scholarly journals Dynamic linkage of COVID-19 test results between Public Health England’s Second Generation Surveillance System and UK Biobank

2020 ◽  
Vol 6 (7) ◽  
Author(s):  
Jacob Armstrong ◽  
Justine K. Rudkin ◽  
Naomi Allen ◽  
Derrick W. Crook ◽  
Daniel J. Wilson ◽  
...  

UK Biobank (UKB) is an international health resource enabling research into the genetic and lifestyle determinants of common diseases of middle and older age. It comprises 500 000 participants. Public Health England’s Second Generation Surveillance System is a centralized microbiology database covering English clinical diagnostics laboratories that provides national surveillance of legally notifiable infections, bacterial isolations and antimicrobial resistance. We previously developed secure, pseudonymized, individual-level linkage of these systems. In this study, we implemented rapid dynamic linkage, which allows us to provide a regular feed of new COVID-19 (SARS-CoV-2) test results to UKB to facilitate rapid and urgent research into the epidemiological and human genetic risk factors for severe infection in the cohort. Here, we have characterized the first 1352 cases of COVID-19 in UKB participants, of whom 895 met our working definition of severe COVID-19 as inpatients hospitalized on or after 16 March 2020. We found that the incidence of severe COVID-19 among UKB cases was 27.4 % lower than the general population in England, although this difference varied significantly by age and sex. The total number of UKB cases could be estimated as 0.6 % of the publicly announced number of cases in England. We considered how increasing case numbers will affect the power of genome-wide association studies. This new dynamic linkage system has further potential to facilitate the investigation of other infections and the prospective collection of microbiological cultures to create a microbiological biobank (bugbank) for studying the interaction of environment, human and microbial genetics on infection in the UKB cohort.

2021 ◽  
Vol 10 ◽  
pp. 204800402110236
Author(s):  
Julia Ramírez ◽  
Stefan van Duijvenboden ◽  
William J Young ◽  
Michele Orini ◽  
Aled R Jones ◽  
...  

The electrocardiogram (ECG) is a commonly used clinical tool that reflects cardiac excitability and disease. Many parameters are can be measured and with the improvement of methodology can now be quantified in an automated fashion, with accuracy and at scale. Furthermore, these measurements can be heritable and thus genome wide association studies inform the underpinning biological mechanisms. In this review we describe how we have used the resources in UK Biobank to undertake such work. In particular, we focus on a substudy uniquely describing the response to exercise performed at scale with accompanying genetic information.


2021 ◽  
Author(s):  
Abhishek Nag ◽  
Lawrence Middleton ◽  
Ryan S Dhindsa ◽  
Dimitrios Vitsios ◽  
Eleanor M Wigmore ◽  
...  

Genome-wide association studies have established the contribution of common and low frequency variants to metabolic biomarkers in the UK Biobank (UKB); however, the role of rare variants remains to be assessed systematically. We evaluated rare coding variants for 198 metabolic biomarkers, including metabolites assayed by Nightingale Health, using exome sequencing in participants from four genetically diverse ancestries in the UKB (N=412,394). Gene-level collapsing analysis, that evaluated a range of genetic architectures, identified a total of 1,303 significant relationships between genes and metabolic biomarkers (p<1x10-8), encompassing 207 distinct genes. These include associations between rare non-synonymous variants in GIGYF1 and glucose and lipid biomarkers, SYT7 and creatinine, and others, which may provide insights into novel disease biology. Comparing to a previous microarray-based genotyping study in the same cohort, we observed that 40% of gene-biomarker relationships identified in the collapsing analysis were novel. Finally, we applied Gene-SCOUT, a novel tool that utilises the gene-biomarker association statistics from the collapsing analysis to identify genes having similar biomarker fingerprints and thus expand our understanding of gene networks.


Author(s):  
Nasa Sinnott-Armstrong ◽  
Sahin Naqvi ◽  
Manuel Rivas ◽  
Jonathan K Pritchard

SummaryGenome-wide association studies (GWAS) have been used to study the genetic basis of a wide variety of complex diseases and other traits. However, for most traits it remains difficult to interpret what genes and biological processes are impacted by the top hits. Here, as a contrast, we describe UK Biobank GWAS results for three molecular traits—urate, IGF-1, and testosterone—that are biologically simpler than most diseases, and for which we know a great deal in advance about the core genes and pathways. Unlike most GWAS of complex traits, for all three traits we find that most top hits are readily interpretable. We observe huge enrichment of significant signals near genes involved in the relevant biosynthesis, transport, or signaling pathways. We show how GWAS data illuminate the biology of variation in each trait, including insights into differences in testosterone regulation between females and males. Meanwhile, in other respects the results are reminiscent of GWAS for more-complex traits. In particular, even these molecular traits are highly polygenic, with most of the variance coming not from core genes, but from thousands to tens of thousands of variants spread across most of the genome. Given that diseases are often impacted by many distinct biological processes, including these three, our results help to illustrate why so many variants can affect risk for any given disease.


Author(s):  
Jack W. O’Sullivan ◽  
John P. A. Ioannidis

AbstractWith the establishment of large biobanks, discovery of single nucleotide polymorphism (SNPs) that are associated with various phenotypes has been accelerated. An open question is whether SNPs identified with genome-wide significance in earlier genome-wide association studies (GWAS) are replicated also in later GWAS conducted in biobanks. To address this question, the authors examined a publicly available GWAS database and identified two, independent GWAS on the same phenotype (an earlier, “discovery” GWAS and a later, replication GWAS done in the UK biobank). The analysis evaluated 136,318,924 SNPs (of which 6,289 had reached p<5e-8 in the discovery GWAS) from 4,397,962 participants across nine phenotypes. The overall replication rate was 85.0% and it was lower for binary than for quantitative phenotypes (58.1% versus 94.8% respectively). There was a18.0% decrease in SNP effect size for binary phenotypes, but a 12.0% increase for quantitative phenotypes. Using the discovery SNP effect size, phenotype trait (binary or quantitative), and discovery p-value, we built and validated a model that predicted SNP replication with area under the Receiver Operator Curve = 0.90. While non-replication may often reflect lack of power rather than genuine false-positive findings, these results provide insights about which discovered associations are likely to be seen again across subsequent GWAS.


2021 ◽  
pp. ASN.2020111599
Author(s):  
Zhi Yu ◽  
Jin Jin ◽  
Adrienne Tin ◽  
Anna Köttgen ◽  
Bing Yu ◽  
...  

Background: Genome-wide association studies (GWAS) have revealed numerous loci for kidney function (estimated glomerular filtration rate, eGFR). The relationship of polygenic predictors of eGFR, risk of incident adverse kidney outcomes, and the plasma proteome is not known. Methods: We developed a genome-wide polygenic risk score (PRS) for eGFR by applying the LDpred algorithm to summary statistics generated from a multiethnic meta-analysis of CKDGen Consortium GWAS (N=765,348) and UK Biobank GWAS (90% of the cohort; N=451,508), followed by best parameter selection using the remaining 10% of UK Biobank (N=45,158). We then tested the association of the PRS in the Atherosclerosis Risk in Communities (ARIC) study (N=8,866) with incident chronic kidney disease, kidney failure, and acute kidney injury. We also examined associations between the PRS and 4,877 plasma proteins measured at at middle age and older adulthood and evaluated mediation of PRS associations by eGFR. Results: The developed PRS showed significant associations with all outcomes with hazard ratios (95% CI) per 1 SD lower PRS ranged from 1.06 (1.01, 1.11) to 1.33 (1.28, 1.37). The PRS was significantly associated with 132 proteins at both time points. The strongest associations were with cystatin-C, collagen alpha-1(XV) chain, and desmocollin-2. Most proteins were higher at lower kidney function, except for 5 proteins including testican-2. Most correlations of the genetic PRS with proteins were mediated by eGFR. Conclusions: A PRS for eGFR is now sufficiently strong to capture risk for a spectrum of incident kidney diseases and broadly influences the plasma proteome, primarily mediated by eGFR.


2019 ◽  
Vol 29 (4) ◽  
pp. 689-702 ◽  
Author(s):  
Thibaud S Boutin ◽  
David G Charteris ◽  
Aman Chandra ◽  
Susan Campbell ◽  
Caroline Hayward ◽  
...  

Abstract Retinal detachment (RD) is a serious and common condition, but genetic studies to date have been hampered by the small size of the assembled cohorts. In the UK Biobank data set, where RD was ascertained by self-report or hospital records, genetic correlations between RD and high myopia or cataract operation were, respectively, 0.46 (SE = 0.08) and 0.44 (SE = 0.07). These correlations are consistent with known epidemiological associations. Through meta-analysis of genome-wide association studies using UK Biobank RD cases (N = 3 977) and two cohorts, each comprising ~1 000 clinically ascertained rhegmatogenous RD patients, we uncovered 11 genome-wide significant association signals. These are near or within ZC3H11B, BMP3, COL22A1, DLG5, PLCE1, EFEMP2, TYR, FAT3, TRIM29, COL2A1 and LOXL1. Replication in the 23andMe data set, where RD is self-reported by participants, firmly establishes six RD risk loci: FAT3, COL22A1, TYR, BMP3, ZC3H11B and PLCE1. Based on the genetic associations with eye traits described to date, the first two specifically impact risk of a RD, whereas the last four point to shared aetiologies with macular condition, myopia and glaucoma. Fine-mapping prioritized the lead common missense variant (TYR S192Y) as causal variant at the TYR locus and a small set of credible causal variants at the FAT3 locus. The larger study size presented here, enabled by resources linked to health records or self-report, provides novel insights into RD aetiology and underlying pathological pathways.


2020 ◽  
Author(s):  
Adam Lavertu ◽  
Gregory McInnes ◽  
Yosuke Tanigawa ◽  
Russ B Altman ◽  
Manuel A. Rivas

AbstractGenetics plays a key role in drug response, affecting efficacy and toxicity. Pharmacogenomics aims to understand how genetic variation influences drug response and develop clinical guidelines to aid clinicians in personalized treatment decisions informed by genetics. Although pharmacogenomics has not been broadly adopted into clinical practice, genetics influences treatment decisions regardless. Physicians adjust patient care based on observed response to medication, which may occur as a result of genetic variants harbored by the patient. Here we seek to understand the genetics of drug selection in statin therapy, a class of drugs widely used for high cholesterol treatment. Genetics are known to play an important role in statin efficacy and toxicity, leading to significant changes in patient outcome. We performed genome-wide association studies (GWAS) on statin selection among 59,198 participants in the UK Biobank and found that variants known to influence statin efficacy are significantly associated with statin selection. Specifically, we find that carriers of variants in APOE and LPA that are known to decrease efficacy of treatment are more likely to be on atorvastatin, a stronger statin. Additionally, carriers of the APOE and LPA variants are more likely to be on a higher intensity dose (a dose that reduces low-density lipoprotein cholesterol by greater than 40%) of atorvastatin than non-carriers (APOE: p(high intensity) = 0.16, OR = 1.7, P = 1.64 × 10−4, LPA: p(high intensity) = 0.17, OR = 1.4, P = 1.14 × 10−2). These findings represent the largest genetic association study of statin selection and statin dose association to date and provide evidence for the role of LPA and APOE in statin response, furthering the possibility of personalized statin therapy.


Author(s):  
Andrea Dugas ◽  
Howard Burkom ◽  
Richard Rothman

In order to provide real-time access to influenza test results, we created a laboratory-based surveillance system which automatically uploaded influenza test results from a rapid PCR-based influenza test, Xpert Flu, and the associated testing times and locations. On-site, type-specific results were available to physicians and uploaded for public health awareness within 100 minutes of patient nasopharyngeal swab. Expansion of this real-time capability to sentinel facilities could improve both local and national surveillance and response, reducing the need for syndromic influenza surveillance.


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