Search

Abstract Background The low-grade inflammation score (INFLA-score) is a composite index that assesses chronic inflammatory status using multiple inflammatory markers. However, its correlation with cardiometabolic diseases (CMDs) in obese populations remains unclear. Methods We conducted a prospective cohort study involving 79,160 participants with obesity (BMI ≥ 30 kg/m2) from the UK Biobank. The INFLA-score was calculated based on high-sensitivity C-reactive protein, leukocyte count, platelet count and granulocyte/lymphocyte ratio. We employed Kaplan–Meier survival curves, multivariable Cox regression, restricted cubic splines and accelerated time-to-failure models to analyse the association between the INFLA-score and CMDs risk, including coronary heart disease (CAD), stroke and type 2 diabetes mellitus (T2DM). Results Over a median follow-up of 161.41 months, we recorded 14,903 CMDs events, comprising 7184 CAD cases, 1914 strokes and 7924 T2DM cases. Cox regression analysis revealed that each unit increase in the INFLA-score corresponded to a 1.5%, 1.1%, 1.2% and 2.4% increase CMDs risk (HR: 1.015, 95% CI 1.013–1.018), CAD risk (HR: 1.011, 95% CI 1.007–1.015), stroke risk (HR: 1.012, 95% CI 1.004–1.020) and T2DM risk (HR: 1.024, 95% CI 1.020–1.028), respectively. Restricted cubic spline analysis indicated a non-linear relationship between cumulative INFLA-score and CMDs risk (P = 0.044). Subgroup analysis revealed interactions between sex, age, history of lipid-lowering drug use, and INFLA-score regarding CMDs risk. Sensitivity analysis corroborated the main findings. Conclusion Our findings strongly support the close association between INFLA-score and CMDs risk, particularly notable in women, those aged

Abstract Background Computational variant effect predictors offer a scalable and increasingly reliable means of interpreting human genetic variation, but concerns of circularity and bias have limited previous methods for evaluating and comparing predictors. Population-level cohorts of genotyped and phenotyped participants that have not been used in predictor training can facilitate an unbiased benchmarking of available methods. Using a curated set of human gene-trait associations with a reported rare-variant burden association, we evaluate the correlations of 24 computational variant effect predictors with associated human traits in the UK Biobank and All of Us cohorts. Results AlphaMissense outperformed all other predictors in inferring human traits based on rare missense variants in UK Biobank and All of Us participants. The overall rankings of computational variant effect predictors in these two cohorts showed a significant positive correlation. Conclusion We describe a method to assess computational variant effect predictors that sidesteps the limitations of previous evaluations. This approach is generalizable to future predictors and could continue to inform predictor choice for personal and clinical genetics.

Abstract Background Liver disease and dementia are both highly prevalent and share common pathological mechanisms. We aimed to investigate the associations between metabolic dysfunction-associated fatty liver disease (MAFLD), metabolic dysfunction-associated steatotic liver disease (MASLD) and the risk of all-cause and cause-specific dementia. Methods We conducted a prospective study with 403,506 participants from the UK Biobank. Outcomes included all-cause dementia, Alzheimer’s disease, and vascular dementia. Multivariable Cox proportional hazards models were used for analyses. Results 155,068 (38.4%) participants had MAFLD, and 111,938 (27.7%) had MASLD at baseline. During a median follow-up of 13.7 years, 5,732 participants developed dementia (2,355 Alzheimer’s disease and 1,274 vascular dementia). MAFLD was associated with an increased risk of vascular dementia (HR 1.32 [95% CI 1.18–1.48]) but a reduced risk of Alzheimer’s disease (0.92 [0.84–1.0]). Differing risks emerged among MAFLD subtypes, with the diabetes subtype increasing risk of all-cause dementia (1.8 [1.65–1.96]), vascular dementia (2.95 [2.53–3.45]) and Alzheimer’s disease (1.46 [1.26–1.69]), the lean metabolic disorder subtype only increasing vascular dementia risk (2.01 [1.25–3.22]), whereas the overweight/obesity subtype decreasing risk of Alzheimer’s disease (0.83 [0.75–0.91]) and all-cause dementia (0.9 [0.84–0.95]). MASLD was associated with an increased risk of vascular dementia (1.24 [1.1–1.39]) but not Alzheimer’s disease (1.0 [0.91–1.09]). The effect of MAFLD on vascular dementia was consistent regardless of MASLD presence, whereas associations with Alzheimer’s disease were only present in those without MASLD (0.78 [0.67–0.91]). Conclusions MAFLD and MASLD are associated with an increased risk of vascular dementia, with subtype-specific variations observed in dementia risks. Further research is needed to refine MAFLD and SLD subtyping and explore the underlying mechanisms contributing to dementia risk.

Abstract Background Although fish oil has been considered to have an anti-inflammatory effect and has been proven to play a beneficial role in the incidence of numerous diseases, the association between fish oil supplementation and the risk of systemic lupus erythematosus (SLE) is still unknown. This study aimed at evaluating the correlation between fish oil use and incident SLE in a large population-based prospective cohort. Methods 390,277 participants without SLE at baseline from the UK Biobank were enrolled. Fish oil use was ascertained through a touchscreen questionnaire at baseline. The incidence of SLE was identified by the International Classification of Diseases version 10 code in medical records or self-report. Cox proportional hazard models were employed to estimate the association between fish oil use and SLE risk. Results Fish oil users accounted for 31.47% of participants. During a median follow-up duration of 11.57 years, 141 participants without fish oil use (4.56/100 000 person-years) and 68 participants with fish oil use (4.78/100 000 person-years) developed SLE. In four models with adjustments for different amounts of confounders, there was no significant difference in the risk of SLE between fish oil users and fish oil non-users (all p-values > 0.05). In subgroup analyses, we found that fish oil supplementation was associated with a lower risk of SLE among females with ultraviolet radiation ≥ 3 h/day (hazard ratio: 0.63, 95% confidence interval: 0.40–0.98), which turned insignificant after further adjustment for female-related factors and sun protection measures. Conclusions No significant association between fish oil use and overall incident SLE was observed, except in females exposed to prolonged ultraviolet radiation. Subgroup analysis suggested that females exposed to prolonged ultraviolet radiation might benefit from fish oil supplementation in terms of preventing SLE, but it needs to be confirmed in further studies.

Abstract Background Type 2 diabetes is associated with a variety of complications, including micro- and macrovascular complications, neurological manifestations and poor wound healing. Adhering to a Mediterranean Diet (MED) is generally considered an effective intervention in individuals at risk for type 2 diabetes mellitus (T2DM). However, little is known about its effect with respect to the different specific manifestations of T2DM. This prompted us to explore the effect of MED on the three most significant microvascular complications of T2DM: diabetic retinopathy (DR), diabetic kidney disease (DKD), and vascular diabetic neuropathies (DN). Methods We examined the association between the MED and the incidence of these microvascular complications in a prospective cohort of 33,441 participants with hyperglycemia free of microvascular complications at baseline, identified in the UK Biobank. For each individual, we calculated the Alternate Mediterranean Diet (AMED) score, which yields a semi-continuous measure of the extent to which an individual’s diet can be considered as MED. We used Cox proportional hazard models to analyze hazard ratios (HRs) and 95% confidence intervals (CIs), adjusting for demographics, lifestyle factors, medical histories and cardiovascular risk factors. Results Over a median of 12.3 years of follow-up, 3,392 cases of microvascular complications occurred, including 1,084 cases of diabetic retinopathy (DR), 2,184 cases of diabetic kidney disease (DKD), and 632 cases of diabetic neuropathies (DN), with some patients having 2 or 3 microvascular complications simultaneously. After adjusting for confounders, we observed that higher AMED scores offer protection against DKD among participants with hyperglycemia (comparing the highest AMED scores to the lowest yielded an HR of 0.79 [95% CIs: 0.67, 0.94]). Additionally, the protective effect of AMED against DKD was more evident in the hyperglycemic participants with T2DM (HR, 0.64; 95% CI: 0.50, 0.83). No such effect, however, was seen for DR or DN. Conclusions In this prospective cohort study, we have demonstrated that higher adherence to a MED is associated with a reduced risk of DKD among individuals with hyperglycemia. Our study emphasizes the necessity for continued research focusing on the benefits of the MED. Such efforts including the ongoing clinical trial will offer further insights into the role of MED in the clinical management of DKD.

Background: Both ambient air pollution and lifestyle factors contribute to the incidence of non-alcoholic fatty liver disease (NAFLD), but previous studies usually focused on single-factor associations. We aimed to assess the joint associations of ambient air pollution and lifestyle with the NAFLD risk and investigate whether lifestyle modifies the association of air pollution with NAFLD risk. Methods: A total of 417,025 participants from the UK Biobank were included in this study. Annual average concentrations of NO2, NOx, PM2.5, PM10, and PM2.5−10 were estimated. A composite lifestyle score was determined based on physical activity, alcohol intake, smoking status, dietary patterns, sedentary time, and sleep duration. Cox proportional hazards regression models were used to estimate the hazard ratios (HRs) and 95% confidence intervals (CIs), as well as the population attributable fraction (PAF). Potential additive interactions of air pollution with lifestyle were also examined by the relative excess risk due to the interaction (RERI) and the attributable proportion due to the interaction (AP). Results: 4752 (1.14%) incident NAFLD events were recorded. Long-term exposure to air pollutants and an unhealthy lifestyle were significantly associated with the increased risk of incident NAFLD. Lifestyle was the primary factor of incident NAFLD, with a PAF of 37.18% (95% CI: 29.67%, 44.69%). In addition, a significant additive interaction between air pollution and lifestyle for NAFLD risk was observed (RERI: 0.36, 95% CI: 0.09–0.63). Conclusions: Long-term exposure to ambient air pollutants and poor lifestyle were jointly associated with a higher risk of NAFLD. [ABSTRACT FROM AUTHOR]

Background: Parkinson's disease (PD) is a neurodegenerative influenced by various clinical factors. The potential relationship between renal function and the risk of PD remains poorly understood. This study aims to explore the association between kidney function and the risk of developing PD. Methods: A population-based cohort study was conducted using data from 400,571 UK Biobank participants. Renal function was assessed using the estimated glomerular filtration rate (eGFR), calculated from serum creatinine and cystatin C levels. The association between eGFR levels and PD risk was evaluated using univariate and multivariate Cox regression analyses, Restricted Cubic Spline (RCS) analysis, and Kaplan-Meier analysis. Additionally, a clinical prediction model was developed and its diagnostic accuracy was evaluated using ROC analysis. A heatmap was also constructed to examine the relationship between clinical factors and gray matter volume in various brain regions. Results: Over a median observation period of 13.8 years, 2740 PD events were recorded. Cox regression and Kaplan-Meier analyses revealed a significant association between decreased eGFR and increased PD risk, particularly in participants with eGFR < 30 ml/min/1.73 m2. This association was confirmed across three adjusted models. RCS analysis demonstrated a nonlinear relationship between decreasing eGFR and increasing PD risk. Furthermore, changes in eGFR were correlated with alterations in subcortical gray matter volume in regions such as the frontal cortex, striatum, and cerebellum. The clinical prediction model showed high diagnostic accuracy with AUC values of 0.776, 0.780, and 0.824 for 4-, 8-, and 16-year predictions, respectively. Conclusion: Renal insufficiency is significantly associated with an increased risk of PD, highlighting the importance of maintaining good kidney function as a potential preventive measure against PD. [ABSTRACT FROM AUTHOR]

Previous studies only focused on the individual social factors, without considering the overall social health patterns. The present study aimed to develop an integrated social health score (SHS) and investigate its associations with all-cause, cardiovascular disease (CVD), cancer mortality. A total of 330,716 participants (mean age 56.3 years; 52.4 % female) from UK Biobank was included between 2006 and 2010, and thereafter followed up to 2021. SHS was calculated by using information on social connections, social engagement and social support. Cox proportional hazards models was used to estimate the hazard ratios and 95 % confidence intervals (CIs) of the association between SHS and all-cause and cause-specific mortality and the 4-way decomposition was used to quantify the mediating effect of lifestyle factors. During a median follow-up period of 12.4 years, 37,897 death cases were recorded, including 4347 CVD and 10,380 cancer cases. The SHS was inversely associated with the risks of all-cause, CVD and cancer mortality in a dose-dependent manner (P for trend <0.001). The association between SHS with all-cause mortality was mediated by lifestyle factors including diet score, smoking status and alcohol consumption. Integrated SHS was inversely associated with risks of all-cause, CVD and cancer mortality, and the associations were partially mediated by lifestyle factors. Our study highlights the importance of maintaining high levels of social health by jointly enhancing social involvement, expanding social networks, and cultivating enduring intimate relationships across the life course. • The social health score was calculated based on information about social connections, engagement, and support, indicting better social health with higher scores. • Social health score was inversely associated with risks of all-cause, CVD and cancer mortality. • The association between social health score with all-cause mortality was mediated by lifestyle factors, including diet score, smoking status, and alcohol consumption. [ABSTRACT FROM AUTHOR]

Accumulating evidence suggests that latent infection with Toxoplasma gondii (T. gondii) is associated with a variety of neuropsychiatric and behavioral conditions. This research aims to explore the potential correlation between T. gondii antibody positivity and neuropsychiatric disorders through a comprehensive prospective cohort study. The cohort study utilized the UK Biobank database to recruit 8814 individuals with no prior diagnosis of neuropsychiatric disorders. Cox proportional hazards models were employed to investigate the associations between T. gondii P22 antibody seropositivity (P22+) and the development of various types of neuropsychiatric disorders. Of the population, 14.65 % tested positive for T. gondii P22 antibody. The presence of T. gondii P22 antibody showed a slight inverse association with epilepsy (HR: 0.28; 95 % CI: 0.10–0.77), while it was positively associated with an increased risk of developing anxiety disorders (HR: 1.38; 95 % CI: 1.04–1.83). The study sample consisted mostly of white British individuals aged 40 to 69 years old. Although we adjusted for potential confounders, there may be other unmeasured and residual confounding factors that could have influenced our reported associations. The findings suggested an increased risk of anxiety and potential evidence of epilepsy associated with T. gondii P22+. However, our analysis did not reveal an increased risk of several other neuropsychiatric conditions including Alzheimer's disease, dementia, substance abuse disorders, depression, and neurodegenerative disorders, associated with P22 antibody seropositivity. • In the UKB, 14.65% of the subjects tested were found to be positive for the T. gondii P22 antibody. • A significant association was observed between T. gondii P22+ and anxiety in a prospective cohort study. • T. gondii P22 antibody-positive individuals had a slightly higher incidence density of neuropsychiatric disorders. [ABSTRACT FROM AUTHOR]

Background: The causal relationship between daytime napping and the risk of Parkinson's disease (PD) remains unclear, with prospective studies providing limited evidence. This study investigated the association between daytime napping frequency and duration and PD incidence and explored the causality relationship between this association by conducting Mendelian randomization (MR) analysis. Methods: This prospective cohort study included 393,302 participants, and accelerometer-measured daytime napping data were available only for 78,141 individuals. Cox proportional hazards regression was used to estimate the association between the daytime napping frequency and duration and the PD risk. The role of the systemic immune-inflammation index (SII) in the association between daytime napping frequency and PD risk was assessed through mediation analyses. Moreover, the causal association between the daytime napping frequency and the PD risk was preliminarily explored by conducting two-sample MR analyses. Results: The median follow-up duration was 12.18 years. The participants who reported napping sometimes or usually exhibited a significantly higher PD risk than those who never/rarely napped during the day [sometimes: hazard ratio (HR), 1.13; 95% confidence interval (CI), 1.03–1.23; usually: HR, 1.33; 95% CI, 1.14–1.55], and SII played a mediating role in this association. However, the MR analyses did not indicate that the daytime napping frequency and PD risk were significantly associated. The participants napping for over 1 h exhibited a significantly elevated PD risk (HR, 1.54; 95% CI, 1.11–2.16). Moreover, no significant interaction was identified between napping frequency or duration and genetic susceptibility to PD (P for interaction > 0.05). Conclusions: In this study, increased daytime napping frequency and duration were associated with an increased PD risk, but no causal relationship was observed between napping frequency and PD risk in the MR analysis. Larger GWAS-based cohort studies and MR studies are warranted to explore potential causal relationships. [ABSTRACT FROM AUTHOR]

Background: The temporal relationships across cardiometabolic diseases (CMDs) were recently conceptualized as the cardiometabolic continuum (CMC), sequence of cardiovascular events that stem from gene-environmental interactions, unhealthy lifestyle influences, and metabolic diseases such as diabetes, and hypertension. While the physiological pathways linking metabolic and cardiovascular diseases have been investigated, the study of the sex and population differences in the CMC have still not been described. Methods: We present a machine learning approach to model the CMC and investigate sex and population differences in two distinct cohorts: the UK Biobank (17,700 participants) and the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil) (7162 participants). We consider the following CMDs: hypertension (Hyp), diabetes (DM), heart diseases (HD: angina, myocardial infarction, or heart failure), and stroke (STK). For the identification of the CMC patterns, individual trajectories with the time of disease occurrence were clustered using k-means. Based on clinical, sociodemographic, and lifestyle characteristics, we built multiclass random forest classifiers and used the SHAP methodology to evaluate feature importance. Results: Five CMC patterns were identified across both sexes and cohorts: EarlyHyp, FirstDM, FirstHD, Healthy, and LateHyp, named according to prevalence and disease occurrence time that depicted around 95%, 78%, 75%, 88% and 99% of individuals, respectively. Within the UK Biobank, more women were classified in the Healthy cluster and more men in all others. In the EarlyHyp and LateHyp clusters, isolated hypertension occurred earlier among women. Smoking habits and education had high importance and clear directionality for both sexes. For ELSA-Brasil, more men were classified in the Healthy cluster and more women in the FirstDM. The diabetes occurrence time when followed by hypertension was lower among women. Education and ethnicity had high importance and clear directionality for women, while for men these features were smoking, alcohol, and coffee consumption. Conclusions: There are clear sex differences in the CMC that varied across the UK and Brazilian cohorts. In particular, disadvantages regarding incidence and the time to onset of diseases were more pronounced in Brazil, against woman. The results show the need to strengthen public health policies to prevent and control the time course of CMD, with an emphasis on women. [ABSTRACT FROM AUTHOR]

Background: Accumulating evidence suggests that cardiovascular diseases and breast cancer share a number of common risk factors, however, evidence on the association between cardiovascular health (CVH) and breast cancer is limited. The present study aimed to assess the association of CVH, defined by Life's Essential 8 (LE8) and genetic risk with breast cancer incidence and mortality among premenopausal and postmenopausal women. Methods: We used data from the UK Biobank and conducted the multivariate Cox proportional-hazards models to examine associations of LE8 score and genetic risk with breast cancer incidence and mortality. Date on LE8 score was collected between 2006 and 2010 and composed of eight components, including behavioral metrics (diet, tobacco or nicotine exposure, physical activity, and sleep health), and biological metrics (body mass index, blood lipids, blood glucose, and blood pressure). The polygenic risk score (PRS) was calculated as the sum of effect sizes of individual genetic variants multiplied by the allele dosage. Results: A total of 150,566 premenopausal and postmenopausal women were included. Compared to postmenopausal women with low LE8 score, those with high LE8 score were associated with 22% lower risk of breast cancer incidence (HR: 0.78, 95% CI: 0.70–0.87) and 43% lower risk of breast cancer mortality (HR: 0.57, 95% CI: 0.36–0.90). By contrast, we did not observe the significant association among premenopausal women. Further analyses stratified by PRS categories showed that high LE8 score was associated with 28% and 71% decreased risk of breast cancer incidence (HR: 0.72, 95% CI: 0.60–0.87) and mortality (HR: 0.29, 95% CI: 0.10–0.83) compared to low LE8 score among high genetic risk groups, but no significant associations were found among low genetic risk groups. Furthermore, compared with postmenopausal women with high LE8 score and low genetic risk, those with low LE8 score and high genetic risk were associated with increased risk of breast cancer incidence (HR: 6.26, 95% CI: 4.43–8.84). Conclusions: The present study suggests that better CVH is a protective factor for both breast cancer incidence and mortality among postmenopausal women. Moreover, the risk of developing breast cancer caused by high genetic susceptibility could be largely offset by better CVH. [ABSTRACT FROM AUTHOR]

Background: Consistent evidence shows that magnesium (Mg) intake is associated with lower blood pressure (BP), and that lower BP is associated with improved cerebral health. However, recent findings indicate that the positive effect of dietary Mg intake on cerebral health is not mediated by a decrease in BP. As Mg's anti-inflammatory action is a plausible alternative mechanism, the objective of this study was to investigate the associations between Mg intake and inflammation to determine whether it mediates any neuroprotective effect. Methods: Participants from the UK Biobank (n = 5775, aged 40–73 years, 54.7% female) were assessed for dietary magnesium using an online food questionnaire, brain and white matter lesion (WML) volumes were segmented with FreeSurfer software, and inflammation markers including high-sensitivity C-reactive protein (hs-CRP), leukocyte, erythrocyte count, and Glycoprotein acetylation (GlycA) were measured using specific laboratory techniques such as immunoturbidimetry, automated cell counting, and nuclear magnetic resonance. Hierarchical linear regression models were performed to investigate the association between dietary Mg, and inflammatory markers and between dietary Mg, brain and WMLs volumes. Mediation analysis was performed to test a possible mediation role of inflammation on the association between dietary Mg and brain and WMLs volumes. Results: Higher dietary Mg intake was associated with lower inflammation: hs-CRP level (− 0.0497%; 95% confidence interval [CI] − 0.0497%, − 0.0199%) leukocytes count (− 0.0015%; 95%CI − 0.00151%, − 0.0011%), and GlycA (− 0.0519%; 95%CI − 0.1298%, − 0.0129%). Moreover, higher dietary Mg intake was associated with larger grey matter volume (0.010%; 95%CI 0.004%, 0.017%), white matter volume (0.012%; 95%CI 0.003, 0.022) and right hippocampal volume (0.002%; 95%CI 0.0007, –0.0025%). Lower hs-CRP levels mediated the positive association between higher dietary Mg intake and larger grey matter volume. Conclusions: The anti-inflammatory effects of dietary Mg intake in the general population, appears to mediate its neuroprotective effect. [ABSTRACT FROM AUTHOR]

The relationship between sarcopenia and the long‐term risk of atrial fibrillation (AF) remains unclear. This study recruited a large prospective Caucasian cohort from the UK Biobank. Participants were assessed at baseline with handgrip strength and muscle mass and were categorized into groups of non‐sarcopenia, probable sarcopenia, and confirmed sarcopenia. Kaplan–Meier method and Cox proportional hazards model were used to explore the association between sarcopenia and the incidence of AF. The genetic predisposition of AF was assessed by polygenic risk score. Sensitivity analyses were performed to validate the results. A total of 384,433 participants with a median age of 58 years and 54.3% women were enrolled in this study. There were 24,007 cases of new‐onset AF over a median follow‐up of 12.56 years. The groups of non‐sarcopenia, probable sarcopenia, and confirmed sarcopenia accounted for 22,290 (6.1%), 1665 (9.2%), and 52 (11.9%) cases, respectively. Compared with the non‐sarcopenia group, participants with probable sarcopenia or confirmed sarcopenia had an 8% (95% CI, 1.03–1.14) or 61% (95% CI, 1.23–2.12) higher risk of AF incidence. The findings remained robust in multiple sensitivity analyses, such as subgroup analysis and further adjustment of genetic predisposition. Notably, the association between sarcopenia and a high AF risk was more pronounced in younger participants, women, and those with valvular heart disease. In conclusion, sarcopenia was associated with a high long‐term risk of AF in Caucasians, supporting sarcopenia as a new independent risk factor of AF. [ABSTRACT FROM AUTHOR]

Our aim was to investigate relative contributions of central and peripheral mechanisms to knee osteoarthritis (OA) diagnosis and their independent causal association with knee OA. We performed longitudinal analysis using data from UK-Biobank participants. Knee OA was defined using International Classification of Diseases manual 10 codes from participants' hospital records. Central mechanisms were proxied using multisite chronic pain (MCP) and peripheral mechanisms using body mass index (BMI). Odds ratios (ORs) and 95% confidence intervals (CIs) were estimated, and proportional risk contribution (PRC) was estimated from receiveroperator-characteristic (ROC) analysis. To estimate the causal effects, we performed 2-sample multivariable Mendelian Randomisation (MR) analysis. We selected genetic instruments from the largest Genome Wide Association Study of BMI (N 5 806,834) and MCP (N 5 387,649) and estimated the instruments genetic associations with knee OA in the largest available dataset (62,497 cases and 333,557 control subjects). The multivariable MR was performed using modified inverse-variance weighting methods. Of the 203,410 participants, 6% developed knee OA. Both MCP (OR 1.23, 95% CI; 1.21-1.24) and BMI (1.10, 95% CI; 1.10-1.11) were associated with knee OA diagnosis. The PRC was 6.9% (95% CI; 6.7%-7.1%) forMCPand 21.9% (95% CI; 21.4%-22.5%) for BMI; the combined PRC was 38.8% (95% CI; 37.9%-39.8%). Body mass index andMCPhad independent causal effects on knee OA (OR 1.76 [95% CI, 1.64-1.88] and 1.83 [95% CI, 1.54-2.16] per unit change, respectively). In conclusion, peripheral risk factors (eg, BMI) contribute more to the development of knee OA than central risk factors (eg, MCP). Peripheral and central factors are independently causal on knee OA. [ABSTRACT FROM AUTHOR]

Background: Triglyceride-glucose (TyG) index is an emerging surrogate indicator of insulin resistance, which has been demonstrated as a risk factor for various cardiovascular diseases including coronary syndrome, in-stent restenosis, and heart failure. However, association of TyG index with incident aortic dissection (AD) and aortic aneurysm (AA) remains to be investigated. Methods: This study included 420,292 participants without baseline AD/AA from the large-scale prospective UK Biobank cohort. The primary outcome was incident AD/AA, comprising AD and AA. Multivariable-adjusted Cox proportional hazards regression models and restricted cubic spline (RCS) analyses were applied to assess the relationship between TyG index and the onset of AD/AA. In addition, the association between TyG index and incident AD/AA was examined within subgroups defined by age, gender, smoking status, drinking status, diabetes, hypertension, and BMI. Results: Over a median follow-up period of 14.8 (14.1, 15.5) years, 3,481 AD/AA cases occurred. The incidence of AD/AA rose along with elevated TyG index. RCS curves showed a linear trend of TyG index with risk of incident AD/AA. TyG index was positively associated with risk of incident AD/AA after adjusting for age, gender, smoking status, drinking status, BMI, hypertension, LDL-c, and HbA1c, with adjusted HRs of 1.0 (reference), 1.20 (95% CI 1.08–1.35), 1.21 (95% CI 1.08–1.35), and 1.30 (95% CI 1.16–1.45) for TyG index quartiles 2, 3, and 4, respectively. Especially, participants in the highest TyG index quartile had highest risk of developing AA, with an adjusted HR of 1.35 (95% CI 1.20–1.52). Conclusions: TyG index is independently associated with a higher risk of incident AD/AA, indicating the importance of using TyG index for risk assessment of AD/AA, especially for AA. [ABSTRACT FROM AUTHOR]

Aims: To estimate the association between long‐term changes in frailty and the risk of incident type 2 diabetes (T2DM) and to evaluate the effect of preventing the worsening of frailty on the risk of T2DM. Methods: We included 348 205 participants free of baseline T2DM and with frailty phenotype (FP) data from the UK Biobank; among them, 36 175 had at least one follow‐up assessment. According to their FP score, participants were grouped into nonfrailty, prefrailty and frailty groups. Frailty assessed at baseline and at follow‐up was used to derive the trajectory of frailty (ΔFP). Cox regression models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs). Results: Compared with those in the nonfrailty group at baseline, the HRs of T2DM for the prefrailty and frailty groups were 1.38 (95% CI 1.33–1.43) and 1.69 (95% CI 1.59–1.79), respectively (both p < 0.001), in the multivariable‐adjusted model. During a median follow‐up of 5.4 years after the final assessment, data for 472 T2DM patients were recorded. A 1‐point increase in the final FP was associated with a 25% (95% CI 1.14–1.38; p < 0.001) increased risk of T2DM. For the trajectory of frailty, each 0.5‐point/year increase in ΔFP was associated with a 52% (95% CI 1.18–1.97; p < 0.001) greater risk of T2DM, independent of the FP score at baseline. Compared with those that remained in the nonfrailty group, the greatest risk of T2DM over time was prefrailty aggravation (HR 3.03, 95% CI 2.00–4.58; p < 0.001). Using the frailty index did not materially change the results. Conclusions: Long‐term changes in frailty were associated with the risk of incident T2DM, irrespective of baseline frailty status. Preventing the worsening of frailty may reduce T2DM risk. [ABSTRACT FROM AUTHOR]

Early life events and environmental factors are associated with type 2 diabetes (T2D) development. We assessed the combined effect of birth weight andambient air pollutants, and effect of their interaction on T2D risk. Totally, 6,474 T2D incidents were recorded over an 8.7-year follow-up period. The adjusted hazard ratios (aHRs) with 95% confidence intervals (CIs) were 1.31 (1.26, 1.36) for each kilogram decrease in birth weight, and 1.08 (1.05, 1.11) for each standard deviation increase in air pollution score (APS). Birth weight<3000 g amplified the T2D risk associated with high APS. A combination of the lowest birth weight (<2500 g) and the highest quintile of APS led to over two-fold increase in T2D risk (aHR: 2.17; 95% CI: 1.79–2.64). There was a significant additive interaction between them. In conclusion, ambient air pollutants increase the risk for T2D, particularly in populations with low birth weight. [ABSTRACT FROM AUTHOR]

Personality traits, especially neuroticism, can influence susceptibility to dementia. Social contact mitigates stress and risk of dementia, the extent to which social contact can mitigate excess risk associated with neuroticism remains unclear. We aim to investigate whether active social contact is associated with lower neuroticism-associated excess risk of dementia. This prospective cohort study examined 393,939 UK Biobank participants (mean [SD] age: 56.4 [8.1] years; 53.7 % female) assessed from 2006 to 2010 and followed up until December 2022. Neuroticism was measured using the Revised Eysenck Personality Questionnaire. Social contact levels were assessed based on household size, contact with family or friends, and group participation. Dementia was determined using linked electronic health records. High neuroticism was associated with increased all-cause dementia risk and cause-specific dementia. Among high neuroticism participants, excess risk of all-cause dementia showed a stepwise decrease with increasing social contact (low: hazard ratios (HR) = 1.27, 95 % confidence interval (CI) = 1.15–1.40; intermediate: HR = 1.20, 95 % CI = 1.12–1.28; high: HR = 1.07, 95 % CI = 1.00–1.15). High social contact similarly decreased excess risk of cause-specific dementia, comparable to those with low neuroticism. Neuroticism and social contact information relied on self-report questionnaires at baseline, with a potential temporal relationship between these factors. Active social contact is associated with a stepwise reduction in excess dementia risk and potentially eliminate excess risk of dementia with high neuroticism individuals, supporting social contact as a preventive strategy to attenuate excess risks of dementia from neuroticism personality trait. • Individuals with high neuroticism personality have markedly higher dementia risk. • Increasing social contact decreases dementia risk stepwise in high neuroticism people. • High social contact potentially eliminates neuroticism-associated excess risk of dementia. [ABSTRACT FROM AUTHOR]

Background There is a close association between diet and abdominal pain; however, relationship between inflammatory diet and characteristics of abdominal pain has not been characterized yet. Methods This study analyzed baseline data from the UK Biobank, 3-item DHQ-Abdominal Pain Questionnaire (DHQ-3Q), which including abdominal pain in the past 3 months, severity of abdominal pain, and frequency of abdominal pain, and data from the National Health and Nutrition Examination Survey (NHANES) from 2017 to 2020. Energy-adjusted Dietary Inflammatory Index (E-DII), constructed based on 26 or 27 nutrients, was analyzed using continuous or categorical methods. Logistic regression and restricted cubic spline analyses examined the association between E-DII and abdominal pain. Results In UK Biobank, compared to participants in the lowest quintile of E-DII, the adjusted ORs for the highest quintile were 1.12 (95% CI 1.02–1.24; P  = .022), 1.05 (95% CI 1.00–1.09; P  = .030), 1.26 (95% CI 1.17–1.36; P  < .001), and 1.10 (95% CI 1.00–1.20; P  = .044) for chronic abdominal pain, abdominal pain in the past three months, severity of abdominal pain, and frequency of abdominal pain, respectively. In NHANES, compared to participants in the lowest quintile of E-DII, the adjusted ORs for the highest quintile were 1.46 (95% CI 1.20–1.77; P  < .001), 1.75 (95% CI 1.20–2.60; P  = .005), 1.45 (95% CI 1.14–1.87; P  = .003), and 1.18 (95% CI 0.82–1.72; P  = .380) for abdominal pain in the past year, upper left abdominal pain, upper middle abdominal pain, and upper right abdominal pain. Additionally, there was a nonlinear correlation between E-DII score and DHQ-3Q (P nonlinear <.001). Conclusion Following a pro-inflammatory diet is linked to a higher likelihood of experiencing abdominal pain, as well as increased severity and frequency of such pain. Therefore, further longitudinal studies are necessary to investigate this relationship. [ABSTRACT FROM AUTHOR]

Background We aimed to investigate the association between OA and treatment with dementia risk and structural brain abnormalities. Methods We recruited a total of 466,460 individuals from the UK Biobank to investigate the impact of OA on the incidence of dementia. Among the total population, there were 63,081 participants diagnosed with OA. We subsequently categorised the OA patients into medication and surgery groups based on treatment routes. Cox regression models explored the associations between OA/OA treatment and dementia risk, with the results represented as hazard ratios (HRs) and 95% confidence intervals (95% CI). Linear regression models assessed the associations of OA/OA therapy with alterations in cortical structure. Results During an average of 11.90 (± 1.01) years of follow-up, 5,627 individuals were diagnosed with all-cause dementia (ACD), including 2,438 AD (Alzheimer's disease), and 1,312 VaD (vascular dementia) cases. Results revealed that OA was associated with the elevated risk of ACD (HR: 1.116; 95% CI: 1.039–1.199) and AD (HR: 1.127; 95% CI: 1.013–1.254). OA therapy lowered the risk of dementia in both medication group (HR: 0.746; 95% CI: 0.652–0.854) and surgery group (HR: 0.841; 95% CI: 0.736–0.960). OA was negatively associated with cortical area, especially precentral, postcentral and temporal regions. Conclusions Osteoarthritis increased the likelihood of developing dementia, and had an association with regional brain atrophy. OA treatment lowered the dementia risk. OA is a promising modifiable risk factor for dementia. [ABSTRACT FROM AUTHOR]

INTRODUCTION: Higher neuroticism might be associated with dementia risk. Here we investigated modification by genetic predisposition to dementia, mediation by mental health and vascular conditions, neuroimaging outcomes, and cognitive function. METHODS: Cox proportional‐hazards models were used to assess the association between neuroticism score and incident dementia over up to 15 years in 1,74,164 participants. Cross‐sectional analyses on dementia‐related neuroimaging outcomes and cognitive function were conducted in 39,459 dementia‐free participants. RESULTS: Higher neuroticism was associated with an 11% higher risk of incident dementia, especially vascular dementia (15% higher risk), regardless of genetic predisposition to dementia. Mental and vascular conditions mediated the association of neuroticism with all‐cause dementia and vascular dementia. Neuroticism was associated with higher cerebrovascular pathology, lower gray matter volume, and worse function across multiple cognitive domains. DISCUSSION: Neuroticism could represent a risk factor for dementia, and vascular and mental health might drive these associations. Highlights: Neuroticism was associated with an increased risk of incident all‐cause dementia, particularly vascular dementia.Associations were not modified by genetic predisposition to dementia.Associations were largely mediated by mental and vascular conditions.Neuroticism was associated with increased cerebrovascular pathology and lower gray matter volume.Neuroticism was associated with worse function across multiple cognitive domains. [ABSTRACT FROM AUTHOR]

Fracture prediction is essential in managing patients with osteoporosis and is an integral component of many fracture prevention guidelines. We aimed to identify the most relevant clinical fracture risk factors in contemporary populations by training and validating short- and long-term fracture risk prediction models in 2 cohorts. We used traditional and machine learning survival models to predict risks of vertebral, hip, and any fractures on the basis of clinical risk factors, T-scores, and treatment history among participants in a nationwide Swiss Osteoporosis Registry (N = 5944 postmenopausal women, median follow-up of 4.1 yr between January 2015 and October 2022; a total of 1190 fractures during follow-up). The independent validation cohort comprised 5474 postmenopausal women from the UK Biobank with 290 incident fractures during follow-up. Uno's C-index and the time-dependent area under the receiver operating characteristics curve were calculated to evaluate the performance of different machine learning models (Random survival forest and eXtreme Gradient Boosting). In the independent validation set, the C-index was 0.74 [0.58, 0.86] for vertebral fractures, 0.83 [0.7, 0.94] for hip fractures, and 0.63 [0.58, 0.69] for any fractures at year 2, and these values further increased for longer estimations of up to 7 yr. In comparison, the 10-yr fracture probability calculated with FRAX Switzerland was 0.60 [0.55, 0.64] for major osteoporotic fractures and 0.62 [0.49, 0.74] for hip fractures. The most important variables identified with Shapley additive explanations values were age, T-scores, and prior fractures, while number of falls was an important predictor of hip fractures. Performances of both traditional and machine learning models showed similar C-indices. We conclude that fracture risk can be improved by including the lumbar spine T-score, trabecular bone score, numbers of falls and recent fractures, and treatment information has a significant impact on fracture prediction. Lay Summary: Fracture prediction is essential in managing patients with osteoporosis. We developed and validated traditional and machine learning models to predict short- and long-term fracture risk and identify the most relevant clinical fracture risk factors for vertebral, hip, and any fractures in contemporary populations. We used data from 5944 postmenopausal women in a Swiss Osteoporosis Registry and validated our findings with 5474 women from the UK Biobank. Our machine learning models performed well, with C-index values of 0.74 for vertebral fractures, 0.83 for hip fractures, and 0.63 for any fractures at year 2, and these values further increased for longer estimations of up to 7 years. In contrast, FRAX Switzerland had lower C-index values (0.60 for major fractures and 0.62 for hip fracture probabilities over 10 years). Key predictors identified included age, T-scores, prior fractures, and number of falls. We conclude that incorporating a broader range of clinical factors, as well as lumbar spine T-scores, fall history, recent fractures, and treatment information, can improve fracture risk assessments in osteoporosis management. Both traditional and machine learning models showed similar effectiveness in predicting fractures. [ABSTRACT FROM AUTHOR]

Objective. Although previous studies have explored the association of drinking with gout risk, we sought to explore the dose-response relationship and the evidence between subtypes of alcoholic beverages and gout risk. Methods. The weekly alcoholic beverage consumption of patients in the UK Biobank was collected and calculated. The Cox regression model was applied to assess the effects of drinking alcohol in general and its subtypes on gout risk by calculating the hazard ratio (HR) and 95% CIs. Additionally, the restricted cubic splines were used to estimate the dose-response relationship between alcohol consumption and gout risk. To evaluate the robustness, we performed subgroup analysis across various demographic characteristics. Results. During a mean follow-up period of 11.7 years, a total of 5728 new incident gout cases were diagnosed among 331,865 participants. We found that light alcohol consumption was linked to a slight decrease in gout incidence among female individuals (HR 0.78, 95% CI 0.65-0.94, P = 0.01), whereas there was no significant association in male individuals. Moreover, the dose-response relationship showed that drinking light red wine and fortified wine could reduce the gout risk, whereas beer or cider, champagne or white wine, and spirits increased the gout risk at any dose. Conclusion. Our study suggested a J-shaped dose-response relationship between drinking and gout risk in female individuals, but not in male individuals. For specific alcoholic beverages, light consumption of red wine and fortified wine was associated with reduced gout risk. These findings offer new insights into the roles of alcoholic beverages in gout incidence risk, although further validation is warranted. [ABSTRACT FROM AUTHOR]

Aims/hypotheses: Glucagon and glucagon-like peptide-1 (GLP-1) are derived from the same precursor; proglucagon, and dual agonists of their receptors are currently being explored for the treatment of obesity and metabolic dysfunction-associated steatotic liver disease (MASLD). Elevated levels of endogenous glucagon (hyperglucagonaemia) have been linked with hyperglycaemia in individuals with type 2 diabetes but are also observed in individuals with obesity and MASLD. GLP-1 levels have been reported to be largely unaffected or even reduced in similar conditions. We investigated potential determinants of plasma proglucagon and associations of glucagon receptor signalling with metabolic diseases based on data from the UK Biobank. Methods: We used exome sequencing data from the UK Biobank for ~410,000 white participants to identify glucagon receptor variants and grouped them based on their known or predicted signalling. Data on plasma levels of proglucagon estimated using Olink technology were available for a subset of the cohort (~40,000). We determined associations of glucagon receptor variants and proglucagon with BMI, type 2 diabetes and liver fat (quantified by liver MRI) and performed survival analyses to investigate if elevated proglucagon predicts type 2 diabetes development. Results: Obesity, MASLD and type 2 diabetes were associated with elevated plasma levels of proglucagon independently of each other. Baseline proglucagon levels were associated with the risk of type 2 diabetes development over a 14 year follow-up period (HR 1.13; 95% CI 1.09, 1.17; n=1562; p=1.3×10−12). This association was of the same magnitude across strata of BMI. Carriers of glucagon receptor variants with reduced cAMP signalling had elevated levels of proglucagon (β 0.847; 95% CI 0.04, 1.66; n=17; p=0.04), and carriers of variants with a predicted frameshift mutation had higher levels of liver fat compared with the wild-type reference group (β 0.504; 95% CI 0.03, 0.98; n=11; p=0.04). Conclusions/interpretation: Our findings support the suggestion that glucagon receptor signalling is involved in MASLD, that plasma levels of proglucagon are linked to the risk of type 2 diabetes development, and that proglucagon levels are influenced by genetic variation in the glucagon receptor, obesity, type 2 diabetes and MASLD. Determining the molecular signalling pathways downstream of glucagon receptor activation may guide the development of biased GLP-1/glucagon co-agonist with improved metabolic benefits. Data availability: All coding is available through https://github.com/nicwin98/UK-Biobank-GCG [ABSTRACT FROM AUTHOR]

Background: Chronic pain was associated with a higher risk of mental disorders (e.g., depression and anxiety). However, the role of 24-h movement behaviors in the association remains unclear. Methods: A total of 72,800 participants with accelerometer data and free of mental disorders from the UK Biobank were analyzed. The compositional mediation model and isotemporal substitution model were used to explore the associations between chronic pain, 24-h movement behaviors, and the incidence of overall mental disorders, depression, and anxiety. Results: With a median follow-up of 13.36 years, participants with chronic pain had a higher rate of incident overall mental disorders (hazard ratio (HR): 1.281, 95% confidence interval (CI): 1.219 to 1.344), anxiety (HR: 1.391, 95% CI: 1.280 to 1.536), and depression (HR: 1.703, 95% CI: 1.551 to 1.871). Increased sedentary behavior (SB) and reduced moderate-to-vigorous physical activity (MVPA) caused by chronic pain both increased the risk of mental disorders. Twenty-four-hour movement behaviors explained the relationship between chronic pain and overall mental disorders, depression, and anxiety by 10.77%, 5.70%, and 6.86%, respectively. Interaction effects were found between MVPA and chronic pain when predicting the incidence of depression and between MVPA, sleep (SLP), and chronic pain when predicting the incidence of mental disorders. People with chronic pain would recommend at least 0.5 h per day of MVPA and 7 h per day of SLP and restricting SB below 11.5 h per day. Conclusions: Twenty-four-hour movement behaviors played a significant mediating role in the association between chronic pain and mental disorders. Individuals with chronic pain should engage in more MVPA, less sedentary behavior, and have 7-h sleep per day. [ABSTRACT FROM AUTHOR]

Background: To investigate the association between cigarette smoking, smoking cessation and the trajectory of cardiometabolic multimorbidity (CMM), and further to examine the association of age at smoking initiation and smoking cessation with CMM. Methods: This study included 298,984 UK Biobank participants without cardiometabolic diseases (CMDs) (including type 2 diabetes, coronary heart diseases, stroke, and hypertension) at baseline. Smoking status was categorized into former, current, and never smokers, with age at smoking initiation and smoking cessation as a proxy for current and former smokers. The multi-state model was performed to evaluate the association between cigarette smoking, smoking cessation and CMM. Results: During a median follow-up of 13.2 years, 59,193 participants developed first cardiometabolic disease (FCMD), 14,090 further developed CMM, and 16,487 died. Compared to former smokers, current smokers had higher risk at all transitions, with hazard ratio (95% confidence interval) = 1.59 (1.55 ∼ 1.63) vs. 1.18 (1.16 ∼ 1.21) (P = 1.48 × 10− 118) from health to FCMD, 1.40 (1.33 ∼ 1.47) vs. 1.09 (1.05 ∼ 1.14) (P = 1.50 × 10− 18) from FCMD to CMM, and 2.87 (2.72 ∼ 3.03) vs. 1.38 (1.32 ∼ 1.45) (P < 0.001) from health, 2.16 (1.98 ∼ 2.35) vs. 1.25 (1.16 ∼ 1.34) (P = 1.18 × 10− 46) from FCMD, 2.02 (1.79 ∼ 2.28) vs. 1.22 (1.09 ∼ 1.35) (P = 3.93 × 10− 17) from CMM to death; whereas quitting smoking reduced the risk attributed to cigarette smoking by approximately 76.5% across all transitions. Reduced risks of smoking cessation were also identified when age at quitting smoking was used as a proxy for former smokers. Conclusions: Cigarette smoking was associated with a higher risk of CMM across all transitions; however, smoking cessation, especially before the age of 35, was associated with a significant decrease in CMM risk attributed to cigarette smoking. [ABSTRACT FROM AUTHOR]

Background and Aims: Metabolic dysfunction-associated steatotic liver disease (MASLD) poses a considerable health risk. Nevertheless, its risk factors are not thoroughly comprehended, and the association between the reticulocyte count and MASLD remains uncertain. This study aimed to explore the relationship between reticulocyte count and MASLD. Methods: A total of 310,091 individuals from the UK Biobank were included in this cross-sectional study, and 7,316 individuals were included in this prospective study. The cross-sectional analysis categorized reticulocyte count into quartiles, considering the sample distribution. Logistic regression models examined the connection between reticulocyte count and MASLD. In the prospective analysis, Cox analysis was utilized to investigate the association. Results: Our study findings indicate a significant association between higher reticulocyte count and an elevated risk of MASLD in both the cross-sectional and prospective analyses. In the cross-sectional analysis, the adjusted odds ratios (ORs) of MASLD increased stepwise over reticulocyte count quartiles (quartile 2:OR 1.22, 95% CI 1.17-1.28, p < 0.001; quartile 3: OR 1.44; 95% CI 1.38-1.51, p < 0.001; quartile 4: OR 1.66, 95% CI 1.59-1.74, p < 0.001). The results of prospective analyses were similar. Conclusion: Increased reticulocyte count was independently associated with a higher risk of MASLD. This discovery offers new insights into the potential of reticulocytes as biomarkers for MASLD. [ABSTRACT FROM AUTHOR]

Background: The low-grade inflammation score (INFLA-score) is a composite index that assesses chronic inflammatory status using multiple inflammatory markers. However, its correlation with cardiometabolic diseases (CMDs) in obese populations remains unclear. Methods: We conducted a prospective cohort study involving 79,160 participants with obesity (BMI ≥ 30 kg/m2) from the UK Biobank. The INFLA-score was calculated based on high-sensitivity C-reactive protein, leukocyte count, platelet count and granulocyte/lymphocyte ratio. We employed Kaplan–Meier survival curves, multivariable Cox regression, restricted cubic splines and accelerated time-to-failure models to analyse the association between the INFLA-score and CMDs risk, including coronary heart disease (CAD), stroke and type 2 diabetes mellitus (T2DM). Results: Over a median follow-up of 161.41 months, we recorded 14,903 CMDs events, comprising 7184 CAD cases, 1914 strokes and 7924 T2DM cases. Cox regression analysis revealed that each unit increase in the INFLA-score corresponded to a 1.5%, 1.1%, 1.2% and 2.4% increase CMDs risk (HR: 1.015, 95% CI 1.013–1.018), CAD risk (HR: 1.011, 95% CI 1.007–1.015), stroke risk (HR: 1.012, 95% CI 1.004–1.020) and T2DM risk (HR: 1.024, 95% CI 1.020–1.028), respectively. Restricted cubic spline analysis indicated a non-linear relationship between cumulative INFLA-score and CMDs risk (P = 0.044). Subgroup analysis revealed interactions between sex, age, history of lipid-lowering drug use, and INFLA-score regarding CMDs risk. Sensitivity analysis corroborated the main findings. Conclusion: Our findings strongly support the close association between INFLA-score and CMDs risk, particularly notable in women, those aged < 55, and individuals with a history of lipid-lowering drug use. These findings offer new insights into the role of inflammation in obesity-related CMDs, suggesting potential applications for prevention and identification of high-risk populations. [ABSTRACT FROM AUTHOR]

Background: The causality between frailty and gestational diabetes mellitus (GDM) has not yet been fully explored. A potential bidirectional causality was also needed to be confirmed. Methods: A bidirectional two-sample Mendelian randomization (MR) was conducted, with frailty-related data was collected from UK Biobank and TwinGen and GDM-related data was collected from the FinnGen consortium. We performed univariable and multivariable-adjusted MR with adjustments for body mass index (BMI). Several methodologies of MR were conducted to confirm the robustness of results. Results: Frailty was significantly associated with elevated risks of GDM (OR, 3.563; 95% CI, 1.737 to 7.309; P< 0.001) and GDM was also significantly associated with elevated risks of frailty (b, 0.087; 95% CI, 0.040 to 0.133; P< 0.001). There is no evidence demonstrating the existence of horizontal pleiotropy and heterogeneity. This association was robust after adjustments for BMI. The sensitivity analyses with Weighted median, Maximum likelihood, Penalised weighted median, MR Egger and MR PRESSO methods indicated consistent results. Conclusion: Our study provides evidence of the bidirectional causal association between frailty and GDM from genetic perspectives, signaling that the identification and assessment of frailty should become a standard strategy during the early stages and care of gestational diabetes. [ABSTRACT FROM AUTHOR]

Background Shift work has become popular along with adverse effects such as disrupted biological rhythms, metabolic changes, sleep disorders and myocardial infarction. Studies have shown a link between myocardial infarction and shift work, but evidence is still lacking. Aims We aim to explore the association between present and past shift work and risk of myocardial infarction in a large population of European workers. Methods We analysed data from the UK Biobank with >500 000 participants and an average 12-year follow-up duration. Cox proportional hazard models were employed to analyse the relationship between present shift work (n  = 265 064), lifetime duration or frequency of shift work (n  = 71 428) and the risk of myocardial infarction, as well as the association between rest day during shift work and myocardial infarction incidents in night shift workers (n  = 14 588). Results Night shift workers had a higher risk of myocardial infarction compared to day workers, including 'shift but never/rarely night shifts' (hazard ratio [HR] = 1.09, 95% confidence interval [CI] 1.00–1.20), 'some night shifts' (HR = 1.13, 95% CI 1.01–1.27) and 'usual/permanent night shifts' (HR = 1.21, 95% CI 1.07–1.37), respectively. Similarly, higher frequency and longer duration of night shift work were associated with the increased risk of myocardial infarction (<10 years: HR = 1.20, 95% CI 1.01–1.42; ≥10 years: HR = 1.51, 95% CI 1.28–1.77; or an average of more than eight nights per month: HR = 1.45, 95% CI 1.23–1.71). However, longer rest days couldn't decrease myocardial infarction risk compared to those who rest 1 day. Conclusions Present and lifetime exposure to night shifts were associated with a risk of myocardial infarction and did not benefit from longer rest days. [ABSTRACT FROM AUTHOR]

Toxoplasma gondii (T. gondii) is an opportunistic pathogen affecting about 1/3 of world population. While often asymptomatic in immunocompetent individuals, it can lead to severe toxoplasmosis in immunocompromised patients. Recent research has unveiled a potential link between T. gondii infection and neuropsychiatric diseases. We implemented both a cohort study and a case control study to further identify this association. In the cohort study, we analyzed data from the UK Biobank database, which included 8814 individuals tested for T. gondii SAG1 antibodies and free of neuropsychiatric disorders at baseline. Among them, 22.52% (n = 1985) tested positive for SAG1 antibody. Over an average follow-up period of 12.26 years, Cox proportional hazards models and logistic regression analysis revealed a significant association between the SAG1 seropositivity at baseline and the incidence of schizophrenia (HR: 5.89; 95% CI: 1.69–20.53). In our case-control study, 239 patients diagnosed with schizophrenia and 455 healthy individuals were involved. Using the modified agglutination test (MAT) to detect T. gondii antibodies, logistic regression analysis showed a higher prevalence of T. gondii infection among schizophrenia patients (10.04%) compared to healthy controls (3.74%). T. gondii infection emerged as a significant risk factor for schizophrenia (OR: 3.33; 95% CI: 1.68–6.61). However, our investigations did not reveal a robust association between T. gondii infection and other neuropsychiatric conditions, including Alzheimer's disease, dementia, anxiety, depression, neurodegenerative disorders, and peripheral neurological disorders such as neurological and plexus disorders. • In the UK Biobank, 22.52% of the subjects tested were found to be positive for the T. gondii SAG1 antibody. • A significant association was observed between T. gondii SAG1 antibody positivity and symptoms of schizophrenia. • Higher neuropsychiatric morbidity was found in T. gondii SAG1 antibody-positive group. [ABSTRACT FROM AUTHOR]

Considering the high prevalence and poor prognosis of cardiometabolic multimorbidity (CMM), identifying causal factors and actively implementing preventive measures is crucial. However, Mendelian randomization (MR), a key method for identifying the causal factors of CMM, requires knowledge of the effects of SNPs on CMM, which remain unknown. We first analyzed the genetic overlap of single cardiometabolic diseases (CMDs) using the latest genome‐wide association study (GWAS) for evidential support and comparison. We observed strong positive genetic correlations and shared loci among all CMDs. Further, GWAS and post‐GWAS analyses of CMM were performed in 407 949 European ancestry individuals from the UK Biobank. Eleven loci and 12 lead SNPs were identified. By comparison, we found these SNPs were a subset of SNPs associated with CMDs, including both shared and non‐shared SNPs. Then, the polygenic risk score model predicted the risk of CMM (C‐index = 0.62) and we identified candidate genes related to lipid metabolism and immune function. Finally, as an example, two‐sample MR analysis based on the GWAS revealed potential causal effects of total cholesterol, serum urate, body mass index, and smoking on CMM. These results provide a basis for future MR research and inspire future studies on the mechanism and prevention of CMM. [ABSTRACT FROM AUTHOR]

Background: Transcriptomic changes in the essential tremor (ET)–associated cerebello‐thalamo‐cortical "tremor network" and their association to brain structure have not been investigated. Objective: The aim was to characterize molecular changes associated with network‐level imaging‐derived phenotypes (IDP) found in ET. Methods: We performed an imaging‐transcriptomic study in British adults using imaging‐genome‐wide association study summary statistics (UK Biobank "BIG40" cohort; n = 33,224, aged 40–69 years). We imputed imaging‐transcriptomic associations for 184 IDPs and analyzed functional enrichment of gene modules and aggregate network‐level phenotypes. Validation was performed in cerebellar‐tissue RNA‐sequencing data from ET patients and controls (n = 55). Results: Among 237,896 individual predicted gene expression levels for 6063 unique genes/transcripts, we detected 2269 genome‐wide significant associations (Bonferroni P < 2.102e‐7, 0.95%). These were concentrated in intracellular volume fraction measures of white matter pathways and in genes with putative links to tremor (MAPT, ARL17A, KANSL1, SPPL2C, LRRC37A4P, PLEKHM1, and FMNL1). Whole‐tremor‐network cortical thickness was associated with a gene module linked to mitochondrial organization and protein quality control (r = 0.91, P = 2e‐70), whereas white‐gray T1‐weighted magnetic resonance imaging (MRI) contrast in the tremor network was associated with a gene module linked to sphingolipid synthesis and ethanolamine metabolism (r = −0.90, P = 2e‐68). Imputed association effect sizes and RNA‐sequencing log‐fold change in the validation dataset were significantly correlated for cerebellar peduncular diffusion MRI phenotypes, and there was a close overlap of significant associations between both datasets for gray matter phenotypes (χ2 = 6.40, P = 0.006). Conclusions: The identified genes and processes are potential treatment targets for ET, and our results help characterize molecular changes that could in future be used for patient treatment selection or prognosis prediction. © 2024 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society. [ABSTRACT FROM AUTHOR]

The UK Biobank (UKB) is a large cohort study that recruited over 500,000 British participants aged 40–69 in 2006–2010 at 22 assessment centers from across the United Kingdom. Self-reported health outcomes and hospital admission data are 2 types of records that include participants' disease status. Coronary artery disease (CAD) is the most common cause of death in the UKB cohort. After distinguishing between prevalence and incidence CAD events for all UKB participants, we identified geographical variations in age-standardized rates of CAD between assessment centers. Significant distributional differences were found between the pooled cohort equation scores of UKB participants from England and Scotland using the Mann–Whitney test. Polygenic risk scores of UKB participants from England and Scotland and from different assessment centers differed significantly using permutation tests. Our aim was to discriminate between assessment centers with different disease rates by collecting data on disease-related risk factors. However, relying solely on individual-level predictions and averaging them to obtain group-level predictions proved ineffective, particularly due to the presence of correlated covariates resulting from participation bias. By using the Mundlak model, which estimates a random effects regression by including the group means of the independent variables in the model, we effectively addressed these issues. In addition, we designed a simulation experiment to demonstrate the functionality of the Mundlak model. Our findings have applications in public health funding and strategy, as our approach can be used to predict case rates in the future, as both population structure and lifestyle changes are uncertain. [ABSTRACT FROM AUTHOR]

Aim: Hypertension and diabetes mellitus (DM) are major causes of morbidity and mortality, with growing burdens in low‐income countries where they are underdiagnosed and undertreated. Advances in machine learning may provide opportunities to enhance diagnostics in settings with limited medical infrastructure. Materials and Methods: A non‐interventional study was conducted to develop and validate a machine learning algorithm to estimate cardiovascular clinical and laboratory parameters. At two sites in Kenya, digital retinal fundus photographs were collected alongside blood pressure (BP), laboratory measures and medical history. The performance of machine learning models, originally trained using data from the UK Biobank, were evaluated for their ability to estimate BP, glycated haemoglobin, estimated glomerular filtration rate and diagnoses from fundus images. Results: In total, 301 participants were enrolled. Compared with the UK Biobank population used for algorithm development, participants from Kenya were younger and would probably report Black/African ethnicity, with a higher body mass index and prevalence of DM and hypertension. The mean absolute error was comparable or slightly greater for systolic BP, diastolic BP, glycated haemoglobin and estimated glomerular filtration rate. The model trained to identify DM had an area under the receiver operating curve of 0.762 (0.818 in the UK Biobank) and the hypertension model had an area under the receiver operating curve of 0.765 (0.738 in the UK Biobank). Conclusions: In a Kenyan population, machine learning models estimated cardiovascular parameters with comparable or slightly lower accuracy than in the population where they were trained, suggesting model recalibration may be appropriate. This study represents an incremental step toward leveraging machine learning to make early cardiovascular screening more accessible, particularly in resource‐limited settings. [ABSTRACT FROM AUTHOR]

Background: Angina pectoris, a debilitating manifestation of coronary artery disease, has been associated with various modifiable risk factors. However, the causal underpinnings of these associations remain unclear. This study leveraged Mendelian randomization (MR) to investigate the causal roles of dietary patterns, smoking behaviors, body mass index (BMI), and physical activity in the development of angina. Methods: Two-sample MR analyses were performed using summary-level data from large-scale genome-wide association studies (GWASs) and biobank resources, including the UK Biobank (UKB) and FinnGen cohorts. Genetic variants associated with various types of exposure such as fruit and salad intake, smoking initiation and intensity, BMI, and physical activity were used as instrumental variables, and their causal effects on angina risk were assessed. Results: In the UKB cohort (336,683 individuals, 10,618 cases), genetically proxied fruit (OR = 0.95, 95% CI: 0.93–0.97) and cheese intake (OR = 0.98, 95% CI: 0.97–0.99) were associated with decreased angina risk, while smoking initiation (OR = 1.01, 95% CI: 1.002–1.012), maternal smoking (OR = 1.06, 95% CI: 1.03–1.09), and BMI (OR = 1.01, 95% CI: 1.01–1.02) were associated with increased risk. In the FinnGen cohort (206,008 individuals, 18,168 cases), fruit (OR = 0.30, 95% CI: 0.17–0.53) and salad intake (OR = 0.31, 95% CI: 0.12–0.55) were found to be protective, while smoking initiation (OR = 1.20, 95% CI: 1.04–1.37) and intensity (OR = 1.15, 95% CI: 1.04–1.26) and BMI (OR = 1.31, 95% CI: 1.18–1.47) increased angina risk. Conclusions: This study provides robust evidence for the causal roles of various modifiable risk factors associated with angina development, highlighting the potential benefits of dietary interventions that promote increased fruit and vegetable consumption, smoking cessation, and weight management to mitigate angina risk. Further investigation is needed to generalize these findings to populations with diverse genetic backgrounds, lifestyles, and environmental exposures. [ABSTRACT FROM AUTHOR]

The intricate dynamics of brain aging, especially the neurodegenerative mechanisms driving accelerated (ABA) and resilient brain aging (RBA), are pivotal in neuroscience. Understanding the temporal dynamics of these phenotypes is crucial for identifying vulnerabilities to cognitive decline and neurodegenerative diseases. Currently, there is a lack of comprehensive understanding of the temporal dynamics and neuroimaging biomarkers linked to ABA and RBA. This study addressed this gap by utilizing a large-scale UK Biobank (UKB) cohort, with the aim to elucidate brain aging heterogeneity and establish the foundation for targeted interventions. Employing Lasso regression on multimodal neuroimaging data, structural MRI (sMRI), diffusion MRI (dMRI), and resting-state functional MRI (rsfMRI), we predicted the brain age and classified individuals into ABA and RBA cohorts. Our findings identified 1949 subjects (6.2%) as representative of the ABA subpopulation and 3203 subjects (10.1%) as representative of the RBA subpopulation. Additionally, the Discriminative Event-Based Model (DEBM) was applied to estimate the sequence of biomarker changes across aging trajectories. Our analysis unveiled distinct central ordering patterns between the ABA and RBA cohorts, with profound implications for understanding cognitive decline and vulnerability to neurodegenerative disorders. Specifically, the ABA cohort exhibited early degeneration in four functional networks and two cognitive domains, with cortical thinning initially observed in the right hemisphere, followed by the temporal lobe. In contrast, the RBA cohort demonstrated initial degeneration in the three functional networks, with cortical thinning predominantly in the left hemisphere and white matter microstructural degeneration occurring at more advanced stages. The detailed aging progression timeline constructed through our DEBM analysis positioned subjects according to their estimated stage of aging, offering a nuanced view of the aging brain's alterations. This study holds promise for the development of targeted interventions aimed at mitigating age-related cognitive decline. [ABSTRACT FROM AUTHOR]

Previous studies have suggested that exposure to air pollutants may be associated with specific blood indicators or anemia in certain populations. However, there is insufficient epidemiological data and prospective evidence to evaluate the relationship between environmental air pollution and specific types of anemia. We conducted a large-scale prospective cohort study based on the UK Biobank. Annual average concentrations of NO2, PM2.5, PM2.5-10, and PM10 were obtained from the ESCAPE study using the Land Use Regression (LUR) model. The association between atmospheric pollutants and different types of anemia was investigated using the Cox proportional hazards model. Furthermore, restricted cubic splines were used to explore exposure-response relationships for positive associations, followed by stratification and effect modification analyses by gender and age. After adjusting for demographic characteristics, 3-4 of the four types of air pollution were significantly associated with an increased risk of iron deficiency, vitamin B12 deficiency and folate deficiency anemia, while there was no significant association with other defined types of anemia. After full adjustment, we estimated that the hazard ratios (HRs) of iron deficiency anemia associated with each 10 μg/m3 increase in NO2, PM2.5, and PM10 were 1.04 (95%CI: 1.02, 1.07), 2.00 (95%CI: 1.71, 2.33), and 1.10 (95%CI: 1.02, 1.20) respectively. The HRs of folate deficiency anemia with each 10 μg/m3 increase in NO2, PM2.5, PM2.5-10, and PM10 were 1.25 (95%CI: 1.12, 1.40), 4.61 (95%CI: 2.03, 10.47), 2.81 (95%CI: 1.11, 7.08), and 1.99 (95%CI: 1.25, 3.15) respectively. For vitamin B12 deficiency anemia, no significant association with atmospheric pollution was found. Additionally, we estimated almost linear exposure-response curves between air pollution and anemia, and interaction analyses suggested that gender and age did not modify the association between air pollution and anemia. Our research provided reliable evidence for the association between long-term exposure to PM10, PM2.5, PM2.5-10, NO2, and several types of anemia. NO2, PM2.5, and PM10 significantly increased the risk of iron deficiency anemia and folate deficiency anemia. Additionally, we found that the smaller the PM diameter, the higher the risk, and folate deficiency anemia was more susceptible to air pollution than iron deficiency anemia. No association was observed between the four types of air pollution and hemolytic anemia, aplastic anemia, and other types of anemia. Although the mechanisms are not well understood, we emphasize the need to limit the levels of PM and NO2 in the environment to reduce the potential impact of air pollution on folate and iron deficiency anemia. [ABSTRACT FROM AUTHOR]

Aim: Knowledge of how circadian rhythm influences brain health remains limited. We aimed to investigate the associations of accelerometer‐measured circadian rest‐activity rhythm (CRAR) with incident dementia, cognitive dysfunction, and structural brain abnormalities in the general population and underlying biological mechanisms. Methods: Fifty‐seven thousand five hundred and two participants aged over 60 years with accelerometer data were included to investigate the association of CRAR with incidental dementia. Non‐parametric CRAR parameters were utilized, including activity level during active periods of the day (M10), activity level during rest periods of the day (L5), and the relative difference between the M10 and L5 (relative amplitude, RA). Associations of CRAR with cognitive dysfunction and brain structure were studied in a subset of participants. Neuroimaging‐transcriptomics analysis was utilized to identify the underlying molecular mechanisms. Results: Over 6.86 (4.94–8.78) years of follow‐up, 494 participants developed dementia. The risk of incident dementia was associated with decreasing M10 (hazard ratio [HR] 1.45; 95% conference interval [CI], 1.28–1.64) and RA (HR 1.37; 95% CI, 1.28–1.64), increasing L5 (HR 1.14, 95% CI 1.07–1.21) and advanced L5 onset time (HR 1.12; 95% CI, 1.02–1.23). The detrimental associations were exacerbated by APOE ε4 status and age (>65 years). Decreased RA was associated with lower processing speed (Beta −0.04; SE 0.011), predominantly mediated by abnormalities in subcortical regions and white matter microstructure. The genes underlying CRAR‐related brain regional structure variation were enriched for synaptic function. Conclusions: Our study underscores the potential of intervention targeting at maintaining a healthy CRAR pattern to prevent dementia risk. [ABSTRACT FROM AUTHOR]

The recently discovered glymphatic system may support the removal of neurotoxic proteins, mainly during sleep, that are associated with neurodegenerative diseases such as Alzheimer's and Parkinson's Disease. Diffusion tensor image analysis along the perivascular space (DTI-ALPS) has been suggested as a method to index the health of glymphatic system (with higher values indicating a more intact glymphatic system). Indeed, in small-scale studies the DTI-ALPS index has been shown to correlate with age, cognitive health, and sleep, and is higher in females than males. To determine whether these relationships are stable we replicated previous findings associating the DTI-ALPS index with demographic, sleep-related, and cognitive markers in a large sample of participants from the UK Biobank. We calculated the DTI-ALPS index in UK Biobank participants (n = 17723). Using Bayesian and Frequentist analysis approaches, we replicate previously reported relationships between the DTI-ALPS index. We found the predicted associations between the DTI-ALPS index and age, longest uninterrupted sleep window (LUSWT) on a typical night, cognitive performance, and sex. However, these effects were substantially smaller than those found in previous studies. Parameter estimates from this study may be used as priors in subsequent studies using a Bayesian approach. These results suggest that the DTI-ALPS index is consistently, and therefore predictably, associated with demographics, LUWST, and cognition. We propose that the metric, calculated for the first time in a large-scale, population-based cohort, is a stable measure, but one for which stronger links to glymphatic system function are needed before it can be used to understand the relationships between glymphatic system function and health outcomes reported in the UK Biobank. • We calculated an index of diffusion along the perivascular space (DTI-ALPS index) in 44073 participants from the UK Biobank. • We replicated analyses from previous studies showing a relationship between the DTI-ALPS index, sex, age, sleep, & cognition. • Although these replications were broadly successful, the effect sizes were substantially smaller than previously reported. [ABSTRACT FROM AUTHOR]

This study aimed to examine the association between past/current sleep duration and macro-/micro-structural brain outcomes and explore whether hypertension or social activity plays a role in such association. Within the UK Biobank, 40 436 dementia-free participants (age 40–70 years) underwent a baseline assessment followed by a brain magnetic resonance imaging (MRI) scan 9 years later. Past (baseline) and current (MRI scans) sleep duration (hours/day) were recorded and classified as short (≤5), intermediate (6–8), and long (≥9). Brain structural volumes and diffusion markers were assessed by MRI scans. Compared with past intermediate sleep, past short sleep was related to smaller cortex volumes (standardized β [95 % CI]: −0.04 [-0.07, −0.02]) and lower regional fractional anisotropy (FA) (−0.08 [-0.13, −0.03]), while past long sleep was related to smaller regional subcortical volumes (standardized β: −0.04 to −0.07 for thalamus, accumbens, and hippocampus). Compared to current intermediate sleep, current short sleep was associated with smaller cortex volumes (−0.03 [-0.05, −0.01]), greater white matter hyperintensities (WMH) volumes (0.04 [0.01, 0.08]), and lower regional FA (−0.07 [-0.11, −0.02]). However, current long sleep was related to smaller total brain (−0.03 [-0.05, −0.02]), grey matter (−0.05 [-0.07, −0.03]), cortex (−0.05 [-0.07, −0.03]), regional subcortical volumes [standardized β: −0.05 to −0.09 for putamen, thalamus, hippocampus, and accumbens]), greater WMH volumes (0.06 [0.03, 0.09]), as well as lower regional FA (−0.05 [-0.09, −0.02]). The association between current long sleep duration and poor brain health was stronger among people with hypertension or low frequency of social activity (all P interaction <0.05). Both past and current short/long sleep are associated with smaller brain volume and poorer white matter health in the brain, especially in individuals with hypertension and low frequency of social activity. Our findings highlight the need to maintain 6–8 h' sleep duration for healthy brain aging. [Display omitted] • Long or short sleep is associated with poorer brain health. • People with hypertension or lack of social activity particularly need healthy sleep to delay brain aging. [ABSTRACT FROM AUTHOR]

Many metabolomics studies of depression have been performed, but these have been limited by their scale. A comprehensive in silico analysis of global metabolite levels in large populations could provide robust insights into the pathological mechanisms underlying depression and candidate clinical biomarkers. Depression-associated metabolomics was studied in 2 datasets from the UK Biobank database: participants with lifetime depression (N = 123,459) and participants with current depression (N = 94,921). The Whitehall II cohort (N = 4744) was used for external validation. CatBoost machine learning was used for modeling, and Shapley additive explanations were used to interpret the model. Fivefold cross-validation was used to validate model performance, training the model on 3 of the 5 sets with the remaining 2 sets for validation and testing, respectively. Diagnostic performance was assessed using the area under the receiver operating characteristic curve. In the lifetime depression and current depression datasets and sex-specific analyses, 24 significantly associated metabolic biomarkers were identified, 12 of which overlapped in the 2 datasets. The addition of metabolic features slightly improved the performance of a diagnostic model using traditional (nonmetabolomics) risk factors alone (lifetime depression: area under the curve 0.655 vs. 0.658 with metabolomics; current depression: area under the curve 0.711 vs. 0.716 with metabolomics). The machine learning model identified 24 metabolic biomarkers associated with depression. If validated, metabolic biomarkers may have future clinical applications as supplementary information to guide early and population-based depression detection. [ABSTRACT FROM AUTHOR]

Background The pathways by which air pollution affects cognition remain to be explored. This study aimed to explore how single air pollutants [including nitrogen oxide (NO X ), nitrogen dioxide (NO2), particulate matter with a diameter of 2.5 micrometers (PM2.5), PM10, and PM2.5–10], and air pollution mixture could affect cognitive function and the incidence of dementia, and determine whether pulmonary function (PF) could play a mediating role in the relationship. Methods Multiple statistical methods were employed to evaluate association of 5 air pollutants (NO X , NO2, PM2.5, PM10, and PM2.5–10) with cognitive function. Bootstrap method was used to estimate mediating role of PF in the association of air pollutants with cognition or the incidence of dementia. Results A mixture of air pollutants was associated with performance on 5 cognitive tests, and global cognition (p  < .05). Significantly negative association was also identified between mixture of air pollutants and PF (β= −0.020, 95% confidence interval (CI) = −0.029 to −0.011). In addition, as PF scores increase, performance on all cognitive tests significantly improve, although the risk of dementia correspondingly decreases. It was noted that PF was shown to mediate the effects of air pollution mixtures on all cognitive tests as well as global cognition. For global cognition, PF mediated 6.08% of the association. PF was also found to have a mediating role in the association between NO X , NO2, PM2.5, and the risk of dementia. Conclusions Mixed air pollution may impact cognitive function, with PF potentially mediating this relationship. [ABSTRACT FROM AUTHOR]

Early identification of people at risk of cancer-related malnutrition, low muscle mass (LMM) and sarcopenia is crucial to mitigate the impact of adverse outcomes. This study investigated risk factors associated with LMM, malnutrition and (probable-) sarcopenia and whether these varied in people with or without a history of cancer. Participants in the UK Biobank, with or without a history of cancer, who completed the Oxford WebQ at the baseline assessment were included. LMM was estimated from fat-free mass derived from bioelectrical impedance analysis, and low muscle strength from handgrip strength, and used to identify probable or confirmed sarcopenia following the European Working Group on Sarcopenia in Older People 2 definition. The Global Leadership Initiative on Malnutrition criteria were applied to determine malnutrition. Generalised linear models were used to estimate prevalence ratios (PR) for associations between risk factors (clinical, functional, nutritional) and study outcomes. Overall, 50,592 adults with (n = 2,287, mean ± SD 59.7 ± 7.1 years) or without (n = 48,305, mean ± SD 55.8 ± 8.2 years) cancer were included. For all participants (PRs [cancer, without cancer]), slow walking pace (PR 1.85; 1.99), multimorbidity (PR 1.72; 1.51), inflammation (PR 2.91; 2.07), and low serum 25(OH)D (PR 1.85, 1.44) were associated with higher prevalence of LMM, while higher energy intake (PR 0.55; 0.49) was associated with lower prevalence. Slow walking pace (PR 1.54 [cancer], 1.51 [without cancer]) and higher protein intake (PR 0.18 [cancer]; 0.11 [without cancer]) were associated with increased or decreased prevalence of malnutrition, respectively regardless of cancer status. Multimorbidity was the only common factor associated with higher prevalence (PR 1.79 [cancer], 1.68 [without cancer]) of (probable-)sarcopenia in all participants. Risk factors for LMM and malnutrition were similar in adults with and without cancer, although these varied between LMM and malnutrition. These findings have implications for the future of risk stratification, screening and assessment for these conditions and the development or modification of existing screening tools. [ABSTRACT FROM AUTHOR]

Aims Disruption of the predictable symmetry of the healthy heart may be an indicator of cardiovascular risk. This study defines the population distribution of ventricular asymmetry and its relationships across a range of prevalent and incident cardiorespiratory diseases. Methods and results The analysis includes 44 796 UK Biobank participants (average age 64.1 ± 7.7 years; 51.9% women). Cardiovascular magnetic resonance (CMR) metrics were derived using previously validated automated pipelines. Ventricular asymmetry was expressed as the ratio of left and right ventricular (LV and RV) end-diastolic volumes. Clinical outcomes were defined through linked health records. Incident events were those occurring for the first time after imaging, longitudinally tracked over an average follow-up time of 4.75 ± 1.52 years. The normal range for ventricular symmetry was defined in a healthy subset. Participants with values outside the 5th-95th percentiles of the healthy distribution were classed as either LV dominant (LV/RV > 112%) or RV dominant (LV/RV < 80%) asymmetry. Associations of LV and RV dominant asymmetry with vascular risk factors, CMR features, and prevalent and incident cardiovascular diseases (CVDs) were examined using regression models, adjusting for vascular risk factors, prevalent diseases, and conventional CMR measures. Left ventricular dominance was linked to an array of pre-existing vascular risk factors and CVDs, and a two-fold increased risk of incident heart failure, non-ischaemic cardiomyopathies, and left-sided valvular disorders. Right ventricular dominance was associated with an elevated risk of all-cause mortality. Conclusion Ventricular asymmetry has clinical utility for cardiovascular risk assessment, providing information that is incremental to traditional risk factors and conventional CMR metrics. [ABSTRACT FROM AUTHOR]

Background: Although observational studies have reported several common biomarkers related to coronary artery disease (CAD) and cancer, there is a shortage of traditional epidemiological data to establish causative linkages. Thus, we conducted a comprehensive two-sample Mendelian randomization (MR) analysis to systematically investigate the causal associations of 109 traits with both CAD and cancer to identify their shared risk and protective factors. Methods: The genetic association datasets pertaining to exposure and outcomes were reviewed using the most recent and public genome-wide association studies (GWAS). Inverse variance weighting (IVW), weighted median (WM), and MR-Egger strategies were implemented for the MR analyses. The heterogeneity and pleiotropy were measured utilizing leave-one-out sensitivity testing, MR-PRESSO outlier detection, and Cochran’s Q test. Results: The IVW analyses revealed that genetic-predicted mean sphered cell volume (MSCV) is a protective factor for CAD, and weight is a risk factor. MSCV and weight also show similar effects on cancer. Furthermore, our study also identified a set of risk and protective factors unique to CAD and cancer, such as telomere length. Conclusions: Our Mendelian randomization study sheds light on shared and unique risk and protective factors for CAD and cancer, offering valuable insights that could guide future research and the development of personalized strategies for preventing and treating these two significant health issues. [ABSTRACT FROM AUTHOR]

Background: Liver disease and dementia are both highly prevalent and share common pathological mechanisms. We aimed to investigate the associations between metabolic dysfunction-associated fatty liver disease (MAFLD), metabolic dysfunction-associated steatotic liver disease (MASLD) and the risk of all-cause and cause-specific dementia. Methods: We conducted a prospective study with 403,506 participants from the UK Biobank. Outcomes included all-cause dementia, Alzheimer's disease, and vascular dementia. Multivariable Cox proportional hazards models were used for analyses. Results: 155,068 (38.4%) participants had MAFLD, and 111,938 (27.7%) had MASLD at baseline. During a median follow-up of 13.7 years, 5,732 participants developed dementia (2,355 Alzheimer's disease and 1,274 vascular dementia). MAFLD was associated with an increased risk of vascular dementia (HR 1.32 [95% CI 1.18–1.48]) but a reduced risk of Alzheimer's disease (0.92 [0.84–1.0]). Differing risks emerged among MAFLD subtypes, with the diabetes subtype increasing risk of all-cause dementia (1.8 [1.65–1.96]), vascular dementia (2.95 [2.53–3.45]) and Alzheimer's disease (1.46 [1.26–1.69]), the lean metabolic disorder subtype only increasing vascular dementia risk (2.01 [1.25–3.22]), whereas the overweight/obesity subtype decreasing risk of Alzheimer's disease (0.83 [0.75–0.91]) and all-cause dementia (0.9 [0.84–0.95]). MASLD was associated with an increased risk of vascular dementia (1.24 [1.1–1.39]) but not Alzheimer's disease (1.0 [0.91–1.09]). The effect of MAFLD on vascular dementia was consistent regardless of MASLD presence, whereas associations with Alzheimer's disease were only present in those without MASLD (0.78 [0.67–0.91]). Conclusions: MAFLD and MASLD are associated with an increased risk of vascular dementia, with subtype-specific variations observed in dementia risks. Further research is needed to refine MAFLD and SLD subtyping and explore the underlying mechanisms contributing to dementia risk. [ABSTRACT FROM AUTHOR]

Background: Although inflammation has been linked to nonalcoholic fatty liver disease (NAFLD), most studies have focused only on a single indicator, leading to inconsistent results. Therefore, a large prospective study that includes a variety of well-documented single and composite indicators of inflammation is needed. This study aimed to thoroughly investigate the potential associations between different systemic inflammatory indicators and NAFLD in the UK Biobank cohort. Methods: After excluding ineligible participants, 378,139 individuals were included in the study. Associations between systemic inflammatory indicators and hepatic steatosis were assessed using multivariate logistic regression. The relationships between systemic inflammatory indicators and nonalcoholic fatty liver disease were analysed using Cox proportional hazards models, and nonlinear associations were investigated using restricted cubic splines. Results: According to the cross-sectional analysis, systemic inflammatory indicators significantly correlated with hepatic steatosis. Over a median followup of 13.9 years, 4,145 individuals developed NAFLD. After sufficient adjustment for confounding factors, CRP levels were found to be nonlinearly positively associated with NAFLD risk (P<0.001), representing the strongest correlation among the tested relationships; lymphocyte count and the LMR showed an L-shaped correlation; monocyte count and neutrophil count showed a linear positive correlation (all P< 0.001); and the NLR, PLR, and SII showed a U-shaped correlation (all P<0.001). Conclusions: Multiple systemic inflammatory indicators are strongly associated with the development of NAFLD, and aggressive systemic inflammation management may have a favourable impact on reducing the burden of NAFLD; further randomized controlled studies are needed. [ABSTRACT FROM AUTHOR]

Background: Multiple sclerosis (MS) is a chronic inflammatory disease affecting the central nervous system. While previous studies have indicated that albumin, the primary protein in human plasma, may exert influence on the inflammatory process and confer beneficial effects in neurodegenerative disorders, its role in the context of MS has been underexplored. Here, we aimed to explore the link between albumin and the risk of MS. Methods: Employing data from the UK Biobank, we investigated the association between baseline levels of serum and urine albumin and the risk of MS using Cox proportional hazards regression analysis. Results: A higher baseline level of serum albumin was associated with a lower risk of incident MS (HR=0.94, 95% CI: 0.91-0.98, P=7.66E-04). Subgroup analysis revealed a more pronounced effect in females, as well as participants with younger ages, less smoking and deficient levels of vitamin D. Conversely, no association was identified between baseline microalbuminuria level and risk of incident MS. Conclusion: Higher serum albumin level at baseline is linked to a reduced risk of MS. These results contribute to an enhanced understanding of albumin's role in MS, propose the potential use of albumin as a biomarker for MS, and have implications for the design of therapeutic interventions targeting albumin in clinical trials. [ABSTRACT FROM AUTHOR]