New role of fat-free mass in cancer risk linked with genetic predisposition.

Cancer risk is associated with the widely debated measure body mass index (BMI). Fat mass and fat-free mass measurements from bioelectrical impedance may further clarify this association. The UK Biobank is a rare resource in which bioelectrical impedance and BMI data was collected on ~ 500,000 individuals. Using this dataset, a comprehensive analysis using regression, principal component and genome-wide genetic association, provided multiple levels of evidence that increasing whole body fat (WBFM) and fat-free mass (WBFFM) are both associated with increased post-menopausal breast cancer risk, and colorectal cancer risk in men. WBFM was inversely associated with prostate cancer. We also identified rs615029[T] and rs1485995[G] as associated in independent analyses with both PMBC (p = 1.56E-17 and 1.78E-11) and WBFFM (p = 2.88E-08 and 8.24E-12), highlighting splice variants of the intriguing long non-coding RNA CUPID1 (LINC01488) as a potential link between PMBC risk and fat-free mass.

Prospective study design and data analysis in UK Biobank.

Population-based prospective studies, such as UK Biobank, are valuable for generating and testing hypotheses about the potential causes of human disease. We describe how UK Biobank's study design, data access policies, and approaches to statistical analysis can help to minimize error and improve the interpretability of research findings, with implications for other population-based prospective studies being established worldwide.

Assessing the importance of primary care diagnoses in the UK Biobank.

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.

Association between metabolic syndrome and risk of incident dementia in UK Biobank.

INTRODUCTION: The association between metabolic syndrome (MetS) and incident dementia remains inconclusive. METHODS: In 176,249 dementia-free UK Biobank participants aged ≥60 years at baseline, Cox proportional-hazards models were used to investigate the association between MetS and incident dementia. MetS was defined as the presence of ≥3 of the following: elevated waist circumference, triglycerides, blood pressure, blood glucose, and reduced high-density lipoprotein cholesterol. RESULTS: Over 15 years of follow-up (median = 12.3), 5255 participants developed dementia. MetS was associated with an increased risk of incident dementia (hazard ratio [HR]: 1.12, 95% confidence interval [CI]: 1.06, 1.18). The association remained consistent when restricting to longer follow-up intervals: >5 to 10 years (HR: 1.17, 95% CI: 1.07, 1.27) and >10 years (HR: 1.22, 95% CI: 1.12, 1.32). Stronger associations were observed in those with ≥4 MetS components and in apolipoprotein-E (APOE)-ε4 non-carriers. DISCUSSION: In this large population-based prospective cohort, MetS was associated with an increased risk of dementia. HIGHLIGHTS: MetS was associated with a 12% increased risk of incident all-cause dementia. Associations remained similar after restricting the analysis to those with longer follow-up. The presence of four or five MetS components was significantly associated with dementia. Stronger associations were observed in those with a low genetic risk for dementia.

Use of Sex-Specific Body Mass Index to Optimize Low Correlation With Height and High Correlation With Fatness: A UK Biobank Study.

Body mass index (BMI; weight (kg)/height (m)2) is commonly used to measure general adiposity. However, evidence of its appropriateness for males and females remains inconsistent. We aimed to identify the most appropriate sex-specific power value that height should be raised to in the formula and the value that would make it achieve height independency and body fatness dependency. We randomly assigned UK Biobank participants recruited in the United Kingdom between 2006 and 2010 (n = 489,873; mean age = 56.5 years; 94.2% White) to training and testing sets (80%:20%). Using height raised to the power of -50.00 to 50.00, we identified the optimal power value that either minimized correlation with height or maximized correlation with body fat percentage, using age-adjusted correlations. The optimal power values for height were 1.77 for males and 1.39 for females. The new formulas resulted in 4.5% of females and 2.4% of males being reclassified into a different BMI category. The formulas did not show significant improvement (in terms of area under the receiver operating characteristic curve, sensitivity, and specificity) in identifying individuals with excessive body fat percentage or in predicting risk of all-cause mortality. Therefore, the conventional BMI formula is still valuable in research and disease screening for both sexes.

Persistence of SARS-CoV-2 antibodies over 18 months following infection: UK Biobank COVID-19 Serology Study.

BACKGROUND: Little is known about the persistence of antibodies after the first year following SARS-CoV-2 infection. We aimed to determine the proportion of individuals that maintain detectable levels of SARS-CoV-2 antibodies over an 18-month period following infection. METHODS: Population-based prospective study of 20 000 UK Biobank participants and their adult relatives recruited in May 2020. The proportion of SARS-CoV-2 cases testing positive for immunoglobulin G (IgG) antibodies against the spike protein (IgG-S), and the nucleocapsid protein (IgG-N), was calculated at varying intervals following infection. RESULTS: Overall, 20 195 participants were recruited. Their median age was 56 years (IQR 39-68), 56% were female and 88% were of white ethnicity. The proportion of SARS-CoV-2 cases with IgG-S antibodies following infection remained high (92%, 95% CI 90%-93%) at 6 months after infection. Levels of IgG-N antibodies following infection gradually decreased from 92% (95% CI 88%-95%) at 3 months to 72% (95% CI 70%-75%) at 18 months. There was no strong evidence of heterogeneity in antibody persistence by age, sex, ethnicity or socioeconomic deprivation. CONCLUSION: This study adds to the limited evidence on the long-term persistence of antibodies following SARS-CoV-2 infection, with likely implications for waning immunity following infection and the use of IgG-N in population surveys.

Central Adiposity Increases Risk of Kidney Stone Disease through Effects on Serum Calcium Concentrations.

SIGNIFICANCE STATEMENT: Kidney stone disease is a common disorder with poorly understood pathophysiology. Observational and genetic studies indicate that adiposity is associated with an increased risk of kidney stone disease. However, the relative contribution of general and central adipose depots and the mechanisms by which effects of adiposity on kidney stone disease are mediated have not been defined. Using conventional and genetic epidemiological techniques, we demonstrate that general and central adiposity are independently associated with kidney stone disease. In addition, one mechanism by which central adiposity increases risk of kidney stone disease is by increasing serum calcium concentration. Therapies targeting adipose depots may affect calcium homeostasis and help to prevent kidney stone disease. BACKGROUND: Kidney stone disease affects approximately 10% of individuals in their lifetime and is frequently recurrent. The disease is linked to obesity, but the mechanisms mediating this association are uncertain. METHODS: Associations of adiposity and incident kidney stone disease were assessed in the UK Biobank over a mean of 11.6 years/person. Genome-wide association studies and Mendelian randomization (MR) analyses were undertaken in the UK Biobank, FinnGen, and in meta-analyzed cohorts to identify factors that affect kidney stone disease risk. RESULTS: Observational analyses on UK Biobank data demonstrated that increasing central and general adiposity is independently associated with incident kidney stone formation. Multivariable MR, using meta-analyzed UK Biobank and FinnGen data, established that risk of kidney stone disease increases by approximately 21% per one standard deviation increase in body mass index (BMI, a marker of general adiposity) independent of waist-to-hip ratio (WHR, a marker of central adiposity) and approximately 24% per one standard deviation increase of WHR independent of BMI. Genetic analyses indicate that higher WHR, but not higher BMI, increases risk of kidney stone disease by elevating adjusted serum calcium concentrations (ß=0.12 mmol/L); WHR mediates 12%-15% of its effect on kidney stone risk in this way. CONCLUSIONS: Our study indicates that visceral adipose depots elevate serum calcium concentrations, resulting in increased risk of kidney stone disease. These findings highlight the importance of weight loss in individuals with recurrent kidney stones and suggest that therapies targeting adipose depots may affect calcium homeostasis and contribute to prevention of kidney stone disease.

Genetically Predicted Vegetable Intake and Cardiovascular Diseases and Risk Factors: An Investigation with Mendelian Randomization.

BACKGROUND: The associations between vegetable intake and cardiovascular diseases have been demonstrated in observational studies, but less sufficiently in randomized trials. Mendelian randomization has been considered a promising alternative in causal inference. The separate effects of cooked and raw vegetable intake remain unclear. This study aimed to investigate the associations between cooked and raw vegetable intake with cardiovascular outcomes using MR. METHODS: We identified 15 and 28 genetic variants statistically and biologically associated with cooked and raw vegetable intake, respectively, from previous genome-wide association studies, which were used as instrumental variables to estimate associations with coronary heart disease (CHD), stroke, heart failure (HF), and atrial fibrillation (AF). The independent effects of genetically predicted cooked and raw vegetable intake were examined using multivariable MR analysis. We performed one-sample and two-sample MR analyses and combined their results using meta-analysis. Bonferroni correction was applied for multiple comparisons. We performed two-sample MR analysis for cardiometabolic risk factors (serum lipids, blood pressure, body mass index, and glycemic traits) to explore the potential mechanisms. RESULTS: In the MR meta-analysis of 1.2 million participants, we found null evidence for associations between genetically predicted cooked and raw vegetable intake with CHD, HF, or AF. Raw vegetable intake was nominally associated with stroke (odds ratio [95% confidence interval] 0.82 [0.69-0.98] per 1 daily serving increase, p = 0.03), but this association did not pass the corrected significance level. We found consistently null evidence for associations with serum lipids, blood pressure, body mass index, or glycemic traits. CONCLUSIONS: We found null evidence for associations between genetically predicted vegetable intake with CHD, AF, HF, or cardiometabolic risk factors in this MR study. Raw vegetable intake may reduce risk of stroke, but this warrants more research. True associations between vegetable intake and CVDs cannot be completely ruled out, and future investigations are required for causal inference in nutritional research.

Demonstrating paths for unlocking the value of cloud genomics through cross cohort analysis.

Recently, large scale genomic projects such as All of Us and the UK Biobank have introduced a new research paradigm where data are stored centrally in cloud-based Trusted Research Environments (TREs). To characterize the advantages and drawbacks of different TRE attributes in facilitating cross-cohort analysis, we conduct a Genome-Wide Association Study of standard lipid measures using two approaches: meta-analysis and pooled analysis. Comparison of full summary data from both approaches with an external study shows strong correlation of known loci with lipid levels (R2 ~ 83-97%). Importantly, 90 variants meet the significance threshold only in the meta-analysis and 64 variants are significant only in pooled analysis, with approximately 20% of variants in each of those groups being most prevalent in non-European, non-Asian ancestry individuals. These findings have important implications, as technical and policy choices lead to cross-cohort analyses generating similar, but not identical results, particularly for non-European ancestral populations.

Social determinants of ethnic disparities in SARS-CoV-2 infection: UK Biobank SARS-CoV-2 Serology Study.

BACKGROUND: The social determinants of ethnic disparities in risk of SARS-CoV-2 infection during the first wave of the pandemic in the UK remain unclear. METHODS: In May 2020, a total of 20 195 adults were recruited from the general population into the UK Biobank SARS-CoV-2 Serology Study. Between mid-May and mid-November 2020, participants provided monthly blood samples. At the end of the study, participants completed a questionnaire on social factors during different periods of the pandemic. Logistic regression yielded ORs for the association between ethnicity and SARS-CoV-2 immunoglobulin G antibodies (indicating prior infection) using blood samples collected in July 2020, immediately after the first wave. RESULTS: After exclusions, 14 571 participants (mean age 56; 58% women) returned a blood sample in July, of whom 997 (7%) had SARS-CoV-2 antibodies. Seropositivity was strongly related to ethnicity: compared with those of White ethnicity, ORs (adjusted for age and sex) for Black, South Asian, Chinese, Mixed and Other ethnic groups were 2.66 (95% CI 1.94-3.60), 1.66 (1.15-2.34), 0.99 (0.42-1.99), 1.42 (1.03-1.91) and 1.79 (1.27-2.47), respectively. Additional adjustment for social factors reduced the overall likelihood ratio statistics for ethnicity by two-thirds (67%; mostly from occupational factors and UK region of residence); more precise measurement of social factors may have further reduced the association. CONCLUSIONS: This study identifies social factors that are likely to account for much of the ethnic disparities in SARS-CoV-2 infection during the first wave in the UK, and highlights the particular relevance of occupation and residential region in the pathway between ethnicity and SARS-CoV-2 infection.

Multi-morbidity and its association with common cancer diagnoses: a UK Biobank prospective study.

BACKGROUND: Whilst multi-morbidity is known to be a concern in people with cancer, very little is known about the risk of cancer in multi-morbid patients. This study aims to investigate the risk of being diagnosed with lung, colorectal, breast and prostate cancer associated with multi-morbidity. METHODS: We investigated the association between multi-morbidity and subsequent risk of cancer diagnosis in UK Biobank. Cox models were used to estimate the relative risks of each cancer of interest in multi-morbid participants, using the Cambridge Multimorbidity Score. The extent to which reverse causation, residual confounding and ascertainment bias may have impacted on the findings was robustly investigated. RESULTS: Of the 436,990 participants included in the study who were cancer-free at baseline, 21.6% (99,965) were multi-morbid (≥ 2 diseases). Over a median follow-up time of 10.9 [IQR 10.0-11.7] years, 9,019 prostate, 7,994 breast, 5,241 colorectal, and 3,591 lung cancers were diagnosed. After exclusion of the first year of follow-up, there was no clear association between multi-morbidity and risk of colorectal, prostate or breast cancer diagnosis. Those with ≥ 4 diseases at recruitment had double the risk of a subsequent lung cancer diagnosis compared to those with no diseases (HR 2.00 [95% CI 1.70-2.35] p for trend < 0.001). These findings were robust to sensitivity analyses aimed at reducing the impact of reverse causation, residual confounding from known cancer risk factors and ascertainment bias. CONCLUSIONS: Individuals with multi-morbidity are at an increased risk of lung cancer diagnosis. While this association did not appear to be due to common sources of bias in observational studies, further research is needed to understand what underlies this association.

Cohort profile: rationale and methods of UK Biobank repeat imaging study eye measures to study dementia.

PURPOSE: The retina provides biomarkers of neuronal and vascular health that offer promising insights into cognitive ageing, mild cognitive impairment and dementia. This article described the rationale and methodology of eye and vision assessments with the aim of supporting the study of dementia in the UK Biobank Repeat Imaging study. PARTICIPANTS: UK Biobank is a large-scale, multicentre, prospective cohort containing in-depth genetic, lifestyle, environmental and health information from half a million participants aged 40-69 enrolled in 2006-2010 across the UK. A subset (up to 60 000 participants) of the cohort will be invited to the UK Biobank Repeat Imaging Study to collect repeated brain, cardiac and abdominal MRI scans, whole-body dual-energy X-ray absorptiometry, carotid ultrasound, as well as retinal optical coherence tomography (OCT) and colour fundus photographs. FINDINGS TO DATE: UK Biobank has helped make significant advances in understanding risk factors for many common diseases, including for dementia and cognitive decline. Ophthalmic genetic and epidemiology studies have also benefited from the unparalleled combination of very large numbers of participants, deep phenotyping and longitudinal follow-up of the cohort, with comprehensive health data linkage to disease outcomes. In addition, we have used UK Biobank data to describe the relationship between retinal structures, cognitive function and brain MRI-derived phenotypes. FUTURE PLANS: The collection of eye-related data (eg, OCT), as part of the UK Biobank Repeat Imaging study, will take place in 2022-2028. The depth and breadth and longitudinal nature of this dataset, coupled with its open-access policy, will create a major new resource for dementia diagnostic discovery and to better understand its association with comorbid diseases. In addition, the broad and diverse data available in this study will support research into ophthalmic diseases and various other health outcomes beyond dementia.

Association between coeliac disease and cardiovascular disease: prospective analysis of UK Biobank data.

Objectives: To investigate whether people with coeliac disease are at increased risk of cardiovascular disease, including ischaemic heart disease, myocardial infarction, and stroke. Design: Prospective analysis of a large cohort study. Setting: UK Biobank database. Participants: 469 095 adults, of which 2083 had coeliac disease, aged 40-69 years from England, Scotland, and Wales between 2006 and 2010 without cardiovascular disease at baseline. Main outcome measure: A composite primary outcome was relative risk of cardiovascular disease, ischaemic heart disease, myocardial infarction, and stroke in people with coeliac disease compared with people who do not have coeliac disease, assessed using Cox proportional hazard models. Results: 40 687 incident cardiovascular disease events occurred over a median follow-up of 12.4 years (interquartile range 11.5-13.1), with 218 events among people with coeliac disease. Participants with coeliac disease were more likely to have a lower body mass index and systolic blood pressure, less likely to smoke, and more likely to have an ideal cardiovascular risk score than people who do not have coeliac disease. Despite this, participants with coeliac disease had an incidence rate of 9.0 cardiovascular disease cases per 1000 person years (95% confidence interval 7.9 to 10.3) compared with 7.4 per 1000 person years (7.3 to 7.4) in people with no coeliac disease. Coeliac disease was associated with an increased risk of cardiovascular disease (hazard ratio 1.27 (95% confidence interval 1.11 to 1.45)), which was not influenced by adjusting for lifestyle factors (1.27 (1.11 to 1.45)), but was strengthened by further adjusting for other cardiovascular risk factors (1.44 (1.26 to 1.65)). Similar associations were identified for ischaemic heart disease and myocardial infarction but fewer stroke events were reported and no evidence of an association between coeliac disease and risk of stroke. Conclusions: Individuals with coeliac disease had a lower prevalence of traditional cardiovascular risk factors but had a higher risk of developing cardiovascular disease than did people with no coeliac disease. Cardiovascular risk scores used in clinical practice might therefore not adequately capture the excess risk of cardiovascular disease in people with coeliac disease, and clinicians should be aware of the need to optimise cardiovascular health in this population.

Laboratory diagnosed microbial infection in English UK Biobank participants in comparison to the general population.

Understanding the genetic and environmental risk factors for serious bacterial infections in ageing populations remains incomplete. Utilising the UK Biobank (UKB), a prospective cohort study of 500,000 adults aged 40-69 years at recruitment (2006-2010), can help address this. Partial implementation of such a system helped groups around the world make rapid progress understanding risk factors for SARS-CoV-2 infection and COVID-19, with insights appearing as early as May 2020. In principle, such approaches could also to be used for bacterial isolations. Here we report feasibility testing of linking an England-wide dataset of microbial reporting to UKB participants, to enable characterisation of microbial infections within the UKB Cohort. These records pertain mainly to bacterial isolations; SARS-CoV-2 isolations were not included. Microbiological infections occurring in patients in England, as recorded in the Public Health England second generation surveillance system (SGSS), were linked to UKB participants using pseudonymised identifiers. By January 2015, ascertainment of laboratory reports from UKB participants by SGSS was estimated at 98%. 4.5% of English UKB participants had a positive microbiological isolate in 2015. Half of UKB isolates came from 12 laboratories, and 70% from 21 laboratories. Incidence rate ratios for microbial isolation, which is indicative of serious infection, from the UKB cohort relative to the comparably aged general population ranged from 0.6 to 1, compatible with the previously described healthy participant bias in UKB. Data on microbial isolations can be linked to UKB participants from January 2015 onwards. This linked data would offer new opportunities for research into the role of bacterial agents on health and disease in middle to-old age.

UK Biobank: a globally important resource for cancer research.

UK Biobank is a large-scale prospective study with deep phenotyping and genomic data. Its open-access policy allows researchers worldwide, from academia or industry, to perform health research in the public interest. Between 2006 and 2010, the study recruited 502,000 adults aged 40-69 years from the general population of the United Kingdom. At enrolment, participants provided information on a wide range of factors, physical measurements were taken, and biological samples (blood, urine and saliva) were collected for long-term storage. Participants have now been followed up for over a decade with more than 52,000 incident cancer cases recorded. The study continues to be enhanced with repeat assessments, web-based questionnaires, multi-modal imaging, and conversion of the stored biological samples to genomic and other '-omic' data. The study has already demonstrated its value in enabling research into the determinants of cancer, and future planned enhancements will make the resource even more valuable to cancer researchers. Over 26,000 researchers worldwide are currently using the data, performing a wide range of cancer research. UK Biobank is uniquely placed to transform our understanding of the causes of cancer development and progression, and drive improvements in cancer treatment and prevention over the coming decades.

UK biobank: Enhanced assessment of the epidemiology and long-term impact of coronavirus disease-2019.

UK Biobank is an intensively characterised prospective cohort of 500,000 adults aged 40-69 years when recruited between 2006 and 2010. The study was established to enable researchers worldwide to undertake health-related research in the public interest. The existence of such a large, detailed prospective cohort with a high degree of participant engagement enabled its rapid repurposing for coronavirus disease-2019 (COVID-19) research. In response to the pandemic, the frequency of updates on hospitalisations and deaths among participants was immediately increased, and new data linkages were established to national severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) testing and primary care health records to facilitate research into the determinants of severe COVID-19. UK Biobank also instigated several sub-studies on COVID-19. In 2020, monthly blood samples were collected from approximately 20,000 individuals to investigate the distribution and determinants of SARS-CoV-2 infection, and to assess the persistence of antibodies following infection with another blood sample collected after 12 months. UK Biobank also performed repeat imaging of approximately 2,000 participants (half of whom had evidence of previous SARS-CoV-2 infection and half did not) to investigate the impact of the virus on changes in measures of internal organ structure and function. In addition, approximately 200,000 UK Biobank participants took part in a self-test SARS-CoV-2 antibody sub-study (between February and November 2021) to collect objective data on previous SARS-CoV-2 infection. These studies are enabling unique research into the genetic, lifestyle and environmental determinants of SARS-CoV-2 infection and severe COVID-19, as well as their long-term health effects. UK Biobank's contribution to the national and international response to the pandemic represents a case study for its broader value, now and in the future, to precision medicine research.

Cigarette Smoking and Endometrial Cancer Risk: Observational and Mendelian Randomization Analyses.

BACKGROUND: Current epidemiologic evidence indicates that smoking is associated with a lower endometrial cancer risk. However, it is unknown if this association is causal or confounded. To further elucidate the role of smoking in endometrial cancer risk, we conducted complementary observational and Mendelian randomization (MR) analyses. METHODS: The observational analyses included 286,415 participants enrolled in the European Prospective Investigation into Cancer and Nutrition and 179,271 participants in the UK Biobank, and multivariable Cox proportional hazards models were used. In two-sample MR analyses, genetic variants robustly associated with lifetime amount of smoking (n = 126 variants) and ever having smoked regularly (n = 112 variants) were selected and their association with endometrial cancer risk (12,906 cancer/108,979 controls from the Endometrial Cancer Association Consortium) was examined. RESULTS: In the observational analysis, lifetime amount of smoking and ever having smoked regularly were associated with a lower endometrial cancer risk. In the MR analysis accounting for body mass index, a genetic predisposition to a higher lifetime amount of smoking was not associated with endometrial cancer risk (OR per 1-SD increment: 1.15; 95% confidence interval: 0.91-1.44). Genetic predisposition to ever having smoked regularly was not associated with risk of endometrial cancer. CONCLUSIONS: Smoking was inversely associated with endometrial cancer in the observational analyses, although unsupported by the MR. Additional studies are required to better understand the possible confounders and mechanisms underlying the observed associations between smoking and endometrial cancer. IMPACT: The results from this analysis indicate that smoking is unlikely to be causally linked with endometrial cancer risk.

New Horizons: the value of UK Biobank to research on endocrine and metabolic disorders.

UK Biobank is an intensively characterized prospective study of 500 000 men and women, aged 40 to 69 years when recruited, between 2006 and 2010, from the general population of the United Kingdom. Established as an open-access resource for researchers worldwide to perform health research that is in the public interest, UK Biobank has collected (and continues to collect) a vast amount of data on genetic, physiological, lifestyle, and environmental factors, with prolonged follow-up of heath conditions through linkage to administrative electronic health records. The study has already demonstrated its unique value in enabling research into the determinants of common endocrine and metabolic diseases. The importance of UK Biobank, heralded as a flagship project for UK health research, will only increase over time as the number of incident disease events accrue, and the study is enhanced with additional data from blood assays (such as whole-genome sequencing, metabolomics, and proteomics), wearable technologies (including physical activity and cardiac monitors), and body imaging (magnetic resonance imaging and dual-energy X-ray absorptiometry). This unique research resource is likely to transform our understanding of the causes, diagnosis, and treatment of many endocrine and metabolic disorders.

Sero-prevalence of 19 infectious pathogens and associated factors among middle-aged and elderly Chinese adults: a cross-sectional study.

OBJECTIVES: To systematically assess the sero-prevalence and associated factors of major infectious pathogens in China, where there are high incidence rates of certain infection-related cancers. DESIGN: Cross-sectional study. SETTING: 10 (5 urban, 5 rural) geographically diverse areas in China. PARTICIPANTS: A subcohort of 2000 participants from the China Kadoorie Biobank. PRIMARY MEASURES: Sero-prevalence of 19 pathogens using a custom-designed multiplex serology panel and associated factors. RESULTS: Of the 19 pathogens investigated, the mean number of sero-positive pathogens was 9.4 (SD 1.7), with 24.4% of participants being sero-positive for >10 pathogens. For individual pathogens, the sero-prevalence varied, being for example, 0.05% for HIV, 6.4% for human papillomavirus (HPV)-16, 53.5% for Helicobacter pylori (H. pylori) and 99.8% for Epstein-Barr virus . The sero-prevalence of human herpesviruses (HHV)-6, HHV-7 and HPV-16 was higher in women than men. Several pathogens showed a decreasing trend in sero-prevalence by birth cohort, including hepatitis B virus (HBV) (51.6% vs 38.7% in those born <1940 vs >1970), HPV-16 (11.4% vs 5.4%), HHV-2 (15.1% vs 8.1%), Chlamydia trachomatis (65.6% vs 28.8%) and Toxoplasma gondii (22.0% vs 9.0%). Across the 10 study areas, sero-prevalence varied twofold to fourfold for HBV (22.5% to 60.7%), HPV-16 (3.4% to 10.9%), H. pylori (16.2% to 71.1%) and C. trachomatis (32.5% to 66.5%). Participants with chronic liver diseases had >7-fold higher sero-positivity for HBV (OR=7.51; 95% CI 2.55 to 22.13). CONCLUSIONS: Among Chinese adults, previous and current infections with certain pathogens were common and varied by area, sex and birth cohort. These infections may contribute to the burden of certain cancers and other non-communicable chronic diseases.

Reproducible disease phenotyping at scale: Example of coronary artery disease in UK Biobank.

IMPORTANCE: A lack of internationally agreed standards for combining available data sources at scale risks inconsistent disease phenotyping limiting research reproducibility. OBJECTIVE: To develop and then evaluate if a rules-based algorithm can identify coronary artery disease (CAD) sub-phenotypes using electronic health records (EHR) and questionnaire data from UK Biobank (UKB). DESIGN: Case-control and cohort study. SETTING: Prospective cohort study of 502K individuals aged 40-69 years recruited between 2006-2010 into the UK Biobank with linked hospitalization and mortality data and genotyping. PARTICIPANTS: We included all individuals for phenotyping into 6 predefined CAD phenotypes using hospital admission and procedure codes, mortality records and baseline survey data. Of these, 408,470 unrelated individuals of European descent had a polygenic risk score (PRS) for CAD estimated. EXPOSURE: CAD Phenotypes. MAIN OUTCOMES AND MEASURES: Association with baseline risk factors, mortality (n = 14,419 over 7.8 years median f/u), and a PRS for CAD. RESULTS: The algorithm classified individuals with CAD into prevalent MI (n = 4,900); incident MI (n = 4,621), prevalent CAD without MI (n = 10,910), incident CAD without MI (n = 8,668), prevalent self-reported MI (n = 2,754); prevalent self-reported CAD without MI (n = 5,623), yielding 37,476 individuals with any type of CAD. Risk factors were similar across the six CAD phenotypes, except for fewer men in the self-reported CAD without MI group (46.7% v 70.1% for the overall group). In age- and sex- adjusted survival analyses, mortality was highest following incident MI (HR 6.66, 95% CI 6.07-7.31) and lowest for prevalent self-reported CAD without MI at baseline (HR 1.31, 95% CI 1.15-1.50) compared to disease-free controls. There were similar graded associations across the six phenotypes per SD increase in PRS, with the strongest association for prevalent MI (OR 1.50, 95% CI 1.46-1.55) and the weakest for prevalent self-reported CAD without MI (OR 1.08, 95% CI 1.05-1.12). The algorithm is available in the open phenotype HDR UK phenotype library (https://portal.caliberresearch.org/). CONCLUSIONS: An algorithmic, EHR-based approach distinguished six phenotypes of CAD with distinct survival and PRS associations, supporting adoption of open approaches to help standardize CAD phenotyping and its wider potential value for reproducible research in other conditions.