SARS-CoV-2 is associated with changes in brain structure in UK Biobank.

There is strong evidence of brain-related abnormalities in COVID-191-13. However, it remains unknown whether the impact of SARS-CoV-2 infection can be detected in milder cases, and whether this can reveal possible mechanisms contributing to brain pathology. Here we investigated brain changes in 785 participants of UK Biobank (aged 51-81 years) who were imaged twice using magnetic resonance imaging, including 401 cases who tested positive for infection with SARS-CoV-2 between their two scans-with 141 days on average separating their diagnosis and the second scan-as well as 384 controls. The availability of pre-infection imaging data reduces the likelihood of pre-existing risk factors being misinterpreted as disease effects. We identified significant longitudinal effects when comparing the two groups, including (1) a greater reduction in grey matter thickness and tissue contrast in the orbitofrontal cortex and parahippocampal gyrus; (2) greater changes in markers of tissue damage in regions that are functionally connected to the primary olfactory cortex; and (3) a greater reduction in global brain size in the SARS-CoV-2 cases. The participants who were infected with SARS-CoV-2 also showed on average a greater cognitive decline between the two time points. Importantly, these imaging and cognitive longitudinal effects were still observed after excluding the 15 patients who had been hospitalised. These mainly limbic brain imaging results may be the in vivo hallmarks of a degenerative spread of the disease through olfactory pathways, of neuroinflammatory events, or of the loss of sensory input due to anosmia. Whether this deleterious effect can be partially reversed, or whether these effects will persist in the long term, remains to be investigated with additional follow-up.

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.

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.

The UK Biobank resource with deep phenotyping and genomic data.

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.

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.

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.

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.

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.

Human Cytomegalovirus and Risk of Incident Cardiovascular Disease in United Kingdom Biobank.

BACKGROUND: Previous studies have yielded conflicting results on the association between human cytomegalovirus (HCMV) and cardiovascular disease (CVD). This study examined associations between HCMV and incident CVD, ischaemic heart disease (IHD) and stroke. METHODS: This study included 8531 women and men of predominantly white ethnic background, aged 40-69 without prevalent CVD from the population-based UK Biobank study, recruited between 2006-2010 with HCMV antibody levels measured. CVD was ascertained via linkage to health administrative records collected until 2020. Multivariate Cox proportional-hazards models were used to determine associations between HCMV seropositivity and incident CVD, IHD and stroke. HCMV seropositive antibody levels in tertiles were used to assess dose-response associations. RESULTS: Over a mean follow-up period of 10.2 years, HCMV seropositivity was not significantly associated with CVD (Cases = 626, Hazard Ratio [HR] =1.01, 95% confidence interval [CI], .86-1.20), IHD (Cases = 539, HR=1.03, 95% CI, .87-1.24) or stroke (Cases = 144, HR = 0.96, 95% CI, .68-1.36). There was no evidence of dose-response associations with any outcome. CONCLUSIONS: We found no significant association between HCMV seropositivity and risk of CVD, IHD or stroke. Further research within understudied populations, such as those of non-white ethnicity, and CVD subtypes is warranted.

Circulating insulin-like growth factor-I and risk of 25 common conditions: outcome-wide analyses in the UK Biobank study.

While there is strong epidemiological evidence that circulating insulin-like growth factor-I (IGF-I) is associated with a higher risk of several cancers, little is known about its association with non-cancer outcomes. We investigated associations of circulating IGF-I with risk of 25 common conditions, other than cancer, in a large British cohort. Study participants were 318,749 middle-aged adults enrolled in the UK Biobank Study. Serum IGF-I concentration was measured in samples collected at baseline (2006-2010), and re-measured in 12,334 participants after an average of 4.3 years. We followed-up participants over an average of 11.5 years by linking to hospital admissions and mortality registries. Multivariable-adjusted Cox regressions estimated hazard ratios (HRs) and 95% confidence intervals (CIs) for associations between circulating IGF-I and 25 common conditions, using the repeated IGF-I measurements to correct for regression dilution bias. After correction for multiple testing (P < 0.002), IGF-I was positively associated with carpal tunnel syndrome (HR per 5 nmol/l higher concentration = 1.12, 95% CI 1.08-1.16), and inversely associated with varicose veins (0.90, 0.85-0.95), cataracts (0.97, 0.95-0.99), diabetes (0.92, 0.90-0.95), and iron deficiency anaemia (0.90, 0.86-0.93). The associations for cataracts and diabetes attenuated when restricted to cases diagnosed after five or more years of follow-up, suggesting that these associations were likely affected by reverse causality. Higher IGF-I concentration might be associated with the risk for several conditions, but genetic studies are needed to clarify which associations may be causal.

Metabolic syndrome biomarkers and prostate cancer risk in the UK Biobank.

We investigated the association between metabolic syndrome (MetS) and its components and risk of prostate cancer (PCa) in a cohort of men enrolled in the UK Biobank. Our study cohort included 220 622 PCa-free men with baseline measurements of triglycerides (TGs), HDL-cholesterol (HDL), glycated hemoglobin (HbA1c), blood pressure (BP), and waist circumference (WC). Multivariable Cox proportional hazards regression was used to analyze associations with PCa for: individual metabolic components (TG, HDL, HbA1c, BP, WC), combinations of two and three components, and MetS overall (three or more components). We conducted mediation analyses to examine potential hormonal and inflammatory pathways (total testosterone [TT], C-reactive protein [CRP], insulin-like growth factor 1 [IGF-1]) through which MetS components may influence PCa risk. A total of 5409 men in the study developed PCa during a median follow-up of 6.9 years. We found no significant association between MetS and PCa risk (hazard ratio [HR] = 0.99, 95% confidence interval [CI] = 0.92-1.06). No associations were found with PCa risk and individual measurements of TG, HDL, BP, or WC. However, an inverse association was observed with elevated HbA1c (≥42 mmol/mol) (HR = 0.89, 95% CI = 0.79-0.98). Consistent inverse associations were observed between HbA1c and risk of PCa. Mediation analysis revealed TT, CRP, and IGF-1 as potential mediating factors for this association contributing 10.2%, 7.1%, and 7.9% to the total effect, respectively. Overall MetS had no association with PCa risk. However, a consistent inverse association with PCa risk was found for HbA1c. This association may be explained in part through hormonal and inflammatory pathways.

Circulating insulin-like growth factor-I, total and free testosterone concentrations and prostate cancer risk in 200 000 men in UK Biobank.

Insulin-like growth factor-I (IGF-I) and testosterone have been implicated in prostate cancer aetiology. Using data from a large prospective full-cohort with standardised assays and repeat blood measurements, and genetic data from an international consortium, we investigated the associations of circulating IGF-I, sex hormone-binding globulin (SHBG), and total and calculated free testosterone concentrations with prostate cancer incidence and mortality. For prospective analyses, risk was estimated using multivariable-adjusted Cox regression in 199 698 male UK Biobank participants. Hazard ratios (HRs) were corrected for regression dilution bias using repeat hormone measurements from a subsample. Two-sample Mendelian randomisation (MR) analysis of IGF-I and risk used genetic instruments identified from UK Biobank men and genetic outcome data from the PRACTICAL consortium (79 148 cases and 61 106 controls). We used cis- and all (cis and trans) SNP MR approaches. A total of 5402 men were diagnosed with and 295 died from prostate cancer (mean follow-up 6.9 years). Higher circulating IGF-I was associated with elevated prostate cancer diagnosis (HR per 5 nmol/L increment = 1.09, 95% CI 1.05-1.12) and mortality (HR per 5 nmol/L increment = 1.15, 1.02-1.29). MR analyses also supported the role of IGF-I in prostate cancer diagnosis (cis-MR odds ratio per 5 nmol/L increment = 1.34, 1.07-1.68). In observational analyses, higher free testosterone was associated with a higher risk of prostate cancer (HR per 50 pmol/L increment = 1.10, 1.05-1.15). Higher SHBG was associated with a lower risk (HR per 10 nmol/L increment = 0.95, 0.94-0.97), neither was associated with prostate cancer mortality. Total testosterone was not associated with prostate cancer. These findings implicate IGF-I and free testosterone in prostate cancer development and/or progression.

Testosterone, sex hormone-binding globulin, insulin-like growth factor-1 and endometrial cancer risk: observational and Mendelian randomization analyses.

BACKGROUND: Dysregulation of endocrine pathways related to steroid and growth hormones may modify endometrial cancer risk; however, prospective data on testosterone, sex hormone-binding globulin (SHBG) and insulin-like growth factor (IGF)-1 are limited. To elucidate the role of these hormones in endometrial cancer risk we conducted complementary observational and Mendelian randomization (MR) analyses. METHODS: The observational analyses included 159,702 women (80% postmenopausal) enrolled in the UK Biobank. Hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated using Cox proportional hazards models. For MR analyses, genetic variants associated with hormone levels were identified and their association with endometrial cancer (12,906 cases/108,979 controls) was examined using two-sample MR. RESULTS: In the observational analysis, higher circulating concentrations of total (HR per unit inverse normal scale = 1.38, 95% CI = 1.22-1.57) and free testosterone (HR per unit log scale = 2.07, 95% CI = 1.66-2.58) were associated with higher endometrial cancer risk. An inverse association was found for SHBG (HR per unit inverse normal scale = 0.76, 95% CI = 0.67-0.86). Results for testosterone and SHBG were supported by the MR analyses. No association was found between genetically predicted IGF-1 concentration and endometrial cancer risk. CONCLUSIONS: Our results support probable causal associations between circulating concentrations of testosterone and SHBG with endometrial cancer risk.

Physical activity in relation to circulating hormone concentrations in 117,100 men in UK Biobank.

PURPOSE: Physical activity may reduce the risk of some types of cancer in men. Biological mechanisms may involve changes in hormone concentrations; however, this relationship is not well established. Therefore, we aimed to investigate the associations of physical activity with circulating insulin-like growth factor-I (IGF-I), sex hormone-binding globulin (SHBG, which modifies sex hormone activity), and total and free testosterone concentrations, and the extent these associations might be mediated by body mass index (BMI). METHODS: Circulating concentrations of these hormones and anthropometric measurements and self-reported physical activity data were available for 117,100 healthy male UK Biobank participants at recruitment. Objectively measured accelerometer physical activity levels were also collected on average 5.7 years after recruitment in 28,000 men. Geometric means of hormone concentrations were estimated using multivariable-adjusted analysis of variance, with and without adjustment for BMI. RESULTS: The associations between physical activity and hormones were modest and similar for objectively measured (accelerometer) and self-reported physical activity. Compared to men with the lowest objectively measured physical activity, men with high physical activity levels had 14% and 8% higher concentrations of SHBG and total testosterone, respectively, and these differences were attenuated to 6% and 3% following adjustment for BMI. CONCLUSION: Our results suggest that the associations of physical activity with the hormones investigated are, at most, modest; and following adjustment for BMI, the small associations with SHBG and total testosterone were largely attenuated. Therefore, it is unlikely that changes in these circulating hormones explain the associations of physical activity with risk of cancer either independently or via BMI.

Prospective analysis of circulating metabolites and endometrial cancer risk.

BACKGROUND: Endometrial cancer is strongly associated with obesity and dysregulation of metabolic factors such as estrogen and insulin signaling are causal risk factors for this malignancy. To identify additional novel metabolic pathways associated with endometrial cancer we performed metabolomic analyses on pre-diagnostic plasma samples from 853 case-control pairs from the European Prospective Investigation into Cancer and Nutrition (EPIC). METHODS: A total of 129 metabolites (acylcarnitines, amino acids, biogenic amines, glycerophospholipids, hexoses, and sphingolipids) were measured by liquid chromatography-mass spectrometry. Conditional logistic regression estimated the associations of metabolites with endometrial cancer risk. An analysis focusing on clusters of metabolites using the bootstrap lasso method was also employed. RESULTS: After adjustment for body mass index, sphingomyelin [SM] C18:0 was positively (OR1SD: 1.18, 95% CI: 1.05-1.33), and glycine, serine, and free carnitine (C0) were inversely (OR1SD: 0.89, 95% CI: 0.80-0.99; OR1SD: 0.89, 95% CI: 0.79-1.00 and OR1SD: 0.91, 95% CI: 0.81-1.00, respectively) associated with endometrial cancer risk. Serine, C0 and two sphingomyelins were selected by the lasso method in >90% of the bootstrap samples. The ratio of esterified to free carnitine (OR1SD: 1.14, 95% CI: 1.02-1.28) and that of short chain to free acylcarnitines (OR1SD: 1.12, 95% CI: 1.00-1.25) were positively associated with endometrial cancer risk. Further adjustment for C-peptide or other endometrial cancer risk factors only minimally altered the results. CONCLUSION: These findings suggest that variation in levels of glycine, serine, SM C18:0 and free carnitine may represent specific pathways linked to endometrial cancer development. If causal, these pathways may offer novel targets for endometrial cancer prevention.

Developing automated methods for disease subtyping in UK Biobank: an exemplar study on stroke.

BACKGROUND: Better phenotyping of routinely collected coded data would be useful for research and health improvement. For example, the precision of coded data for hemorrhagic stroke (intracerebral hemorrhage [ICH] and subarachnoid hemorrhage [SAH]) may be as poor as < 50%. This work aimed to investigate the feasibility and added value of automated methods applied to clinical radiology reports to improve stroke subtyping. METHODS: From a sub-population of 17,249 Scottish UK Biobank participants, we ascertained those with an incident stroke code in hospital, death record or primary care administrative data by September 2015, and ≥ 1 clinical brain scan report. We used a combination of natural language processing and clinical knowledge inference on brain scan reports to assign a stroke subtype (ischemic vs ICH vs SAH) for each participant and assessed performance by precision and recall at entity and patient levels. RESULTS: Of 225 participants with an incident stroke code, 207 had a relevant brain scan report and were included in this study. Entity level precision and recall ranged from 78 to 100%. Automated methods showed precision and recall at patient level that were very good for ICH (both 89%), good for SAH (both 82%), but, as expected, lower for ischemic stroke (73%, and 64%, respectively), suggesting coded data remains the preferred method for identifying the latter stroke subtype. CONCLUSIONS: Our automated method applied to radiology reports provides a feasible, scalable and accurate solution to improve disease subtyping when used in conjunction with administrative coded health data. Future research should validate these findings in a different population setting.

Body size, body composition and endometrial cancer risk among postmenopausal women in UK Biobank.

Previous studies on the association of adiposity with endometrial cancer risk have mostly used body mass index (BMI) as the main exposure of interest. Whether more precise measures of body fat, such as body fat percentage and fat mass estimated by bioimpedance analyses, are better indicators of risk than BMI is unknown. The role of central adiposity and fat-free mass in endometrial cancer development remains unclear. We used Cox regression models to estimate hazard ratios (HR) and corresponding 95% confidence intervals (CI) for the associations of various measures of body size/composition with the risk of endometrial cancer among 135 110 postmenopausal women enrolled in UK Biobank. During a mean follow up of 6.8 years, 706 endometrial cancers were diagnosed, with a mean age at diagnosis of 65.5 years. The HRs (95% CIs) for endometrial cancer per 1 SD increase in BMI, body fat percentage and fat mass were broadly comparable, being 1.71 (1.61-1.82), 1.92 (1.75-2.11) and 1.73 (1.63-1.85), respectively. There was an indication of positive association between central adiposity, as reflected by waist circumference (HRper 1-SD increase = 1.08, 95% CI: 1.00-1.17) and waist to hip ratio (HRper 1-SD increase = 1.13, 95% CI: 1.01-1.26), and endometrial cancer risk after accounting for BMI. Fat-free mass was not an independent predictor of risk in this cohort. These findings suggest that body fat percentage and fat mass are not better indicators of endometrial cancer risk than BMI. Further studies are needed to establish whether central adiposity contributes to risk beyond overall adiposity.

Hormone-related diseases and prostate cancer: An English national record linkage study.

Insulin-like growth factor-I (IGF-I) and testosterone may be related to prostate cancer risk. Acromegaly is associated with clinically high IGF-I concentrations. Klinefelter's syndrome, testicular hypofunction and hypopituitarism are associated with clinically low testosterone concentrations. We aimed to investigate whether diagnosis with these conditions was associated with subsequent prostate cancer diagnosis and mortality. We used linked English national Hospital Episode Statistics and mortality data from 1999 to 2017 to construct and follow-up cohorts of men aged ≥35 years diagnosed with (i) acromegaly (n = 2,495) and (ii) hypogonadal-associated diseases (n = 18,763): Klinefelter's syndrome (n = 1,992), testicular hypofunction (n = 8,086) and hypopituitarism (n = 10,331). We estimated adjusted hazard ratios (HRs) and confidence intervals (CIs) for prostate cancer diagnosis and death using Cox regression in comparison with an unexposed reference cohort of 4.3 million men, who were admitted to hospital for a range of minor surgeries and conditions (n observed cases = 130,000, n prostate cancer deaths = 30,000). For men diagnosed with acromegaly, HR for prostate cancer diagnosis was 1.33 (95% CI 1.09-1.63; p = 0.005; n observed cases = 96), HR for prostate cancer death was 1.44 (95% CI 0.92-2.26; p = 0.11; n deaths = 19). Diagnosis with Klinefelter's syndrome was associated with a lower prostate cancer risk (HR = 0.58, 95% CI 0.37-0.91; p = 0.02; n observed cases = 19) and hypopituitarism was associated with a reduction in prostate cancer death (HR = 0.53, 95% CI 0.35-0.79; p = 0.002; n deaths = 23). These results support the hypothesised roles of IGF-I and testosterone in prostate cancer development and/or progression. These findings are important because they provide insight into prostate cancer aetiology.

Theoretical potential for endometrial cancer prevention through primary risk factor modification: Estimates from the EPIC cohort.

Endometrial cancer (EC) incidence rates vary ~10-fold worldwide, in part due to variation in EC risk factor profiles. Using an EC risk model previously developed in the European EPIC cohort, we evaluated the prevention potential of modified EC risk factor patterns and whether differences in EC incidence between a European population and low-risk countries can be explained by differences in these patterns. Predicted EC incidence rates were estimated over 10 years of follow-up for the cohort before and after modifying risk factor profiles. Risk factors considered were: body mass index (BMI, kg/m2 ), use of postmenopausal hormone therapy (HT) and oral contraceptives (OC) (potentially modifiable); and, parity, ages at first birth, menarche and menopause (environmentally conditioned, but not readily modifiable). Modeled alterations in BMI (to all ≤23 kg/m2 ) and HT use (to all non-HT users) profiles resulted in a 30% reduction in predicted EC incidence rates; individually, longer duration of OC use (to all ≥10 years) resulted in a 42.5% reduction. Modeled changes in not readily modifiable exposures (i.e., those not contributing to prevention potential) resulted in ≤24.6% reduction in predicted EC incidence. Women in the lowest decile of a risk score based on the evaluated exposures had risk similar to a low risk countries; however, this was driven by relatively long use of OCs (median = 23 years). Our findings support avoidance of overweight BMI and of HT use as prevention strategies for EC in a European population; OC use must be considered in the context of benefits and risks.

Examination of potential novel biochemical factors in relation to prostate cancer incidence and mortality in UK Biobank.

BACKGROUND: Although prostate cancer is a leading cause of cancer death, its aetiology is not well understood. We aimed to identify novel biochemical factors for prostate cancer incidence and mortality in UK Biobank. METHODS: A range of cardiovascular, bone, joint, diabetes, renal and liver-related biomarkers were measured in baseline blood samples collected from up to 211,754 men at recruitment and in a subsample 5 years later. Participants were followed-up via linkage to health administrative datasets to identify prostate cancer cases. Hazard ratios (HRs) and 95% confidence intervals were calculated using multivariable-adjusted Cox regression corrected for regression dilution bias. Multiple testing was accounted for by using a false discovery rate controlling procedure. RESULTS: After an average follow-up of 6.9 years, 5763 prostate cancer cases and 331 prostate cancer deaths were ascertained. Prostate cancer incidence was positively associated with circulating vitamin D, urea and phosphate concentrations and inversely associated with glucose, total protein and aspartate aminotransferase. Phosphate and cystatin-C were the only biomarkers positively and inversely, respectively, associated with risk in analyses excluding the first 4 years of follow-up. There was little evidence of associations with prostate cancer death. CONCLUSION: We found novel associations of several biomarkers with prostate cancer incidence. Future research will examine associations by tumour characteristics.