UK Biobank Cohort Research Articles

Genetic and vascular risk factors for ischemic stroke and cortical morphometry in individuals without a history of stroke: A UK Biobank observational cohort study

BackgroundStroke risk factors may contribute to cognitive decline and dementia by altering brain tissue integrity. If their effects on brain are nonnegligible, the target regions for stroke rehabilitation with brain stimulation identified by cross-sectional case-control studies may be biased due to the pre-existing brain differences caused by these risk factors. Here, we investigated the effects of stroke risk factors on cortical thickness (CT) and surface area (SA) in individuals without a history of stroke. MethodsIn this observational study, we used data from the UK Biobank cohort to explore the effects of polygenic risk score for ischemic stroke (PRSIS), systolic blood pressure (SBP), diastolic blood pressure (DBP), glycated hemoglobin (HbA1c), triglycerides (TG), and low-density lipoprotein (LDL) on CT and SA of 62 cerebral regions. We excluded non-Caucasian participants and participants with missing data, unqualified brain images, or a history of stroke or any other brain diseases. We constructed a multivariate linear regression model for each phenotype to simultaneously test the effect of each factor and interaction between factors. The results were verified by sensitivity analyses of SDP or DBP input and adjusting for body-mass index, high-density lipoprotein cholesterol, or smoking and alcohol intake. By excluding participants with abnormal blood pressure, glucose, or lipid, we tested whether vascular risk factor within normal range also affected cortical phenotypes. To determine clinical relevance of our findings, we also investigated the effects of stroke risk factors and cortical phenotypes on cognitive decline assessed by fluid intelligence score (FIQ) and the mediation of cortical phenotype for the association between stroke risk factor and FIQ. ResultsThe study consisted of 27 120 eligible participants. Stroke risk factors were associated with 16 CT and two SA phenotypes in both main and sensitivity analyses (all p < 0.0004, Bonferroni corrected), which could explain portions of variances (partial R2, median 0.62 % [IQR 0.44–0.75 %] in main analyses) in these phenotypes. Among the 18 cortical phenotypes associated with stroke risk factors, we identified 26 specific predictor-phenotype associations (all p < 0.0026), including the positive associations between PRSIS and SA and between HbA1c and CT, negative associations of SBP and TG with CT, and mixed associations of PRSIS and DBP with CT. Neither LDL nor interactions between risk factors affected cortical phenotypes. Of the 16 associations between vascular risk factors and cortical phenotypes, ten were still significant after excluding participants with abnormal vascular risk assessments and diagnoses. Stroke risk factors were associated with FIQ in all analyses (p < 0.0004; partial R2, range 0.22–0.3 %), of which the associations of PRSIS and SBP with cognitive decline were mediated by CT phenotypes. ConclusionsStroke risk factors have substantial effects on cortical morphometry and cognitive decline in middle-aged and older people, which should be considered in the prevention of dementia and in the identification of target regions for stroke rehabilitation with brain stimulation.

Association between self-reported child maltreatment and risk of hospital-treated infectious diseases in middle-aged and older adults: A UK Biobank cohort study.

This study aimed to explore the association between child maltreatment and hospital-treated infectious diseases in middle-aged and older adults. 145,151 participants aged 38-72 years from the UK Biobank between 2006 and 2010 were enrolled and interviewed. Child maltreatment included five types: physical abuse, physical neglect, emotional abuse, emotional neglect, and sexual abuse. Patterns of maltreatment were identified using latent class analysis (LCA). Cox regression was employed to estimate the associations between child maltreatment (number of types, individual types, and patterns) and infectious diseases. Further, we evaluated potential mediators using mediation analysis. Over a median follow-up of 13.4 years, 22,688 participants (12.26 per 1000 person-years) were hospitalized for an infectious disease. Participants reporting any maltreatment had elevated infectious diseases risk (HR 1.18, 95 % CI: 1.15-1.21) than those without maltreatment. A dose-response relationship was observed between the number of maltreatment types and infectious disease (one, HR 1.09 [95 % CI 1.06-1.13]; two, HR 1.17 [95 % CI 1.12-1.23]; three to five, HR 1.48 [95 %CI 1.41-1.55]; Ptrend < 0.001). Each type of maltreatment was associated with increased infectious diseases risk. LCA identified four patterns (low maltreatment, child neglect, child abuse, and poly-maltreatment), with those experiencing poly-maltreatment exhibiting the highest infectious diseases risk (HR 1.51, 95 % CI: 1.43-1.59). The association between child maltreatment and infectious diseases was mediated by C-reactive protein, phenotypic age acceleration, loneliness, psychiatric disorders, and unhealthy lifestyles. Child maltreatment may increase susceptibility to a broad spectrum of infectious diseases in adulthood, highlighting the need for early-life maltreatment prevention policies.

Polyconnectomic scoring of functional connectivity patterns across eight neuropsychiatric and three neurodegenerative disorders

BackgroundNeuropsychiatric and neurodegenerative disorders involve diverse changes in brain functional connectivity. As an alternative to approaches searching for specific mosaic patterns of affected connections and networks, we used polyconnectomic scoring to quantify disorder-related whole-brain connectivity signatures into interpretable, personalized scores. MethodsThe polyconnectomic score (PCS) measures the extent to which an individual's functional connectivity (FC) mirrors the whole-brain circuitry characteristics of a trait. We computed PCS for eight neuropsychiatric conditions (attention-deficit/hyperactivity disorder, anxiety-related disorders, autism spectrum disorder, obsessive-compulsive disorder, bipolar disorder, major depressive disorder, schizoaffective disorder, and schizophrenia) and three neurodegenerative conditions (Alzheimer's disease, frontotemporal dementia, and Parkinson’s disease) across 22 datasets with resting-state functional MRI of 10,667 individuals (5,325 patients, 5,342 controls). We further examined PCS in 26,673 individuals from the population-based UK Biobank cohort. ResultsPCS was consistently higher in out-of-sample patients across six of the eight neuropsychiatric and across all three investigated neurodegenerative disorders ([min, max]: AUC = [0.55, 0.73], pFDR = [1.8 x 10-16, 4.5 x 10-2]). Individuals with elevated PCS levels for neuropsychiatric conditions exhibited higher neuroticism (pFDR < 9.7 x 10-5), lower cognitive performance (pFDR < 5.3 x 10-5), and lower general wellbeing (pFDR < 9.7 x 10-4). ConclusionsOur findings reveal generalizable whole-brain connectivity alterations in brain disorders. PCS effectively aggregates disorder-related signatures across the entire brain into an interpretable, subject-specific metric. A toolbox is provided for PCS computation.

Does sedentary time and physical activity predict chronic back pain and morphological brain changes? A UK biobank cohort study in 33,402 participants

BackgroundThe relationship between sedentary time, physical activity, and chronic back pain remains unclear. The study aims to investigate whether sedentary time and physical activity predict chronic back pain and morphological brain changes.MethodsThis cohort study recruited adults aged 37–73 years enrolled between 2006 and 2010, with follow-up until 2014. The total cohort comprised 33,402 participants (mean age: 54.53). Data were collected on daily sedentary time, physical activity, lifestyle factors, and health outcomes.ResultsAfter nearly 8-year follow-up, 3,006 individuals (9.00%) reported chronic back pain in total. Individuals with daily sedentary time exceeding 6 h had a 33% higher risk of chronic back pain compared to those with sedentary time of 2 h or less (RR, 1.33, 95%CI, 1.17–1.52). Sedentary time was also associated with decreased grey matter volume in several brain regions, including bilateral primary somatosensory cortex (S1), secondary somatosensory cortex, putamen, primary motor cortex (M1), insula, hippocampus, amygdala, as well as right supplementary motor area, left medial frontal cortex, and right anterior cingulate cortex (FDR-corrected p-value < 0.05). Compared to individuals who sat for more than 6 h with light physical activity, those engaging in moderate physical activity with sedentary time of 2 h or less (RR, 0.71, 95%CI, 0.52–0.99) exhibited a significant decrease in chronic back pain risk. In addition, replacing sedentary time with equivalent amount of physical activity also demonstrated a reduction in the risk of chronic back pain (RR, 0.87, 95%CI, 0.77–0.99) and increased the reginal grey matter volumes including the amygdala, insula, M1, putamen and S1.ConclusionsProlonged sedentary time is associated with heightened risks of chronic back pain and deterioration in brain health.

Associations of Lifestyle, Ambient Air Pollution With Progression of Asthma in Adults: A Comprehensive Analysis of UK Biobank Cohort.

We aim to investigate the associations between lifestyle, ambient air pollution with crucial outcomes in the progression of adult asthma, including asthma new-onset and asthma hospitalisation. 176,800 participants were included to assess the prospective association between baseline risk exposures and the subsequent asthma onset, 17,387 participants were used to evaluate asthma hospitalisation. Cox regression models were employed to examine the associations. In terms of lifestyle factors, the HRs (95% CIs) of the least healthy lifestyle categories for asthma incidence and hospitalization were 1.099 (1.017-1.187) and 1.064 (1.008-1.123), respectively. For pollutants, PM2.5, especially the traffic-related PM2.5 component, was consistently recognized as a significant risk factor for asthma onset (HR = 1.064, 95% CI: 1.034-1.094) and hospitalisation (HR = 1.031, 95% CI: 1.010-1.052) under various model adjustments. Low socioeconomic status also played a major role in the progression of adult asthma. Our study provides crucial insights into factors influencing the progression of adult asthma. Monitoring and reducing exposure to air pollution, particularly PM2.5, promoting healthier lifestyle, and addressing socioeconomic inequity are important in preventing and managing asthma.

Association of Adding Salt to Foods and Potassium Intake with Incident Atrial Fibrillation in the UK Biobank Study.

High sodium and low potassium consumption are related to hypertension and cardiovascular disease. We aimed to determine the relationship between the frequency of salt addition and potassium consumption with the risk of new-onset atrial fibrillation (AF). Our study used the UK Biobank cohort, which included over 500,000 individuals enrolled from the United Kingdom between 2006 and 2010. This study involved 416,868 participants who filled out the dietary recall regarding the frequency of salt addition. During follow-up, 19,164 (4.6%) developed AF. The incidence of new-onset AF was increased based on the frequency of salt addition (never/rarely 3.83; always 4.72 per 1000 person-years). Compared with the group that never/rarely added salt, those adding salt always were at significantly higher risk of incident AF after adjusting for multiple variables (hazard ratio (HR) 1.15; 95% confidence interval (CI) 1.06-1.24), and additional adjustment of dietary and total energy consumption (HR 1.37; 95% CI 1.08-1.73). In the subgroup analysis, the risk of AF incident according to the frequency of salt addition significantly increased in low urine potassium levels compared to high (p for interaction = 0.046). In the subgroup analysis for AF patients, higher salt addition frequency was related to increased all-cause mortality. Our study demonstrated that adding salt to foods more frequently increases the risk of incident AF, even after adjusting for dietary and total energy consumption. In the high urine potassium group, the impact of high sodium consumption on incident AF was attenuated.

Validation of the BOADICEA model for epithelial tubo-ovarian cancer risk prediction in UK Biobank

BackgroundThe clinical validity of the multifactorial BOADICEA model for epithelial tubo-ovarian cancer (EOC) risk prediction has not been assessed in a large sample size or over a longer term.MethodsWe evaluated the model discrimination and calibration in the UK Biobank cohort comprising 199,429 women (733 incident EOCs) of European ancestry without previous cancer history. We predicted 10-year EOC risk incorporating data on questionnaire-based risk factors (QRFs), family history, a 36-SNP polygenic risk score and pathogenic variants (PV) in six EOC susceptibility genes (BRCA1, BRCA2, RAD51C, RAD51D, BRIP1 and PALB2).ResultsDiscriminative ability was maximised under the multifactorial model that included all risk factors (AUC = 0.68, 95% CI: 0.66–0.70). This model was well calibrated in deciles of predicted risk with calibration slope=0.99 (95% CI: 0.98–1.01). Discriminative ability was similar in women younger or older than 60 years. The AUC was higher when analyses were restricted to PV carriers (0.76, 95% CI: 0.69–0.82). Using relative risk (RR) thresholds, the full model classified 97.7%, 1.7%, 0.4% and 0.2% women in the RR < 2.0, 2.0 ≤ RR < 2.9, 2.9 ≤ RR < 6.0 and RR ≥ 6.0 categories, respectively, identifying 9.1 of incident EOC among those with RR ≥ 2.0.DiscussionBOADICEA, implemented in CanRisk (www.canrisk.org), provides valid 10-year EOC risks and can facilitate clinical decision-making in EOC risk management.

A plasma proteomic signature for atherosclerotic cardiovascular disease risk prediction in the UK Biobank cohort.

While risk stratification for atherosclerotic cardiovascular disease (ASCVD) is essential for primary prevention, current clinical risk algorithms demonstrate variability and leave room for further improvement. The plasma proteome holds promise as a future diagnostic and prognostic tool that can accurately reflect complex human traits and disease processes. We assessed the ability of plasma proteins to predict ASCVD. Clinical, genetic, and high-throughput plasma proteomic data were analyzed for association with ASCVD in a cohort of 41,650 UK Biobank participants. Selected features for analysis included clinical variables such as a UK-based cardiovascular clinical risk score (QRISK3) and lipid levels, 36 polygenic risk scores (PRSs), and Olink protein expression data of 2,920 proteins. We used least absolute shrinkage and selection operator (LASSO) regression to select features and compared area under the curve (AUC) statistics between data types. Randomized LASSO regression with a stability selection algorithm identified a smaller set of more robustly associated proteins. The benefit of plasma proteins over standard clinical variables, the QRISK3 score, and PRSs was evaluated through the derivation of Δ AUC values. We also assessed the incremental gain in model performance using proteomic datasets with varying numbers of proteins. To identify potential causal proteins for ASCVD, we conducted a two-sample Mendelian randomization (MR) analysis. The mean age of our cohort was 56.0 years, 60.3% were female, and 9.8% developed incident ASCVD over a median follow-up of 6.9 years. A protein-only LASSO model selected 294 proteins and returned an AUC of 0.723 (95% CI 0.708-0.737). A clinical variable and PRS-only LASSO model selected 4 clinical variables and 20 PRSs and achieved an AUC of 0.726 (95% CI 0.712-0.741). The addition of the full proteomic dataset to clinical variables and PRSs resulted in a Δ AUC of 0.010 (95% CI 0.003-0.018). Fifteen proteins selected by a stability selection algorithm offered improvement in ASCVD prediction over the QRISK3 risk score [Δ AUC: 0.013 (95% CI 0.005-0.021)]. Filtered and clustered versions of the full proteomic dataset (consisting of 600-1,500 proteins) performed comparably to the full dataset for ASCVD prediction. Using MR, we identified 11 proteins as potentially causal for ASCVD. A plasma proteomic signature performs well for incident ASCVD prediction but only modestly improves prediction over clinical and genetic factors. Further studies are warranted to better elucidate the clinical utility of this signature in predicting the risk of ASCVD over the standard practice of using the QRISK3 score.

Association between long-term exposure to low ambient PM2.5 and cardiovascular hospital admissions: A UK Biobank study

IntroductionA causal link between air pollution exposure and cardiovascular events has been suggested. However fewer studies have investigated the shape of the associations at low levels of air pollution and identified the most important temporal window of exposure. Here we assessed long-term associations between particulate matter < 2.5 µm (PM2.5) at low concentrations and multiple cardiovascular endpoints using the UK Biobank cohort. MethodsUsing data on adults (aged > 40) from the UK Biobank cohort, we investigated the associations between 1-year, 3-year and 5-year time-varying averages of PM2.5 and incidence of major adverse cardiovascular events (MACE), myocardial infarction (MI), heart failure, atrial fibrillation and flutter and cardiac arrest. We also investigated outcome subtypes for MI and stroke. Events were defined as hospital inpatient admissions. We fitted Cox proportional hazard regression models applying extensive control for confounding at both individual and area level. Finally, we assessed the shape of the exposure–response functions to assess effects at low levels of exposure. ResultsWe analysed data from 377,736 study participants after exclusion of prevalent subjects. The average follow-up (2006–2021) was 12.9 years. We detected 19,353 cases of MACE, 6,562 of acute MI, 6,278 of heart failure, 1,258 for atrial fibrillation and flutter, and 16,327 for cardiac arrest. Using a 5-year exposure window, we detected positive associations (for 5 μg/m3 increase in PM2.5) for 5-point MACE of [1.12 (95 %CI: 1.00–1.26)], heart failure [1.22 (1.00–1.50)] and cardiac arrest [1.16 (1.03–1.31)]. We did not find any association with acute MI, while non-ST-elevation MI was associated with the 1-year exposure window [1.52 (1.12–2.07)]. The assessment of the shape of the exposure–response relationships suggested that risk is approximately linear for most of the outcomes. ConclusionsWe found positive associations between long-term exposure to PM2.5 and multiple cardiovascular outcomes for different exposure windows. The cardiovascular risk tends to rise even at exposure concentrations below 12–15 μg/m3, indicating high risk below UK national and international thresholds.

Proteogenomic Analysis Identifies a Causal Association between Plasma Apolipoprotein B Levels and Liver Cancer Risk.

Liver oncogenesis is accompanied by discernible protein changes in the bloodstream. By employing plasma proteomic profiling, we can delve into the molecular mechanisms of liver cancer and pinpoint potential biomarkers. In this nested case-control study, we applied liquid chromatography-tandem mass spectrometry for proteome profiling in baseline plasma samples. Differential protein expression was determined and was subjected to functional enrichment, network, and Mendelian randomization (MR) analyses. We identified 193 proteins with notable differential levels between the groups. Of these proteins, MR analysis offered a compelling negative association between apolipoprotein B (APOB) and liver cancer. This association was further corroborated in the UK Biobank cohort: genetically predicted APOB levels were associated with a 31% (95% CI 19-42%) decreased risk of liver cancer; and phenotypic analysis indicated an 11% (95% CI 8-14%) decreased liver cancer risk for every 0.1 g/L increase of circulating APOB levels. Multivariable MR analysis suggested that the hepatic fat content might fully mediate the APOB-liver cancer connection. In summary, we identified some plasma proteins, particularly APOB, as potential biomarkers of liver cancer. Our findings underscore the intricate link between lipid metabolism and liver cancer, offering hints for targeted prophylactic strategies and early detection.

Cardiovascular health and cancer mortality: evidence from US NHANES and UK Biobank cohort studies

BackgroundThe American Heart Association recently introduced a novel cardiovascular health (CVH) metric, Life's Essential 8 (LE8), for health promotion. However, the relationship between LE8 and cancer mortality risk remains uncertain.MethodsWe investigated 17,076 participants from US National Health and Nutrition Examination Survey (US NHANES) and 272,727 participants from UK Biobank, all free of cancer at baseline. The CVH score, based on LE8 metrics, incorporates four health behaviors (diet, physical activity, smoking, and sleep) and four health factors (body mass index, lipid, blood glucose, and blood pressure). Self-reported questionnaires assessed health behaviors. Primary outcomes were mortality rates for total cancer and its subtypes. The association between CVH score (continuous and categorical variable) and outcomes was examined using Cox model with adjustments. Cancer subtypes-related polygenic risk score (PRS) was constructed to evaluate its interactions with CVH on cancer death risk.ResultsOver 141,526 person-years in US NHANES, 424 cancer-related deaths occurred, and in UK Biobank, 8,872 cancer deaths were documented during 3,690,893 person-years. High CVH was associated with reduced overall cancer mortality compared to low CVH (HR 0.58, 95% CI 0.37–0.91 in US NHANES; 0.51, 0.46–0.57 in UK Biobank). Each one-standard deviation increase in CVH score was linked to a 19% decrease in cancer mortality (HR: 0.81; 95% CI: 0.73–0.91) in US NHANES and a 19% decrease (HR: 0.81; 95% CI: 0.79–0.83) in UK Biobank. Adhering to ideal CVH was linearly associated with decreased risks of death from lung, bladder, liver, kidney, esophageal, breast, colorectal, pancreatic, and gastric cancers in UK Biobank. Furthermore, integrating genetic data revealed individuals with low PRS and high CVH exhibited the lowest mortality from eight cancers (HRs ranged from 0.36 to 0.57) compared to those with high PRS and low CVH. No significant modification of the association between CVH and mortality risk for eight cancers by genetic predisposition was observed. Subgroup analyses showed a more pronounced protective association for overall cancer mortality among younger participants and those with lower socio-economic status.ConclusionsMaintaining optimal CVH is associated with a substantial reduction in the risk of overall cancer mortality. Adherence to ideal CVH correlates linearly with decreased mortality risk across multiple cancer subtypes. Individuals with both ideal CVH and high genetic predisposition demonstrated significant health benefits. These findings support adopting ideal CVH as an intervention strategy to mitigate cancer mortality risk and promote healthy aging.

Association of metabolic signatures of air pollution with MASLD: Observational and Mendelian randomization study

Background & AimsTo identify metabolic signatures associated with exposure to ambient air pollution and to explore their associations with risk of metabolic dysfunction-associated steatotic liver disease (MASLD). MethodsWe utilized data from the UK Biobank Cohort. Annual mean concentrations of PM2.5, PM10, NO2 and NOx were assessed for each participant using bilinear interpolation. The Elastic Net regression model was used to identify metabolites associated with four air pollutants and to construct metabolic signatures, respectively. Associations between air pollutants, metabolic signatures and MASLD were analyzed using Cox models. Mendelian randomization (MR) analysis was used to examine potential causality. Mediation analysis was employed to examine the role of metabolic signatures in the association between air pollutants and MASLD. ResultsA total of 244,842 participants from the UK Biobank were included in this analysis. We identified 87, 65, 76, and 71 metabolites as metabolic signatures of PM2.5, PM10, NO2, and NOx, respectively. Metabolic signatures were associated with risk of MASLD, with hazard ratios (HRs) and 95% confidence intervals (95% CIs) were 1.10 (1.06, 1.14), 1.06 (1.02, 1.10), 1.24 (1.20, 1.29) and 1.14 (1.10, 1.19). The four pollutants were associated with increased risk of MASLD, with HRs (95% CIs) of 1.03 (1.01, 1.05), 1.02 (1.01, 1.04), 1.01 (1.01, 1.02) and 1.01 (1.00, 1.01). MR analysis indicated an association between PM2.5, NO2 and NOx-related metabolic signatures and MASLD. Metabolic signatures mediated the association of PM2.5, PM10, NO2 and NOx with MASLD. ConclusionThere may be association between PM2.5, PM10, NO2 and NOx-related metabolic signatures and MASLD, and metabolic signatures mediate the increase of PM2.5, PM10, NO2 and NOx in the risk of MASLD. Impact and implicationsAir pollution is a significant public health issue and an important risk factor for metabolic dysfunction-associated steatotic liver disease (MASLD), however, the mechanism by which air pollution affects MASLD remains unclear. Our study used integrated serological metabolic data of 251 metabolites from a large-scale cohort study to demonstrate that metabolic signatures play a crucial role in the elevated risk of MASLD caused by air pollution. These results are relevant to patients and policymakers because they suggest that air pollution-related metabolic signatures are not only potentially associated with MASLD but also involved in mediating the process by which PM2.5, PM10, NO2, and NOx increase the risk of MASLD. Focusing on changes in air pollution-related metabolic signatures may offer a new perspective for preventing air pollution-induced MASLD and serve as protective measures to address this emerging public health challenge.

Higher docosahexaenoic acid proportions in blood are inversely associated with the prevalence of prediabetes: Evidence from the UK Biobank

Prediabetes and type 2 diabetes mellitus are growing global health concerns, predisposing individuals to various vascular complications. Lifestyle modifications, including dietary interventions, offer promising avenues for prevention and management. Using a multivariable-adjusted model, we analyzed the cross-sectional associations between plasma proportions (% of total fatty acids) of omega-3 polyunsaturated fatty acids (n3 PUFA, including total n3 PUFA, docosahexaenoic acid [DHA], non-DHA n3 PUFA), and glycated hemoglobin A1c (HbA1c) as well as the prevalence of prediabetes in a sample from the UK Biobank cohort. Our hypothesis was that proportions of n3 PUFA, especially DHA, would by inversely associated with the prediabetes prevalence. The sample (n = 92,762; 54.5% females) had an average age of 56 years and was overweight (mean body mass index = 27). The mean plasma DHA proportion in the sample was 2.03% (standard deviation [SD] = 0.67%), non-DHA n3 PUFA was 2.41% (SD = 1.02%) and total n3 PUFA was 4.43% (SD = 1.56%). Prediabetic individuals were identified by blood HbA1c proportions between 5.7% and 6.4% (39-46 mmol/mol) according to American Diabetes Association criteria. Each of the three n3 PUFA biomarkers was inversely associated with HbA1c proportions. In particular, DHA showed the strongest inverse association, with an OR of 0.62 (95% confidence intervals: 0.58, 0.67; P < .001) when comparing quintiles 5 to 1 in a fully adjusted model. These findings suggest a potential protective role of n3 PUFA, particularly DHA, in mitigating the risk of having prediabetes. Further prospective investigations are needed to clarify whether long-chain n3 PUFA could function as modifiable factors for prediabetes.

Associations between Aircraft Noise, Sleep, and Sleep-Wake Cycle: Actimetric Data from the UK Biobank Cohort near Four Major Airports.

Nighttime aircraft noise may affect people's sleep, yet large-scale evidence using objective and subjective measures remains limited. Our aim was to investigate associations between nighttime aircraft noise exposure and objectively measured sleep disturbance using a large UK cohort. We used data from 105,770 UK Biobank cohort participants exposed and unexposed to aircraft noise who lived in 44 local authority districts near 4 international airports in England. We used a generalized linear regression model to examine cross-sectional associations between aircraft noise (23:00 hours-07:00 hours) and 7-d actimetric measures collected 2013-2015 (). We also used Logit and generalized estimating equations models to examine associations between and self-reported sleep measures at enrollment (2006-2010) and follow-up (2012-2013). This approach allowed us to compare and contrast the results and support potential future meta-analyses on noise-related sleep disturbance. Cross-sectional analyses of actimetric data suggested sleep disturbance associated with , showing higher level of movements during the least active continuous 8-h time period [: 0.12 milligravitational units; 95% confidence interval (CI): 0.013, 0.23]. We also saw disrupted sleep-wake cycles as indicated by index scores of lower relative amplitude (: ; 95% CI: , ), poorer interdaily stability (: ; 95% CI: , ), and greater intradaily variability (: 0.021; 95% CI: 0.019, 0.023), comparing dB with dB. Repeated cross-sectional analyses found a 52% higher odds of more frequent daytime dozing [odds ratio (OR) ; 95% CI: 1.32, 1.75] for dB in comparison with dB, whereas the likelihood for more frequent sleeplessness was more uncertain (; 95% CI: 0.92, 1.39). Higher effect sizes were seen in preidentified vulnerable groups, including individuals of age and those with diabetes or dementia. Individuals exposed to higher levels of aircraft noise experienced objectively higher levels of sleep disturbance and changes in sleep-wake cycle. https://doi.org/10.1289/EHP14156.

P083 CHANGES IN STANDARD CUFF AND CENTRAL BLOOD PRESSURES ARE EQUALLY ASSOCIATED WITH CHANGES IN LEFT VENTRICULAR MASS: LONGITUDINAL ANALYSIS FROM THE UK BIOBANK COHORT STUDY

Background and objective. Central blood pressure (BP) measurement purports to aid hypertension management. This concept is founded on cross-sectional studies, however, findings are mixed and none report longitudinal relationships between changes in BP and outcomes. This study aimed to determine associations of changes in cuff BP and central BP with changes in left ventricular mass index (LVMi), as an important hypertension-related clinical outcome. Methods. Standard cuff BP and central BP (Vicorder, Skidmore Medical, UK; SBP/DBP calibration of waveforms) were measured at the same time as cardiac magnetic resonance imaging for LVMi among a cohort of adults from the UK Biobank Cohort Study assessed at two time points (2014+ and 2019+). Linear regression adjusted for demographic and clinical characteristics were used to determine cross sectional associations and associations between changes in cuff BP and central BP with LVMi. Results. Data were evaluable for 681 participants (aged 50.1±7.1 years, 54% female) followed over 1161±582 days (mean ± SD). Cross-sectional analysis showed the association of cuff systolic BP with LVMi (β±SE 3.47x10-2±6.38x10-3 g/m2.7/mmHg) and central systolic BP with LVMi (β±SE=3.52x10-2±6.40x10-3 g/m2.7/mmHg) were comparable (p&lt;0.001 both). In the longitudinal analysis, associations between the changes in BP and changes in LVMi were identical for both central and cuff systolic BP (β±SE=0.011±0.003 g/m2.7/mmHg; p&lt;0.001 both). Conclusion. Changes over time in standard cuff BP provides similar information to central BP on risk for hypertension-related changes in LVMi. These findings are likely to be generalisable to central BP devices using SBP/DBP calibration.

Reevaluating the fraction of cancer attributable to excess weight: overcoming the hidden impact of prediagnostic weight loss

ObjectiveTo evaluate the magnitude of the potential underestimation of the proportion of cancer cases attributable to excess weight, known as population attributable fraction (PAF), due to potential bias from prediagnostic weight loss already present at baseline of cohort studies and to overcome it as much as possible.MethodsData from the UK Biobank cohort participants aged 40–69 without prior cancer diagnosis were analyzed. We assessed the magnitude of associations of excess weight with the incidence of obesity-related cancers combined, and separately for gastrointestinal (GI) and other cancers. Using multivariable Cox proportional hazards models, hazard ratios (HR) and their 95% confidence intervals (CI), and PAFs for excess weight at baseline were estimated for various periods of time after weight measurements.FindingsOf 458,660 participants, 20,218 individuals developed obesity-related cancers during a median 11.0-year follow-up, comprising 8,460 GI, and 11,765 non-GI cancers. PAFs were much higher for cancers occurring more than four years after recruitment than for cancers occurring within the initial four years: 17.7% versus 7.2%, 21.4% versus 11.7% for GI, non-GI and all obesity-related cancers combined, respectively. With respect to total cancer (including cancers with no established relationship with excess weight), PAFs were estimated as 5.1% and 8.8% for the 0–4 and 4-14-year periods of follow-up.ConclusionThe proportion of cancers attributable to excess weight is likely substantially larger than previously estimated based on cohort studies with short follow-up time or no or only limited exclusion of the early years of follow-up from the analyses.

Association between common chronic pulmonary diseases and lung cancer: Mendelian randomization analysis

BackgroundLung cancer is a leading public health concern worldwide. Previous evidence suggests that chronic obstructive pulmonary disease (COPD) and asthma may contribute to its development. However, whether these common chronic pulmonary diseases are causal factors of lung cancer remained unclear.MethodsSummary statistics from genome-wide association studies (GWAS) were used for Mendelian randomization (MR) analysis. Genetic data for COPD were obtained from the Global Biobank Meta-Analysis Initiative, and asthma data were retrieved from the UK Biobank cohort. Suitable instrumental variables were selected based on quality control measures. GWAS summary data for lung cancer were obtained from a large study involved 85,716 participants. MR analysis was performed using various methods, and sensitivity analyses were conducted. Multivariable MR (MVMR) analysis was employed to account for potential confounding factors.ResultsOur MR analysis revealed a significant causal association between COPD and lung cancer, including its subtypes such as lung squamous cell carcinoma, lung adenocarcinoma, and small cell lung carcinoma. Genetically predicted COPD was associated with a 64% increased risk of lung cancer and a 2.3 to 2.8-fold increased risk of the different subtypes. However, in the MVMR analysis adjusting for smoking, alcohol drinking, and body mass index, the association between COPD and lung cancer became non-significant. No significant association was observed between asthma (childhood-onset and adult-onset) and lung cancer and its histological subtypes.ConclusionsOur study suggests a potential causal association between COPD and lung cancer. However, this association became non-significant after adjusting for smoking in the multivariable analysis.

Multifaceted association of overweight and metabolically unhealthy with the risk of Barrett's esophagus in the UK Biobank cohort

The association of overweight/obesity and metabolically unhealthy (MU) with the risk of developing Barrett's esophagus (BE) remains uncertain. We evaluated whether MU and overweight/obesity are associated with increased BE incidence and whether they have a synergistic impact on BE development. We analyzed the body mass index (BMI) and metabolic indicators at baseline of 402,510 individuals from the UK Biobank with no history of BE. Overweight/obesity and MU were defined as BMI ≥ 25.0 kg/m2 and presence of ≥ 1 MU indicators, respectively. Accordingly, the participants were categorized into four groups: (1) metabolically healthy non-overweight/obesity (MHNO), (2) metabolically unhealthy non-overweight/obesity (MUNO), (3) metabolically healthy overweight/obesity (MHO), and (4) metabolically unhealthy overweight/obesity (MUO). During a median follow-up of 13.5 years, 6195 (1.5%) individuals were newly diagnosed with BE. Among them, 39,281 (9.8%), 92,000 (22.9%), 25,297 (6.3%), and 245,932 (61.1%) individuals were classified as MHNO, MUNO, MHO, and MUO, respectively. In Cox regression analyses, both MU and overweight/obesity were independently associated with BE incidence. Moreover, BE incidence was significantly higher in the MUNO, MHO, and MUO groups, compared to the MHNO group. MU and overweight/obesity are independent risk factors for BE and have a synergistic effect on BE development.

Multi-omics correlates of insulin resistance and circadian parameters mapped directly from human serum.

While it is generally known that metabolic disorders and circadian dysfunction are intertwined, how the two systems affect each other is not well understood, nor are the genetic factors that might exacerbate this pathological interaction. Blood chemistry is profoundly changed in metabolic disorders, and we have previously shown that serum factors change cellular clock properties. To investigate if circulating factors altered in metabolic disorders have circadian modifying effects, and whether these effects are of genetic origin, we measured circadian rhythms in U2OS cell in the presence of serum collected from diabetic, obese or control subjects. We observed that circadian period lengthening in U2OS cells was associated with serum chemistry that is characteristic of insulin resistance. Characterizing the genetic variants that altered circadian period length by genome-wide association analysis, we found that one of the top variants mapped to the E3 ubiquitin ligase MARCH1 involved in insulin sensitivity. Confirming our data, the serum circadian modifying variants were also enriched in type 2 diabetes and chronotype variants identified in the UK Biobank cohort. Finally, to identify serum factors that might be involved in period lengthening, we performed detailed metabolomics and found that the circadian modifying variants are particularly associated with branched chain amino acids, whose levels are known to correlate with diabetes and insulin resistance. Overall, our multi-omics data showed comprehensively that systemic factors serve as a path through which metabolic disorders influence circadian system, and these can be examined in human populations directly by simple cellular assays in common cultured cells.

The prognostic impact of psychiatric intervention on alcohol-associated liver disease: The UK Biobank cohort study.

Alcohol-associated liver disease (ALD) is a public health concern. ALD patients often have psychiatric comorbidities, but the effects of psychiatric interventions on ALD are not well-established. This study explores the prognostic impact of psychiatric intervention on ALD within UK Biobank cohort. This population-based study included 2,417 ALD patients from the UK Biobank cohort. Psychiatric intervention was defined by a consultation with psychiatrists during hospitalization or a history of medication related to alcohol use disorder and psychiatric comorbidities. Survival analysis was conducted, incorporating propensity score matching (PSM), to precisely assess the impact of psychiatric intervention. Among 2,417 ALD patients, those with F10 (mental disorders due to alcohol) codes had poorer survival outcomes. Psychiatric intervention significantly improved the outcomes of both all-cause and liver-related mortality and reduced the incidence of liver cirrhosis. In subgroup or 2-year landmark analyses, psychiatric intervention consistently showed a survival benefit in ALD patients. In the multivariate analysis, psychiatric intervention was identified as a favorable prognostic factor (hazard ratio, 0.780; P=0.002 after PSM). This study demonstrates the favorable effect of psychiatric intervention in ALD patients with psychiatric comorbidities. These findings emphasize the importance of integrated management for ALD patients to address both their medical and psychiatric aspects. Therefore, we suggest the potential benefits of early psychiatric interventions in improving survival outcomes in ALD.