Diurnal timing of physical activity and risk of colorectal cancer in the UK Biobank.

BACKGROUND: Physical activity reduces colorectal cancer risk, yet the diurnal timing of physical activity in colorectal cancer etiology remains unclear. METHODS: This study used 24-h accelerometry time series from UK Biobank participants aged 42 to 79 years to derive circadian physical activity patterns using functional principal component analysis. Multivariable Cox proportional hazard models were used to examine associations with colorectal cancer risk. RESULTS: Among 86,252 participants (56% women), 529 colorectal cancer cases occurred during a median 5.3-year follow-up. We identified four physical activity patterns that explained almost 100% of the data variability during the day. A pattern of continuous day-long activity was inversely associated with colorectal cancer risk (hazard ratio (HR) = 0.94, 95% confidence interval (CI) = 0.89-0.99). A second pattern of late-day activity was suggestively inversely related to risk (HR = 0.93, 95% CI = 0.85-1.02). A third pattern of early- plus late-day activity was associated with decreased risk (HR = 0.89, 95% CI = 0.80-0.99). A fourth pattern of mid-day plus night-time activity showed no relation (HR = 1.02, 95% CI = 0.88-1.19). Our results were consistent across various sensitivity analyses, including the restriction to never smokers, the exclusion of the first 2 years of follow-up, and the adjustment for shift work. CONCLUSIONS: A pattern of early- plus late-day activity is related to reduced colorectal cancer risk, beyond the benefits of overall activity. Further research is needed to confirm the role of activity timing in colorectal cancer prevention.

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

BACKGROUND: Nighttime aircraft noise may affect people's sleep, yet large-scale evidence using objective and subjective measures remains limited. OBJECTIVE: Our aim was to investigate associations between nighttime aircraft noise exposure and objectively measured sleep disturbance using a large UK cohort. METHODS: 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 Lnight (23:00 hours-07:00 hours) and 7-d actimetric measures collected 2013-2015 (n=22,102). We also used Logit and generalized estimating equations models to examine associations between Lnight 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. RESULTS: Cross-sectional analyses of actimetric data suggested sleep disturbance associated with Lnight, showing higher level of movements during the least active continuous 8-h time period [ß: 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 (ß: -0.006; 95% CI: -0.007, -0.005), poorer interdaily stability (ß: -0.010; 95% CI: -0.014, -0.006), and greater intradaily variability (ß: 0.021; 95% CI: 0.019, 0.023), comparing Lnight ≥55 dB with <45 dB. Repeated cross-sectional analyses found a 52% higher odds of more frequent daytime dozing [odds ratio (OR) =1.52; 95% CI: 1.32, 1.75] for Lnight ≥55 dB in comparison with <45 dB, whereas the likelihood for more frequent sleeplessness was more uncertain (OR=1.13; 95% CI: 0.92, 1.39). Higher effect sizes were seen in preidentified vulnerable groups, including individuals >65y of age and those with diabetes or dementia. CONCLUSION: 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.

Hippocampal and limbic microstructure changes associated with stress across the lifespan: a UK biobank study.

Experiencing highly stressful events can have detrimental and lasting effects on brain morphology. The current study explores the effects of stress during childhood and adulthood on grey matter macro- and microstructure using a sub-sample of 720 participants from the UK Biobank with very high or very low childhood and adulthood stress scores. We used T1-weighted and diffusion MRI data to assess grey matter macro- and microstructure within bilateral hippocampus, amygdala and thalamus. Findings showed that childhood stress is associated with changes in microstructural measures bilaterally within the hippocampus and amygdala. No effects of adulthood stress on brain microstructure were found. No interaction effects between sex and stress (either childhood or adulthood) were observed for any brain imaging measure. Analysis of sub-segments of the hippocampus showed that childhood stress predominantly impacted the bilateral heads of the hippocampus. Overall, these findings suggest that highly stressful experiences during childhood, but not adulthood, have lasting impact on brain microstructure. The effects of these experiences in childhood appear to persist regardless of experiences of high or low stress in adulthood.

A systematic evaluation of the performance and properties of the UK Biobank Polygenic Risk Score (PRS) Release.

We assess the UK Biobank (UKB) Polygenic Risk Score (PRS) Release, a set of PRSs for 28 diseases and 25 quantitative traits that has been made available on the individuals in UKB, using a unified pipeline for PRS evaluation. We also release a benchmarking software tool to enable like-for-like performance evaluation for different PRSs for the same disease or trait. Extensive benchmarking shows the PRSs in the UKB Release to outperform a broad set of 76 published PRSs. For many of the diseases and traits we also validate the PRS algorithms in a separate cohort (100,000 Genomes Project). The availability of PRSs for 53 traits on the same set of individuals also allows a systematic assessment of their properties, and the increased power of these PRSs increases the evidence for their potential clinical benefit.

Genetic links between ovarian ageing, cancer risk and de novo mutation rates.

Human genetic studies of common variants have provided substantial insight into the biological mechanisms that govern ovarian ageing1. Here we report analyses of rare protein-coding variants in 106,973 women from the UK Biobank study, implicating genes with effects around five times larger than previously found for common variants (ETAA1, ZNF518A, PNPLA8, PALB2 and SAMHD1). The SAMHD1 association reinforces the link between ovarian ageing and cancer susceptibility1, with damaging germline variants being associated with extended reproductive lifespan and increased all-cause cancer risk in both men and women. Protein-truncating variants in ZNF518A are associated with shorter reproductive lifespan-that is, earlier age at menopause (by 5.61 years) and later age at menarche (by 0.56 years). Finally, using 8,089 sequenced trios from the 100,000 Genomes Project (100kGP), we observe that common genetic variants associated with earlier ovarian ageing associate with an increased rate of maternally derived de novo mutations. Although we were unable to replicate the finding in independent samples from the deCODE study, it is consistent with the expected role of DNA damage response genes in maintaining the genetic integrity of germ cells. This study provides evidence of genetic links between age of menopause and cancer risk.

Association between personality, lifestyle behaviors, and cardiovascular diseases in type 2 diabetes mellitus: a population-based cohort study of UK Biobank data.

INTRODUCTION: Various strategies aim to better assess risks and refine prevention for patients with type 2 diabetes mellitus (T2DM), who vary in cardiovascular disease (CVD) risk. However, the prognostic value of personality and its association with lifestyle factors remain elusive. RESEARCH DESIGN AND METHODS: We identified 8794 patients with T2DM from the UK Biobank database between 2006 and 2010 and followed them up until the end of 2021. We assessed personality traits using the Big Five proxies derived from UK Biobank data: sociability, warmth, diligence, curiosity, and nervousness. Healthy lifestyle behaviors were determined from information about obesity, smoking status, and physical activity. The primary outcome was a composite of incident CVD, including myocardial infarction (MI), ischemic stroke (IS), atrial fibrillation (AF), and heart failure (HF). RESULTS: During a median follow-up of 13.6 years, a total of 2110 patients experienced CVDs. Among personality traits, diligence was significantly associated with a reduced risk of primary and secondary outcomes. The adjusted HRs with 95% CIs were: composite CVD, 0.93 (0.89-0.97); MI 0.90 (0.82-1.00); IS 0.83 (0.74-0.94); AF 0.92 (0.85-0.98); HF 0.84 (0.76-0.91). Healthy lifestyle behaviors significantly reduced the risk of composite CVDs in groups with high and low diligence. The findings of a structural equation model showed that diligence directly affected the risk of the primary outcome or indirectly by modifying lifestyle behaviors. CONCLUSION: This study revealed which personality traits can influence CVD risk during T2DM and how patients might benefit from adopting healthy lifestyle behaviors in relation to personality.

NOTCH3 p.Arg1231Cys is markedly enriched in South Asians and associated with stroke.

The genetic factors of stroke in South Asians are largely unexplored. Exome-wide sequencing and association analysis (ExWAS) in 75 K Pakistanis identified NM_000435.3(NOTCH3):c.3691 C > T, encoding the missense amino acid substitution p.Arg1231Cys, enriched in South Asians (alternate allele frequency = 0.58% compared to 0.019% in Western Europeans), and associated with subcortical hemorrhagic stroke [odds ratio (OR) = 3.39, 95% confidence interval (CI) = [2.26, 5.10], p = 3.87 × 10-9), and all strokes (OR [CI] = 2.30 [1.77, 3.01], p = 7.79 × 10-10). NOTCH3 p.Arg231Cys was strongly associated with white matter hyperintensity on MRI in United Kingdom Biobank (UKB) participants (effect [95% CI] in SD units = 1.1 [0.61, 1.5], p = 3.0 × 10-6). The variant is attributable for approximately 2.0% of hemorrhagic strokes and 1.1% of all strokes in South Asians. These findings highlight the value of diversity in genetic studies and have major implications for genomic medicine and therapeutic development in South Asian populations.

Disease prediction with multi-omics and biomarkers empowers case-control genetic discoveries in the UK Biobank.

The emergence of biobank-level datasets offers new opportunities to discover novel biomarkers and develop predictive algorithms for human disease. Here, we present an ensemble machine-learning framework (machine learning with phenotype associations, MILTON) utilizing a range of biomarkers to predict 3,213 diseases in the UK Biobank. Leveraging the UK Biobank's longitudinal health record data, MILTON predicts incident disease cases undiagnosed at time of recruitment, largely outperforming available polygenic risk scores. We further demonstrate the utility of MILTON in augmenting genetic association analyses in a phenome-wide association study of 484,230 genome-sequenced samples, along with 46,327 samples with matched plasma proteomics data. This resulted in improved signals for 88 known (P < 1 × 10-8) gene-disease relationships alongside 182 gene-disease relationships that did not achieve genome-wide significance in the nonaugmented baseline cohorts. We validated these discoveries in the FinnGen biobank alongside two orthogonal machine-learning methods built for gene-disease prioritization. All extracted gene-disease associations and incident disease predictive biomarkers are publicly available ( http://milton.public.cgr.astrazeneca.com ).

Sleep patterns, genetic susceptibility, and venous thromboembolism: A prospective study of 384,758 UK Biobank participants.

BACKGROUND: Although healthy sleep patterns have been linked to a lower risk of cardiovascular disease in earlier research, it is unclear how beneficial they are for venous thromboembolism (VTE). AIM: This research aimed to examine the correlation between sleep patterns, genetic susceptibility, and VTE. METHODS: In the UK Biobank cohort, healthy sleep behaviors were defined as early chronotype, 7-8 hours of sleep each day, no snoring, infrequent insomnia, and infrequent daytime sleepiness. Each of the five criteria was given 1 point, creating a healthy sleep score ranging from 0 to 5. Cox proportional hazards regression models were utilized to examine the associations between genetic susceptibility, healthy sleep score and VTE. RESULTS: The UK Biobank study included 384,758 participants aged 56.6 ± 8.0 years. After a median of 11.9 years of follow-up, 8,885 (2.3%) participants were diagnosed with VTE. A healthy sleep score inversely affected VTE risk. For participants with a score of 5, the hazard ratio of VTE was 0.813 (95% confidence interval: 0.758-0.873, P<0.001) compared to those with a score ≤2. Early chronotype, sleeping 7-8 hours each day, infrequent insomnia, and infrequent daytime sleepiness were significantly associated with a 7.9%, 8.3%, 5.1%, and 20.7% lower risk of VTE, respectively. In addition, the correlation between sleep pattern and the incidence of VTE was consistent, regardless of genetic susceptibility (P for interaction = 0.366). CONCLUSIONS: Our secondary analysis of a large-scale prospectively gathered registry revealed that individuals with a healthy sleep pattern are significantly correlated with lower risk of developing VTE, irrespective of genetic susceptibility.

Association of Retinal Nerve Fiber Layer Thinning With Elevated High Density Lipoprotein Cholesterol in UK Biobank.

Purpose: The purpose of this study was to investigate the association between retinal nerve fiber layer (RNFL) thickness and high-density lipoprotein cholesterol (HDL-C) in a healthy population. Methods: This cross-sectional study included 31,738 UK Biobank participants with high quality optical coherence tomography (OCT) images, excluding those with neurological or ocular diseases. The locally estimated scatterplot smoothing (LOESS) curve and multivariable piecewise linear regression models were applied to assess the association between HDL-C and RNFL thickness, and HDL-C subclasses were further analyzed using nuclear magnetic resonance (NMR) spectroscopy. Results: Multivariate piecewise linear regression revealed that high HDL-C levels (>1.7 mmol/L in women or > 1.5 mmol/L in men) were associated with thinner RNFL thickness (women: ß = -0.13, 95% confidence interval [CI] = -0.23 to -0.02, P = 0.017; male: ß = -0.23, 95% CI = -0.37 to -0.10, P = 0.001). Conversely, a significant positive association between HDL-C and RNFL thickness was observed when HDL-C was between 1.4 and 1.7 mmol/L for female participants (ß = 0.13, 95% CI = 0.02 to 0.24, P = 0.025). NMR analysis showed that these associations are potentially driven by distinct HDL-C subclasses. Conclusions: This study revealed an association between HDL-C levels and retinal markers of neurodegenerative diseases, suggesting that elevated HDL-C may serve as a new risk factor for neurodegenerative conditions. These findings may contribute to the implementation of preventive interventions and improved patient outcomes.

Identifying combinations of long-term conditions associated with sarcopenia: a cross-sectional decision tree analysis in the UK Biobank study.

OBJECTIVES: This study aims to determine whether machine learning can identify specific combinations of long-term conditions (LTC) associated with increased sarcopenia risk and hence address an important evidence gap-people with multiple LTC (MLTC) have increased risk of sarcopenia but it has not yet been established whether this is driven by specific combinations of LTC. DESIGN: Decision trees were used to identify combinations of LTC associated with increased sarcopenia risk. Participants were classified as being at risk of sarcopenia based on maximum grip strength of <32 kg for men and <19 kg for women. The combinations identified were triangulated with logistic regression. SETTING: UK Biobank. PARTICIPANTS: UK Biobank participants with MLTC (two or more LTC) at baseline. RESULTS: Of 140 001 participants with MLTC (55.3% women, median age 61 years), 21.0% were at risk of sarcopenia. Decision trees identified several LTC combinations associated with an increased risk of sarcopenia. These included drug/alcohol misuse and osteoarthritis, and connective tissue disease and osteoporosis in men, which showed the relative excess risk of interaction of 3.91 (95% CI 1.71 to 7.51) and 2.27 (95% CI 0.02 to 5.91), respectively, in age-adjusted models. CONCLUSION: Knowledge of LTC combinations associated with increased sarcopenia risk could aid the identification of individuals for targeted interventions, recruitment of participants to sarcopenia studies and contribute to the understanding of the aetiology of sarcopenia.

A metabolomic profile of biological aging in 250,341 individuals from the UK Biobank.

The metabolomic profile of aging is complex. Here, we analyse 325 nuclear magnetic resonance (NMR) biomarkers from 250,341 UK Biobank participants, identifying 54 representative aging-related biomarkers associated with all-cause mortality. We conduct genome-wide association studies (GWAS) for these 325 biomarkers using whole-genome sequencing (WGS) data from 95,372 individuals and perform multivariable Mendelian randomization (MVMR) analyses, discovering 439 candidate "biomarker - disease" causal pairs at the nominal significance level. We develop a metabolomic aging score that outperforms other aging metrics in predicting short-term mortality risk and exhibits strong potential for discriminating aging-accelerated populations and improving disease risk prediction. A longitudinal analysis of 13,263 individuals enables us to calculate a metabolomic aging rate which provides more refined aging assessments and to identify candidate anti-aging and pro-aging NMR biomarkers. Taken together, our study has presented a comprehensive aging-related metabolomic profile and highlighted its potential for personalized aging monitoring and early disease intervention.

The association of psychological and trauma-related factors with biological and facial aging acceleration: evidence from the UK Biobank.

BACKGROUND: Psychological and trauma-related factors are associated with many diseases and mortality. However, a comprehensive assessment of the association between psycho-trauma exposures and aging acceleration is currently lacking. METHODS: Using data from 332,359 UK Biobank participants, we calculated biological aging acceleration, indexed by the presence of leukocyte telomere length (LTL) deviation (i.e., the difference between genetically determined and observed LTL > 0). The acceleration of facial aging (i.e., looking older than the chronological age) was assessed using a self-report question. Then, we estimated the associations of each psycho-trauma factor with biological and facial aging acceleration, using logistic regression models adjusted for multiple important covariates. Furthermore, restricted to 99,180 participants with complete psychological and trauma-related data, we identified clusters of individuals with distinct psycho-trauma patterns using the latent class analysis method and assessed their associations with aging acceleration using similar models. RESULTS: We observed most of the studied psycho-trauma factors were associated with biological and facial aging acceleration. Compared to the "Absence of trauma and psychopathology" cluster, the "adverse childhood experiences (ACEs) with psychopathology" cluster showed strong associations with those aging measurements (odds ratio [OR] = 1.13 [1.05 - 1.23] for biological and 1.52 [1.18 - 1.95] for facial aging acceleration), while no such association was observed for the "ACEs without psychopathology" cluster (1.04 [0.99 - 1.09] and 1.02 [0.84 - 1.24]. CONCLUSIONS: Our study demonstrated significant associations of psycho-trauma factors with both biological and facial aging acceleration. The differential aging consequences observed among ACEs exposed individuals with and without psychopathology prompt interventions aimed to improve individuals' psychological resilience to prevent aging acceleration.

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

BACKGROUND: The 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. METHODS: We 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. RESULTS: Over 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. CONCLUSIONS: Maintaining 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.

Joint and interactive associations of body mass index and genetic factors with cardiovascular disease: a prospective study in UK Biobank.

BACKGROUND: Both body mass index (BMI) and genetic factors independently contribute to cardiovascular disease (CVD). However, it is unclear whether genetic risk modifies the association between BMI and the risk of incident CVD. This study aimed to investigate whether BMI categories and genetic risk jointly and interactively contribute to incident CVD events, including hypertension (HTN), atrial fibrillation (AF), coronary heart disease (CHD), stroke, and heart failure (HF). METHODS: A total of 496,851 participants from the UK Biobank with one or more new-onset CVD events were included in the analyses. BMI was categorized as normal weight (< 25.0 kg/m2), overweight (25.0-29.9 kg/m2), and obesity (≥ 30.0 kg/m2). Genetic risk for each outcome was defined as low (lowest tertile), intermediate (second tertile), and high (highest tertile) using polygenic risk score. The joint associations of BMI categories and genetic risk with incident CVD were investigated using Cox proportional hazard models. Additionally, additive interactions were evaluated. RESULTS: Among the 496,851 participants, 270,726 (54.5%) were female, with a mean (SD) age was 56.5 (8.1) years. Over a median follow-up (IQR) of 12.4 (11.5-13.1) years, 102,131 (22.9%) participants developed HTN, 26,301 (5.4%) developed AF, 32,222 (6.9%) developed CHD, 10,684 (2.2%) developed stroke, and 13,304 (2.7%) developed HF. Compared with the normal weight with low genetic risk, the obesity with high genetic risk had the highest risk of CVD: HTN (HR: 3.96; 95%CI: 3.84-4.09), AF (HR: 3.60; 95%CI: 3.38-3.83), CHD (HR: 2.76; 95%CI: 2.61-2.91), stroke (HR: 1.44; 95%CI: 1.31-1.57), and HF (HR: 2.47; 95%CI: 2.27-2.69). There were significant additive interactions between BMI categories and genetic risk for HTN, AF, and CHD, with relative excess risk of 0.53 (95%CI: 0.43-0.62), 0.67 (95%CI: 0.51-0.83), and 0.37 (95%CI: 0.25-0.49), respectively. CONCLUSIONS: BMI and genetic factors jointly and interactively contribute to incident CVD, especially among participants with high genetic risk. These findings have public health implications for identifying populations more likely to have cardiovascular benefit from weight loss interventions.

Association between surgical admissions, cognition, and neurodegeneration in older people: a population-based study from the UK Biobank.

BACKGROUND: Previous studies have shown that major surgical and medical hospital admissions are associated with cognitive decline in older people (aged 40-69 years at recruitment), which is concerning for patients and caregivers. We aimed to validate these findings in a large cohort and investigate associations with neurodegeneration using MRI. METHODS: For this population-based study, we analysed data from the UK Biobank collected from March 13, 2006, to July 16, 2023, linked to the National Health Service Hospital Episode Statistics database, excluding participants with dementia diagnoses. We constructed fully adjusted models that included age, time, sex, Lancet Commission dementia risk factors, stroke, and hospital admissions with a participant random effect. Primary outcomes were hippocampal volume and white matter hyperintensities, both of which are established markers of neurodegeneration, and exploratory analyses investigated the cortical thickness of Desikan-Killiany-Tourville atlas regions. The main cognitive outcomes were reaction time, fluid intelligence, and prospective and numeric memory. Surgeries were calculated cumulatively starting from 8 years before the baseline evaluation. FINDINGS: Of 502 412 participants in the UK Biobank study, 492 802 participants were eligible for inclusion in this study, of whom 46 706 underwent MRI. Small adverse associations with cognition were found per surgery: reaction time increased by 0·273 ms, fluid intelligence score decreased by 0·057 correct responses, prospective memory (scored as correct at first attempt) decreased (odds ratio 0·96 [95% CI 0·95 to 0·97]), and numeric memory maximum correct matches decreased by 0·025 in fully adjusted models. Surgeries were associated with smaller hippocampal volume (ß=-5·76 mm³ [-7·89 to -3·64]) and greater white matter hyperintensities volume (ß=100·02 mm³ [66·17 to 133·87]) in fully adjusted models. Surgeries were also associated with neurodegeneration of the insula and superior temporal cortex. INTERPRETATION: This population-based study corroborates that surgeries are generally safe but cumulatively are associated with cognitive decline and neurodegeneration. Perioperative brain health should be prioritised for older and vulnerable patients, particularly those who have multiple surgical procedures. FUNDING: The Australian and New Zealand College of Anaesthetists (ANZCA) Foundation and the University of Sydney.

Association of triglyceride-glucose index and its combination with adiposity-related indices with the incidence of myocardial infarction: a cohort study from the UK Biobank.

BACKGROUND: The triglyceride-glucose (TyG) index performs better at reflecting insulin resistance when combined with waist circumference (WC), body mass index (BMI), and waist-to-height ratio (WHtR) than when used alone. This study aimed to prospectively examine the relationships between TyG, TyG-BMI, TyG-WC, and TyG-WHtR with the incidence of myocardial infarction (MI) and its subtypes. METHODS: This cohort study included 370,390 participants from the UK Biobank. The Cox proportional hazards model and restricted cubic spline regression model were used to assess the associations of TyG, TyG-BMI, TyG-WC, and TyG-WHtR with MI, ST-elevation MI (STEMI) and non-ST-elevation MI (NSTEMI). The receiver operating characteristic (ROC) curve and the area under the curve (AUC) were employed to examine the predictive value of four indicators. RESULTS: The hazard ratios (HRs) and 95% confidence intervals (CIs) of MI in the highest quartiles for TyG, TyG-BMI, TyG-WC, and TyG-WHtR were 1.36 (1.28-1.44), 1.47 (1.39-1.56), 1.53 (1.43-1.64), and 1.58 (1.48-1.68) in the fully-adjusted model. Comparable findings were observed when the outcomes were reclassified as STEMI or NSTEMI. However, the associations of TyG-BMI, TyG-WC, and TyG-WHtR with the risk of STEMI were weaker than MI and NSTEMI. A linear dose-response association between TyG and the risk of MI and NSTEMI were demonstrated. TyG-BMI, TyG-WC, and TyG-WHtR all showed nonlinear patterns in their associations with the risk of MI, STEMI, and NSTEMI. TyG-WC was most effective in diagnosing MI (AUC: 0.648, 95% CI: 0.644-0.653), STEMI (AUC: 0.631, 95% CI: 0.622-0.639), and NSTEMI (AUC: 0.647, 95% CI: 0.641-0.654). CONCLUSION: The TyG index was linearly associated with increased risk of MI and NSTEMI, whereas TyG-BMI, TyG-WC, and TyG-WHtR were nonlinearly associated with increased risk of MI and NSTEMI. There were distinct patterns in the relationships between these indicators with STEMI. TyG-WC provided the best diagnostic effectiveness for MI, STEMI, and NSTEMI.

Unraveling the influence of childhood emotional support on adult aging: Insights from the UK Biobank.

BACKGROUND: Exploring the association between Childhood Emotional Support (CES) and the mechanisms of aging is pivotal for understanding its potential to lessen the incidence of age-related pathologies and promote a milieu for healthy aging. METHODS: Utilizing data from the UK Biobank comprising nearly 160,000 individuals, comprehensive analyses were conducted to explore associations between CES levels and age-related diseases, biological age and aging hallmarks. Cox proportional hazards regression models were used to investigate the relationship between CES and the risk of hospitalization for age-related diseases. Linear regression models were employed to explore the associations between CES and the frailty index (FI), Klemera-Doubal method (KDM) biological age acceleration, homeostatic dysregulation (HD), C-reactive protein (CRP), white blood cell (WBC) count, and telomere length. RESULTS: The analyses revealed a significant association between higher CES levels and a decreased risk of hospitalization for age-related diseases in later life. After adjustments for covariates, the hazard ratio for age-related diseases was 0.87 (95 % confidence interval, 0.83-0.91, p < 0.001) in those with the highest CES level compared to those with the lowest CES level. Participants with the highest CES level exhibited lower FI scores (coefficient = -0.033, p < 0.001), reduced CRP level (coefficient = -0.097, p < 0.05) and lower WBC counts (coefficient = -0.034, p < 0.05). Stratified analyses based on genetic susceptibility further elucidated the protective role of CES against age-related diseases. CONCLUSION: These findings underscore the potential of early interventions targeting CES to promote healthy aging and alleviating the burden of age-related diseases.

Serum Uric Acid Levels Associated with Outcomes of Neurodegenerative Disorders and Brain Health: Findings from the UK Biobank.

BACKGROUND: The relationship between serum uric acid (SUA) levels and brain-related health remains uncertain. OBJECTIVES: This study aimed to investigate the relationship between SUA levels and some neurodegenerative disorders and brain structure. DESIGN: A longitudinal study. SETTING AND PARTICIPANTS: 384,517 participants who did not have stroke, dementia, and Parkinsonism, with complete urate testes and covariates were included. MEASUREMENTS: Cox proportional hazards models, competing risk models, and restricted cubic spine models were applied. RESULTS: During the median follow-up time of 12.7 years (interquartile range [IQR]:12.0, 13.5), 7821 (2.0%) participants developed stroke, 5103 (1.3%) participants developed dementia, and 2341 (0.6%) participants developed Parkinsonism. Nonlinear relationships were identified between SUA levels and stroke (J-shaped), dementia, and Parkinsonism (U-shaped). SUA levels of 4.2 mg/dl, 6.4 mg/dl, and 6.6 mg/dl yielded the lowest risk of stroke, dementia, and Parkinsonism, respectively. Besides, we found high SUA levels reduced the volumes of total brain, grey matter, white matter, grey matter in the hippocampus, and hippocampus, but increased lateral-ventricle volume. Inflammation accounted for 9.1% and 10.0% in the association of SUA with stroke and lateral-ventricle volume. CONCLUSIONS: Lower SUA levels increased the risk of Parkinsonism, while both lower and higher SUA levels were positively associated with increased risk of stroke and dementia. Moreover, high SUA levels reduced brain structure volumes. Our findings suggest the association between SUA levels and brain-related disorders and highlight the importance of SUA management.

A Genomics England haplotype reference panel and imputation of UK Biobank.

We built a reference panel with 342 million autosomal variants using 78,195 individuals from the Genomics England (GEL) dataset, achieving a phasing switch error rate of 0.18% for European samples and imputation quality of r2 = 0.75 for variants with minor allele frequencies as low as 2 × 10-4 in white British samples. The GEL-imputed UK Biobank genome-wide association analysis identified 70% of associations found by direct exome sequencing (P < 2.18 × 10-11), while extending testing of rare variants to the entire genome. Coding variants dominated the rare-variant genome-wide association results, implying less disruptive effects of rare non-coding variants.