Biobanks and Legislation in Switzerland – a data protection perspective

2007 ◽  
Vol 4 (5) ◽  
Author(s):  
Claudia Mund

AbstractThe combination of health and lifestyle data with bodily substances and genetic information has led over the last few years to the creation of so-called biobanks. These biobanks are used to research a large number of diseases of modern civilization and their genetic interactions. One of the best-known projects in this respect is without a doubt the Icelandic biobank, operated since 1998 by a private pharmaceutical company, deCode Genetics, and set up with government support. The database contains family histories and medical records, as well as biological samples taken from a large section of Iceland's homogeneous population. The hope is that this data will allow a correlation to be established between genetic predispositions and the onset of widespread diseases. Other examples of population-based biobanks include the Estonian Genome Project, launched in 2001 by the Estonian Government, as well as the UK Biobank in the UK and PopGen in the state of Schleswig-Holstein in Germany.

BMJ ◽  
2021 ◽  
pp. n214
Author(s):  
Weedon MN ◽  
Jackson L ◽  
Harrison JW ◽  
Ruth KS ◽  
Tyrrell J ◽  
...  

Abstract Objective To determine whether the sensitivity and specificity of SNP chips are adequate for detecting rare pathogenic variants in a clinically unselected population. Design Retrospective, population based diagnostic evaluation. Participants 49 908 people recruited to the UK Biobank with SNP chip and next generation sequencing data, and an additional 21 people who purchased consumer genetic tests and shared their data online via the Personal Genome Project. Main outcome measures Genotyping (that is, identification of the correct DNA base at a specific genomic location) using SNP chips versus sequencing, with results split by frequency of that genotype in the population. Rare pathogenic variants in the BRCA1 and BRCA2 genes were selected as an exemplar for detailed analysis of clinically actionable variants in the UK Biobank, and BRCA related cancers (breast, ovarian, prostate, and pancreatic) were assessed in participants through use of cancer registry data. Results Overall, genotyping using SNP chips performed well compared with sequencing; sensitivity, specificity, positive predictive value, and negative predictive value were all above 99% for 108 574 common variants directly genotyped on the SNP chips and sequenced in the UK Biobank. However, the likelihood of a true positive result decreased dramatically with decreasing variant frequency; for variants that are very rare in the population, with a frequency below 0.001% in UK Biobank, the positive predictive value was very low and only 16% of 4757 heterozygous genotypes from the SNP chips were confirmed with sequencing data. Results were similar for SNP chip data from the Personal Genome Project, and 20/21 individuals analysed had at least one false positive rare pathogenic variant that had been incorrectly genotyped. For pathogenic variants in the BRCA1 and BRCA2 genes, which are individually very rare, the overall performance metrics for the SNP chips versus sequencing in the UK Biobank were: sensitivity 34.6%, specificity 98.3%, positive predictive value 4.2%, and negative predictive value 99.9%. Rates of BRCA related cancers in UK Biobank participants with a positive SNP chip result were similar to those for age matched controls (odds ratio 1.31, 95% confidence interval 0.99 to 1.71) because the vast majority of variants were false positives, whereas sequence positive participants had a significantly increased risk (odds ratio 4.05, 2.72 to 6.03). Conclusions SNP chips are extremely unreliable for genotyping very rare pathogenic variants and should not be used to guide health decisions without validation.


Gut ◽  
2018 ◽  
Vol 68 (4) ◽  
pp. 672-683 ◽  
Author(s):  
Todd Smith ◽  
David C Muller ◽  
Karel G M Moons ◽  
Amanda J Cross ◽  
Mattias Johansson ◽  
...  

ObjectiveTo systematically identify and validate published colorectal cancer risk prediction models that do not require invasive testing in two large population-based prospective cohorts.DesignModels were identified through an update of a published systematic review and validated in the European Prospective Investigation into Cancer and Nutrition (EPIC) and the UK Biobank. The performance of the models to predict the occurrence of colorectal cancer within 5 or 10 years after study enrolment was assessed by discrimination (C-statistic) and calibration (plots of observed vs predicted probability).ResultsThe systematic review and its update identified 16 models from 8 publications (8 colorectal, 5 colon and 3 rectal). The number of participants included in each model validation ranged from 41 587 to 396 515, and the number of cases ranged from 115 to 1781. Eligible and ineligible participants across the models were largely comparable. Calibration of the models, where assessable, was very good and further improved by recalibration. The C-statistics of the models were largely similar between validation cohorts with the highest values achieved being 0.70 (95% CI 0.68 to 0.72) in the UK Biobank and 0.71 (95% CI 0.67 to 0.74) in EPIC.ConclusionSeveral of these non-invasive models exhibited good calibration and discrimination within both external validation populations and are therefore potentially suitable candidates for the facilitation of risk stratification in population-based colorectal screening programmes. Future work should both evaluate this potential, through modelling and impact studies, and ascertain if further enhancement in their performance can be obtained.


2019 ◽  
Vol 29 (12) ◽  
pp. 5217-5233 ◽  
Author(s):  
Lauren E Salminen ◽  
Rand R Wilcox ◽  
Alyssa H Zhu ◽  
Brandalyn C Riedel ◽  
Christopher R K Ching ◽  
...  

Abstract Secondhand smoke exposure is a major public health risk that is especially harmful to the developing brain, but it is unclear if early exposure affects brain structure during middle age and older adulthood. Here we analyzed brain MRI data from the UK Biobank in a population-based sample of individuals (ages 44–80) who were exposed (n = 2510) or unexposed (n = 6079) to smoking around birth. We used robust statistical models, including quantile regressions, to test the effect of perinatal smoke exposure (PSE) on cortical surface area (SA), thickness, and subcortical volumes. We hypothesized that PSE would be associated with cortical disruption in primary sensory areas compared to unexposed (PSE−) adults. After adjusting for multiple comparisons, SA was significantly lower in the pericalcarine (PCAL), inferior parietal (IPL), and regions of the temporal and frontal cortex of PSE+ adults; these abnormalities were associated with increased risk for several diseases, including circulatory and endocrine conditions. Sensitivity analyses conducted in a hold-out group of healthy participants (exposed, n = 109, unexposed, n = 315) replicated the effect of PSE on SA in the PCAL and IPL. Collectively our results show a negative, long term effect of PSE on sensory cortices that may increase risk for disease later in life.


2014 ◽  
Vol 71 (Suppl 1) ◽  
pp. A19.1-A19
Author(s):  
Sara De Matteis ◽  
Lesley Rushton ◽  
Debbie Jarvis ◽  
Magda Wheatley ◽  
Hadia Azhar ◽  
...  

PLoS ONE ◽  
2016 ◽  
Vol 11 (10) ◽  
pp. e0164095 ◽  
Author(s):  
Pearse A. Keane ◽  
Carlota M. Grossi ◽  
Paul J. Foster ◽  
Qi Yang ◽  
Charles A. Reisman ◽  
...  

2021 ◽  
Author(s):  
Elena P. Sorokin ◽  
Nicolas Basty ◽  
Brandon Whitcher ◽  
Yi Liu ◽  
Jimmy D. Bell ◽  
...  

AbstractAging, and the pathogenesis of many common diseases, involves iron homeostasis. A key role in iron homeostasis is played by the spleen, which is the largest filter of the blood and performs iron reuptake from old or damaged erythrocytes. Despite this important role, spleen iron content has not been measured previously in a large, population-based cohort. In this study, we quantify spleen iron in 41,764 participants of the UK Biobank using magnetic resonance imaging (MRI). We find that epidemiologic and environmental factors such as increased age, higher red meat consumption and lower alcohol intake correlate with higher spleen iron. Through genome-wide association study, we identify genetic associations between spleen iron and common variation at seven loci, including in two hereditary spherocytosis (HS) genes, ANK1 and SPTA1. HS-causing mutations in these genes are associated with lower reticulocyte volume and increased reticulocyte percentage, while our common alleles are associated with increased expression of ANK1 and SPTA1 in blood and with larger reticulocyte volume and reduced reticulocyte percentage. As genetic modifiers, these common alleles may explain mild spherocytosis phenotypes observed in some HS allele carriers. Further, we identify an association between spleen iron and MS4A7, which colocalizes with a quantitative trait locus for MS4A7 alternative splicing in whole blood, and with monocyte count and fraction. Through quantification of spleen iron in a large human cohort, we extend our understanding of epidemiological and genetic factors associated with iron recycling and erythrocyte morphology.


2018 ◽  
Vol 77 (4) ◽  
pp. 620-623 ◽  
Author(s):  
Elisabetta Casalone ◽  
Ioanna Tachmazidou ◽  
Eleni Zengini ◽  
Konstantinos Hatzikotoulas ◽  
Sophie Hackinger ◽  
...  

ObjectivesOsteoarthritis (OA) is a complex disease, but its genetic aetiology remains poorly characterised. To identify novel susceptibility loci for OA, we carried out a genome-wide association study (GWAS) in individuals from the largest UK-based OA collections to date.MethodsWe carried out a discovery GWAS in 5414 OA individuals with knee and/or hip total joint replacement (TJR) and 9939 population-based controls. We followed-up prioritised variants in OA subjects from the interim release of the UK Biobank resource (up to 12 658 cases and 50 898 controls) and our lead finding in operated OA subjects from the full release of UK Biobank (17 894 cases and 89 470 controls). We investigated its functional implications in methylation, gene expression and proteomics data in primary chondrocytes from 12 pairs of intact and degraded cartilage samples from patients undergoing TJR.ResultsWe detect a genome-wide significant association at rs10116772 with TJR (P=3.7×10−8; for allele A: OR (95% CI) 0.97 (0.96 to 0.98)), an intronic variant in GLIS3, which is expressed in cartilage. Variants in strong correlation with rs10116772 have been associated with elevated plasma glucose levels and diabetes.ConclusionsWe identify a novel susceptibility locus for OA that has been previously implicated in diabetes and glycaemic traits.


Author(s):  
Minakshi Bhardwaj

AbstractScientists are making attempts to develop a detailed understanding of the heritable variation in the human genome at individual and population level. It is claimed that population based genomics research will be crucial in understanding the differences in the human susceptibility to diseases, drug responses and the complex interaction of genetic and environmental factors in the production of particular phenotypes (DoH white paper 2003). These efforts led to the phenomenon of biobanking and setting up mega- genetic databases. Since the development of the Icelandic Health Sector Database, the biobanking phenomenon is taking up pace and several countries of the world are starting several large-scale population based genomics projects under the umbrella of biobanking and genetic databases. At the time of an increased interest in acquiring information on gene-gene interactions and gene-environmental interactions, it is important to acknowledge that although promising, these prospects face major scientific hurdles and ethical questions in practice. The definitions, applications and prospective implications of genetic databases and biobanks on health and healthcare are understood and implied in several ways both in clinical and biological research. The term genetic database can imply to a collection of biological material (biobank) from which genetic information, for example genealogical and clinical information can be derived, systematically organized and used for research purposes. Different countries have used different terminologies for their collections of biological materials and have organised genetic information in large databases. Sometimes the term biobank also includes a complex network of databases assembled and accredited in one system. COGENE, the ‘Coordination of Genome Research Across Europe’ refers to biobanks as cohort studies. Cohort studies involve comparative studies between a diseased group with some common parameters such as geography, age, employment, a disease condition or any other determinant within a general group. The groups are compared for a long period of time for specific tests. For instance, the unified database of the Latvian Population is popularly called the Latvian Genome Project. The Latvian Project aims to create ‘a unified national network of genetic information and data processing, to collect representative amount of genetic material for genotyping of the Latvian population and to compare genomic data with the clinical information and the information available about specific pedigrees’ (Pirags and Grens 2005). Genomic data will contain the sum-total of genetic information in the entire DNA of the Latvian population. Other examples are the UK population-based genetic database, which has started under the name of the UK Biobank. It involves systematic collections of biological samples and medical and genetic information. The Estonian Genome Project uses the concept of Gene bank to refer to its genetic database. Gene banks and genomic banks are similar in that they contain large sets of genetic information in the form of datasets and sequences of the population.


2020 ◽  
Author(s):  
Quanli Wang ◽  
Ryan S. Dhindsa ◽  
Keren Carss ◽  
Andrew R Harper ◽  
Abhishek Nag ◽  
...  

The UK Biobank (UKB) represents an unprecedented population-based study of 502,543 participants with detailed phenotypic data and linkage to medical records. While the release of genotyping array data for this cohort has bolstered genomic discovery for common variants, the contribution of rare variants to this broad phenotype collection remains relatively unknown. Here, we use exome sequencing data from 177,882 UKB participants to evaluate the association between rare protein-coding variants with 10,533 binary and 1,419 quantitative phenotypes. We performed both a variant-level phenome-wide association study (PheWAS) and a gene-level collapsing analysis-based PheWAS tailored to detecting the aggregate contribution of rare variants. The latter revealed 911 statistically significant gene-phenotype relationships, with a median odds ratio of 15.7 for binary traits. Among the binary trait associations identified using collapsing analysis, 83% were undetectable using single variant association tests, emphasizing the power of collapsing analysis to detect signal in the setting of high allelic heterogeneity. As a whole, these genotype-phenotype associations were significantly enriched for loss-of-function mediated traits and currently approved drug targets. Using these results, we summarise the contribution of rare variants to common diseases in the context of the UKB phenome and provide an example of how novel gene-phenotype associations can aid in therapeutic target prioritisation.


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