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BACKGROUND: Cardiometabolic diseases (CMDs) including type 2 diabetes, heart disease, and stroke have been linked to a higher risk of dementia. We examined whether high levels of cognitive reserve (CR) can attenuate the increased dementia risk and brain pathologies associated with CMDs. METHODS: Within the UK Biobank, 216,178 dementia-free participants aged ≥ 60 were followed for up to 15 years. Baseline CMDs and incident dementia were ascertained from medical records, medication use, and medical history. Latent class analysis was used to generate an indicator of CR (low, moderate, and high) based on education, occupational attainment, confiding in others, social contact, leisure activities, and television watching time. A subsample (n = 13,663) underwent brain MRI scans during follow-up. Volumes of total gray matter (GMV), hippocampus (HV), and white matter hyperintensities (WMHV) were ascertained, as well as mean diffusivity (MD) and fractional anisotropy (FA) in white matter tracts. RESULTS: At baseline, 43,402 (20.1%) participants had at least one CMD. Over a mean follow-up of 11.7 years, 6,600 (3.1%) developed dementia. The presence of CMDs was associated with 57% increased risk of dementia (HR 1.57 [95% CI 1.48, 1.67]). In joint effect analysis, the HRs of dementia for people with CMDs and moderate-to-high CR and low CR were 1.78 [1.66, 1.91] and 2.13 [1.97, 2.30]), respectively (reference: CMD-free, moderate-to-high CR). Dementia risk was 17% lower (HR 0.83 [0.77, 0.91], p

Understanding the contribution of gene-environment interactions (GxE) to complex trait variation can provide insights into disease mechanisms, explain sources of heritability, and improve genetic risk prediction. While large biobanks with genetic and deep phenotypic data hold promise for obtaining novel insights into GxE, our understanding of GxE architecture in complex traits remains limited. We introduce a method to estimate the proportion of trait variance explained by GxE (GxE heritability) and additive genetic effects (additive heritability) across the genome and within specific genomic annotations. We show that our method is accurate in simulations and computationally efficient for biobank-scale datasets. We applied our method to common array SNPs (MAF ≥1%), fifty quantitative traits, and four environmental variables (smoking, sex, age, and statin usage) in unrelated white British individuals in the UK Biobank. We found 68 trait-E pairs with significant genome-wide GxE heritability (p

INTRODUCTION: We estimated the ages when associations between Alzheimers disease (AD) genes and brain volumes begin among middle-aged and older adults. METHODS: Among 45,616 dementia-free participants aged 45-80, linear regressions tested whether genetic risk score for AD (AD-GRS) had age-dependent associations with 38 regional brain magnetic resonance imaging volumes. Models were adjusted for sex, assessment center, genetic ancestry, and intracranial volume. RESULTS: AD-GRS modified the estimated effect of age (per decade) on the amygdala (-0.41 mm3 [-0.42, -0.40]); hippocampus (-0.45 mm3 [-0.45, -0.44]), nucleus accumbens (-0.55 mm3 [-0.56, -0.54]), thalamus (-0.38 mm3 [-0.39, -0.37]), and medial orbitofrontal cortex (-0.23 mm3 [-0.24, -0.22]). Trends began by age 45 for the nucleus accumbens and thalamus, 48 for the hippocampus, 51 for the amygdala, and 53 for the medial orbitofrontal cortex. An AD-GRS excluding apolipoprotein E (APOE) was additionally associated with entorhinal and middle temporal cortices. DISCUSSION: APOE and other genes that increase AD risk predict lower hippocampal and other brain volumes by middle age.

Nearly two hundred common-variant depression risk loci have been identified by genome-wide association studies (GWAS). However, the impact of rare coding variants on depression remains poorly understood. Here, we present whole-exome sequencing analyses of depression with seven different definitions based on survey, questionnaire, and electronic health records in 320,356 UK Biobank participants. We showed that the burden of rare damaging coding variants in loss-of-function intolerant genes is significantly associated with risk of depression with various definitions. We compared the rare and common genetic architecture across depression definitions by genetic correlation and showed different genetic relationships between definitions across common and rare variants. In addition, we demonstrated that the effects of rare damaging coding variant burden and polygenic risk score on depression risk are additive. The gene set burden analyses revealed overlapping rare genetic variant components with developmental disorder, autism, and schizophrenia. Our study provides insights into the contribution of rare coding variants, separately and in conjunction with common variants, on depression with various definitions and their genetic relationships with neurodevelopmental disorders.

Context/Objectives: Hydroxychoroquine has hypoglycemic effects and may reduce the risk of diabetes mellitus (DM). We determined the association between hydroxychoroquine use and the incidence of DM in a population-based cohort of pations with Rheumatic disease Methods: A prospective cohort study among 502392 Potentially eligible participants in the context of UK Biobank, recruitment to the database began between 2006 and 2010. Patients diagnosed with diabetes and fasting glucose greater than or equal to 7 mmol/L at baseline (n=619) were excluded and patients diagnosed with either RA or SLE at baseline (n=6793) were followed up until 2022. Diagnosis was recorded using the International Classification of Diseases, tenth edition (ICD-10) code. The mean follow-up was 13.78 years and the primary outcome was newly recorded type 2 diabetes mellitus (T2DM), with the time of onset of diabetes as the follow-up endpoint date. Results: During a median follow-up period of 13.78 (12.93, 14.49) years, diabetes developed in 537 participants, with an incidence of 7.9%. New diabetes cases not taking hydroxychloroquine and taking hydroxychloroquine was 504 (8.03%) and 33 (6.36%), respectively. In univariate models, the hazard ratio for diabetes was 0.89 (95% confidence interval, 0.81-0.98, P =0.014) for hydroxychloroquine users compared with those not taking hydroxychloroquine. After adjusting for age, sex, race, education level, and BMI the hazard ratio for incident diabetes among hydroxychloroquine users was 0.88 (95% confidence interval, 0.80-0.97, P =0.008). In complete multivariate model hazard ratio for hydroxychloroquine was 0.87 (95% confidence interval, 0.79- 0.96, P =0.005). Conclusion: Hydroxychloroquine was associated with decreased risk of DM among rheumatoid arthritis patients, our data taken together with correlational studies, warrant further investigation of the potential preventive effect of hydroxychloroquine against T2DM. [ABSTRACT FROM AUTHOR]

Background Methods Results Conclusion We sought to investigate the association between obesity, metabolic syndrome, and metabolic health with incident primary open‐angle glaucoma (POAG).We included 103 249 UK Biobank participants without previously diagnosed glaucoma or glaucoma‐related procedures at enrolment. The primary outcome was POAG identified from diagnostic coding via linked hospital inpatient and primary care data. We used multivariable Cox regression to evaluate the association of body mass index (BMI), and the interaction with metabolic syndrome (MetS) and a novel definition of metabolic health status with incident POAG. BMI was modelled as a time‐varying coefficient. Multivariable analysis was adjusted for age, sex, ethnicity, intraocular pressure, spherical equivalent, polygenic risk score and stratified by the presence of primary care data.There were 647 events of incident POAG over 464 117 580 person‐years and a mean follow‐up of 12.6 years. At baseline (time = 0), each one unit increase in BMI was associated with a 9% lower hazard of incident glaucoma (HR 0.91, CI 0.86–0.97, p = 0.0066). Further, compared to a normal BMI range of 18.5–24 kg/m2, a BMI ≥30 kg/m2 was associated with a 65% relative hazard reduction (HR 0.35, CI 0.16–0.80, p = 0.012). There was no significant interaction between BMI and metabolic syndrome or metabolic health (all p > 0.05).The effect of BMI on the risk of incident POAG varied with time. Higher BMI was associated with a decreased risk of incident POAG in this large prospective cohort. There was no significant association with systemic metabolic health. [ABSTRACT FROM AUTHOR]

Reduced muscle mass has been associated with the progression and prognosis of amyotrophic lateral sclerosis (ALS). However, it remains unclear whether decreased muscle mass is a risk factor for ALS or a consequence of motor neuron degeneration. Recently, serum creatinine-to-cystatin C ratio (CCR) have emerged as promising biomarkers for assessing muscle mass. We aimed to explore the association between CCR and the incidence of ALS using data from the UK Biobank. Between 2006 and 2010, 446,945 participants were included in the baseline. CCR was calculated as the ratio of serum creatinine to cystatin C. Cox regression models were used to analyze the relationship between CCR and ALS incidence. Furthermore, subgroup analyses were conducted to investigate potential covariates in these relationships. After adjusting for all covariates, the multivariate Cox regression analysis revealed a significant association between decreased CCR and an increased risk of ALS (hazard ratio (HR) = 0.990, 95% confidence interval (CI): 0.982–0.999, P = 0.026). Participants were stratified into groups based on CCR tertiles. Compared with participants in the highest tertiles of CCR, those in the lowest (HR = 1.388, 95% CI: 1.032–1.866, P = 0.030) and medium tertiles (HR = 1.348, 95% CI: 1.045–1.739, P = 0.021) had an increased risk of ALS incidence. Subgroup analysis showed that the relationship between CCR and ALS incidence was particularly significant among participants aged < 65 years (CCR tertile 1: HR = 1.916, 95% CI: 1.366–2.688, P < 0.001; CCR tertile 2: HR = 1.699, 95% CI: 1.267–2.278, P < 0.001). The present results demonstrate that lower CCR is significantly associated with a higher risk of ALS. [ABSTRACT FROM AUTHOR]

Background: Bias from data missing not at random (MNAR) is a persistent concern in health-related research. A bias analysis quantitatively assesses how conclusions change under different assumptions about missingness using bias parameters that govern the magnitude and direction of the bias. Probabilistic bias analysis specifies a prior distribution for these parameters, explicitly incorporating available information and uncertainty about their true values. A Bayesian bias analysis combines the prior distribution with the data's likelihood function whilst a Monte Carlo bias analysis samples the bias parameters directly from the prior distribution. No study has compared a Monte Carlo bias analysis to a Bayesian bias analysis in the context of MNAR missingness. Methods: We illustrate an accessible probabilistic bias analysis using the Monte Carlo bias analysis approach and a well-known imputation method. We designed a simulation study based on a motivating example from the UK Biobank study, where a large proportion of the outcome was missing and missingness was suspected to be MNAR. We compared the performance of our Monte Carlo bias analysis to a principled Bayesian bias analysis, complete case analysis (CCA) and multiple imputation (MI) assuming missing at random. Results: As expected, given the simulation study design, CCA and MI estimates were substantially biased, with 95% confidence interval coverages of 7–48%. Including auxiliary variables (i.e., variables not included in the substantive analysis that are predictive of missingness and the missing data) in MI's imputation model amplified the bias due to assuming missing at random. With reasonably accurate and precise information about the bias parameter, the Monte Carlo bias analysis performed as well as the Bayesian bias analysis. However, when very limited information was provided about the bias parameter, only the Bayesian bias analysis was able to eliminate most of the bias due to MNAR whilst the Monte Carlo bias analysis performed no better than the CCA and MI. Conclusion: The Monte Carlo bias analysis we describe is easy to implement in standard software and, in the setting we explored, is a viable alternative to a Bayesian bias analysis. We caution careful consideration of choice of auxiliary variables when applying imputation where data may be MNAR. [ABSTRACT FROM AUTHOR]

Background and aims: Previous study found that estimated glucose disposal rate (eGDR) was significantly associated with cardiovascular disease (CVD). However, little is known about the change in eGDR over time and its association with the development of CVD. The aim of this study was to investigate the association of change in eGDR with CVD risk. Methods: This study used data of two prospective cohorts: UK Biobank and China Health and Retirement Longitudinal Study (CHARLS) with two measurements of eGDR. Changes in the eGDR were classified using K‑means clustering analysis, and the cumulative eGDR was also calculated. Cox proportional hazard models were used to calculate the hazard ratio (HR) and 95% confidence interval (95% CI) after adjusting for potential confounders. Results: A total of 11,682 individuals from the UK Biobank, and 4,974 individuals from the CHARLS were included. The median follow-up periods were 9.7 years in the UK Biobank and 3.0 years in the CHARLS. Compared with persistently high level of eGDR (class 1), individuals with low level increasing (class 3) and persistently low level of eGDR (class 4) showed elevated risks of incident CVD in both UK Biobank (HR = 2.79, 95% 2.15–3.62 for class 3; HR = 3.19, 95% 2.50–4.08 for class 4) and CHARLS (HR = 1.66, 95% 1.29–2.13 for class 3; HR = 1.69, 95% 1.34–2.14 for class 4). In addition, lower level of cumulative eGDR were associated with elevated risks of incident CVD. The dose-response curve between cumulative eGDR and CVD risk showed a negative linear relationship. Conclusion: Different changes in eGDR level are associated with different risks of incident CVD. Dynamic monitoring of eGDR level is of significant importance for the CVD prevention and treatment. [ABSTRACT FROM AUTHOR]

Background: Patients with irritable bowel syndrome (IBS) often have chronic low-grade inflammation in the intestinal mucosa. Some dietary components are known to be associated with inflammation. However, there is currently limited research on the relationship between dietary inflammatory potential and the risk of IBS. Methods: A total of 129,408 participants in the UK Biobank were included in this study. Energy-Adjusted Dietary Inflammatory Index (E-DII) based on 26 nutrients and the Empirical Dietary Inflammatory Pattern (EDIP) based on 17 food groups were constructed, and on the basis of the tertiles, the continuous score was categorized into proinflammatory, neutral, and antiinflammatory categories. Associations between IBS and E-DII and EDIP were investigated by multivariable Cox proportional hazard models. Potential confounders including sociodemographic, lifestyle, body mass index (BMI), psychological state, type 2 diabetes, and thyroiditis were adjusted. In addition, subgroup analysis and sensitivity analysis were also performed. Finally, a two-sample Mendelian randomization (MR) analysis was employed to explore the independent causality of nutrients and dietary-derived serum antioxidants with IBS. Results: In the cohort study, over a median follow-up period of 13.26 years, 2421(1.87%) participants developed IBS. In the E-DII categories, after adjusting for the confounders, individuals in the proinflammatory diet category had a higher risk of IBS compared with the antiinflammatory category (HR 1.15, 95% CI 1.03–1.28, p = 0.015, p trend = 0.017) and neutral category (HR 1.13, 95% CI 1.01–1.26, p = 0.030, p trend = 0.017). In the EDIP categories, after adjusting for the confounders, individuals in the proinflammatory diet category had a higher risk of IBS compared with antiinflammatory category (HR 1.19, 95% CI 1.06–1.33, p = 0.002, p trend = 0.002) but no significant association compared with neutral category (HR 1.10, 95% CI 0.99–1.23, p = 0.067, p trend = 0.002). In the MR analysis, genetically determined intake levels of 16 nutrients and 6 dietary sources of circulating antioxidants did not have a causal effect on IBS. Conclusions: Our findings indicate that proinflammatory dietary components are independent risk factors for IBS. However, there is no causal relationship between individual nutrient intake or serum antioxidants from dietary sources and IBS. [ABSTRACT FROM AUTHOR]

Background: Modifiable (physical activity) and non-modifiable (sex and genotype) risk factors interact to affect Alzheimer's disease (AD) risk. Further investigation is necessary to understand if these factors influence brain volume and cognition. Objective: The study aimed to assess the effect of physical activity, APOE genotype, and sex on AD risk, brain volume, and cognition. Methods: UK Biobank data from 2006 to 2023 was accessed. Physical activity was measured by accelerometers, and International Physical Activity Questionnaire. Outcomes were AD incidence; brain volume (ventricular cerebrospinal fluid and total brain); and cognition (executive function, memory, visuospatial ability, processing speed, and reaction time). Logistic and linear regression models were conducted. Results: 69,060 participants met inclusion criteria (mean age: 62.28 years, SD: 7.84; 54.64% female). Higher self-reported (OR = 0.63, 95% CI [0.40, 1.00], p = 0.047) and accelerometer-assessed (OR = 0.96 [0.93, 0.98], p = 0.002) physical activity was associated with lower disease incidence. Smaller ventricular cerebrospinal fluid volume (β= – 65.43 [– 109.68, – 17.40], p = 0.007), and larger total brain volume (β= 4398.46 [165.11, 8631.82], p < 0.001) was associated with increased accelerometer-assessed and self-reported physical activity respectively. Both brain volume analyses were moderated by sex. Increased accelerometer-assessed physical activity levels were associated with faster reaction time (β= – 0.43 [– 0.68, – 0.18], p = 0.001); though poorer visuospatial ability (β= – 0.06 [– 0.09, – 0.03], p < 0.001), and executive function (β= 0.49 [0.31, 0.66], p < 0.001; β= 0.27 [0.10, 0.45], p = 0.002) was related to self-reported physical activity levels. Conclusions: Higher levels of physical activity reduce AD risk independently of non-modifiable risk factors. Moderation of sex on brain volume highlighted the importance of incorporating non-modifiable risk factors in analysis. [ABSTRACT FROM AUTHOR]

Aim: To evaluate the association of glycated haemoglobin (HbA1c) and serum glucose with intraocular pressure (IOP) in a large UK general population. Materials and Methods: Participants were selected from the UK Biobank, excluding those with eye conditions that may affect IOP. IOP was measured using an ocular response analyser. Goldmann‐correlated IOP (IOPg) and corneal‐compensated IOP (IOPcc) were outcomes of interest, and ocular hypertension was defined as left‐eye IOPg or IOPcc > 21 mmHg. HbA1c and random (non‐fasting) serum glucose were the exposures of interest. Multivariate restricted cubic spline models, as well as linear regression, were applied to explore the associations of interest. Results: Among 68 806 participants (46.5% male), the mean age was 56.7 years. The mean (standard deviation) for IOPg was 15.7 (3.6) mmHg and 15.9 (3.6) mmHg for IOPcc. Occular hypertension was prevalent in 8055 participants (11.7%) and 4178 participants (6.1%) had diabetes. Those with diabetes had higher IOP and a higher prevalence of ocular hypertension. After adjustment for demographic and clinical variables, HbA1c was positively associated with IOP in participants with diabetes, but not in those without diabetes. For every 10‐mmol/mol increase in HbA1c, IOPg increased by 0.20 mmHg (95% confidence interval [CI] 0.12, 0.28) and IOPcc by 0.15 mmHg (95% CI 0.07, 0.23); the odds of ocular hypertension was increased by 6% (95% CI 1.00, 1.13) in participants with diabetes. A borderline positive association between serum glucose and IOP was found only in participants without diabetes. Conclusions: Impaired glycaemic control was associated with elevated IOP and a possible risk of ocular hypertension among participants with diabetes but of normal ocular health. [ABSTRACT FROM AUTHOR]

The interplay between genetic and lifestyle factors in the development of bipolar disorder (BD) remains unclear. A cohort study was carried out on 365,517 participants from the UK Biobank. Lifestyle scores, based on smoking, physical activity, diet, alcohol consumption, sedentary behavior, sleep duration, and social contact, were grouped as favorable (scores 6–7), intermediate (scores 4–5), or unfavorable (scores 0–3). The BD polygenic risk score (PRS) was also categorized into high, intermediate, and low-risk groups using PRS tertiles. Cox regression models determined hazard ratios (HRs) and 95 % confidence intervals (CIs) for BD. During the 12.9-year follow-up, 529 individuals developed BD. Comparing those with favorable lifestyles to those with unfavorable participants, the HR of developing BD was 3.28 (95 % CI, 2.76–3.89). Similarly, individuals with a high PRS had a risk of 3.20 (95 % CI, 2.83–3.63) compared to those with a low PRS. Notably, individuals with both a high PRS and an unfavorable lifestyle had a significantly higher risk of BD (HR = 6.31, 95 % CI, 4.14–9.63) compared to those with a low PRS and a favorable lifestyle. Additionally, the interaction between PRS and lifestyle contributed an additional risk, with a relative excess risk of 1.74 (95 % CI, 0.40–3.07) and an attributable proportion due to the interaction of 0.37 (95 % CI, 0.16–0.58). Our findings suggest that genetic liability for BD, measured as PRS, and lifestyle have an additive effect on the risk of developing BD. A favorable lifestyle was associated with a reduced risk of developing BD. • High polygenic risk score (PRS) and unfavorable lifestyles both increase risk of bipolar disorder (BD). • The coexistence of high PRS and unfavorable lifestyle has an additive interaction on the risk of developing BD. • Irrespective of PRS, adopting a favorable lifestyle was consistently linked to a decreased risk of BD. [ABSTRACT FROM AUTHOR]

Older parental age at birth is associated with increased risk of autism spectrum disorders (ASD) in offspring. Independently, shorter telomere length (TL) has also been shown to be associated with ASD in children. However, older paternal age at birth, with or without controlling for maternal age, has been associated with longer TL, a seemingly contradictory finding. Here, we conducted a retrospective cohort study among participants in the UK Biobank to disentangle associations between leukocyte TL and ASD status in adults, and the potential moderation by parental age on adult offspring's TL. Participants with ASD diagnosis (N = 87) with a mean age of 46.0 (SD 4.4) years were matched to participants without ASD diagnosis (N = 870) based on age, sex, ethnicity, education, household income, and assessment center. No statistically significant differences were seen in TL between participants with and without ASD when parental age at birth was not considered. However, there was a significant interaction between ASD diagnostic status and parental age on participants' TL, such that older paternal or maternal age at birth was more strongly associated with longer TL in participants with ASD. This study suggests that the shortened TL observed in children with ASD in previous research may partially depend on parental age at birth. Future studies tracking TL attrition before ASD diagnosis are warranted to depict temporal associations and the interacting effects of parental age at birth and ASD status on TL across the lifespan. Lay Summary: Older biological age, as measured by shortened telomere length, has been observed in children with autism spectrum disorders (ASD). In contrast, older parental age at birth has been related to both ASD risk and longer telomere length. In the present study, telomere length did not differ significantly between adults with and without ASD. However, we found that longer telomere length among adults with ASD versus adults without ASD could be more apparent in individuals with older parents. These findings suggest that parental age at birth may explain telomere length differences between individuals with and without ASD, and that the shorter telomere length previously found in children with ASD may depend on parental age at birth. [ABSTRACT FROM AUTHOR]

Objective: Approximately 30% of adults globally suffer from sleep disorders. However, there are few longitudinal studies on the association between dietary vitamin C and sleep disorders. This study aimed to investigate the association between dietary vitamin C intake and various types of sleep disorders, including sleep apnea and insomnia. Methods: We enrolled 68,221 participants from the UK Biobank. Dietary vitamin C intake was assessed using a 24 h dietary recall questionnaire. We employed a Cox regression model to assess the association between dietary vitamin C and sleep disorders and used restricted cubic spline models to investigate potential nonlinear relationships. Stratified and sensitivity analyses were also conducted to validate the findings. Results: The results indicated that vitamin C intake at the Q4 level (132.88–191.51 mg/d) was significantly associated with a reduced risk of sleep disorders, with an HR (95% CI) of 0.78 (0.65–0.94), and against sleep apnea, with an HR (95% CI) of 0.75 (0.62–0.92). The protective effect persisted significant in stratified analyses of men and those aged ≤ 60 years; the results were consistent in the sensitivity analyses. Conclusions: Our findings suggest that sufficient dietary vitamin C intake may help to prevent sleep disorders. [ABSTRACT FROM AUTHOR]

Background: The protective effect of a healthy diet combined with stair climbing on cardiovascular health is unclear. We aimed to assess the independent and joint associations of dietary patterns and stair climbing with major adverse cardiovascular events (MACEs). Methods: We included 117,384 participants with information on dietary intake and stair climbing from the UK Biobank (UKBB). We excluded participants with MACEs at baseline and death within two years of follow-up. We used restricted cubic spline (RCS) plots describing the linear or nonlinear associations between dietary patterns (the alternate Mediterranean diet score (AMED), dietary approaches to stop hypertension (DASH), the healthful planted-based diet index (HPDI) and the alternate healthy eating index-2010 (AHEI-2010)) and stair climbing and MACEs. COX regressions estimated the hazard ratios (HRs) for incident MACEs associated with dietary patterns combined with stair climbing, and adjusted for sociodemographic, lifestyle and medical factors. Results: The UKBB documented 9408 MACEs over a median follow-up of 13.3 years. Four dietary patterns were negatively and linearly associated with MACEs (P-nonlinear > 0.05), whereas daily stair climbing was negatively and nonlinearly associated with MACEs (P-nonlinear = 0.011). All of the dietary patterns had significant multiplicative interactions with stair climbing (all p-values < 0.05). The three dietary patterns had the lowest risk ratios for MACEs in the highest tertile (T3) combined with daily stair climbing of 60–100 steps (AMED: 0.78 (0.68, 0.89), DASH: 0.80 (0.70, 0.91) and HPDI: 0.86 (0.75, 0.98)), whereas the AHEI-2010 had the lowest HRs for MACEs in the T1 combined with stair climbing of 110–150 steps (AHEI-2010: 0.81 (0.71, 0.93)). Conclusions: Maintaining healthy dietary patterns and adhering to an average of 60–100 steps of stair climbing per day at home can be effective in preventing cardiovascular health-related events. [ABSTRACT FROM AUTHOR]

Objective: To investigate the association between serum 25(OH)D and kidney stone disease (KSD) in participants from the UK Biobank. Methods: We used data from the UK Biobank. Our analysis involved Cox proportional hazards models to calculate hazard ratios (HRs) and 95% confidence intervals (CIs) to estimate the association between serum 25(OH)D levels (measured at the time of recruitment) and the risk of KSD, which was determined using hospital records. Results: This study involved 444,343 participants, with 4,458 cases of KSD identified during an average follow-up period of 12.6 years. Higher 25(OH)D levels were not associated with developing kidney stones in general population model 3 (HR = 0.88 [95% CI 0.77–1.01]). Interestingly, higher serum 25(OH)D concentrations in women over 60 years old were associated with a lower risk of kidney stone disease. The multivariate HRs and 95% CIs for participants who had serum 25(OH)D ≥ 50 nmol/L or ≥ 75 nmol/L, compared with those who were severely deficient (25[OH]D < 25 nmol/L), were 0.74 (0.58–0.95), 0.60 (0.43–0.85) for KSD, respectively (P for trend < 0.01). However, this trend was not statistically significant in the subgroup analysis of serum calcium ion concentration. Conclusion: High 25(OH)D levels were not associated with a higher incidence of kidney stones if serum calcium levels are within a normal range. The findings alleviate physiological concerns regarding the supplementation of vitamin D alone to raise serum 25(OH)D concentration. [ABSTRACT FROM AUTHOR]

Objectives To address the need for interactive visualization tools and databases in characterizing multimorbidity patterns across different populations, we developed the Phenome-wide Multi-Institutional Multimorbidity Explorer (PheMIME). This tool leverages three large-scale EHR systems to facilitate efficient analysis and visualization of disease multimorbidity, aiming to reveal both robust and novel disease associations that are consistent across different systems and to provide insight for enhancing personalized healthcare strategies. Materials and Methods PheMIME integrates summary statistics from phenome-wide analyses of disease multimorbidities, utilizing data from Vanderbilt University Medical Center, Mass General Brigham, and the UK Biobank. It offers interactive and multifaceted visualizations for exploring multimorbidity. Incorporating an enhanced version of associationSubgraphs, PheMIME also enables dynamic analysis and inference of disease clusters, promoting the discovery of complex multimorbidity patterns. A case study on schizophrenia demonstrates its capability for generating interactive visualizations of multimorbidity networks within and across multiple systems. Additionally, PheMIME supports diverse multimorbidity-based discoveries, detailed further in online case studies. Results The PheMIME is accessible at https://prod.tbilab.org/PheMIME/. A comprehensive tutorial and multiple case studies for demonstration are available at https://prod.tbilab.org/PheMIME%5fsupplementary%5fmaterials/. The source code can be downloaded from https://github.com/tbilab/PheMIME. Discussion PheMIME represents a significant advancement in medical informatics, offering an efficient solution for accessing, analyzing, and interpreting the complex and noisy real-world patient data in electronic health records. Conclusion PheMIME provides an extensive multimorbidity knowledge base that consolidates data from three EHR systems, and it is a novel interactive tool designed to analyze and visualize multimorbidities across multiple EHR datasets. It stands out as the first of its kind to offer extensive multimorbidity knowledge integration with substantial support for efficient online analysis and interactive visualization. [ABSTRACT FROM AUTHOR]

Background: There have been many efforts to expand existing data collection initiatives to include COVID-19 related data. One program that expanded is UK Biobank, a large-scale research and biomedical data collection resource that added several COVID-19 related data fields including questionnaires (exposures and symptoms), viral testing, and serological data. This study aimed to analyze this COVID-19 data to understand how COVID-19 data was collected and how it can be used to attribute COVID-19 and analyze differences in cohorts and time periods. Methods: A cohort of COVID-19 infected individuals was defined from the UK Biobank population using viral testing, diagnosis, and self-reported data. Changes over time, from March 2020 to October 2021, in total case counts and changes in case counts by identification source (diagnosis from EHR, measurement from viral testing and self-reported from questionnaire) were also analyzed. For the questionnaires, an analysis of the structure and dynamics of the questionnaires was done which included the amount and type of questions asked, how often and how many individuals answered the questions and what responses were given. In addition, the amount of individuals who provided responses regarding different time segments covered by the questionnaire was calculated along with how often responses changed. The analysis included changes in population level responses over time. The analyses were repeated for COVID and non-COVID individuals and compared responses. Results: There were 62 042 distinct participants who had COVID-19, with 49 120 identified through diagnosis, 30 553 identified through viral testing and 934 identified through self-reporting, with many identified in multiple methods. This included vast changes in overall cases and distribution of case data source over time. 6 899 of 9 952 participants completing the exposure questionnaire responded regarding every time period covered by the questionnaire including large changes in response over time. The most common change came for employment situation, which was changed by 74.78% of individuals from the first to last time of asking. On a population level, there were changes as face mask usage increased each successive time period. There were decreases in nearly every COVID-19 symptom from the first to the second questionnaire. When comparing COVID to non-COVID participants, COVID participants were more commonly keyworkers (COVID: 33.76%, non-COVID: 15.00%) and more often lived with young people attending school (61.70%, 45.32%). Conclusion: To develop a robust cohort of COVID-19 participants from the UK Biobank population, multiple types of data were needed. The differences based on time and exposures show the important of comprehensive data capture and the utility of COVID-19 related questionnaire data. [ABSTRACT FROM AUTHOR]

Background: Shapley values have been used extensively in machine learning, not only to explain black box machine learning models, but among other tasks, also to conduct model debugging, sensitivity and fairness analyses and to select important features for robust modelling and for further follow-up analyses. Shapley values satisfy certain axioms that promote fairness in distributing contributions of features toward prediction or reducing error, after accounting for non-linear relationships and interactions when complex machine learning models are employed. Recently, feature selection methods using predictive Shapley values and p-values have been introduced, including powershap. Methods: We present a novel feature selection method, LLpowershap, that takes forward these recent advances by employing loss-based Shapley values to identify informative features with minimal noise among the selected sets of features. We also enhance the calculation of p-values and power to identify informative features and to estimate number of iterations of model development and testing. Results: Our simulation results show that LLpowershap not only identifies higher number of informative features but outputs fewer noise features compared to other state-of-the-art feature selection methods. Benchmarking results on four real-world datasets demonstrate higher or comparable predictive performance of LLpowershap compared to other Shapley based wrapper methods, or filter methods. LLpowershap is also ranked the best in mean ranking among the seven feature selection methods tested on the benchmark datasets. Conclusion: Our results demonstrate that LLpowershap is a viable wrapper feature selection method that can be used for feature selection in large biomedical datasets and other settings. [ABSTRACT FROM AUTHOR]

Background: Malnutrition is a complication of chronic kidney disease (CKD). Whether malnutrition, assessed via the geriatric nutritional risk index (GNRI), is associated with the incidence and risk of CKD in older individuals remains unclear. Methods: Data from the National Health and Nutrition Examination Survey and the UK Biobank database were used. Older participants over 60 years old with available data for GNRI assessment and CKD diagnosis were enrolled. Logistic regression models and Cox regression models were used to assess associations between the geriatric nutritional risk index and the risk of and mortality associated with CKD. Results: This study enrolled 13,162 participants from the NHANES and 66,326 participants from the UK Biobank. We identified 6,135 and 16,662 CKD patients in the NHANES and UK Biobank, respectively, with the majority being male (74% in the NHANES and 52% in the UK Biobank). The average age of CKD patients was 72.3 (SD 7.2) years in the NHANES and 64.9 (SD 2.9) years in the UK Biobank. The median follow-up times of older CKD patients were 81 months and 162 months in the NHANES and UK Biobank, respectively. According to the cross-sectional analysis, individuals with a lower GNRI had an increased likelihood of having CKD, with odds ratios of 1.38 (95% CI: 1.05–1.80, P = 0.020) in the NHANES and 2.35 (95% CI: 1.89–2.92, P < 0.001) in the UK Biobank. According to our analysis of the risk of incident CKD in the UK Biobank, a lower GNRI was associated with a greater incidence of CKD (HR: 1.11, 95% CI: 1.04–1.18; P = 0.002). According to the analysis of the risk of mortality, a lower GNRI was associated with an increased risk of death among older CKD patients (NHANES: HR: 1.69, 95% CI: 1.13–2.53, P = 0.011; UK Biobank: HR: 2.28, 95% CI: 1.94–2.69, P < 0.001). Conclusion: Malnutrition assessed by the GNRI was significantly and independently associated with the incidence of CKD. Moreover, CKD patients with malnutrition also have a high risk of mortality. [ABSTRACT FROM AUTHOR]

Summary We explored the effects of daylight saving time clock changes on sleep duration in a large accelerometer dataset. Our sample included UK Biobank participants (n = 11,780; aged 43–78 years) with accelerometer data for one or more days during the 2 weeks surrounding the Spring and Autumn daylight saving time transitions from October 2013 and November 2015. Between‐individual t‐tests compared sleep duration on the Sunday (midnight to midnight) of the clock changes with the Sunday before and the Sunday after. We also compared sleep duration on all other days (Monday–Saturday) before and after the clock changes. In Spring, mean sleep duration was 65 min lower on the Sunday of the clock changes than the Sunday before (95% confidence interval −72 to −58 min), and 61 min lower than the Sunday after (95% confidence interval −69 to −53). In Autumn, the mean sleep duration on the Sunday of the clock changes was 33 min higher than the Sunday before (95% confidence interval 27–39 min), and 38 min higher than the Sunday after (95% confidence interval 32–43 min). There was some evidence of catch‐up sleep after both transitions, with sleep duration a little higher on the Monday–Friday than before, although this was less pronounced in Autumn. Future research should use large datasets with longer periods of accelerometer wear to capture sleep duration before and after the transition in the same individuals, and examine other aspects of sleep such as circadian misalignment, sleep fragmentation or daytime napping. [ABSTRACT FROM AUTHOR]

Background: Loneliness has garnered significant attention globally, with extensive exploration of its association with cardiovascular disease. However, a notable research gap persists concerning loneliness and its potential link to atrial fibrillation (AF). Methods: This prospective cohort study utilized data from the UK Biobank (UKB), encompassing 441,056 participants. Loneliness was assessed through self-reported questionnaires gauging feelings of isolation and willingness to confide. AF diagnoses were ascertained using hospitalization records and cause-of-death registry data. The association between loneliness and AF risk was analyzed through multivariable Cox proportional hazard models. Results: Over a median follow-up period of 13.9 years, 25,386 AF cases were identified. In comparison to individuals without reported loneliness, those in the loneliness group exhibited a significantly higher risk of AF (loneliness vs. non-loneliness: hazard ratio [HR]: 1.11, 95% confidence interval [CI] 1.07–1.16). Subgroup analysis revealed that the association between loneliness and increased AF risk was significant solely in individuals without heart valve disease (HR: 1.12, 95% CI 1.07–1.16). Additionally, significant associations between loneliness and heightened AF risk were noted across strata of genetic susceptibility to AF, with no observable impact on these associations by genetic susceptibility (P for interaction = 0.070). Conclusions: This study establishes a robust association between loneliness and an elevated long-term risk of AF. Notably, this association is particularly pronounced in individuals without valvular disease and does not appear to be influenced by genetic predisposition to AF. [ABSTRACT FROM AUTHOR]

Background and Aims This study assessed whether a model incorporating clinical features and a polygenic score for ascending aortic diameter would improve diameter estimation and prediction of adverse thoracic aortic events over clinical features alone. Methods Aortic diameter estimation models were built with a 1.1 million-variant polygenic score (AORTA Gene) and without it. Models were validated internally in 4394 UK Biobank participants and externally in 5469 individuals from Mass General Brigham (MGB) Biobank, 1298 from the Framingham Heart Study (FHS), and 610 from All of Us. Model fit for adverse thoracic aortic events was compared in 401 453 UK Biobank and 164 789 All of Us participants. Results AORTA Gene explained more of the variance in thoracic aortic diameter compared to clinical factors alone: 39.5% (95% confidence interval 37.3%–41.8%) vs. 29.3% (27.0%–31.5%) in UK Biobank, 36.5% (34.4%–38.5%) vs. 32.5% (30.4%–34.5%) in MGB, 41.8% (37.7%–45.9%) vs. 33.0% (28.9%–37.2%) in FHS, and 34.9% (28.8%–41.0%) vs. 28.9% (22.9%–35.0%) in All of Us. AORTA Gene had a greater area under the receiver operating characteristic curve for identifying diameter ≥ 4 cm: 0.836 vs. 0.776 (P <.0001) in UK Biobank, 0.808 vs. 0.767 in MGB (P <.0001), 0.856 vs. 0.818 in FHS (P <.0001), and 0.827 vs. 0.791 (P =.0078) in All of Us. AORTA Gene was more informative for adverse thoracic aortic events in UK Biobank (P =.0042) and All of Us (P =.049). Conclusions A comprehensive model incorporating polygenic information and clinical risk factors explained 34.9%–41.8% of the variation in ascending aortic diameter, improving the identification of ascending aortic dilation and adverse thoracic aortic events compared to clinical risk factors. [ABSTRACT FROM AUTHOR]

Background: Type 2 diabetes mellitus (T2DM) is a major risk factor for heart failure with preserved ejection fraction and cardiac arrhythmias. Precursors of these complications, such as diabetic cardiomyopathy, remain incompletely understood and underdiagnosed. Detection of early signs of cardiac deterioration in T2DM patients is critical for prevention. Our goal is to quantify T2DM-driven abnormalities in ECG and cardiac imaging biomarkers leading to cardiovascular disease. Methods: We quantified ECG and cardiac magnetic resonance imaging biomarkers in two matched cohorts of 1781 UK Biobank participants, with and without T2DM, and no diagnosed cardiovascular disease at the time of assessment. We performed a pair-matched cross-sectional study to compare cardiac biomarkers in both cohorts, and examined the association between T2DM and these biomarkers. We built multivariate multiple linear regression models sequentially adjusted for socio-demographic, lifestyle, and clinical covariates. Results: Participants with T2DM had a higher resting heart rate (66 vs. 61 beats per minute, p < 0.001), longer QTc interval (424 vs. 420ms, p < 0.001), reduced T wave amplitude (0.33 vs. 0.37mV, p < 0.001), lower stroke volume (72 vs. 78ml, p < 0.001) and thicker left ventricular wall (6.1 vs. 5.9mm, p < 0.001) despite a decreased Sokolow-Lyon index (19.1 vs. 20.2mm, p < 0.001). T2DM was independently associated with higher heart rate (beta = 3.11, 95% CI = [2.11,4.10], p < 0.001), lower stroke volume (beta = −4.11, 95% CI = [−6.03, −2.19], p < 0.001) and higher left ventricular wall thickness (beta = 0.133, 95% CI = [0.081,0.186], p < 0.001). Trends were consistent in subgroups of different sex, age and body mass index. Fewer significant differences were observed in participants of non-white ethnic background. QRS duration and Sokolow-Lyon index showed a positive association with the development of cardiovascular disease in cohorts with and without T2DM, respectively. A higher left ventricular mass and wall thickness were associated with cardiovascular outcomes in both groups. Conclusion: T2DM prior to cardiovascular disease was linked with a higher heart rate, QTc prolongation, T wave amplitude reduction, as well as lower stroke volume and increased left ventricular wall thickness. Increased QRS duration and left ventricular wall thickness and mass were most strongly associated with future cardiovascular disease. Although subclinical, these changes may indicate the presence of autonomic dysfunction and diabetic cardiomyopathy. [ABSTRACT FROM AUTHOR]

Background : To investigate the association between surgical removal of tonsils and risk of COVID-19 with different severity. Methods: Through a nested case–control study during January 31st to December 31st 2020, including 58,888 participants of the UK Biobank, we investigated the association of tonsillectomy with the future risk of mild and severe COVID-19, using binomial logistic regression. We further examined the associations of such surgery with blood inflammatory, lipid and metabolic biomarkers to understand potential mechanisms. Finally, we replicated the analysis of severe COVID-19 in the Swedish AMORIS Cohort (n = 451,960). Results: Tonsillectomy was associated with a lower risk of mild (odds ratio [95% confidence interval]: 0.80 [0.75–0.86]) and severe (0.87 [0.77–0.98]) COVID-19 in the UK Biobank. The associations did not differ substantially by sex, age, Townsend deprivation index, or polygenic risk score for critically ill COVID-19. Levels of blood inflammatory, lipid and metabolic biomarkers did, however, not differ greatly by history of surgical removal of tonsils. An inverse association between tonsillectomy and severe COVID-19 was also observed in the AMORIS Cohort, primarily among older individuals (> 70 years) and those with ≤ 12 years of education. Conclusions: Surgical removal of tonsils may be associated with a lower risk of COVID-19. This association is unlikely attributed to alterations in common blood inflammatory, lipid and metabolic biomarkers. [ABSTRACT FROM AUTHOR]

Urolithiasis, a common and recurrent condition, imposes a significant global health burden. This study investigates the causal relationship between various types of fluid intake and urolithiasis using univariable and multivariable Mendelian randomization (MR) approaches. Genetic data for urolithiasis were obtained from the FinnGen Consortium (n = 400,681), while genetic measures for nine fluid types were sourced from meta-analyses of genome-wide association studies (GWAS). The analysis revealed that genetically predicted coffee intake (OR: 0.571, 95% confidence interval (CI): 0.341–0.958, p = 0.034) and ground coffee intake (OR: 0.219, 95% CI: 0.005–0.923, p = 0.038) were protective factors for upper urinary calculi. Additionally, a standard deviation (SD) increase in tea intake was associated with a 53% reduction in risk (OR: 0.473, 95% CI: 0.320–0.700, p < 0.001). Conversely, milk intake (OR: 1.072, 95% CI: 1.018–1.130) and alcohol intakefrequency (OR: 1.304, 95% CI: 1.083–1.570, p = 0.005) increased the risk of upper urinary calculi. These findings highlight the association of tea with reduced risk of urolithiasis, instead for milk and alcohol intake, in formulating prevention strategies for urolithiasis. [ABSTRACT FROM AUTHOR]

Aims: Brain structural alterations begin long before the presentation of brain disorders; therefore, we aimed to systematically investigate a wide range of influencing factors on neuroimaging markers of brain health. Methods: Utilizing data from 30,651 participants from the UK Biobank, we explored associations between 218 modifiable factors and neuroimaging markers of brain health. We conducted an exposome‐wide association study using the least absolute shrinkage and selection operator (LASSO) technique. Restricted cubic splines (RCS) were further employed to estimate potential nonlinear correlations. Weighted standardized scores for neuroimaging markers were computed based on the estimates for individual factors. Finally, stratum‐specific analyses were performed to examine differences in factors affecting brain health at different ages. Results: The identified factors related to neuroimaging markers of brain health fell into six domains, including systematic diseases, lifestyle factors, personality traits, social support, anthropometric indicators, and biochemical markers. The explained variance percentage of neuroimaging markers by weighted standardized scores ranged from 0.5% to 7%. Notably, associations between systematic diseases and neuroimaging markers were stronger in older individuals than in younger ones. Conclusion: This study identified a series of factors related to neuroimaging markers of brain health. Targeting the identified factors might help in formulating effective strategies for maintaining brain health. [ABSTRACT FROM AUTHOR]

Polygenic risk scores (PRSs) are rapidly emerging as a way to measure disease risk by aggregating multiple genetic variants. Understanding the interplay of the PRS with environmental factors is critical for interpreting and applying PRSs in a wide variety of settings. We develop an efficient method for simultaneously modeling gene-environment correlations and interactions using the PRS in case-control studies. We use a logistic-normal regression modeling framework to specify the disease risk and PRS distribution in the underlying population and propose joint inference across the 2 models using the retrospective likelihood of the case-control data. Extensive simulation studies demonstrate the flexibility of the method in trading-off bias and efficiency for the estimation of various model parameters compared with standard logistic regression or a case-only analysis for gene-environment interactions, or a control-only analysis, for gene-environment correlations. Finally, using simulated case-control data sets within the UK Biobank study, we demonstrate the power of our method for its ability to recover results from the full prospective cohort for the detection of an interaction between long-term oral contraceptive use and the PRS on the risk of breast cancer. This method is computationally efficient and implemented in a user-friendly R package. [ABSTRACT FROM AUTHOR]

Traditional cardiovascular risk factors, including hypertension, only explain part of major adverse cardiac events (MACEs). Understanding what other risk factors contribute to MACE is essential for prevention. Constipation shares common risk factors with hypertension and is associated with an increased risk of several cardiovascular diseases. We hypothesized that constipation is an underappreciated risk factor for MACE. We used the population healthcare and genomic data in the UK Biobank (n = 408,354) to study the contribution of constipation (ICD10 K59.0) to the risk of MACE, defined by any episode of acute coronary syndrome (ACS), ischemic stroke, and heart failure (HF). Analyses were controlled for traditional cardiovascular risk factors. We also assessed genetic correlations (rg) between constipation and MACE. Constipation cases (n = 23,814) exhibited a significantly higher risk of MACE compared with those with normal bowel habits [odds ratio (OR) = 2.15, P < 1.00 × 10−300]. Constipation was also significantly associated with individual MACE subgroups, in order: HF (OR = 2.72, P < 1.00 × 10−300), ischemic stroke (OR = 2.36, P = 2.02 × 10−230), and ACS (OR = 1.62, P = 5.82 × 10−113). In comparison with patients with constipation-free hypertension, patients with hypertension with constipation showed significantly higher odds of MACE (OR = 1.68, P = 1.05 × 10−136) and a 34% increased risk of MACE occurrence (P = 2.3 × 10−50) after adjustment for medications that affect gut motility and other traditional cardiovascular risk factors. Finally, we detected positive genetic correlations between constipation and MACE subgroups ACS (rg = 0.27, P = 2.12 × 10−6), ischemic stroke (rg = 0.23, P = 0.011), and HF (rg = 0.21, P = 0.0062). We identified constipation as a potential risk factor independently associated with higher MACE prevalence. These findings warrant further studies on their causal relationship and identification of pathophysiological mechanisms. NEW & NOTEWORTHY: Analyzing 408,354 participants of the UK Biobank, we show that constipation cases exhibited a significantly higher risk of major adverse cardiac events (MACEs) than those with regular bowel habits. In comparison with patients with constipation-free hypertension, patients with hypertension with constipation showed significantly higher odds of MACE and a 34% increased risk of subsequent MACE occurrence. Finally, we detected positive genetic correlations between constipation and MACE. This association holds potential for therapeutic exploitation and prevention based on individuals' risk assessment. [ABSTRACT FROM AUTHOR]

Background and objectives: Amyotrophic lateral sclerosis (ALS) causes profound impairments in neurological function, and a cure for this devastating disease remains elusive. This study aimed to identify pre-disposing genetic, phenotypic, and exposure-related factors for amyotrophic lateral sclerosis using multi-modal data and assess their joint predictive potential. Methods: Utilizing data from the UK (United Kingdom) Biobank, we analyzed an unrelated set of 292 ALS cases and 408,831 controls of European descent. Two polygenic risk scores (PRS) are constructed: "GWAS Hits PRS" and "PRS-CS," reflecting oligogenic and polygenic ALS risk profiles, respectively. Time-restricted phenome-wide association studies (PheWAS) were performed to identify pre-existing conditions increasing ALS risk, integrated into phenotypic risk scores (PheRS). A poly-exposure score ("PXS") captures the influence of environmental exposures measured through survey questionnaires. We evaluate the performance of these scores for predicting ALS incidence and stratifying risk, adjusting for baseline demographic covariates. Results: Both PRSs modestly predicted ALS diagnosis but with increased predictive power when combined (covariate-adjusted receiver operating characteristic [AAUC] = 0.584 [0.525, 0.639]). PheRS incorporated diagnoses 1 year before ALS onset (PheRS1) modestly discriminated cases from controls (AAUC = 0.515 [0.472, 0.564]). The "PXS" did not significantly predict ALS. However, a model incorporating PRSs and PheRS1 improved the prediction of ALS (AAUC = 0.604 [0.547, 0.667]), outperforming a model combining all risk scores. This combined risk score identified the top 10% of risk score distribution with a fourfold higher ALS risk (95% CI [2.04, 7.73]) versus those in the 40%–60% range. Discussion: By leveraging UK Biobank data, our study uncovers pre-disposing ALS factors, highlighting the improved effectiveness of multi-factorial prediction models to identify individuals at highest risk for ALS. [ABSTRACT FROM AUTHOR]

Aim: To comprehensively examine the associations of childhood and adulthood body size, and child‐to‐adult body size change with adult leucocyte telomere length (LTL). Methods: We included 453 602 participants from the UK Biobank. Childhood body size at the age of 10 years was collected through a questionnaire. Adulthood body size was assessed using body mass index (BMI), waist circumference (WC), waist‐to‐hip ratio (WHR), fat mass index (FMI), and fat‐free mass index (FFMI). Results: Individuals with plumper body size in childhood exhibited shorter LTL in adulthood (−0.0086 [−0.0017, −0.0004]). Adulthood BMI (−0.0286 [−0.0315, −0.0258]), WC (−0.0271 [−0.0303, −0.0238]), WHR (−0.0269 [−0.0308, −0.0230]) and FMI (−0.0396 [−0.0438, −0.0351]) were negatively associated with LTL, whereas FFMI (0.0095 [0.0039, 0.0152]) was positively associated with LTL. Compared to individuals consistently having an average/normal weight in both childhood and adulthood, those who maintained or developed overweight/obesity from childhood to adulthood had a shorter adult LTL, regardless of childhood body size. Notably, the LTL shortening effect was not observed in individuals with plumper body size in childhood but normal weight in adulthood. Conclusions: Childhood and adulthood obesity are both associated with LTL shortening in adulthood. Transitioning to or maintaining overweight/obese status from childhood to adulthood is associated with shorter adult LTL, whereas this effect can be reversed if plumper children become normal weight. [ABSTRACT FROM AUTHOR]

Triglyceride-rich lipoproteins and remnants (TRL/remnants) have a causal, but not yet quantified, relationship with coronary heart disease (CHD): myocardial infarction plus revascularization. The authors sought to estimate TRL/remnant per-particle atherogenicity, investigate causal relationships with inflammation, and determine whether differences in the atherogenicity of TRL/remnants and low-density lipoprotein (LDL) impact the causal association of non–high-density lipoprotein cholesterol (non–HDL-C) with CHD. Single nucleotide polymorphisms (SNPs) (N = 1,357) identified by genome-wide association in the UK Biobank were ranked into 10 clusters according to the effect on TRL/remnant-C vs LDL-C. Mendelian randomization analysis was used to estimate for each SNP cluster CHD ORs per 10 mg/dL apolipoprotein B (apoB) and per 0.33 mmol/L non–HDL-cholesterol, and to evaluate association of TRL/remnants with biomarkers of systemic inflammation. SNPs in cluster 1 predominantly affected LDL-C, whereas SNPs in cluster 10 predominantly affected TRL/remnant-C. CHD risk per genetically predicted increase in apoB and in non–HDL-C rose across clusters. ORs per 10 mg/dL higher apoB was 1.15 (95% CI: 1.11-1.19) in cluster 1 vs 1.70 (95% CI: 1.52-1.90) in cluster 10. Comparing ORs between these TRL/remnant-predominant and LDL-predominant clusters, we estimated that TRL/remnants were at least 3.9 (95% CI: 2.8-5.4) times more atherogenic than LDL on a per-particle basis. For non–HDL-C, CHD ORs per 0.33 mmol/L rose from 1.15 (95% CI: 1.11-1.19) for cluster 1 to 1.40 (95% CI: 1.30-1.50) for cluster 10. TRL/remnants exhibited causal relationships with inflammation, but this did not explain their greater atherogenicity. TRL/remnants are about 4 times more atherogenic than LDL. Variation in the causal association of non–HDL-C with CHD indicates that adjustment for percentage TRL/remnant-C may be needed for accurate risk prediction. [ABSTRACT FROM AUTHOR]

Sodium intake reduction is crucial for cardiovascular health, however, its lasting impact on dementia remains unclear. We included 458,577 UK Biobank participants without dementia at baseline. We estimated 24-h urinary sodium (E24hUNa) using spot urinary parameters and obtained the incidence of all-cause dementia, Alzheimer's disease, and vascular dementia from multiple sources. The mean E24hUNa was 3.0 g (1st-99th percentile: 1.5 g–5.1 g). Over a mean follow-up of 13.6 years, 7886 (1.7 %) participants developed all-cause dementia, including 3763 (0.8 %) Alzheimer's disease and 1851 (0.4 %) vascular dementia. In the restricted cubic spline model, we identify a potential cutoff of 3.13 g for E24hUNa, below which each 1 g decrease in E24hUNa was associated with 21 % (95 % confidence interval [CI] 1.11–1.34) higher all-cause dementia risk and 35 % (95 % CI 1.11–1.63) higher vascular dementia risk (P -value <0.001 for non-linearity). The hazard ratios were 1.15 (95 % CI, 1.07–1.24) for all-cause dementia and 1.21 (95 % CI 1.04–1.40) for vascular dementia among individuals with E24hUNa below 3.13 g compared to those with E24hUNa higher than 3.13 g. One of the major limitations is the estimation of 24-h urinary sodium with spot urine samples. An E24hUNa level below 3.13 g, equivalent to 3.37 g daily sodium intake, is associated with increased risks of all-cause and vascular dementia. This exploratory study suggests a potential lower limit below which the risk of dementia increases with a lower sodium level. Future studies are necessary to validate our findings. • We evaluated the prospective association between E24hUNa and the risk of dementia. • E24hUNa associated with dementia in a non-linear dose-response manner. • 3.13 g seemed the cut-point for E24hUNa. • E24hUNa < 3.13 g in participants linked to 15 % higher dementia risk than >3.13 g. • When <3.13 g, each 1 g decrease in E24hUNa raised dementia risk by 21 %. [ABSTRACT FROM AUTHOR]

Both adverse childhood experiences (ACEs) and lifestyle factors have been associated with risk of cardiovascular diseases (CVDs) in later life, but whether and to what extent adherence to a healthy lifestyle in adulthood can offset the increased cardiovascular risk associated with ACEs is unclear. We aimed to determine whether and to what extent adopting to a healthy lifestyle in adulthood can offset the risk of CVDs in individuals according to their ACEs. A prospective cohort study included 143,869 participants aged 38–72 years, free of CVDs at baseline from the UK Biobank. The history of ACEs was assessed using the Childhood Trauma Screener. Participants were divided into three risk groups based on ACEs: low (no ACEs), intermediate (one or two ACEs), and high (three or more ACEs). A healthy lifestyle score in adulthood was constructed as the sum of four modifiable lifestyle factors (no smoking, adequate physical activity, healthy diet, no obesity), and participants were then categorized into three groups based on this score (unfavorable [0–1 point], intermediate [2–3 points], favorable [4 points]). Cox proportional hazard models were conducted to investigate the association between ACEs, healthy lifestyle, and incident CVDs. During a median follow-up of 12.49 years, 13,373 incident cases of overall CVDs were identified. This included 7521 cases of coronary heart disease (CHD), 6175 cases of atrial fibrillation (AF) and 1813 cases of stroke. Individuals with high ACEs had a greater risk of incident overall CVDs (hazard ratio [HR] = 1.39, [95%CI = 1.29 to 1.50]), CHD (1.50 [1.36 to 1.65]) and AF (1.18 [1.05 to 1.33]) compared to those with low ACEs. The risk of CVDs decreased moving from unfavorable to favorable lifestyle categories (P for trend<0.001), with the lowest risk observed among individuals with a favorable lifestyle (0.70 [0.66 to 0.74] for overall CVDs, 0.69 [0.64 to 0.75] for CHD, and 0.71 [0.65 to 0.78] for AF). Participants with high ACEs and a favorable lifestyle had a 39 %, 40 % and 47 % lower risk of developing overall CVDs (0.61 [0.48 to 0.76]), CHD (0.60 [0.44 to 0.81], and AF (0.53 [0.36 to 0.77]) than those with high ACEs and an unfavorable lifestyle. Having a healthy lifestyle in adulthood could substantially attenuate the increased risk of overall CVDs, CHD, and AF conferred by ACEs. • Adverse childhood experiences (ACEs) independently increased the risk of incident cardiovascular diseases (CVDs). • Adopting a healthy lifestyle was significantly associated with a decreased risk of CVDs, regardless of ACEs category. • While exposure to ACEs is unmodifiable, the potential CVD risk can be significantly reduced by adopting a healthy lifestyle. [ABSTRACT FROM AUTHOR]

Impairments of object recognition are core features of neurodegenerative syndromes, in particular posterior cortical atrophy (PCA; the 'visual-variant Alzheimer's disease'). These impairments arise from damage to higher-level cortical visual regions and are often missed or misattributed to common ophthalmological conditions. Consequently, diagnosis can be delayed for years with considerable implications for patients. We report a new test for the rapid measurement of cortical visual loss – the Graded Incomplete Letters Test (GILT). The GILT is an optimised psychophysical variation of a test used to diagnose cortical visual impairment, which measures thresholds for recognising letters under levels of increasing visual degradation (decreasing "completeness") in a similar fashion to ophthalmic tests. The GILT was administered to UK Biobank participants (total n=2,359) and participants with neurodegenerative conditions characterised by initial cortical visual (PCA, n=18) or memory loss (typical Alzheimer's disease, n=9). UK Biobank participants, including both typical adults and those with ophthalmological conditions, were able to recognise letters under low levels of completeness. In contrast, participants with PCA consistently made errors with only modest decreases in completeness. GILT sensitivity to PCA was 83.3% for participants reaching the 80% accuracy cut-off, increasing to 88.9% using alternative cut-offs (60% or 100% accuracy). Specificity values were consistently over 94% when compared to UK Biobank participants without or with documented visual conditions, regardless of accuracy cut-off. These first-release UK Biobank and clinical verification data suggest the GILT has utility in both rapidly detecting visual perceptual losses following posterior cortical damage and differentiating perceptual losses from common eye-related conditions. [ABSTRACT FROM AUTHOR]

BACKGROUND: Currently, there are no reliable methods for predicting and preventing atrial fibrillation (AF) in its early stages. This study aimed to identify plasma proteins associated with AF to discover biomarkers and potential drug targets. METHODS: The UK Biobank Pharma Proteomics Project examined 2923 circulating proteins using the Olink platform, forming the basis of this prospective cohort study. The UK Biobank Pharma Proteomics Project included a randomly selected discovery cohort and the consortium-selected replication cohort. The study's end point was incident AF, identified using International Classification of Diseases, Tenth Revision codes. The association between plasma proteins and incident AF was evaluated using Cox proportional hazard models in both cohorts. Proteins present in both cohorts underwent Mendelian randomization analysis to delineate causal connections, utilizing cis-protein quantitative trait loci as genetic tools. The predictive efficacy of the identified proteins for AF was assessed using the area under the receiver operating characteristic curve, and their druggability was explored. RESULTS: Data from 38 784 participants were included in this study. Incident AF cases were identified in the discovery cohort (1894; 5.5%) within a median follow-up of 14.5 years and in the replication cohort (451; 10.6%) within a median follow-up of 14.4 years. Twenty-one proteins linked to AF were identified in both cohorts. Specifically, COL4A1 (collagen IV α-1; odds ratio, 1.11 [95% CI, 1.04--1.19]; false discovery rate, 0.016) and RET (proto-oncogene tyrosine-protein kinase receptor Ret; odds ratio, 0.96 [95% CI, 0.94--0.98]; false discovery rate, 0.013) demonstrated a causal link with AF, and RET is druggable. COL4A1 improved the short- and long-term predictive performance of established AF models, as evidenced by significant enhancements in the area under the receiver operating characteristic, integrated discrimination improvement, and net reclassification index, all with P values below 0.05. CONCLUSIONS: COL4A1 and RET are associated with the development of AF. RET is identified as a potential drug target for AF prevention, while COL4A1 serves as a biomarker for AF prediction. Future studies are needed to evaluate the effectiveness of targeting these proteins to reduce AF risk. GRAPHIC ABSTRACT: A graphic abstract is available for this article. [ABSTRACT FROM AUTHOR]

BACKGROUND: High heritability of salt sensitivity suggests an essential role for genetics in the relationship between sodium intake and blood pressure (BP). The role of glycosaminoglycan genes, which are crucial for salinity tolerance, remains to be elucidated. METHODS: Interactions between 54 126 variants in 130 glycosaminoglycan genes and daily sodium excretion on BP were explored in 20 420 EPIC-Norfolk (European Prospective Investigation Into Cancer in Norfolk) subjects. The UK Biobank (n=414 132) and the multiethnic HELIUS study (Healthy Life in an Urban Setting; n=2239) were used for validation. Afterward, the urinary glycosaminoglycan composition was studied in HELIUS participants (n=57) stratified by genotype and upon dietary sodium loading in a time-controlled crossover intervention study (n=12). RESULTS: rs2892799 in NDST3 (heparan sulfate N-deacetylase/N-sulfotransferase 3) showed the strongest interaction with sodium on mean arterial pressure (false discovery rate 0.03), with higher mean arterial pressure for the C allele in high sodium conditions. Also, rs9654628 in HS3ST5 (heparan sulfate-glucosamine 3-sulfotransferase 5) showed an interaction with sodium on systolic BP (false discovery rate 0.03). These interactions were multiethnically validated. Stratifying for the rs2892799 genotype showed higher urinary expression of N-sulfated heparan sulfate epitope D0S0 for the T allele. Conversely, upon dietary sodium loading, urinary D0S0 expression was higher in participants with stable BP after sodium loading, and sodium-induced effects on this epitope were opposite in individuals with and without BP response to sodium. CONCLUSIONS: The C allele of rs2892799 in NDST3 exhibits higher BP in high sodium conditions when compared with low sodium conditions, whereas no differences were detected for the T allele. Concomitantly, both alleles demonstrate distinct expressions of D0S0, which, in turn, correlates with sodium-mediated BP elevation. These findings underscore the potential significance of genetic glycosaminoglycan variation in human BP regulation. [ABSTRACT FROM AUTHOR]

Evidence regarding the role of chronic low-grade inflammation in the progression of cardiometabolic diseases (CMDs) and cardiometabolic multimorbidity (CMM) is currently limited. This prospective cohort study, utilising data from the UK Biobank, included 273,804 adults aged 40–69 years initially free of CMD at baseline. CMM was defined as the coexistence of two or more CMDs, such as coronary artery disease, type 2 diabetes mellitus, hypertension and stroke. The aggregated inflammation score (INFLA-score), incorporating C-reactive protein, white blood cell count, platelet count and granulocyte-to-lymphocyte ratio, quantified chronic low-grade inflammation. Absolute risks (ARs), hazard ratios (HRs) and 95% confidence intervals (CIs) assessed the association of increased INFLA-score with the risk of CMMs and CMDs. The accelerated failure time model explored the effect of INFLA-score on the time to CMM onset, and a restricted cubic spline characterised the dose-dependent relationship between INFLA-score and CMM risk. After a median follow-up of 166.37 months, 13,755 cases of CMM were identified. In quartiles with increasing INFLA-score levels, CMM ARs were 4.41%, 4.49%, 5.04% and 6.01%, respectively; HR increased by 2%, 15% and 36%, respectively, compared to the lowest quartile. The INFLA-score and CMM risk relationship was nonlinear (P for nonlinear < 0.001), exhibiting a significant risk trend change at a score of 9. For INFLA-score < 9, CMM risk increased by 1.9% for each 1-point increase; for INFLA-score ≥ 9, the risk increased by 5.9% for each 1-point increase. Additionally, a higher INFLA-score was associated with an earlier onset of CMM (P < 0.001). Compared to the first INFLA-score quartile, the AFT model revealed adjusted median times to CMM occurrence were 2.92, 6.10 and 13.19 months earlier in the second, third and fourth quartile groups, respectively. Chronic low-grade inflammation is associated with a higher risk of cardiometabolic multimorbidity and earlier onset among middle-aged and older adults. Monitoring and screening the INFLA-score in adults without CMDs may improve early prevention of CMM. [ABSTRACT FROM AUTHOR]

Background: Accelerated biological aging has been verified to be a critical risk factor for a number of age-related diseases, but its role in dementia remained unclear. Whether it modified the effects of genetic factors was also unknown. This study evaluated the associations between accelerated biological aging and dementia and the moderating role of accelerated biological aging in the genetic susceptibility to the disease. Methods: We included 200,731 participants in the UK biobank. Nine clinical blood biomarkers and chronological age were used to calculate Phenotypic age acceleration (PhenoAgeAccel), which is a novel indicator for accelerated biological aging. The associations of PhenoAgeAccel with dementia, both young-onset and late-onset dementia, were assessed by Cox proportional hazard models. Apolipoprotein E (APOE) alleles and polygenic risk scores (PRS) were used to evaluate the genetic risk of dementia. The interactions between genetic susceptibility and biological aging were tested on both multiplicative and additive scales. Results: These findings showed individuals who were in the highest quartile of PhenoAgeAccel had a higher risk with incidence of dementia compared to individuals in the lowest quartile of PhenoAgeAccel (HR: 1.145 (95% CI: 1.050, 1.249)). Individuals with biologically older had a higher risk of dementia than individuals with biologically younger (HR: 1.069 (95% CI: 1.004, 1.138)). Furthermore, compared to individuals with biologically younger and low APOE ε4-related genetic risk, individuals with biologically younger and high APOE ε4-related genetic risk (HR:3.048 (95% CI: 2.811, 3.305)) had a higher risk of dementia than individuals with biologically older and high APOE ε4-related genetic risk (HR: 2.765 (95% CI: 2.523, 3.029)). Meanwhile, referring to low dementia PRS and biologically younger, the risk of dementia increased by 72.7% (HR: 1.727 (95% CI: 1.538, 1.939) in the biologically younger and high PRS group and 58.7% (HR: 1.587 (95% CI: 1.404, 1.793) in the biologically older and high PRS group, respectively. The negative interactions between PhenoAgeAccel with APOE ε4 and PRS were also tested on the additive scale. Conclusions: Accelerated biological aging could bring the extra risk of dementia but attenuate the effects of genetic risk on dementia. These findings provide insights for precise prevention and intervention of dementia. [ABSTRACT FROM AUTHOR]

Sex-differential selection (SDS), which occurs when the fitness effects of alleles differ between males and females, can have profound impacts on the maintenance of genetic variation, disease risk, and other key aspects of natural populations. Because the sexes mix their autosomal genomes each generation, quantifying SDS is not possible using conventional population genetic approaches. Here, we introduce a method that exploits subtle sex differences in haplotype frequencies resulting from SDS acting in the current generation. Using data from 300K individuals in the UK Biobank, we estimate the strength of SDS throughout the genome. While only a handful of loci under SDS are individually significant, we uncover highly polygenic signals of genome-wide SDS for both viability and fecundity. Selection coefficients of s = 10-3 may be typical. Despite its ubiquity, SDS may impose a mortality load of less than 1%. An interesting life-history tradeoff emerges: Alleles that increase viability more strongly in females than males tend to increase fecundity more strongly in males than in females. Finally, we find marginal evidence of SDS on fecundity acting on alleles affecting arm fat-free mass. Taken together, our findings connect the long-standing evidence of SDS acting on human phenotypes with its impact on the genome. [ABSTRACT FROM AUTHOR]

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

Background: Sedentary behavior (SB) has emerged as a significant health concern that deserves attention. This study aimed to examine the associations between prolonged sedentary behavior and the risk of all-cause and cause-specific mortality as well as to explore desirable alternatives to sitting in terms of physical activity (PA). Methods: Two prospective cohort investigations were conducted using the UK Biobank and NHANES datasets, with a total of 490,659 and 33,534 participants, respectively. Cox proportional hazards regression models were used to estimate the associations between SB and the risk of all-cause and cause-specific mortality due to cancer, cardiovascular disease (CVD), respiratory diseases, and digestive diseases. In addition, we employed isotemporal substitution models to examine the protective effect of replacing sitting with various forms of PA. Results: During the average follow-up times of 13.5 and 6.7 years, 36,109 and 3057 deaths were documented in the UK Biobank and NHANES, respectively. Both cohorts demonstrated that, compared with individuals sitting less than 5 h per day, individuals with longer periods of sitting had higher risks of all-cause and cause-specific mortality due to cancer, CVD, and respiratory diseases but not digestive diseases. Moreover, replacing SB per day with PA, even substituting 30 min of walking for pleasure, reduced the risk of all-cause mortality by 3.5% (hazard ratio [HR] 0.965, 95% confidence interval [CI] 0.954–0.977), whereas cause-specific mortality from cancer, CVD, and respiratory diseases was reduced by 1.6% (HR 0.984, 95% CI 0.968–1.000), 4.4% (HR 0.956, 95% CI 0.930–0.982), and 15.5% (HR 0.845, 95% CI 0.795–0.899), respectively. Furthermore, the protective effects of substitution became more pronounced as the intensity of exercise increased or the alternative duration was extended to 1 h. Conclusions: SB was significantly correlated with substantially increased risks of all-cause mortality and cause-specific mortality from cancer, CVD, and respiratory diseases. However, substituting sitting with various forms of PA, even for short periods involving relatively light and relaxing physical activity, effectively reduced the risk of both overall and cause-specific mortality. [ABSTRACT FROM AUTHOR]

Introduction: Cardiovascular disease (CVD) is responsible for over 30% of mortality worldwide. CVD arises from the complex influence of molecular, clinical, social, and environmental factors. Despite the growing number of autosomal genetic variants contributing to CVD, the cause of most CVDs is still unclear. Mitochondria are crucial in the pathophysiology, development and progression of CVDs; the impact of mitochondrial DNA (mtDNA) variants and mitochondrial haplogroups in the context of CVD has recently been highlighted. Aims: We investigated the role of genetic variants in both mtDNA and nuclearencoded mitochondrial genes (NEMG) in CVD, including coronary artery disease (CAD), hypertension, and serum lipids in the UK Biobank, with sub-group analysis for diabetes. Methods: We investigated 371,542 variants in 2,527 NEMG, along with 192 variants in 32 mitochondrial genes in 381,994 participants of the UK Biobank, stratifying by presence of diabetes. Results: Mitochondrial variants showed associations with CVD, hypertension, and serum lipids. Mitochondrial haplogroup J was associated with CAD and serum lipids, whereas mitochondrial haplogroups T and U were associated with CVD. Among NEMG, variants within Nitric Oxide Synthase 3 (NOS3) showed associations with CVD, CAD, hypertension, as well as diastolic and systolic blood pressure. We also identified Translocase Of Outer Mitochondrial Membrane 40 (TOMM40) variants associated with CAD; Solute carrier family 22 member 2 (SLC22A2) variants associated with CAD and CVD; and HLA-DQA1 variants associated with hypertension. Variants within these three genes were also associated with serum lipids. Conclusion: Our study demonstrates the relevance of mitochondrial related variants in the context of CVD. We have linked mitochondrial haplogroup U to CVD, confirmed association of mitochondrial haplogroups J and T with CVD and proposed new markers of hypertension and serum lipids in the context of diabetes. We have also evidenced connections between the etiological pathways underlying CVDs, blood pressure and serum lipids, placing NOS3, SLC22A2, TOMM40 and HLA-DQA1 genes as common nexuses. [ABSTRACT FROM AUTHOR]

Mendelian randomization (MR) is a powerful epidemiological method for causal inference. However, its recent surge in popularity has brought two concerning trends. First, the public availability of summary results from genome-wide association studies has led to an explosion of low-quality two-sample mendelian randomization (2SMR) studies. These studies add minimal – if any – value and overwhelm reviewers and journals. Second, the availability of large datasets with individual-level genotype data, like UK Biobank, has spurred the development and use of novel MR methods. However, some methods are being applied without proper testing, leading to misleading results, as exemplified by recent spurious findings that are being retracted and/or corrected relating to vitamin D. What can editors and peer reviewers do to handle the deluge of 2SMR studies and the premature application of highly complex MR methods? We advise editors to simply reject papers that only report 2SMR findings, with no additional supporting evidence. For reviewers receiving such papers, we provide a template for rejection. In addition, reviewers should demand rigorous testing of novel methods, including through the use of positive and negative controls before they are applied. Rejecting non-contributory 2SMR papers and imposing intensive scrutiny to novel methods is crucial if the scientific community is to reclaim MR. [ABSTRACT FROM AUTHOR]

Background: Sex disparity between metabolic-obesity (defined by body mass index, BMI) phenotypes and obesity-related cancer (ORC) remains unknown. Considering BMI reflecting overall obesity but not fat distribution, we aimed to systematically assess the association of our newly proposed metabolic-anthropometric phenotypes with risk of overall and site-specific ORC by sex. Methods: A total of 141,579 men (mean age: 56.37 years, mean follow-up time: 12.04 years) and 131,047 women (mean age: 56.22 years, mean follow up time: 11.82 years) from the UK Biobank was included, and designated as metabolic-anthropometric phenotypes based on metabolic status (metabolically healthy/unhealthy), BMI (non-obesity/obesity) and body shape (pear/slim/apple/wide). The sex-specific association of different phenotypes with overall and site-specific ORC was assessed by hazard ratios (HRs) and 95% confidence intervals (CIs) using Cox proportional hazards regression models. Results: We found metabolically unhealthy and/or obesity phenotypes conveyed a higher risk in men than in women for overall ORC and colorectal cancer compared with metabolically healthy non-obesity phenotype (Pinteraction < 0.05). Of note, metabolically healthy obesity phenotype contributed to increased risks of most ORC in men (HRs: 1.58 ~ 2.91), but only correlated with higher risks of endometrial (HR = 1.89, 95% CI: 1.54–2.32) and postmenopausal breast cancers (HR = 1.17, 95% CI: 1.05–1.31) in women. Similarly, even under metabolically healthy, men carrying apple and wide shapes phenotypes (metabolically healthy apple/wide and metabolically healthy non-obesity apple/wide) suffered an increased risk of ORC (mainly colorectal, liver, gastric cardia, and renal cancers, HRs: 1.20 ~ 3.81) in comparison with pear shape or non-obesity pear shape. Conclusions: There was a significant sex disparity between metabolic-anthropometric phenotypes and ORC risk. We advised future ORC prevention and control worth taking body shape and sex disparity into account. [ABSTRACT FROM AUTHOR]

The lack of sex-specific cardiovascular disease criteria contributes to the underdiagnosis of women compared to that of men. For more than half a century, the Framingham Risk Score has been the gold standard to estimate an individual's risk of developing cardiovascular disease based on the age, sex, cholesterol levels, blood pressure, diabetes status, and the smoking status. Now, machine learning can offer a much more nuanced insight into predicting the risk of cardiovascular diseases. The UK Biobank is a large database that includes traditional risk factors and tests related to the cardiovascular system: magnetic resonance imaging, pulse wave analysis, electrocardiograms, and carotid ultrasounds. Here, we leverage 20,542 datasets from the UK Biobank to build more accurate cardiovascular risk models than the Framingham Risk Score and quantify the underdiagnosis of women compared to that of men. Strikingly, for a first-degree atrioventricular block and dilated cardiomyopathy, two conditions with non-sex-specific diagnostic criteria, our study shows that women are under-diagnosed 2× and 1.4× more than men. Similarly, our results demonstrate the need for sex-specific criteria in essential primary hypertension and hypertrophic cardiomyopathy. Our feature importance analysis reveals that out of the top 10 features across three sexes and four disease categories, traditional Framingham factors made up between 40% and 50%; electrocardiogram, 30%–33%; pulse wave analysis, 13%–23%; and magnetic resonance imaging and carotid ultrasound, 0%–10%. Improving the Framingham Risk Score by leveraging big data and machine learning allows us to incorporate a wider range of biomedical data and prediction features, enhance personalization and accuracy, and continuously integrate new data and knowledge, with the ultimate goal to improve accurate prediction, early detection, and early intervention in cardiovascular disease management. Our analysis pipeline and trained classifiers are freely available at https://github. com/LivingMatterLab/CardiovascularDiseaseClassification. [ABSTRACT FROM AUTHOR]