IgG antibody production and persistence to 6 months following SARS-CoV-2 vaccination: a Northern Ireland observational study

BACKGROUND: This study evaluates spike protein IgG antibody response following Oxford-AstraZeneca COVID-19 vaccination using the AbC-19™ lateral flow device. METHODS: 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. RESULTS: 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. CONCLUSION: 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 largely persist beyond six months after first vaccination

Mutation-independent Allele-Specific Editing by CRISPR-Cas9, a Novel Approach to Treat Autosomal Dominant Disease

CRISPR-Cas9 provides a tool to treat autosomal dominant disease by non-homologous end joining (NHEJ) gene disruption of the mutant allele. In order to discriminate between wild-type and mutant alleles, Streptococcus pyogenes Cas9 (SpCas9) must be able to detect a single nucleotide change. Allele-specific editing can be achieved by using either a guide-specific approach, in which the missense mutation is found within the guide sequence, or a protospacer-adjacent motif (PAM)-specific approach, in which the missense mutation generates a novel PAM. While both approaches have been shown to offer allele specificity in certain contexts, in cases where numerous missense mutations are associated with a particular disease, such as TGFBI (transforming growth factor β-induced) corneal dystrophies, it is neither possible nor realistic to target each mutation individually. In this study, we demonstrate allele-specific CRISPR gene editing independent of the disease-causing mutation that is capable of achieving complete allele discrimination, and we propose it as a targeting approach for autosomal dominant disease. Our approach utilizes natural variants in the target region that contain a PAM on one allele that lies in cis with the causative mutation, removing the constraints of a mutation-dependent approach. Our innovative patient-specific guide design approach takes into account the patient’s individual genetic make-up, allowing on- and off-target activity to be assessed in a personalized manner

Quantitative assessment of the conjunctival microcirculation using a smartphone and slit-lamp biomicroscope

Purpose: The conjunctival microcirculation is a readily-accessible vascular bed for quantitative haemodynamic assessment and has been studied previously using a digital charge-coupled device (CCD). Smartphone video imaging of the conjunctiva, and haemodynamic parameter quantification, represents a novel approach. We report the feasibility of smartphone video acquisition and subsequent haemodynamic measure quantification via semi-automated means. Methods: Using an Apple iPhone 6 s and a Topcon SL-D4 slit-lamp biomicroscope, we obtained videos of the conjunctival microcirculation in 4 fields of view per patient, for 17 low cardiovascular risk patients. After image registration and processing, we quantified the diameter, mean axial velocity, mean blood volume flow, and wall shear rate for each vessel studied. Vessels were grouped into quartiles based on their diameter i.e. group 1 (&lt;11 μm), 2 (11–16 μm), 3 (16–22 μm) and 4 (&gt;22 μm). Results: From the 17 healthy controls (mean QRISK3 6.6%), we obtained quantifiable haemodynamics from 626 vessel segments. The mean diameter of microvessels, across all sites, was 21.1μm (range 5.8–58 μm). Mean axial velocity was 0.50mm/s (range 0.11–1mm/s) and there was a modestly positive correlation (r 0.322) seen with increasing diameter, best appreciated when comparing group 4 to the remaining groups (p &lt; .0001). Blood volume flow (mean 145.61pl/s, range 7.05–1178.81pl/s) was strongly correlated with increasing diameter (r 0.943, p &lt; .0001) and wall shear rate (mean 157.31 s − 1, range 37.37–841.66 s − 1) negatively correlated with increasing diameter (r − 0.703, p &lt; .0001). Conclusions: We, for the first time, report the successful assessment and quantification of the conjunctival microcirculatory haemodynamics using a smartphone-based system. </p

Development and validation of resource-driven risk prediction models for incident chronic kidney disease in type 2 diabetes

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/1.73m2. 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

Evaluation of the IgG antibody response to SARS CoV-2 infection and performance of a lateral flow immunoassay: cross-sectional and longitudinal analysis over 11 months

OBJECTIVE: To 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. DESIGN: Nationwide serological study. SETTING: Northern Ireland, UK, May 2020–February 2021. PARTICIPANTS: Plasma 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 MEASURES: SARS-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. RESULTS: We 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%). CONCLUSIONS: Through 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

Whole genome sequence analysis suggests intratumoral heterogeneity in dissemination of breast cancer to lymph nodes.

BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSION: 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

Molecular analysis of circulating cell-free DNA in breast cancer patients

Identifying disease-related variants is a primary aim of human genetics. In breast cancer, loss of heterozygosity at specific loci was previously demonstrated in paired tumour and circulating plasma cell-free DNA (cfDNA) samples. However, alterations unique to cfDNA were also found in all cases, suggesting disease progression. These results prompted the characterisation of the circulating breast cancer genome in more detail in this thesis, to test the hypothesis that cfDNA acts as a surrogate tumour marker. This was achieved using Affymetrix SNP 6.0 technology and bioinformatics to map SNP and copy number variation (CNV), comparing cfDNA with matched normal lymphocyte and tumour DNA in 65 breast cancer patients and 8 healthy female controls. Results in this thesis show that comparison of cfDNA SNP genotypes can distinguish between primary breast cancer patients and healthy controls (p<0.0001), and between pre-surgical breast cancer patients and those who already had surgery/treatment (p=0.0016). A significant difference (p=0.0006) was also found between cfDNA samples taken an average of 3 years apart in women on follow-up, again suggesting progression. In addition, CNV amplification was observed in matched tumour and cfDNA at numerous loci on different chromosome arms. Many of these tumour-specific CNVs contributed significantly to disease through logistic regression analysis and remained detectable in cfDNA up to 12 years after diagnosis despite no other evidence of disease. This finding strongly infers breast cancer dormancy in the majority of patients on follow-up. In addition, candidate CNVs were validated by real-time qPCR and additional bioinformatics revealed key SNP and CNV signatures of breast cancer patients. If validated in other patient series, the results could alter the diagnostic and prognosti