Circulating metabolic biomarkers and risk of new-onset hypertension: findings from the UK Biobank.

OBJECTIVE: The evidence regarding the associations of circulating metabolic biomarkers with hypertension risk is scarce. We aimed to examine the associations between circulating metabolites and risk of hypertension. METHODS: We included 49 422 individuals free of hypertension at baseline with a mean (SD) age of 53.5 (8.0) years from the UK Biobank. Nuclear magnetic resonance spectroscopy was used to quantify 143 individual metabolites. Multivariable-adjusted Cox regression models were used to estimate hazard ratios and 95% confidence intervals (CIs). RESULTS: During a mean (SD) follow-up of 11.2 (1.8) years, 2686 incident hypertension cases occurred. Out of 143 metabolites, 76 were associated with incident hypertension, among which phenylalanine (hazard ratio: 1.40; 95% CI: 1.24-1.58) and apolipoprotein A1 (hazard ratio: 0.76; 95% CI: 0.66-0.87) had the strongest association when comparing the highest to the lowest quintile. In general, very-low-density lipoprotein (VLDL) particles were positively, whereas high-density lipoprotein (HDL) particles were inversely associated with risk of hypertension. Similar patterns of cholesterol, phospholipids, and total lipids within VLDL and HDL particles were observed. Triglycerides within all lipoproteins were positively associated with hypertension risk. Other metabolites showed significant associations with risk of hypertension included amino acids, fatty acids, ketone bodies, fluid balance and inflammation markers. Adding 10 selected metabolic biomarkers to the traditional hypertension risk model modestly improved discrimination (C-statistic from 0.745 to 0.752, P < 0.001) for prediction of 10-year hypertension incidence. CONCLUSION: Among UK adults, disturbances in metabolic biomarkers are associated with incident hypertension. Comprehensive metabolomic profiling may provide potential novel biomarkers to identify high-risk individuals.

Association between household size and risk of incident dementia in the UK Biobank study.

Currently, the relationship between household size and incident dementia, along with the underlying neurobiological mechanisms, remains unclear. This prospective cohort study was based on UK Biobank participants aged ≥ 50 years without a history of dementia. The linear and non-linear longitudinal association was assessed using Cox proportional hazards regression and restricted cubic spline models. Additionally, the potential mechanisms driven by brain structures were investigated by linear regression models. We included 275,629 participants (mean age at baseline 60.45 years [SD 5.39]). Over a mean follow-up of 9.5 years, 6031 individuals developed all-cause dementia. Multivariable analyses revealed that smaller household size was associated with an increased risk of all-cause dementia (HR, 1.06; 95% CI 1.02-1.09), vascular dementia (HR, 1.08; 95% CI 1.01-1.15), and non-Alzheimer's disease non-vascular dementia (HR, 1.09; 95% CI 1.03-1.14). No significant association was observed for Alzheimer's disease. Restricted cubic splines demonstrated a reversed J-shaped relationship between household size and all-cause and cause-specific dementia. Additionally, substantial associations existed between household size and brain structures. Our findings suggest that small household size is a risk factor for dementia. Additionally, brain structural differences related to household size support these associations. Household size may thus be a potential modifiable risk factor for dementia.

Modifiable lifestyle factors and lifetime risk of atrial fibrillation: longitudinal data from the Korea NHIS-HealS and UK Biobank cohorts.

BACKGROUND: The reason for higher incidence of atrial fibrillation (AF) in Europe compared with East Asia is unclear. We aimed to investigate the association between modifiable lifestyle factors and lifetime risk of AF in Europe and East Asia, along with race/ethnic similarities and disparities. METHODS: 1:1 propensity score matched pairs of 242,763 East Asians and 242,763 White Europeans without AF were analyzed. Modifiable lifestyle factors considered were blood pressure, body mass index, cigarette smoking, diabetes, alcohol consumption, and physical activity, categorized as non-adverse or adverse levels. Lifetime risk of AF was estimated from the index age of 45 years to the attained age of 85 years, accounting for the competing risk of death. RESULTS: The overall lifetime risk of AF was higher in White Europeans than East Asians (20.9% vs 15.4%, p < 0.001). The lifetime risk of AF was similar between the two races in individuals with non-adverse lifestyle factor profiles (13.4% vs 12.9%, p = 0.575), whereas it was higher in White Europeans with adverse lifestyle factor profiles (22.1% vs 15.8%, p < 0.001). The difference in the lifetime risk of AF between the two races increased as the burden of adverse lifestyle factors worsened (1 adverse lifestyle factor; 4.3% to ≥ 3 adverse lifestyle factors; 11.2%). Compared with East Asians, the relative risk of AF in White Europeans was 23% and 62% higher for one (hazard ratio [HR] 1.23, 95% confidence interval [CI] 1.16-1.29) and ≥ 3 adverse lifestyle factors (HR 1.62, 95% CI 1.51-1.75), respectively. CONCLUSIONS: The overall higher lifetime risk of AF in White Europeans compared with East Asians might be attributable to adverse lifestyle factors. Adherence to healthy lifestyle factors was associated with the lifetime risk of AF of about 1 in 8 regardless of race/ethnicity.

Peripheral GFAP and NfL as early biomarkers for dementia: longitudinal insights from the UK Biobank.

BACKGROUND: Peripheral glial fibrillary acidic protein (GFAP) and neurofilament light chain (NfL) are sensitive markers of neuroinflammation and neuronal damage. Previous studies with highly selected participants have shown that peripheral GFAP and NfL levels are elevated in the pre-clinical phase of Alzheimer's disease (AD) and dementia. However, the predictive value of GFAP and NfL for dementia requires more evidence from population-based cohorts. METHODS: This was a prospective cohort study to evaluate UK Biobank participants enrolled from 2006 to 2010 using plasma GFAP and NfL measurements measured by Olink Target Platform and prospectively followed up for dementia diagnosis. Primary outcome was the risk of clinical diagnosed dementia. Secondary outcomes were cognition. Linear regression was used to assess the associations between peripheral GFAP and NfL with cognition. Cox proportional hazard models with cross-validations were used to estimate associations between elevated GFAP and NfL with risk of dementia. All models were adjusted for covariates. RESULTS: A subsample of 48,542 participants in the UK Biobank with peripheral GFAP and NfL measurements were evaluated. With an average follow-up of 13.18 ± 2.42 years, 1312 new all-cause dementia cases were identified. Peripheral GFAP and NfL increased up to 15 years before dementia diagnosis was made. After strictly adjusting for confounders, increment in NfL was found to be associated with decreased numeric memory and prolonged reaction time. A greater annualized rate of change in GFAP was significantly associated with faster global cognitive decline. Elevation of GFAP (hazard ratio (HR) ranges from 2.25 to 3.15) and NfL (HR ranges from 1.98 to 4.23) increased the risk for several types of dementia. GFAP and NfL significantly improved the predictive values for dementia using previous models (area under the curve (AUC) ranges from 0.80 to 0.89, C-index ranges from 0.86 to 0.91). The AD genetic risk score and number of APOE*E4 alleles strongly correlated with GFAP and NfL levels. CONCLUSIONS: These results suggest that peripheral GFAP and NfL are potential biomarkers for the early diagnosis of dementia. In addition, anti-inflammatory therapies in the initial stages of dementia may have potential benefits.

Double Chromogen-based Immunohistochemical Staining: An Efficient Approach for Utilizing Long-term Formalin-fixed Tissue in Biobanks.

The New South Wales Brain Tissue Resource Centre is a human brain bank that provides top-quality brain tissue for cutting-edge neuroscience research spanning various conditions from alcohol use disorder to neurodegenerative diseases. However, the conventional practice of preserving brain tissue in formalin poses challenges for immunofluorescent staining primarily due to the formalin's tendency, over time, to create cross-links between antigens, which can obscure epitopes of interest. In addition, researchers can encounter issues such as spectral bleeding, limitations in using multiple colors, autofluorescence, and cross-reactivity when working with long-term formalin-fixed brain tissue. The purpose of the study was to test chromogen-based double immunolabeling to negate the issues with immunofluorescent staining. Colocalization of antigens was explored using chromogens 3-amino-9-ethylcarbazole (AEC) and 3,3,-diaminobenzidine in a sequential staining procedure where the AEC signal was eliminated by alcohol treatment. Combinations of 2 or 3 primary antibodies from the same or different species were trialed successfully with this protocol. The colocalization of antigens was also demonstrated with pseudocoloring that mimicked immunofluorescence staining. This staining technique increases the utility of archival formalin-fixed tissue samples.

Reweighting UK Biobank corrects for pervasive selection bias due to volunteering.

BACKGROUND: Biobanks typically rely on volunteer-based sampling. This results in large samples (power) at the cost of representativeness (bias). The problem of volunteer bias is debated. Here, we (i) show that volunteering biases associations in UK Biobank (UKB) and (ii) estimate inverse probability (IP) weights that correct for volunteer bias in UKB. METHODS: Drawing on UK Census data, we constructed a subsample representative of UKB's target population, which consists of all individuals invited to participate. Based on demographic variables shared between the UK Census and UKB, we estimated IP weights (IPWs) for each UKB participant. We compared 21 weighted and unweighted bivariate associations between these demographic variables to assess volunteer bias. RESULTS: Volunteer bias in all associations, as naively estimated in UKB, was substantial-in some cases so severe that unweighted estimates had the opposite sign of the association in the target population. For example, older individuals in UKB reported being in better health, in contrast to evidence from the UK Census. Using IPWs in weighted regressions reduced 87% of volunteer bias on average. Volunteer-based sampling reduced the effective sample size of UKB substantially, to 32% of its original size. CONCLUSIONS: Estimates from large-scale biobanks may be misleading due to volunteer bias. We recommend IP weighting to correct for such bias. To aid in the construction of the next generation of biobanks, we provide suggestions on how to best ensure representativeness in a volunteer-based design. For UKB, IPWs have been made available.

Phenome-wide identification of therapeutic genetic targets, leveraging knowledge graphs, graph neural networks, and UK Biobank data.

The ongoing expansion of human genomic datasets propels therapeutic target identification; however, extracting gene-disease associations from gene annotations remains challenging. Here, we introduce Mantis-ML 2.0, a framework integrating AstraZeneca's Biological Insights Knowledge Graph and numerous tabular datasets, to assess gene-disease probabilities throughout the phenome. We use graph neural networks, capturing the graph's holistic structure, and train them on hundreds of balanced datasets via a robust semi-supervised learning framework to provide gene-disease probabilities across the human exome. Mantis-ML 2.0 incorporates natural language processing to automate disease-relevant feature selection for thousands of diseases. The enhanced models demonstrate a 6.9% average classification power boost, achieving a median receiver operating characteristic (ROC) area under curve (AUC) score of 0.90 across 5220 diseases from Human Phenotype Ontology, OpenTargets, and Genomics England. Notably, Mantis-ML 2.0 prioritizes associations from an independent UK Biobank phenome-wide association study (PheWAS), providing a stronger form of triaging and mitigating against underpowered PheWAS associations. Results are exposed through an interactive web resource.

Quality of plant-based diets and frailty incidence: a prospective analysis of UK biobank participants.

BACKGROUND: Substantial evidence supports the inverse association between adherence to healthy dietary patterns and frailty risk. However, the role of plant-based diets, particularly their quality, is poorly known. OBJECTIVE: To examine the association of two plant-based diets with incidence of physical frailty in middle-aged and older adults. DESIGN: Prospective cohort. SETTING: United Kingdom. SUBJECTS: 24,996 individuals aged 40-70 years, followed from 2009-12 to 2019-22. METHODS: Based on at least two 24-h diet assessments, we built two diet indices: (i) the healthful Plant-based Diet Index (hPDI) and (ii) the unhealthful Plant-based Diet Index (uPDI). Incident frailty was defined as developing ≥3 out of 5 of the Fried criteria. We used Cox models to estimate relative risks (RR), and their 95% confidence interval (CI), of incident frailty adjusted for the main potential confounders. RESULTS: After a median follow-up of 6.72 years, 428 cases of frailty were ascertained. The RR (95% CI) of frailty was 0.62 (0.48-0.80) for the highest versus lowest tertile of the hPDI and 1.61 (1.26-2.05) for the uPDI. The consumption of healthy plant foods was associated with lower frailty risk (RR per serving 0.93 (0.90-0.96)). The hPDI was directly, and the uPDI inversely, associated with higher risk of low physical activity, slow walking speed and weak hand grip, and the uPDI with higher risk of exhaustion. CONCLUSIONS: In British middle-age and older adults, greater adherence to the hPDI was associated with lower risk of frailty, whereas greater adherence to the uPDI was associated with higher risk.

The impact of sunlight exposure on brain structural markers in the UK Biobank.

Sunlight is closely intertwined with daily life. It remains unclear whether there are associations between sunlight exposure and brain structural markers. General linear regression analysis was used to compare the differences in brain structural markers among different sunlight exposure time groups. Stratification analyses were performed based on sex, age, and diseases (hypertension, stroke, diabetes). Restricted cubic spline was performed to examine the dose-response relationship between natural sunlight exposure and brain structural markers, with further stratification by season. A negative association of sunlight exposure time with brain structural markers was found in the upper tertile compared to the lower tertile. Prolonged natural sunlight exposure was associated with the volumes of total brain (ß: - 0.051, P < 0.001), white matter (ß: - 0.031, P = 0.023), gray matter (ß: - 0.067, P < 0.001), and white matter hyperintensities (ß: 0.059, P < 0.001). These associations were more pronounced in males and individuals under the age of 60. The results of the restricted cubic spline analysis showed a nonlinear relationship between sunlight exposure and brain structural markers, with the direction changing around 2 h of sunlight exposure. This study demonstrates that prolonged exposure to natural sunlight is associated with brain structural markers change.

Genetic influence on within-person longitudinal change in anthropometric traits in the UK Biobank.

The causes of temporal fluctuations in adult traits are poorly understood. Here, we investigate the genetic determinants of within-person trait variability of 8 repeatedly measured anthropometric traits in 50,117 individuals from the UK Biobank. We found that within-person (non-directional) variability had a SNP-based heritability of 2-5% for height, sitting height, body mass index (BMI) and weight (P ≤ 2.4 × 10-3). We also analysed longitudinal trait change and show a loss of both average height and weight beyond about 70 years of age. A variant tracking the Alzheimer's risk APOE- E 4 allele (rs429358) was significantly associated with weight loss ( ß = -0.047 kg per yr, s.e. 0.007, P = 2.2 × 10-11), and using 2-sample Mendelian Randomisation we detected a relationship consistent with causality between decreased lumbar spine bone mineral density and height loss (bxy = 0.011, s.e. 0.003, P = 3.5 × 10-4). Finally, population-level variance quantitative trait loci (vQTL) were consistent with within-person variability for several traits, indicating an overlap between trait variability assessed at the population or individual level. Our findings help elucidate the genetic influence on trait-change within an individual and highlight disease risks associated with these changes.

Temporal change in multimorbidity prevalence, clustering patterns, and the association with mortality: findings from the China Kadoorie Biobank study in Jiangsu Province.

Objectives: The characteristics of multimorbidity in the Chinese population are currently unclear. We aimed to determine the temporal change in multimorbidity prevalence, clustering patterns, and the association of multimorbidity with mortality from all causes and four major chronic diseases. Methods: This study analyzed data from the China Kadoorie Biobank study performed in Wuzhong District, Jiangsu Province. A total of 53,269 participants aged 30-79 years were recruited between 2004 and 2008. New diagnoses of 15 chronic diseases and death events were collected during the mean follow-up of 10.9 years. Yule's Q cluster analysis method was used to determine the clustering patterns of multimorbidity. A Cox proportional hazards model was used to estimate the associations of multimorbidity with mortalities. Results: The overall multimorbidity prevalence rate was 21.1% at baseline and 27.7% at the end of follow-up. Multimorbidity increased more rapidly during the follow-up in individuals who had a higher risk at baseline. Three main multimorbidity patterns were identified: (i) cardiometabolic multimorbidity (diabetes, coronary heart disease, stroke, and hypertension), (ii) respiratory multimorbidity (tuberculosis, asthma, and chronic obstructive pulmonary disease), and (iii) mental, kidney and arthritis multimorbidity (neurasthenia, psychiatric disorders, chronic kidney disease, and rheumatoid arthritis). There were 3,433 deaths during the follow-up. The mortality risk increased by 24% with each additional disease [hazard ratio (HR) = 1.24, 95% confidence interval (CI) = 1.20-1.29]. Compared with those without multimorbidity at baseline, both cardiometabolic multimorbidity and respiratory multimorbidity were associated with increased mortality from all causes and four major chronic diseases. Cardiometabolic multimorbidity was additionally associated with mortality from cardiovascular diseases and diabetes, with HRs of 2.64 (95% CI = 2.19-3.19) and 28.19 (95% CI = 14.85-53.51), respectively. Respiratory multimorbidity was associated with respiratory disease mortality, with an HR of 9.76 (95% CI = 6.22-15.31). Conclusion: The prevalence of multimorbidity has increased substantially over the past decade. This study has revealed that cardiometabolic multimorbidity and respiratory multimorbidity have significantly increased mortality rates. These findings indicate the need to consider high-risk populations and to provide local evidence for intervention strategies and health management in economically developed regions.

Association of Cognitive Reserve Indicator with Cognitive Decline and Structural Brain Differences in Middle and Older Age: Findings from the UK Biobank.

BACKGROUND: Cognitive reserve (CR) contributes to preserving cognition when facing brain aging and damage. CR has been linked to dementia risk in late life. However, the association between CR and cognitive changes and brain imaging measures, especially in midlife, is unclear. OBJECTIVE: We aimed to explore the association of CR with cognitive decline and structural brain differences in middle and older age. DESIGN: This longitudinal study was from the UK Biobank project where participants completed baseline surveys between 2006 to 2010 and were followed (mean follow-up: 9 years). SETTING: A population-based study. PARTICIPANTS: A total of 42,301 dementia-free participants aged 40-70 were followed-up to detect cognitive changes. A subsample (n=34,041) underwent brain magnetic resonance imaging scans. MEASUREMENTS: We used latent class analysis to generate a CR indicator (categorized as high, moderate, and low) based on education, occupation, and multiple cognitively stimulating activities. Cognitive tests for global and domain-specific cognition were administrated at baseline and follow-up. Total brain, white matter, grey matter, hippocampal, and white matter hyperintensity volumes (TBV, WMV, GMV, HV, and WMHV) were assessed at the follow-up examination. Data were analyzed using mixed-effects models and analysis of covariance. RESULTS: At baseline, 16,032 (37.9%), 10,709 (25.3%), and 15,560 (36.8%) participants had low, moderate, and high levels of CR, respectively. Compared with low CR, high CR was associated with slower declines in global cognition (ß [95% confidence interval]: 0.10 [0.08, 0.11]), prospective memory (0.10 [0.06, 0.15]), fluid intelligence (0.07 [0.04, 0.10]), and reaction time (0.04 [0.02, 0.06]). Participants with high CR had lower TBV, WMV, GMV, and WMHV, but higher HV when controlling for global cognition (corrected P <0.01 for all). The significant relationships between CR and cognition and TBV were present among both middle-aged (<60 years) and older (≥60 years) participants. The CR-cognition association remained significant despite reductions in brain structural properties. CONCLUSIONS: Higher CR is associated with slower cognitive decline, higher HV, and lower microvascular burden, especially in middle age. Individuals with high CR could tolerate smaller brain volumes while maintaining cognition. The benefit of CR for cognition is independent of structural brain differences. Our findings highlight the contribution of enhancing CR to helping compensate for neuroimaging alterations and ultimately prevent cognitive decline.

Circulating fatty acids and risk of hepatocellular carcinoma and chronic liver disease mortality in the UK Biobank.

Nuclear magnetic resonance (NMR)-based plasma fatty acids are objective biomarkers of many diseases. Herein, we aim to explore the associations of NMR-based plasma fatty acids with the risk of hepatocellular carcinoma (HCC) and chronic liver disease (CLD) mortality in 252,398 UK Biobank participants. Here we show plasma levels of n-3 poly-unsaturated fatty acids (PUFA) and n-6 PUFA are negatively associated with the risk of incident HCC [HRQ4vsQ1: 0.48 (95% CI: 0.33-0.69) and 0.48 (95% CI: 0.28-0.81), respectively] and CLD mortality [HRQ4vsQ1: 0.21 (95% CI: 0.13-0.33) and 0.15 (95% CI: 0.08-0.30), respectively], whereas plasma levels of saturated fatty acids are positively associated with these outcomes [HRQ4vsQ1: 3.55 (95% CI: 2.25-5.61) for HCC and 6.34 (95% CI: 3.68-10.92) for CLD mortality]. Furthermore, fibrosis stage significantly modifies the associations between PUFA and CLD mortality. This study contributes to the limited prospective evidence on the associations between plasma-specific fatty acids and end-stage liver outcomes.

Interaction of physical activity and low-level air pollution on cardiovascular disease: a prospective cohort study in UK Biobank.

To investigate the associations of physical activity (PA), low-level air pollution, and interaction on cardiovascular diseases (CVD) incidence based on the UK Biobank. PA was measured by the International Physical Activity Questionnaire and five air pollutants were estimated using Land Use Regression. All association estimates were based on Cox regression. Dose-response relationship was explored by restricted cubic spline, while multiplicative and additive interaction were examined by Pinteraction and relative excess risk due to interaction (RERI). As deviating proportional hazards assumption, we analyzed data as follow-up < 4 years and ≥ 4 years, separately. PA with 1000-4000 Metabolic Equivalent Task (MET) min/week showed the strongest protective impact on CVD incidence, while only low-level nitrogen dioxides (NO2) showed negative impact among five air pollutants and was considered for further analysis. Multiplicative interaction between PA and NO2 was observed during ≥ 4 years follow-up (Pinteraction = 0.049) while not during < 4 years (Pinteraction = 0.290). Positive additive interactions were found for high PA and low NO2 (< 20 µg/m3) group (RERI: 0.07, 95% confidence intervals: 0.02-0.11) during < 4 years, and for moderate PA with NO2 at 40- µg/m3 (0.07, 0.02-0.13) and < 20 µg/m3 (0.07, 0.02-0.12), while high PA showed similar results with NO2 at 40-, 20- and < 20 µg/m3 during ≥ 4 years. PA about 1000-4000 METs min/week showed the lowest CVD risk. Possibility of interaction with PA and NO2 is more likely to present with the increase in follow-up duration. We call for the optimal thresholds of PA, and exploring interaction thoroughly by considering types of PA.

Common conditions of use elements. Atomic concepts for consistent and effective information governance.

Myriad policy, ethical and legal considerations underpin the sharing of biological resources, implying the need for standardised and yet flexible ways to digitally represent diverse 'use conditions'. We report a core lexicon of terms that are atomic, non-directional 'concepts of use', called Common Conditions of use Elements. This work engaged biobanks and registries relevant to the European Joint Programme for Rare Diseases and aimed to produce a lexicon that would have generalised utility. Seventy-six concepts were initially identified from diverse real-world settings, and via iterative rounds of deliberation and user-testing these were optimised and condensed down to 20 items. To validate utility, support software and training information was provided to biobanks and registries who were asked to create Sharing Policy Profiles. This succeeded and involved adding standardised directionality and scope annotations to the employed terms. The addition of free-text parameters was also explored. The approach is now being adopted by several real-world projects, enabling this standard to evolve progressively into a universal basis for representing and managing conditions of use.

Association between combined exposure to ambient air pollutants, genetic risk, and incident gout risk: A prospective cohort study in the UK Biobank.

BACKGROUND: Limited research has been conducted on the association between long-term exposure to air pollutants and the incidence of gout. OBJECTIVES: This study aims to assess the individual and combined effects of prolonged exposure to five air pollutants (NO2, NOx, PM10, PMcoarse and PM2.52) on the incidence of gout among 458,884 initially gout-free participants enrolled in the UK Biobank. METHODS: Employing a land use regression model, we utilized an estimation method to ascertain the annual concentrations of the five air pollutants. Subsequently, we devised a weighted air pollution score to facilitate a comprehensive evaluation of exposure. The Cox proportional hazards model was utilized to investigate the association between ambient air pollution and gout risk. Interaction and stratification analyses were conducted to evaluate age, sex, BMI, and genetic predisposition as potential effect modifiers in the air pollution-gout relationship. Furthermore, mediation analyses were conducted to explore the potential involvement of biomarkers in mediating the association between air pollution and gout. RESULTS: Over a median follow-up time of 12.0 years, 7,927 cases of gout were diagnosed. Significant associations were observed between the risk of gout and a per IQR increase in NO2 (HR3: 1.05, 95 % CI4: 1.02-1.08, p = 0.003), NOx (HR: 1.04, 95 % CI: 1.01-1.06, p = 0.003), and PM2.5 (HR: 1.03, 95 % CI: 1.00-1.06, p = 0.030). Per IQR increase in the air pollution score was associated with an elevated risk of gout (p = 0.005). Stratified analysis revealed a significant correlation between the air pollution score and gout risk in participants ≥60 years (HR: 1.05, 95 % CI: 1.02-1.09, p = 0.005), but not in those <60 years (p = 0.793), indicating a significant interaction effect with age (p-interaction=0.009). Mediation analyses identified five serum biomarkers (SUA:15.87 %, VITD: 5.04 %, LDLD: 3.34 %, GGT: 1.90 %, AST: 1.56 %5) with potential mediation effects on this association. CONCLUSIONS: Long-term exposure to air pollutants, particularly among the elderly population, is associated with an increased risk of gout. The underlying mechanisms of these associations may involve the participation of five serum biomarkers.

Depressive symptoms and neuroticism mediate the association between traumatic events and suicidality - A latent class mediation analysis of UK Biobank Database.

BACKGROUND: Mental disorders that follow traumatic experience may increase risk of suicidality, but a comprehensive approach to understand how these mental disorders mediate the association between psychological traumatic experience and suicidality should be elucidated. In this study, we attempted to provide comprehensive evidence on how depressive symptoms and neuroticism can mediate the association between psychological traumatic experiences and suicidal behaviours including suicidal ideation, suicidal planning, and suicide attempts. METHODS: We analyzed 111,931 participants from UK Biobank who had completed mental health web-based questionnaire from 2016 to 2017. "Self-harm and suicidal behaviour and ideation (SSBI) score" was calculated by the response from suicidal behaviours and self-harm questionnaires. Conducting multivariate linear regression, depressive symptoms, anxiety symptoms, and neuroticism were selected as potential mediators. We constructed a latent class mediation model estimated direct effect of psychological traumatic events on suicidality and indirect effect of psychological traumatic events mediated by depressive symptoms and neuroticism. RESULTS: Psychological traumatic events were positively associated with suicidal behaviours. Depressive symptoms and neuroticism significantly mediated the effect of psychological traumatic events on suicidality. Anxiety symptoms did not mediate the association between psychological traumatic events and suicidality. CONCLUSION: Psychological traumatic events, irrespective of life stage of occurrence, are associated with suicidality. The association between psychological traumatic events and suicidality can be partially explained by depressive symptoms and neuroticism of those who were exposed to psychological trauma.

Assessment of new-onset heart failure prediction in a diabetic population using left ventricular global strain: a prospective cohort study based on UK Biobank.

Background: Impaired glucose utilization influences myocardial contractile function. However, the prognostic importance of left ventricular global radial strain (LV-GRS), left ventricular global circumferential strain (LV-GCS), and left ventricular global longitudinal strain (LV-GLS) in predicting new-onset heart failure (HF) in a population with diabetes is unclear. Methods: The study design is prospective cohort from the UK Biobank. Totally 37,899 participants had a complete data of cardiac magnetic resonance (CMR), of which 940 patients with diabetes were included, and all the participants completed follow-up. LV-GRS, LV-GCS, and LV-GLS were measured by completely automated CMR with tissue tagging. Cox proportional hazards regression analysis and C-index was performed to evaluate the association between the strain parameters and the new-onset HF in patients suffering from diabetes. Results: The average age of the 940 participants was 57.67 ± 6.97 years, with males comprising 66.4% of the overall population. With an average follow-up period of 166.82 ± 15.26 months, 35 (3.72%) patients reached the endpoint (emergence of new-onset HF). Significant associations were found for the three strain parameters and the new-onset HF (LV-GRS-hazard ratio [HR]: 0.946, 95% CI: 0.916-0.976; LV-GCS-HR: 1.162, 95% CI: 1.086-1.244; LV-GCS-HR: 1.181, 95% CI: 1.082-1.289). LV-GRS, LV-GCS, and LV-GLS were closely related to the related indicators to HF, and showed a high relationship to new-onset HF in individuals with diabetes at 5 and 10 years: LV-GRS: 0.75 (95% CI, 0.41-0.94) and 0.76 (95% CI, 0.44-0.98), respectively; LV-GCS: 0.80 (95% CI, 0.50-0.96) and 0.75 (95% CI, 0.41-0.98), respectively; LV-GLS: 0.72 (95% CI, 0.40-0.93) and 0.76 (95% CI, 0.48-0.97), respectively. In addition, age, sex, body mass index (BMI), and presence of hypertension or coronary artery disease (CAD) made no impacts on the association between the global strain parameters and the incidence of HF. Conclusion: LV-GRS, LV-GCS, and LV-GLS is significantly related to new-onset HF in patients with diabetes at 5 and 10 years.