An integrated national scale SARS-CoV-2 genomic surveillance network.

The Coronavirus Disease 2019 (COVID-19) Genomics UK Consortium (COG-UK) was launched in March, 2020, with £20 million support from UK Research and Innovation, the UK Department of Health and Social Care, and Wellcome Trust. The goal of this consortium is to sequence severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) for up to 230 000 patients, health-care workers, and other essential workers in the UK with COVID-19, which will help to enable the tracking of SARS-CoV-2 transmission, identify viral mutations, and integrate with health data to assess how the viral genome interacts with cofactors and consequences of COVID-19

SCFD1 expression quantitative trait loci in amyotrophic lateral sclerosis are differentially expressed

Evidence indicates that common variants found in genome-wide association studies increase risk of disease through gene regulation via expression Quantitative Trait Loci. Using multiple genome-wide methods, we examined if Single Nucleotide Polymorphisms increase risk of Amyotrophic Lateral Sclerosis through expression Quantitative Trait Loci, and whether expression Quantitative Trait Loci expression is consistent across people who had Amyotrophic Lateral Sclerosis and those who did not. In combining public expression Quantitative Trait Loci data with Amyotrophic Lateral Sclerosis genome-wide association studies, we used Summary-data-based Mendelian Randomization to confirm that SCFD1 was the only gene that was genome-wide significant in mediating Amyotrophic Lateral Sclerosis risk via expression Quantitative Trait Loci (Summary-data-based Mendelian Randomization beta = 0.20, standard error = 0.04, P-value = 4.29 × 10-6). Using post-mortem motor cortex, we tested whether expression Quantitative Trait Loci showed significant differences in expression between Amyotrophic Lateral Sclerosis (n = 76) and controls (n = 25), genome-wide. Of 20 757 genes analysed, the two most significant expression Quantitative Trait Loci to show differential in expression between Amyotrophic Lateral Sclerosis and controls involve two known Amyotrophic Lateral Sclerosis genes (SCFD1 and VCP). Cis-acting SCFD1 expression Quantitative Trait Loci downstream of the gene showed significant differences in expression between Amyotrophic Lateral Sclerosis and controls (top expression Quantitative Trait Loci beta = 0.34, standard error = 0.063, P-value = 4.54 × 10-7). These SCFD1 expression Quantitative Trait Loci also significantly modified Amyotrophic Lateral Sclerosis survival (number of samples = 4265, hazard ratio = 1.11, 95% confidence interval = 1.05-1.17, P-value = 2.06 × 10-4) and act as an Amyotrophic Lateral Sclerosis trans-expression Quantitative Trait Loci hotspot for a wider network of genes enriched for SCFD1 function and Amyotrophic Lateral Sclerosis pathways. Using gene-set analyses, we found the genes that correlate with this trans-expression Quantitative Trait Loci hotspot significantly increase risk of Amyotrophic Lateral Sclerosis (beta = 0.247, standard deviation = 0.017, P = 0.001) and schizophrenia (beta = 0.263, standard deviation = 0.008, P-value = 1.18 × 10-5), a disease that genetically correlates with Amyotrophic Lateral Sclerosis. In summary, SCFD1 expression Quantitative Trait Loci are a major factor in Amyotrophic Lateral Sclerosis, not only influencing disease risk but are differentially expressed in post-mortem Amyotrophic Lateral Sclerosis. SCFD1 expression Quantitative Trait Loci show distinct expression profiles in Amyotrophic Lateral Sclerosis that correlate with a wider network of genes that also confer risk of the disease and modify the disease's duration

Visual Function, Social Position, and Health and Life Chances: The UK Biobank Study

Importance: The adverse impact of visual impairment and blindness and correlations with socioeconomic position are known. Understanding of the effect of the substantially more common near-normal vision (mild impairment) and associations with social position as well as health and life chances is limited. Objective: To investigate the association of visual health (across the full acuity spectrum) with social determinants of general health and the association between visual health and health and social outcomes. Design, Setting, and Participants: A cross-sectional epidemiologic study was conducted using UK Biobank data from 6 regional centers in England and Wales. A total of 112 314 volunteers (aged 40-73 years) were assessed in June 2009 and July 2010. Data analysis was performed from May 20, 2013, to November 19, 2014. Main Outcomes and Measures: Habitual (correction if prescribed) distance visual acuity was used to assign participants to 1 of 8 categories from bilateral normal visual acuity (logMAR, 0.2 or better; Snellen equivalent, 6/9.5 or better) to visual impairment or blindness (logMAR, 0.5 or worse; Snellen equivalent, 6/19 or worse) using World Health Organization and International Statistical Classification of Diseases and Related Health Problems, Tenth Revision taxonomy. Relationships between vision, key social determinants and health and social outcomes (including the main factors that define an individual's life-the social, economic, educational, and employment opportunities and outcomes experienced by individuals during their life course) were examined using multivariable regression. Results: Of the of 112 314 participants, 61 169 were female (54.5%); mean (SD) age was 56.8 (8.1) years. A total of 759 (0.7%) of the participants had visual impairment or blindness, and an additional 25 678 (22.9%) had reduced vision in 1 or both eyes. Key markers of social position were independently associated with vision in a gradient across acuity categories; in a gradient of increasing severity, all-cause impaired visual function was associated with adverse social outcomes and impaired general and mental health. These factors, including having no educational qualifications (risk ratio [RR], 1.86 [95% CI, 1.69-2.04]), having a higher deprivation score (RR, 1.08 [95% CI, 1.07-1.09]), and being in a minority ethnic group (eg, Asian) (RR, 2.05 [95% CI, 1.83-2.30]), were independently associated with being in the midrange vision category (at legal threshold for driving). This level of vision was associated with an increased risk of being unemployed (RR, 1.55 [95% CI, 1.31-1.84]), having a lower-status job (RR, 1.24 [95% CI, 1.09-1.41]), living alone (RR, 1.24 [95% CI, 1.10-1.39]), and having mental health problems (RR, 1.12 [95% CI, 1.04-1.20]). Conclusions and Relevance: Impaired vision in adults is common, and even near-normal vision, potentially unrecognized without assessment, has a tangible influence on quality of life. Because inequalities in visual health by social position mirror other health domains, inclusion of vision in generic initiatives addressing health inequalities could address the existing significant burden of underrecognized and/or latent visual disability. Longitudinal investigations are needed to elucidate pathophysiologic pathways and target modifiable mechanisms

Genome-wide association studies for corneal and refractive astigmatism in UK Biobank demonstrate a shared role for myopia susceptibility loci.

Previous studies have suggested that naturally occurring genetic variation contributes to the risk of astigmatism. The purpose of this investigation was to identify genetic markers associated with corneal and refractive astigmatism in a large-scale European ancestry cohort (UK Biobank) who underwent keratometry and autorefraction at an assessment centre. Genome-wide association studies for corneal and refractive astigmatism were performed in individuals of European ancestry (N = 86,335 and 88,005 respectively), with the mean corneal astigmatism or refractive astigmatism in fellow eyes analysed as a quantitative trait (dependent variable). Genetic correlation between the two traits was calculated using LD Score regression. Gene-based and gene-set tests were carried out using MAGMA. Single marker-based association tests for corneal astigmatism identified four genome-wide significant loci (P < 5 × 10-8) near the genes ZC3H11B (1q41), LINC00340 (6p22.3), HERC2/OCA2 (15q13.1) and NPLOC4/TSPAN10 (17q25.3). Three of these loci also demonstrated genome-wide significant association with refractive astigmatism: LINC00340, HERC2/OCA2 and NPLOC4/TSPAN10. The genetic correlation between corneal and refractive astigmatism was 0.85 (standard error = 0.068, P = 1.37 × 10-35). Here, we have undertaken the largest genome-wide association studies for corneal and refractive astigmatism to date and identified four novel loci for corneal astigmatism, two of which were also novel loci for refractive astigmatism. These loci have previously demonstrated association with axial length (ZC3H11B), myopia (NPLOC4), spherical equivalent refractive error (LINC00340) and eye colour (HERC2). The shared role of these novel candidate genes for astigmatism lends further support to the shared genetic susceptibility of myopia and astigmatism

Frequency and Distribution of Refractive Error in Adult Life: Methodology and Findings of the UK Biobank Study

PURPOSE: To report the methodology and findings of a large scale investigation of burden and distribution of refractive error, from a contemporary and ethnically diverse study of health and disease in adults, in the UK. METHODS: U K Biobank, a unique contemporary resource for the study of health and disease, recruited more than half a million people aged 40-69 years. A subsample of 107,452 subjects undertook an enhanced ophthalmic examination which provided autorefraction data (a measure of refractive error). Refractive error status was categorised using the mean spherical equivalent refraction measure. Information on socio-demographic factors (age, gender, ethnicity, educational qualifications and accommodation tenure) was reported at the time of recruitment by questionnaire and face-to-face interview. RESULTS: Fifty four percent of participants aged 40-69 years had refractive error. Specifically 27% had myopia (4% high myopia), which was more common amongst younger people, those of higher socio-economic status, higher educational attainment, or of White or Chinese ethnicity. The frequency of hypermetropia increased with age (7% at 40-44 years increasing to 46% at 65-69 years), was higher in women and its severity was associated with ethnicity (moderate or high hypermetropia at least 30% less likely in non-White ethnic groups compared to White). CONCLUSIONS: Refractive error is a significant public health issue for the UK and this study provides contemporary data on adults for planning services, health economic modelling and monitoring of secular trends. Further investigation of risk factors is necessary to inform strategies for prevention. There is scope to do this through the planned longitudinal extension of the UK Biobank study

A robust clustering algorithm for identifying problematic samples in genome-wide association studies

Summary: High-throughput genotyping arrays provide an efficient way to survey single nucleotide polymorphisms (SNPs) across the genome in large numbers of individuals. Downstream analysis of the data, for example in genome-wide association studies (GWAS), often involves statistical models of genotype frequencies across individuals. The complexities of the sample collection process and the potential for errors in the experimental assay can lead to biases and artefacts in an individual's inferred genotypes. Rather than attempting to model these complications, it has become a standard practice to remove individuals whose genome-wide data differ from the sample at large. Here we describe a simple, but robust, statistical algorithm to identify samples with atypical summaries of genome-wide variation. Its use as a semi-automated quality control tool is demonstrated using several summary statistics, selected to identify different potential problems, and it is applied to two different genotyping platforms and sample collections

Detecting SARS-CoV-2 variants with SNP genotyping.

Tracking genetic variations from positive SARS-CoV-2 samples yields crucial information about the number of variants circulating in an outbreak and the possible lines of transmission but sequencing every positive SARS-CoV-2 sample would be prohibitively costly for population-scale test and trace operations. Genotyping is a rapid, high-throughput and low-cost alternative for screening positive SARS-CoV-2 samples in many settings. We have designed a SNP identification pipeline to identify genetic variation using sequenced SARS-CoV-2 samples. Our pipeline identifies a minimal marker panel that can define distinct genotypes. To evaluate the system, we developed a genotyping panel to detect variants-identified from SARS-CoV-2 sequences surveyed between March and May 2020 and tested this on 50 stored qRT-PCR positive SARS-CoV-2 clinical samples that had been collected across the South West of the UK in April 2020. The 50 samples split into 15 distinct genotypes and there was a 61.9% probability that any two randomly chosen samples from our set of 50 would have a distinct genotype. In a high throughput laboratory, qRT-PCR positive samples pooled into 384-well plates could be screened with a marker panel at a cost of < £1.50 per sample. Our results demonstrate the usefulness of a SNP genotyping panel to provide a rapid, cost-effective, and reliable way to monitor SARS-CoV-2 variants circulating in an outbreak. Our analysis pipeline is publicly available and will allow for marker panels to be updated periodically as viral genotypes arise or disappear from circulation

Detecting SARS-CoV-2 variants with SNP genotyping.

Tracking genetic variations from positive SARS-CoV-2 samples yields crucial information about the number of variants circulating in an outbreak and the possible lines of transmission but sequencing every positive SARS-CoV-2 sample would be prohibitively costly for population-scale test and trace operations. Genotyping is a rapid, high-throughput and low-cost alternative for screening positive SARS-CoV-2 samples in many settings. We have designed a SNP identification pipeline to identify genetic variation using sequenced SARS-CoV-2 samples. Our pipeline identifies a minimal marker panel that can define distinct genotypes. To evaluate the system, we developed a genotyping panel to detect variants-identified from SARS-CoV-2 sequences surveyed between March and May 2020 and tested this on 50 stored qRT-PCR positive SARS-CoV-2 clinical samples that had been collected across the South West of the UK in April 2020. The 50 samples split into 15 distinct genotypes and there was a 61.9% probability that any two randomly chosen samples from our set of 50 would have a distinct genotype. In a high throughput laboratory, qRT-PCR positive samples pooled into 384-well plates could be screened with a marker panel at a cost of < £1.50 per sample. Our results demonstrate the usefulness of a SNP genotyping panel to provide a rapid, cost-effective, and reliable way to monitor SARS-CoV-2 variants circulating in an outbreak. Our analysis pipeline is publicly available and will allow for marker panels to be updated periodically as viral genotypes arise or disappear from circulation