Curating a longitudinal research resource using linked primary care EHR data-a UK Biobank case study.
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ABSTRACT:
SUBMITTER: Darke P
PROVIDER: S-EPMC8800530 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Metformin is a commonly prescribed diabetes medication whose mechanism of action is poorly understood. In this study we utilized EHR-linked biobank data to elucidate the impact of genomic variation on glycemic response to metformin. Our study found significant gene- and SNP-level associations within the beta-2 subunit of the heterotrimeric adenosine monophosphate-activated protein kinase complex. Using EHR phenotypes where were able to add additional clarity to ongoing metformin pharmacogenomic dialogue.
| S-EPMC5051541 | biostudies-literature
Project description:The UK Biobank (UKB) is a health research resource of major international importance, incorporating comprehensive characterization of >500?000 men and women recruited between 2006 and 2010 from across the UK. There is prospective tracking of health outcomes for all participants through linkages with national cohorts (death registers, cancer registers, electronic hospital records, and primary care records). The dataset has been enhanced with the UKB imaging study, which aims to scan a subset of 100?000 participants. The imaging protocol includes magnetic resonance imaging of the brain, heart, and abdomen, carotid ultrasound, and whole-body dual X-ray absorptiometry. Since its launch in 2015, over 48?000 participants have completed the imaging study with scheduled completion in 2023. Repeat imaging of 10?000 participants has been approved and commenced in 2019. The cardiovascular magnetic resonance (CMR) scan provides detailed assessment of cardiac structure and function comprising bright blood anatomic assessment (sagittal, coronal, and axial), left and right ventricular cine images (long and short axes), myocardial tagging, native T1 mapping, aortic flow, and imaging of the thoracic aorta. The UKB is an open access resource available to health researchers across all scientific disciplines from both academia and industry with no preferential access or exclusivity. In this paper, we consider how we may best utilize the UKB CMR data to advance cardiovascular research and review notable achievements to date.
| S-EPMC7899275 | biostudies-literature
Project description:The UK Biobank project is a prospective cohort study with deep genetic and phenotypic data collected on approximately 500,000 individuals from across the United Kingdom, aged between 40 and 69 at recruitment. The open resource is unique in its size and scope. A rich variety of phenotypic and health-related information is available on each participant, including biological measurements, lifestyle indicators, biomarkers in blood and urine, and imaging of the body and brain. Follow-up information is provided by linking health and medical records. Genome-wide genotype data have been collected on all participants, providing many opportunities for the discovery of new genetic associations and the genetic bases of complex traits. Here we describe the centralized analysis of the genetic data, including genotype quality, properties of population structure and relatedness of the genetic data, and efficient phasing and genotype imputation that increases the number of testable variants to around 96 million. Classical allelic variation at 11 human leukocyte antigen genes was imputed, resulting in the recovery of signals with known associations between human leukocyte antigen alleles and many diseases.
| S-EPMC6786975 | biostudies-literature
Project description:ObjectivesThe UK Biobank (UKB) is making primary care electronic health records (EHRs) for 500 000 participants available for COVID-19-related research. Data are extracted from four sources, recorded using five clinical terminologies and stored in different schemas. The aims of our research were to: (a) develop a semi-supervised approach for bootstrapping EHR phenotyping algorithms in UKB EHR, and (b) to evaluate our approach by implementing and evaluating phenotypes for 31 common biomarkers.Materials and methodsWe describe an algorithmic approach to phenotyping biomarkers in primary care EHR involving (a) bootstrapping definitions using existing phenotypes, (b) excluding generic, rare, or semantically distant terms, (c) forward-mapping terminology terms, (d) expert review, and (e) data extraction. We evaluated the phenotypes by assessing the ability to reproduce known epidemiological associations with all-cause mortality using Cox proportional hazards models.ResultsWe created and evaluated phenotyping algorithms for 31 biomarkers many of which are directly related to COVID-19 complications, for example diabetes, cardiovascular disease, respiratory disease. Our algorithm identified 1651 Read v2 and Clinical Terms Version 3 terms and automatically excluded 1228 terms. Clinical review excluded 103 terms and included 44 terms, resulting in 364 terms for data extraction (sensitivity 0.89, specificity 0.92). We extracted 38 190 682 events and identified 220 978 participants with at least one biomarker measured.Discussion and conclusionBootstrapping phenotyping algorithms from similar EHR can potentially address pre-existing methodological concerns that undermine the outputs of biomarker discovery pipelines and provide research-quality phenotyping algorithms.
| S-EPMC7717266 | biostudies-literature
Project description:BackgroundMultimorbidity is an emerging public health priority. Physical activity (PA) is recommended as one of the main lifestyle behaviours, yet the benefits of PA for people with multimorbidity are unclear. We assessed the benefits of PA on mortality and life expectancy in people with and without multimorbidity.MethodsUsing the UK Biobank dataset, we extracted data on 36 chronic conditions and defined multimorbidity as (a) 2 or more conditions, (b) 2 or more conditions combined with self-reported overall health, and (c) 2 or more top-10 most common comorbidities. Leisure-time PA (LTPA) and total PA (TPA) were measured by questionnaire and categorised as low (< 600 metabolic equivalent (MET)-min/week), moderate (600 to < 3000 MET-min/week), and high (≥ 3000 MET-min/week), while objectively assessed PA was assessed by wrist-worn accelerometer and categorised as low (4 min/day), moderate (10 min/day), and high (22 min/day) walking at brisk pace. Survival models were applied to calculate adjusted hazard ratios (HRs) and predict life expectancy differences.Results491,939 individuals (96,622 with 2 or more conditions) had a median follow-up of 7.0 (IQR 6.3-7.6) years. Compared to low LTPA, for participants with multimorbidity, HR for mortality was 0.75 (95% CI 0.70-0.80) and 0.65 (0.56-0.75) in moderate and high LTPA groups, respectively. This finding was consistent when using TPA measures. Using objective PA, HRs were 0.49 (0.29-0.80) and 0.29 (0.13-0.61) in the moderate and high PA groups, respectively. These findings were similar for participants without multimorbidity. In participants with multimorbidity, at the age of 45 years, moderate and high LTPA were associated with an average of 3.12 (95% CI 2.53, 3.71) and 3.55 (2.34, 4.77) additional life years, respectively, compared to low LTPA; in participants without multimorbidity, corresponding figures were 1.95 (1.59, 2.31) and 1.85 (1.19, 2.50). Similar results were found with TPA. For objective PA, moderate and high levels were associated with 3.60 (- 0.60, 7.79) and 5.32 (- 0.47, 11.11) life years gained compared to low PA for those with multimorbidity and 3.88 (1.79, 6.00) and 4.51 (2.15, 6.88) life years gained in those without. Results were consistent when using other definitions of multimorbidity.ConclusionsThere was an inverse dose-response association between PA and mortality. A moderate exercise is associated with a longer life expectancy, also in individuals with multimorbidity.
| S-EPMC6560907 | biostudies-literature
Project description:The evidence on the association between alcohol consumption and adiposity is inconsistent and fragmented. We investigated the longitudinal association between alcohol consumption pattern and four different adiposity markers with repeated measures of adiposity and obesity incidence. We categorized current drinkers based on the sex-specific quartiles of their weekly alcohol consumption and the UK alcohol drinking guidelines. We used multivariable adjusted generalised linear models. With the exception of a direct association between alcohol volume and body fat percentage (BF%) in women (B = 0.42%; 95%CI: 0.04, 0.80% for women in the top quartile), we found no associations between alcohol consumption and adiposity markers for either sex. Red wine and champagne/white wine consumption were inversely associated with waist circumference (WC) for both sexes (B = -0.58 cm, 95%CI: -0.77, -0.38 cm and B= -0.49 cm, 95%CI: -0.68, -0.29 cm, respectively, for women; B = -0.28 cm, 95%CI: -0.47, -0.08 cm and B = -0.23 cm, 95%CI: -0.42, -0.04 cm, respectively, for men). Female and male spirit drinkers had higher WC than non-spirit drinkers. Alcohol consumption was associated with a lower risk of obesity incidence in women (OR:0.60, 95%CI:0.45, 0.80 for the 2nd quartile, OR:0.53, 95%CI: 0.40, 0.70 for the 3rd quartile and OR:0.61, 95%CI:0.46, 0.80 for the 4th quartile). We found limited evidence of longitudinal associations between alcohol intake and adiposity. The few statistically significant associations we observed are unlikely to be of clinical importance.
| S-EPMC9565835 | biostudies-literature
Project description:BackgroundThe UK Biobank is a large prospective cohort, based in the UK, that has deep phenotypic and genomic data on roughly a half a million individuals. Included in this resource are data on approximately 78,000 individuals with "non-white British ancestry." While most epidemiology studies have focused predominantly on populations of European ancestry, there is an opportunity to contribute to the study of health and disease for a broader segment of the population by making use of the UK Biobank's "non-white British ancestry" samples. Here, we present an empirical description of the continental ancestry and population structure among the individuals in this UK Biobank subset.ResultsReference populations from the 1000 Genomes Project for Africa, Europe, East Asia, and South Asia were used to estimate ancestry for each individual. Those with at least 80% ancestry in one of these four continental ancestry groups were taken forward (N = 62,484). Principal component and K-means clustering analyses were used to identify and characterize population structure within each ancestry group. Of the approximately 78,000 individuals in the UK Biobank that are of "non-white British" ancestry, 50,685, 6653, 2782, and 2364 individuals were associated to the European, African, South Asian, and East Asian continental ancestry groups, respectively. Each continental ancestry group exhibits prominent population structure that is consistent with self-reported country of birth data and geography.ConclusionsMethods outlined here provide an avenue to leverage UK Biobank's deeply phenotyped data allowing researchers to maximize its potential in the study of health and disease in individuals of non-white British ancestry.
| S-EPMC8800339 | biostudies-literature
Project description:The UK Biobank has made general practitioner (GP) data (censoring date 2016-2017) available for approximately 45% of the cohort, whilst hospital inpatient and death registry (referred to as "HES/Death") data are available cohort-wide through 2018-2022 depending on whether the data comes from England, Wales or Scotland. We assessed the importance of case ascertainment via different data sources in UKB for three diseases that are usually first diagnosed in primary care: Parkinson's disease (PD), type 2 diabetes (T2D), and all-cause dementia. Including GP data at least doubled the number of incident cases in the subset of the cohort with primary care data (e.g. from 619 to 1390 for dementia). Among the 786 dementia cases that were only captured in the GP data before the GP censoring date, only 421 (54%) were subsequently recorded in HES. Therefore, estimates of the absolute incidence or risk-stratified incidence are misleadingly low when based only on the HES/Death data. For incident cases present in both HES/Death and GP data during the full follow-up period (i.e. until the HES censoring date), the median time difference between an incident diagnosis of dementia being recorded in GP and HES/Death was 2.25 years (i.e. recorded 2.25 years earlier in the GP records). Similar lag periods were also observed for PD (median 2.31 years earlier) and T2D (median 2.82 years earlier). For participants with an incident GP diagnosis, only 65.6% of dementia cases, 69.0% of PD cases, and 58.5% of T2D cases had their diagnosis recorded in HES/Death within 7 years since GP diagnosis. The effect estimates (hazard ratios, HR) of established risk factors for the three health outcomes mostly remain in the same direction and with a similar strength of association when cases are ascertained either using HES only or further adding GP data. The confidence intervals of the HR became narrower when adding GP data, due to the increased statistical power from the additional cases. In conclusion, it is desirable to extend both the coverage and follow-up period of GP data to allow researchers to maximise case ascertainment of chronic health conditions in the UK.
| S-EPMC10904436 | biostudies-literature
Project description:BackgroundDespite high metastasis rates, adjuvant/neoadjuvant systemic therapy for localised soft tissue sarcoma (STS) is not used routinely. Progress requires tailoring therapy to features of tumour biology, which need exploration in well-documented cohorts. Hypoxia has been linked to metastasis in STS and is targetable. This study evaluated hypoxia prognostic markers in the phase III adjuvant radiotherapy VorteX trial.MethodsFormalin-fixed paraffin-embedded tumour biopsies, fresh tumour/normal tissue and blood were collected before radiotherapy. Immunohistochemistry for HIF-1?, CAIX and GLUT1 was performed on tissue microarrays and assessed by two scorers (one pathologist). Prognostic analysis of disease-free survival (DFS) used Kaplan-Meier and Cox regression.ResultsBiobank and outcome data were available for 203 out of 216 randomised patients. High CAIX expression was associated with worse DFS (hazard ratio 2.28, 95% confidence interval: 1.44-3.59, P<0.001). Hypoxia-inducible factor-1? and GLUT1 were not prognostic. Carbonic anhydrase IX remained prognostic in multivariable analysis.ConclusionsThe VorteX-Biobank contains tissue with linked outcome data and is an important resource for research. This study confirms hypoxia is linked to poor prognosis in STS and suggests that CAIX may be the best known marker. However, overlap between single marker positivity was poor and future work will develop an STS hypoxia gene signature to account for tumour heterogeneity.
| S-EPMC5846059 | biostudies-literature
Project description:Introduction: The foundation PATH (Patients' Tumour Bank of Hope) collects in a tumour bank samples of blood, tumour, and tumour-near normal tissue from breast cancer patients and supplements them systematically with health-care data. Material and Methods: For patients from the diagnosis years 2006-2009 quantitative data were evaluated with the help of mean values and standard deviations while for qualitative data absolute and relative incidences were assessed. Demographic and clinical features of women who used different numbers of information sources were tested for statistical significance by means of ANOVA and χ2 tests. The benchmark report of the WBC and two DMP reports were used to compare oncological care. Results: For research purposes tumour tissue samples are available for 59 % of the cases, normal tissue for 62 % and blood serum samples for 92 %. From 3573 women (diagnoses 2006-2009), a total of 2697 women (75.5 %) took part in follow-up. The characteristics of the follow-up patients did not relevantly differ from those of all the patients. The responsible physician was named as the most important source of information about the disease. Young women in particular consulted several sources and also used the internet to obtain information. Discussion: Compared with data on therapy from WBC and the DMP breast cancer in Bavaria or, respectively, North Rhineland reports, the PATH patients represent an only slightly selected sample. The PATH biobank is a (still) poorly used data and sample source, which is made available upon request and positive evaluation of the study protocol. Thus, it is possible to address current questions in a short time without having to undertake extensive recruiting procedures.
| S-EPMC4078118 | biostudies-literature