pathogenic mutation was identified in known tumor suppressor genes. In order to identify a potential subgroup of BRAF (V600E) positive patients, who might progress to higher stages, low frequency mutations accompanying BRAF (V600E) were also identified. In conclusion, our findings imply that SCNA have a substantial contribution to early stages of PTC. Experimental validation of the observed genomic alterations could help to stratify patients at the time of diagnosis, and to move toward precision medicine in PTC.

Several circulating biomarkers are reported to be associated with diabetic retinopathy (DR). However, their relative contributions to DR compared to known risk factors, such as hyperglycaemia, hypertension, and hyperlipidaemia, remain unclear. In this data driven study, we used novel models to evaluate the associations of over 400 laboratory parameters with DR compared to the established risk factors. Methods: we performed an environment-wide association study (EWAS) of laboratory parameters available in National Health and Nutrition Examination Survey (NHANES) 2007–2008 in individuals with diabetes with DR as the outcome (test set). We employed independent variable (feature) selection approaches, including parallelised univariate regression modelling, Principal Component Analysis (PCA), penalised regression, and RandomForest™. These models were replicated in NHANES 2005–2006 (replication set). Our test and replication sets consisted of 1025 and 637 individuals with available DR status and laboratory data respectively. Glycohemoglobin (HbA1c) was the strongest risk factor for DR. Our PCA-based approach produced a model that incorporated 18 principal components (PCs) that had an Area under the Curve (AUC) 0.796 (95% CI 0.761–0.832), while penalised regression identified a 9-feature model with 78.51% accuracy and AUC 0.74 (95% CI 0.72–0.77). RandomForest™ identified a 31-feature model with 78.4% accuracy and AUC 0.71 (95% CI 0.65–0.77). On grouping the selected variables in our RandomForest™, hyperglycaemia alone achieved AUC 0.72 (95% CI 0.68–0.76). The AUC increased to 0.84 (95% CI 0.78–0.9) when the model also included hypertension, hypercholesterolemia, haematocrit, renal, and liver function tests.

This study evaluates spike protein IgG antibody response following Oxford-AstraZeneca COVID-19 vaccination using the AbC-19™ lateral flow device. Plasma samples were collected from n = 111 individuals from Northern Ireland. The majority were >50 years old and/or clinically vulnerable. Samples were taken at five timepoints from pre-vaccination until 6-months post-first dose. 20.3% of participants had detectable IgG responses pre-vaccination, indicating prior COVID-19. Antibodies were detected in 86.9% of participants three weeks after the first vaccine dose, falling to 74.7% immediately prior to the second dose, and rising to 99% three weeks post-second vaccine. At 6-months post-first dose, this decreased to 90.5%. At all timepoints, previously infected participants had significantly higher antibody levels than those not previously infected. This study demonstrates that strong anti-spike protein antibody responses are evoked in almost all individuals that receive two doses of Oxford-AstraZeneca vaccine, and which largely persist beyond six months after first vaccination.