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Key Points: Question: Is there an association between sedentary behavior and risk of all-cause dementia in older adults? Findings: In this retrospective study of prospectively collected data of 49 841 adults participating in the UK Biobank, more time spent in sedentary behaviors (determined through a machine learning–based analysis of wrist-worn accelerometer data) was significantly associated with higher risk of incident dementia. Meaning: Among older adults, more time spent in sedentary behaviors was associated with higher risk of incident all-cause dementia. Importance: Sedentary behavior is associated with cardiometabolic disease and mortality, but its association with dementia is unclear. Objective: To investigate whether accelerometer-assessed sedentary behavior is associated with incident dementia. Design, Setting, and Participants: A retrospective study of prospectively collected data from the UK Biobank including 49 841 adults aged 60 years or older without a diagnosis of dementia at the time of wearing the wrist accelerometer and living in England, Scotland, or Wales. Follow-up began at the time of wearing the accelerometer (February 2013 to December 2015) and continued until September 2021 in England, July 2021 in Scotland, and February 2018 in Wales. Exposures: Mean daily sedentary behavior time (included in the primary analysis) and mean daily sedentary bout length, maximum daily sedentary bout length, and mean number of daily sedentary bouts (included in the secondary analyses) were derived from a machine learning–based analysis of 1 week of wrist-worn accelerometer data. Main Outcome and Measures: Incident all-cause dementia diagnosis from inpatient hospital records and death registry data. Cox proportional hazard models with linear and cubic spline terms were used to assess associations. Results: A total of 49 841 older adults (mean age, 67.19 [SD, 4.29] years; 54.7% were female) were followed up for a mean of 6.72 years (SD, 0.95 years). During this time, 414 individuals were diagnosed with incident all-cause dementia. In the fully adjusted models, there was a significant nonlinear association between time spent in sedentary behavior and incident dementia. Relative to a median of 9.27 hours/d for sedentary behavior, the hazard ratios (HRs) for dementia were 1.08 (95% CI, 1.04-1.12, P <.001) for 10 hours/d, 1.63 (95% CI, 1.35-1.97, P <.001) for 12 hours/d, and 3.21 (95% CI, 2.05-5.04, P <.001) for 15 hours/d. The adjusted incidence rate of dementia per 1000 person-years was 7.49 (95% CI, 7.48-7.49) for 9.27 hours/d of sedentary behavior, 8.06 (95% CI, 7.76-8.36) for 10 hours/d, 12.00 (95% CI, 10.00-14.36) for 12 hours/d, and 22.74 (95% CI, 14.92-34.11) for 15 hours/d. Mean daily sedentary bout length (HR, 1.53 [95% CI, 1.03-2.27], P =.04 and 0.65 [95% CI, 0.04-1.57] more dementia cases per 1000 person-years for a 1-hour increase from the mean of 0.48 hours) and maximum daily sedentary bout length (HR, 1.15 [95% CI, 1.02-1.31], P =.02 and 0.19 [95% CI, 0.02-0.38] more dementia cases per 1000 person-years for a 1-hour increase from the mean of 1.95 hours) were significantly associated with higher risk of incident dementia. The number of sedentary bouts per day was not associated with higher risk of incident dementia (HR, 1.00 [95% CI, 0.99-1.01], P =.89). In the sensitivity analyses, after adjustment for time spent in sedentary behavior, the mean daily sedentary bout length and the maximum daily sedentary bout length were no longer significantly associated with incident dementia. Conclusions and Relevance: Among older adults, more time spent in sedentary behaviors was significantly associated with higher incidence of all-cause dementia. Future research is needed to determine whether the association between sedentary behavior and risk of dementia is causal. This study of prospectively collected data from the UK Biobank investigates whether accelerometer-assessed sedentary behavior is associated with incident dementia in adults aged 60 years or older without a diagnosis of dementia at the time of wearing the wrist accelerometer. [ABSTRACT FROM AUTHOR]

Physical activity and cognitive functioning are strongly intertwined. However, the causal relationships underlying this association are still unclear. Physical activity can enhance brain functions, but healthy cognition may also promote engagement in physical activity. Here, we assessed the bidirectional relationships between physical activity and general cognitive functioning using Latent Heritable Confounder Mendelian Randomization (LHC-MR). Association data were drawn from two large-scale genome-wide association studies (UK Biobank and COGENT) on accelerometer-measured moderate, vigorous, and average physical activity (N = 91,084) and cognitive functioning (N = 257,841). After Bonferroni correction, we observed significant LHC-MR associations suggesting that increased fraction of both moderate (b = 0.32, CI95% = [0.17,0.47], P = 2.89e − 05) and vigorous physical activity (b = 0.22, CI95% = [0.06,0.37], P = 0.007) lead to increased cognitive functioning. In contrast, we found no evidence of a causal effect of average physical activity on cognitive functioning, and no evidence of a reverse causal effect (cognitive functioning on any physical activity measures). These findings provide new evidence supporting a beneficial role of moderate and vigorous physical activity (MVPA) on cognitive functioning. [ABSTRACT FROM AUTHOR]

Sedentary behavior (SB) is associated with cardiometabolic disease and mortality, but its association with dementia is currently unclear. This study investigates whether SB is associated with incident dementia regardless of engagement in physical activity (PA). A total of 146,651 participants from the UK Biobank who were 60 years or older and did not have a diagnosis of dementia (mean [SD] age: 64.59 [2.84] years) were included. Selfreported leisure-time SBs were divided into two domains: time spent watching television (TV) or time spent using a computer. A total of 3,507 individuals were diagnosed with all-cause dementia over a mean follow-up of 11.87 (±1.17) years. In models adjusted for a wide range of covariates, including time spent in PA, time spent watching TV was associated with increased risk of incident dementia (HR [95% CI] = 1.24 [1.15 to 1.32]) and time spent using a computer was associated with decreased risk of incident dementia (HR [95% CI] = 0.85 [0.81 to 0.90]). In joint associations with PA, TV time and computer time remained significantly associated with dementia risk at all PA levels. Reducing time spent in cognitively passive SB (i.e., TV time) and increasing time spent in cognitively active SB (i.e., computer time) may be effective behavioral modification targets for reducing risk of dementia regardless of engagement in PA. [ABSTRACT FROM AUTHOR]

Introduction: A lack of physical activity (PA) is one of the most pressing health issues today. Our individual propensity for PA is influenced by genetic factors. Stated liking of different PA types may help capture additional and informative dimensions of PA behavior genetics. Methods: In over 157,000 individuals from the UK Biobank, we performed genome-wide association studies of five items assessing the liking of different PA types, plus an additional derived trait of overall PA-liking. We attempted to replicate significant associations in the Netherlands Twin Register (NTR) and TwinsUK. Additionally, polygenic scores (PGS) were trained in the UK Biobank for each PA-liking item and for self-reported PA behavior, and tested for association with PA in the NTR. Results: We identified a total of 19 unique significant loci across all five PA-liking items and the overall PA-liking trait, and these showed strong directional consistency in the replication cohorts. Four of these loci were previously identified for PA behavior, including CADM2 , which was associated with three PA-liking items. The PA-liking items were genetically correlated with self-reported (r g = 0.38–0.80) and accelerometer (r g = 0.26–0.49) PA measures, and with a wide range of health-related traits. Each PA-liking PGS significantly predicted the same PA-liking item in NTR. The PGS of liking for going to the gym predicted PA behavior in the NTR (r 2 = 0.40%) nearly as well as a PGS based on self-reported PA behavior (r 2 = 0.42%). Combining the two PGS into a single model increased the r 2 to 0.59%, suggesting that PA-liking captures distinct and relevant dimensions of PA behavior. Conclusions: We have identified the first loci associated with PA-liking and extended our understanding of the genetic basis of PA behavior. [ABSTRACT FROM AUTHOR]

Although hyperlipidemia is traditionally considered a risk factor for type 2 diabetes (T2D), evidence has emerged from statin trials and candidate gene investigations suggesting that lower LDL cholesterol (LDL-C) increases T2D risk. We thus sought to more comprehensively examine the phenotypic and genotypic relationships of LDL-C with T2D. Using data from the UK Biobank, we found that levels of circulating LDL-C were negatively associated with T2D prevalence (odds ratio 0.41 [95% CI 0.39, 0.43] per mmol/L unit of LDL-C), despite positive associations of circulating LDL-C with HbA1c and BMI. We then performed the first genome-wide exploration of variants simultaneously associated with lower circulating LDL-C and increased T2D risk, using data on LDL-C from the UK Biobank (n = 431,167) and the Global Lipids Genetics Consortium (n = 188,577), and data on T2D from the Diabetes Genetics Replication and Meta-Analysis consortium (n = 898,130). We identified 31 loci associated with lower circulating LDL-C and increased T2D, capturing several potential mechanisms. Seven of these loci have previously been identified for this dual phenotype, and nine have previously been implicated in nonalcoholic fatty liver disease. These findings extend our current understanding of the higher T2D risk among individuals with low circulating LDL-C and of the underlying mechanisms, including those responsible for the diabetogenic effect of LDL-C-lowering medications. [ABSTRACT FROM AUTHOR]

Importance: Increasing evidence shows that physical activity is associated with reduced risk for depression, pointing to a potential modifiable target for prevention. However, the causality and direction of this association are not clear; physical activity may protect against depression, and/or depression may result in decreased physical activity.Objective: To examine bidirectional relationships between physical activity and depression using a genetically informed method for assessing potential causal inference.Design, Setting, and Participants: This 2-sample mendelian randomization (MR) used independent top genetic variants associated with 2 physical activity phenotypes-self-reported (n = 377 234) and objective accelerometer-based (n = 91 084)-and with major depressive disorder (MDD) (n = 143 265) as genetic instruments from the largest available, nonoverlapping genome-wide association studies (GWAS). GWAS were previously conducted in diverse observational cohorts, including the UK Biobank (for physical activity) and participating studies in the Psychiatric Genomics Consortium (for MDD) among adults of European ancestry. Mendelian randomization estimates from each genetic instrument were combined using inverse variance weighted meta-analysis, with alternate methods (eg, weighted median, MR Egger, MR-Pleiotropy Residual Sum and Outlier [PRESSO]) and multiple sensitivity analyses to assess horizontal pleiotropy and remove outliers. Data were analyzed from May 10 through July 31, 2018.Main Outcomes and Measures: MDD and physical activity.Results: GWAS summary data were available for a combined sample size of 611 583 adult participants. Mendelian randomization evidence suggested a protective relationship between accelerometer-based activity and MDD (odds ratio [OR], 0.74 for MDD per 1-SD increase in mean acceleration; 95% CI, 0.59-0.92; P = .006). In contrast, there was no statistically significant relationship between MDD and accelerometer-based activity (β = -0.08 in mean acceleration per MDD vs control status; 95% CI, -0.47 to 0.32; P = .70). Furthermore, there was no significant relationship between self-reported activity and MDD (OR, 1.28 for MDD per 1-SD increase in metabolic-equivalent minutes of reported moderate-to-vigorous activity; 95% CI, 0.57-3.37; P = .48), or between MDD and self-reported activity (β = 0.02 per MDD in standardized metabolic-equivalent minutes of reported moderate-to-vigorous activity per MDD vs control status; 95% CI, -0.008 to 0.05; P = .15).Conclusions and Relevance: Using genetic instruments identified from large-scale GWAS, robust evidence supports a protective relationship between objectively assessed-but not self-reported-physical activity and the risk for MDD. Findings point to the importance of objective measurement of physical activity in epidemiologic studies of mental health and support the hypothesis that enhancing physical activity may be an effective prevention strategy for depression. [ABSTRACT FROM AUTHOR]

Introduction: Physical activity (PA) is recognized as one of the key lifestyle behaviors that reduces risk of developing dementia late in life. However, PA also leads to increased respiration, and in areas with high levels of air pollution, PA may increase exposure to pollutants linked with higher risk of developing dementia. Here, we investigate whether air pollution attenuates the association between PA and dementia risk. Methods: This prospective cohort study included 35,562 adults 60 yrs and older from the UK Biobank. Average acceleration magnitude (ACCave) from wrist-worn accelerometers was used to assess PA levels. Air pollution levels (NO, NO2, PM10, PM2.5, PM2.5–10, and PM2.5 absorbance) were estimated with land use regression methods. Incident all-cause dementia was derived from inpatient hospital records and death registry data. Results: In adjusted models, ACCave was associated with reduced risk of developing dementia (HR = 0.71, 95% confidence interval [CI] = 0.60–0.83), whereas air pollution variables were not associated with dementia risk. There were significant interactions between ACCave and PM2.5 (HRinteraction = 1.33, 95% CI = 1.13–1.57) and PM2.5 absorbance (HRinteraction = 1.24, 95% CI = 1.07–1.45) on incident dementia. At the lowest tertiles of pollution, ACCave was associated with reduced risk of incident dementia (HRPM 2.5 = 0.66, 95% CI = 0.49–0.91; HRPM 2.5 absorbance = 0.60, 95% CI = 0.44–0.81). At the highest tertiles of these pollutants, there was no significant association of ACCave with incident dementia (HRPM 2.5 = 0.88, 95% CI = 0.68–1.14; HRPM 2.5 absorbance = 0.79, 95% CI = 0.60–1.04). Conclusions: PA is associated with reduced risk of developing all-cause dementia. However, exposure to even moderate levels of air pollution attenuates the benefits of PA on risk of dementia. [ABSTRACT FROM AUTHOR]

Air pollution may cause inflammatory and oxidative stress damage to the brain, leading to neurodegenerative disease. The association between air pollution and dementia, and modification by apolipoprotein E genotype 4 (APOE -ε4) has yet to be fully investigated. To examine associations of air pollution with three types of incident dementias (Alzheimer's disease (AD), frontotemporal dementia (FTD), and vascular dementia (VAD)), and their potential modification by APOE -ε4 genotype. The UK Biobank enrolled >500,000 participants (2006–2010) with ongoing follow-up. We used annual averages of air pollution (PM 2.5 , PM 10 , PM 2.5-10 , PM 2.5absorbance , NO 2 , NO X) for 2010 scaled to interquartile ranges (IQR). We included individuals aged ≥60 years, with no dementia diagnosis prior to January 1, 2010. Time to incident dementia and follow-up time were reported from baseline (January 01, 2010) to last censor event (death, last hospitalization, or loss to follow-up). Cox proportional hazard ratios (HR) and 95% confidence intervals (95% CI) were calculated to estimate the association of air pollutants and incident dementia, and modification of these associations by APOE -ε4. Our sample included 187,194 individuals (including N = 680 AD, N = 377 VAD, N = 63 FTD) with a mean follow-up of 7.04 years. We observed consistent associations of PM 2.5 with greater risk of all-cause dementia (HR = 1.17, 95% CI: 1.10, 1.24) and AD (HR = 1.17, 95% CI: 1.06, 1.29). NO 2 was also associated with greater risk of any incident dementia (HR = 1.18, 95% CI: 1.10, 1.25), AD (HR = 1.15, 95% CI: 1.04, 1.28) and VAD (HR = 1.18, 95% CI: 1.03, 1.35). APOE -ε4 did not modify the association between any air pollutants and dementia. PM 2.5 and NO 2 levels were associated with several types of dementia, and these associations were not modified by APOE -ε4. Findings from the UK Biobank support and extend to other epidemiological evidence for the potential association of air pollutants with detrimental brain health during aging. • Examined air pollution and dementia incidence over 10 years in the UK Biobank. • PM2.5, NO2, and NOX, was associated with higher incidence of dementia. • APOE -ε4 did not modify the association of air pollution with dementia. [ABSTRACT FROM AUTHOR]

Lipedema is a common disorder characterized by excessive deposition of subcutaneous adipose tissue (SAT) in the legs, hips, and buttocks, mainly occurring in adult women. Although it appears to be heritable, no specific genes have yet been identified. To identify potential genetic risk factors for lipedema, we used bioelectrical impedance analysis and anthropometric data from the UK Biobank to identify women with and without a lipedema phenotype. Specifically, we identified women with both a high percentage of fat in the lower limbs and a relatively small waist, adjusting for hip circumference. We performed a genome-wide association study (GWAS) for this phenotype, and performed multiple sensitivity GWAS. In an independent case/control study of lipedema based on strict clinical criteria, we attempted to replicate our top hits. We identified 18 significant loci (p < 5 × 10 -9 ), several of which have previously been identified in GWAS of waist-to-hip ratio with larger effects in women. Two loci (VEGFA and GRB14-COBLL1) were significantly associated with lipedema in the independent replication study. Follow-up analyses suggest an enrichment of genes expressed in blood vessels and adipose tissue, among other tissues. Our findings provide a starting point towards better understanding the genetic and physiological basis of lipedema., (© 2022. The Author(s), under exclusive licence to European Society of Human Genetics.)

Air pollution has consistently been associated with cardiometabolic outcomes, although associations with obesity have only been recently reported. Studies of air pollution and adiposity have mostly relied on body mass index (BMI) rather than body fat percentage (BF%), and most have not accounted for noise as a possible confounder. Additionally, it is unknown whether genetic predisposition for obesity increases susceptibility to the obesogenic effects of air pollution. To help fill these gaps, we used the UK Biobank, a large, prospective cohort study in the United Kingdom, to explore the relationship between air pollution and adiposity, and modification by a polygenic risk score for BMI. We used 2010 annual averages of air pollution estimates from land use regression (NO 2 , NO X , PM 2.5 , PM 2.5absorbance , PM 2.5-10 , PM 10 ), traffic intensity (TI), inverse distance to road (IDTR), along with examiner-measured BMI, waist-hip-ratio (WHR), and impedance measures of BF%, which were collected at enrollment (2006-2010, n = 473,026) and at follow-up (2012-2013, n = 19,518). We estimated associations of air pollution with BMI, WHR, and BF% at enrollment and follow-up, and with obesity, abdominal obesity, and BF%-obesity at enrollment and follow-up. We used linear and logistic regression and controlled for noise and other covariates. We also assessed interactions of air pollution with a polygenic risk score for BMI. On average, participants at enrollment were 56 years of age, 54% were female, and 32% had completed college or a higher degree. Almost all participants (~95%) were white. All air pollution measures except IDTR were positively associated with at least one continuous measure of adiposity at enrollment. However, NO 2 was negatively associated with BMI but positively associated with WHR at enrollment, and IDTR was also negatively associated with BMI. At follow-up (controlling for enrollment adiposity), we observed positive associations for PM 2.5-10 with BMI, PM 10 with BF%, and TI with BF% and BMI. Associations were similar for binary measures of adiposity, with minor differences for some pollutants. Associations of NO X , NO 2 , PM 2.5absorbance , PM 2.5 and PM 10 , with BMI at enrollment, but not at follow-up, were stronger among individuals with higher BMI polygenic risk scores (interaction p <0.05). In this large, prospective cohort, air pollution was associated with several measures of adiposity at enrollment and follow-up, and associations with adiposity at enrollment were modified by a polygenic risk score for obesity., Competing Interests: Declaration of competing interest The authors have no conflicts of interest to declare., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Background/objectives: Physical activity (PA) protects against a wide range of diseases. Habitual PA appears to be heritable, motivating the search for specific genetic variants that may inform efforts to promote PA and target the best type of PA for each individual., Subjects/methods: We used data from the UK Biobank to perform the largest genome-wide association study of PA to date, using three measures based on self-report (n max  = 377,234) and two measures based on wrist-worn accelerometry data (n max  = 91,084). We examined genetic correlations of PA with other traits and diseases, as well as tissue-specific gene expression patterns. With data from the Atherosclerosis Risk in Communities (ARIC; n = 8,556) study, we performed a meta-analysis of our top hits for moderate-to-vigorous PA (MVPA)., Results: We identified ten loci across all PA measures that were significant in both a basic and a fully adjusted model (p < 5 × 10 -9 ). Upon meta-analysis of the nine top hits for MVPA with results from ARIC, eight were genome-wide significant. Interestingly, among these, the rs429358 variant in the APOE gene was the most strongly associated with MVPA, whereby the allele associated with higher Alzheimer's risk was associated with greater MVPA. However, we were not able to rule out possible selection bias underlying this result. Variants in CADM2, a gene previously implicated in obesity, risk-taking behavior and other traits, were found to be associated with habitual PA. We also identified three loci consistently associated (p < 5 × 10 -5 ) with PA across both self-report and accelerometry, including CADM2. We found genetic correlations of PA with educational attainment, chronotype, psychiatric traits, and obesity-related traits. Tissue enrichment analyses implicate the brain and pituitary gland as locations where PA-associated loci may exert their actions., Conclusions: These results provide new insight into the genetic basis of habitual PA, and the genetic links connecting PA with other traits and diseases.