Genome-wide association analyses of physical activity and sedentary behavior provide insights into underlying mechanisms and roles in disease prevention

Large changes in detected selection signatures after a selection limit in mice bred for voluntary wheel-running behavior

In various organisms, sequencing of selectively bred lines at apparent selection limits has demonstrated that genetic variation can remain at many loci, implying that evolution at the genetic level may continue even if the population mean phenotype remains constant. We compared selection signatures at generations 22 and 61 of the "High Runner" mouse experiment, which includes 4 replicate lines bred for voluntary wheel-running behavior (HR) and 4 non-selected control (C) lines. Previously, we reported multiple regions of differentiation between the HR and C lines, based on whole-genome sequence data for 10 mice from each line at generation 61, which was >31 generations after selection limits had been reached in all HR lines. Here, we analyzed pooled sequencing data from ~20 mice for each of the 8 lines at generation 22, around when HR lines were reaching limits. Differentiation analyses of allele frequencies at ~4.4 million SNP loci used the regularized T-test and detected 258 differentiated regions with FDR = 0.01. Comparable analyses involving pooling generation 61 individual mouse genotypes into allele frequencies by line produced only 11 such regions, with almost no overlap among the largest and most statistically significant peaks between the two generations. These results implicate a sort of "genetic churn" that continues at loci relevant for running. Simulations indicate that loss of statistical power due to random genetic drift and sampling error are insufficient to explain the differences in selection signatures. The 13 differentiated regions at generation 22 with strict culling measures include 79 genes related to a wide variety of functions. Gene ontology identified pathways related to olfaction and vomeronasal pathways as being overrepresented, consistent with generation 61 analyses, despite those specific regions differing between generations. Genes Dspp and Rbm24 are also identified as potentially explaining known bone and skeletal muscle differences, respectively, between the linetypes.

The role of hypertension in the relationship between leisure screen time, physical activity and migraine: a 2-sample Mendelian randomization study

BACKGROUND

The relationship between lifestyle and migraine is complex, as it remains uncertain which specific lifestyle factors play the most prominent role in the development of migraine, or which modifiable metabolic traits serve as mediators in establishing causality.

METHODS

Independent genetic variants strongly associated with 20 lifestyle factors were selected as instrumental variables from corresponding genome-wide association studies (GWASs). Summary-level data for migraine were obtained from the FinnGen consortium (18,477 cases and 287,837 controls) as a discovery set and the GWAS meta-analysis data (26,052 cases and 487,214 controls) as a replication set. Estimates derived from the two datasets were combined using fixed-effects meta-analysis. Two-step univariable MR (UVMR) and multivariable Mendelian randomization (MVMR) analyses were conducted to evaluate 19 potential mediators of association and determine the proportions of these mediators.

RESULTS

The combined effect of inverse variance weighted revealed that a one standard deviation (SD) increase in genetically predicted Leisure screen time (LST) was associated with a 27.7% increase (95% CI: 1.14-1.44) in migraine risk, while Moderate or/and vigorous physical activity (MVPA) was associated with a 26.9% decrease (95% CI: 0.61-0.87) in migraine risk. The results of the mediation analysis indicated that out of the 19 modifiable metabolic risk factors examined, hypertension explains 24.81% of the relationship between LST and the risk of experiencing migraine. Furthermore, hypertension and diastolic blood pressure (DBP) partially weaken the association between MVPA and migraines, mediating 4.86% and 4.66% respectively.

CONCLUSION

Our research findings indicated that both LST and MVPA in lifestyle have independent causal effects on migraine. Additionally, we have identified that hypertension and DBP play a mediating role in the causal pathway between these two factors and migraine.

Trait selection strategy in multi-trait GWAS: Boosting SNP discoverability

Since the first genome-wide association studies (GWASs), thousands of variant-trait associations have been discovered. However, comprehensively mapping the genetic determinant of complex traits through univariate testing can require prohibitive sample sizes. Multi-trait GWAS can circumvent this issue and improve statistical power by leveraging the joint genetic architecture of human phenotypes. Although many methodological hurdles of multi-trait testing have been solved, the strategy to select traits has been overlooked. In this study, we conducted multi-trait GWAS on approximately 20,000 combinations of 72 traits using an omnibus test as implemented in the Joint Analysis of Summary Statistics. We assessed which genetic features of the sets of traits analyzed were associated with an increased detection of variants compared with univariate screening. Several features of the set of traits, including the heritability, the number of traits, and the genetic correlation, drive the multi-trait test gain. Using these features jointly in predictive models captures a large fraction of the power gain of the multi-trait test (Pearson's r between the observed and predicted gain equals 0.43, p < 1.6 × 10-60). Applying an alternative multi-trait approach (Multi-Trait Analysis of GWAS), we identified similar features of interest, but with an overall 70% lower number of new associations. Finally, selecting sets based on our data-driven models systematically outperformed the common strategy of selecting clinically similar traits. This work provides a unique picture of the determinant of multi-trait GWAS statistical power and outlines practical strategies for multi-trait testing.

Distinct biological signature and modifiable risk factors underlie the comorbidity between major depressive disorder and cardiovascular disease

Major depressive disorder (MDD) and cardiovascular disease (CVD) are often comorbid, resulting in excess morbidity and mortality. Here we show that CVDs share most of their genetic risk factors with MDD. Multivariate genome-wide association analysis of shared genetic liability between MDD and atherosclerotic CVD revealed seven loci and distinct patterns of tissue and brain cell-type enrichments, suggesting the involvement of the thalamus. Part of the genetic overlap was explained by shared inflammatory, metabolic and psychosocial or lifestyle risk factors. Our data indicated causal effects of genetic liability to MDD on CVD risk, but not from most CVDs to MDD, and showed that the causal effects were partly explained by metabolic and psychosocial or lifestyle factors. The distinct signature of MDD-atherosclerotic CVD comorbidity suggests an immunometabolic subtype of MDD that is more strongly associated with CVD than overall MDD. In summary, we identified biological mechanisms underlying MDD-CVD comorbidity and modifiable risk factors for prevention of CVD in individuals with MDD.

A Mendelian randomization-based study of the causal relationship between leisure sedentary behavior and delirium

BACKGROUND

Delirium is an acute or subacute change in mental status caused by various factors. We evaluated the causal relationship between leisure sedentary behaviors (LSBs) and delirium.

METHODS

A two-sample Mendelian randomization (MR) study was performed to evaluate the causal relationship between sedentary behaviors (time spent watching television, time spent using computer, and time spent driving) and delirium. Statistical information for the associations between single nucleotide polymorphisms (SNPs) and the traits of interest was obtained from independent consortia that focused on European populations. The dataset for LSBs was acquired from genome-wide association studies (GWAS) comprising a substantial sample size: 437887 samples for time spent watching television, 360,895 for time spent using computer, and 310,555 for time spent driving. A GWAS with 1269 delirium cases and 209,487 controls was used to identify genetic variation underlying the time of LSBs. We used five complementary MR methods, including inverse variance weighted method (IVW), MR-Egger, weighted median, weighted mode, and simple mode.

RESULTS

Genetically predicted time spent watching television (odds ratio [OR]: 2.921, 95 % confidence interval [CI]: 1.381-6.179) demonstrated significant association with delirium (P = 0.005), whereas no significant associations were observed between time spent using computer (OR: 0.556, 95 % CI: 0.246-1.257, P = 0.158) and time spent driving (OR: 1.747, 95 % CI: 0.09-3. 40, P = 0.713) and delirium. Sensitivity analyses supported a causal interpretation, with limited evidence of significant bias from genetic pleiotropy. Moreover, our MR assumptions appeared to be upheld, enhancing the credibility of our conclusions.

LIMITATIONS

Larger sample sizes are needed to validate the findings of our study.

CONCLUSION

Time spent watching television is a significant risk factor for delirium. Reducing television time may be an important intervention for those at higher risk of delirium.

Integrative Modeling of Accelerometry-Derived Sleep, Physical Activity, and Circadian Rhythm Domains With Current or Remitted Major Depression

Importance

Accelerometry has been increasingly used as an objective index of sleep, physical activity, and circadian rhythms in people with mood disorders. However, most prior research has focused on sleep or physical activity alone without consideration of the strong within- and cross-domain intercorrelations; and few studies have distinguished between trait and state profiles of accelerometry domains in major depressive disorder (MDD).

Objectives

To identify joint and individual components of the domains derived from accelerometry, including sleep, physical activity, and circadian rhythmicity using the Joint and Individual Variation Explained method (JIVE), a novel multimodal integrative dimension-reduction technique; and to examine associations between joint and individual components with current and remitted MDD.

Design, Setting, and Participants

This cross-sectional study examined data from the second wave of a population cohort study from Lausanne, Switzerland. Participants included 2317 adults (1164 without MDD, 185 with current MDD, and 968 with remitted MDD) with accelerometry for at least 7 days. Statistical analysis was conducted from January 2021 to June 2023.

Main Outcomes and Measures

Features derived from accelerometry for 14 days; current and remitted MDD. Logistic regression adjusted for age, sex, body mass index, and anxiety and substance use disorders.

Results

Among 2317 adults included in the study, 1261 (54.42%) were female, and mean (SD) age was 61.79 (9.97) years. JIVE reduced 28 accelerometry features to 3 joint and 6 individual components (1 sleep, 2 physical activity, 3 circadian rhythms). Joint components explained 58.5%, 79.5%, 54.5% of the total variation in sleep, physical activity, and circadian rhythm domains, respectively. Both current and remitted depression were associated with the first 2 joint components that were distinguished by the salience of high-intensity physical activity and amplitude of circadian rhythm and timing of both sleep and physical activity, respectively. MDD had significantly weaker circadian rhythmicity.

Conclusions and Relevance

Application of a novel multimodal dimension-reduction technique demonstrates the importance of joint influences of physical activity, circadian rhythms, and timing of both sleep and physical activity with MDD; dampened circadian rhythmicity may constitute a trait marker for MDD. This work illustrates the value of accelerometry as a potential biomarker for subtypes of depression and highlights the importance of consideration of the full 24-hour sleep-wake cycle in future studies.

Sedentary lifestyle, physical activity, and gastrointestinal diseases: evidence from mendelian randomization analysis

BACKGROUND

The causal associations of physical activity and sedentary behavior with the risk of gastrointestinal disease are unclear. We performed a Mendelian randomization analysis to examine these associations.

METHODS

Genetic instruments associated with leisure screen time (LST, an indicator of a sedentary lifestyle) and moderate-to-vigorous intensity physical activity (MVPA) at the genome-wide significance (P < 5 × 10-8) level were selected from a genome-wide association study. Summary statistics for gastrointestinal diseases were obtained from the UK Biobank study, the FinnGen study, and large consortia. Multivariable MR analyses were conducted for genetically determined LST with adjustment for MVPA and vice versa. We also performed multivariable MR with adjustment for genetically proxied smoking, body mass index (BMI), waist-to-hip ratio, type 2 diabetes, and fasting insulin for both exposures.

FINDINGS

Genetically proxied longer LST was associated with an increased risk of gastrointestinal reflux, gastric ulcer, duodenal ulcer, chronic gastritis, irritable bowel syndrome, diverticular disease, Crohn's disease, ulcerative colitis, non-alcoholic fatty liver disease, alcoholic liver disease, cholangitis, cholecystitis, cholelithiasis, acute pancreatitis, chronic pancreatitis, and acute appendicitis. Most associations remained after adjustment for genetic liability to MVPA. Genetic liability to MVPA was associated with decreased risk of gastroesophageal reflux, gastric ulcer, chronic gastritis, irritable bowel syndrome, cholecystitis, cholelithiasis, acute and chronic pancreatitis. The associations attenuated albeit directionally remained after adjusting for genetically predicted LST. Multivariable MR analysis found that BMI and type 2 diabetes mediated the associations of LST and MVPA with several gastrointestinal diseases.

INTERPRETATION

The study suggests that a sedentary lifestyle may play a causal role in the development of many gastrointestinal diseases.

FUNDING

Natural Science Fund for Distinguished Young Scholars of Zhejiang Province (LR22H260001), Natural Science Foundation of Hunan Province (2021JJ30999), Swedish Heart-Lung Foundation (Hjärt-Lungfonden, 20210351), Swedish Research Council (Vetenskapsrådet, 2019-00977), Swedish Cancer Society (Cancerfonden), the Wellcome Trust (225790/7/22/Z), United Kingdom Research and Innovation Medical Research Council (MC_UU_00002/7) and National Institute for Health Research Cambridge Biomedical Research Centre (NHIR203312).

Physical activity diminished adverse associations of obesity with lipid metabolism in the population of rural regions of China

The interactive effects of obesity and physical inactivity on lipid metabolism and prevalent dyslipidemia are scarcely reported in rural regions. 39029 subjects were obtained from the Henan Rural Cohort, and their metabolic equivalents (METs) of physical activity (PA) were computed. Independent associations of the obesity indices and PA with either lipid indices or prevalent dyslipidemia were analyzed by generalized linear models, and additive effects of obesity and PA on prevalent dyslipidemia were further quantified. Each obesity index was positively associated with total cholesterol, triglyceride, low-density lipoprotein or prevalent dyslipidemia but negatively associated with high-density lipoprotein, whereas the opposite association of PA with either each lipid index or prevalent dyslipidemia was observed. Joint association of PA and each obesity index with each lipid index and prevalent dyslipidemia was observed. Furthermore, the association of each obesity index in association with each lipid index was attenuated by increased PA levels.

Acute pancreatitis and metabolic syndrome: genetic correlations and causal associations

BACKGROUND

Although there is a definite correlation between the Metabolic Syndrome (MetS) and Acute Pancreatitis (AP), cause is yet unknown. The current work combined linkage disequilibrium score (LDSC) regression and Mendelian randomization (MR) approaches to fill this important information gap.

METHODS

In this study, we harnessed the power of publicly available gene-wide association databases (GWAS) to explore the intricate relationship between MetS and its components with AP. The cornerstone of our analysis was the Inverse-Variance Weighted (IVW) method, serving as our primary analytical tool. In addition to IVW, we complemented our investigation with several other robust MR methods, including MR-Egger, Weighted Median, Maximum Likelihood, and MR-PRESSO. By employing this diverse set of analytical approaches, we sought to ensure the comprehensiveness and robustness of our findings.

RESULT

LDSC regression indicated a genetic correlation between MetS and AP. Univariate MR results indicated a genetic association between MetS (OR = 1.084; 95% CI, 1.005-1.170; P = 0.037), BMI (OR = 1.459; 95% CI, 1.325-1.606; P = 1.46E-14), WHR (OR = 1.189; 95% CI, 1.068-1.323; P = 1.56 E-03), TG (OR = 1.110; 95% CI, 1.001-1.231; P = 0.047), and FI (OR = 1.798; 95% CI, 1.245-2.595; P = 1.74E-03) were able to significantly increase the risk of AP. The results of multivariate MR analysis revealed that these causality associations still existed.

CONCLUSION

Our investigation has yielded compelling evidence that substantiates the presence of both a genetic correlation and a causal relationship between MetS and AP.

The impact of exercise on gene regulation in association with complex trait genetics

Endurance exercise training is known to reduce risk for a range of complex diseases. However, the molecular basis of this effect has been challenging to study and largely restricted to analyses of either few or easily biopsied tissues. Extensive transcriptome data collected across 15 tissues during exercise training in rats as part of the Molecular Transducers of Physical Activity Consortium has provided a unique opportunity to clarify how exercise can affect tissue-specific gene expression and further suggest how exercise adaptation may impact complex disease-associated genes. To build this map, we integrate this multi-tissue atlas of gene expression changes with gene-disease targets, genetic regulation of expression, and trait relationship data in humans. Consensus from multiple approaches prioritizes specific tissues and genes where endurance exercise impacts disease-relevant gene expression. Specifically, we identify a total of 5523 trait-tissue-gene triplets to serve as a valuable starting point for future investigations [Exercise; Transcription; Human Phenotypic Variation].

Assessing the causal role of physical activity and leisure sedentary behaviours with chronic obstructive pulmonary disease: a Mendelian randomisation study

BACKGROUND

Observational studies show that patients with chronic obstructive pulmonary disease (COPD) tend to be sedentary during leisure time. Physical activity (PA) may reduce the risk of COPD, but the causal relationship is unclear. We used a Mendelian randomisation (MR) method to elucidate the association of leisure sedentary behaviours (LSB) and PA with lung function and COPD.

METHODS

Data on LSB (n=422 218), PA (n=608 595), COPD (n=299 929) and lung function (n=79 055) were obtained from the large-scale genome-wide association study. Causal inference used inverse variance-weighted, MR-Egger and weighted median. Sensitivity analysis was performed to assess heterogeneity and pleiotropy, and radial MR was used to distinguish outliers. The primary outcome was analysed by multifactorial MR adjusted for daily smoking.

RESULTS

The inverse variance weighted analysis indicated that increased moderate-to-vigorous PA (MVPA) is associated with higher levels of forced vital capacity (FVC) (beta=0.27, 95% CI 0.12 to 0.42; p=3.51×10-4). For each increment of 2.8 hours in television watching, the odds of COPD were 2.25 times greater (OR=2.25; 95% CI 1.84 to 2.75; p=2.38×10-15). For early-onset COPD, the odds were 2.11 times greater (OR=2.11; 95% CI 1.56 to 2.85; p=1.06×10-6), and for late-onset COPD, the odds were 2.16 times greater (OR=2.16; 95% CI 1.64 to 2.84; p=3.12×10-8). Similarly, the odds of hospitalisation for COPD were 2.02 times greater with increased television watching (OR=2.02; 95% CI 1.59 to 2.55; p=4.68×10-9). Television watching was associated with lower FVC (beta=-0.19, 95% CI -0.28 to -0.10; p=1.54×10-5) and forced expiratory volume in the 1 s (FEV1) (beta=-0.16, 95% CI -0.25 to -0.08; p=1.21×10-4) levels. The results remained significant after adjustment for smoking.

CONCLUSIONS

Our study suggests a potential association with LSB, particularly television watching, is associated with higher odds of COPD and lower indices of lung function as measured continuously, including FEV1 and FVC. Conversely, an increase in MVPA is associated with higher indices of lung function, particularly reflected in increased FVC levels.

Transforming the cardiometabolic disease landscape: Multimodal AI-powered approaches in prevention and management

The rise of artificial intelligence (AI) has revolutionized various scientific fields, particularly in medicine, where it has enabled the modeling of complex relationships from massive datasets. Initially, AI algorithms focused on improved interpretation of diagnostic studies such as chest X-rays and electrocardiograms in addition to predicting patient outcomes and future disease onset. However, AI has evolved with the introduction of transformer models, allowing analysis of the diverse, multimodal data sources existing in medicine today. Multimodal AI holds great promise in more accurate disease risk assessment and stratification as well as optimizing the key driving factors in cardiometabolic disease: blood pressure, sleep, stress, glucose control, weight, nutrition, and physical activity. In this article we outline the current state of medical AI in cardiometabolic disease, highlighting the potential of multimodal AI to augment personalized prevention and treatment strategies in cardiometabolic disease.

Physical activity, sedentary behavior, and the risk of functional gastrointestinal disorders: A two-sample Mendelian randomization study

OBJECTIVES

Functional dyspepsia (FD) and irritable bowel syndrome (IBS) are prevalent functional gastrointestinal disorders (FGIDs). In this study we aimed to explore the causal association between physical activity or sedentary behavior and the risk of FD and IBS.

METHODS

Mendelian randomization (MR) analysis was employed. Candidate genetic instruments for physical activity and sedentary behavior were retrieved from the latest published Genome-Wide Association Study (GWAS), which included up to 703 901 participants. Summary-level GWAS data for FD (8 875 cases and 320 387 controls) and IBS (9 323 cases and 301 931 controls) were obtained from the FinnGen study. The causal effects were mainly estimated by inverse variance weighted (IVW) method. Sensitivity analyses were implemented with Cochran's Q test, MR-Egger intercept test, leave-one-out analysis, and the funnel plot.

RESULTS

No significant association of moderate-to-vigorous intensity physical activity (MVPA), leisure screen time (LST), sedentary behavior at work (SDW), and sedentary commuting (SDC) with the risk of FD was found. However, there was a suggestive correlation between MVPA and the decreased risk of FD (odds ratio [OR] 0.63, 95% confidence interval [CI] 0.39-0.99, P = 0.047). Genetically predicted MVPA decreased the risk of IBS (OR 0.58, 95% CI 0.40-0.84, P = 0.004), while increased LST was positively associated with IBS risk (OR 1.33, 95% CI 1.15-1.53, P < 0.001). No causal effects of SDW or SDC on IBS risk were observed.

CONCLUSION

MVPA and LST are causally linked to the development of IBS, which will facilitate primary prevention of IBS.

Collider bias correction for multiple covariates in GWAS using robust multivariable Mendelian randomization

Genome-wide association studies (GWAS) have identified many genetic loci associated with complex traits and diseases in the past 20 years. Multiple heritable covariates may be added into GWAS regression models to estimate direct effects of genetic variants on a focal trait, or to improve the power by accounting for environmental effects and other sources of trait variations. When one or more covariates are causally affected by both genetic variants and hidden confounders, adjusting for them in GWAS will produce biased estimation of SNP effects, known as collider bias. Several approaches have been developed to correct collider bias through estimating the bias by Mendelian randomization (MR). However, these methods work for only one covariate, some of which utilize MR methods with relatively strong assumptions, both of which may not hold in practice. In this paper, we extend the bias-correction approaches in two aspects: first we derive an analytical expression for the collider bias in the presence of multiple covariates, then we propose estimating the bias using a robust multivariable MR (MVMR) method based on constrained maximum likelihood (called MVMR-cML), allowing the presence of invalid instrumental variables (IVs) and correlated pleiotropy. We also established the estimation consistency and asymptotic normality of the new bias-corrected estimator. We conducted simulations to show that all methods mitigated collider bias under various scenarios. In real data analyses, we applied the methods to two GWAS examples, the first a GWAS of waist-hip ratio with adjustment for only one covariate, body-mass index (BMI), and the second a GWAS of BMI adjusting metabolomic principle components as multiple covariates, illustrating the effectiveness of bias correction.

Unravelling the complex causal effects of substance use behaviours on common diseases

BACKGROUND

Substance use behaviours (SUB) including smoking, alcohol consumption, and coffee intake are associated with many health outcomes. However, whether the health effects of SUB are causal remains controversial, especially for alcohol consumption and coffee intake.

METHODS

In this study, we assess 11 commonly used Mendelian Randomization (MR) methods by simulation and apply them to investigate the causal relationship between 7 SUB traits and health outcomes. We also combine stratified regression, genetic correlation, and MR analyses to investigate the dosage-dependent effects.

RESULTS

We show that smoking initiation has widespread risk effects on common diseases such as asthma, type 2 diabetes, and peripheral vascular disease. Alcohol consumption shows risk effects specifically on cardiovascular diseases, dyslipidemia, and hypertensive diseases. We find evidence of dosage-dependent effects of coffee and tea intake on common diseases (e.g., cardiovascular disease and osteoarthritis). We observe that the minor allele effect of rs4410790 (the top signal for tea intake level) is negative on heavy tea intake ( b ̂ G W A S = - 0.091 , s . e . = 0.007 , P = 4.90 × 10 - 35 ) but positive on moderate tea intake ( b ̂ G W A S = 0.034 , s . e . = 0.006 , P = 3.40 × 10 - 8 ) , compared to the non-tea-drinkers.

CONCLUSION

Our study reveals the complexity of the health effects of SUB and informs design for future studies aiming to dissect the causal relationships between behavioural traits and complex diseases.

Sedentary behavior, physical activity, sleep duration and obesity risk: Mendelian randomization study

BACKGROUND

Observational studies have suggested associations between sedentary behaviors (SB), physical activity (PA), sleep duration (SD), and obesity, but the causal relationships remain unclear.

METHODS

We used Mendelian randomization (MR) with genetic variation as instrumental variables (IVs) to assess the causality between SB/PA/SD and obesity. Genetic variants associated with SB/PA/SD were obtained from Genome-wide association study (GWAS), and obesity data came from FinnGen. The primary MR analysis used the instrumental variable weighted (IVW) method, with sensitivity tests including Cochran Q, MR-Egger intercepts, and MR-Radial. Expression Quantitative Trait Loci (eQTL) analysis was applied to identify significant genetic associations and biological pathways in obesity-related tissues.

RESULTS

The MR analysis revealed causal relationships between four SB-related lifestyle patterns and obesity. Specifically, increased genetic liability to television watching (IVW MR Odds ratio [OR] = 1.55, [95% CI]:[1.27, 1.90], p = 1.67×10-5), computer use ([OR] = 1.52, [95% CI]:[1.08, 2.13], p = 1.61×10-2), leisure screen time (LST) ([OR] = 1.62, [95% CI] = [1.43, 1.84], p = 6.49×10-14, and driving (MR [OR] = 2.79, [95% CI]:[1.25, 6.21], p = 1.23×10-2) was found to increase the risk of obesity. Our findings indicate that no causal relationships were observed between SB at work, sedentary commuting, PA, SD, and obesity. The eQTL analysis revealed strong associations between specific genes (RPS26, TTC12, CCDC92, NICN1) and SNPs (rs10876864, rs2734849, rs4765541, rs7615206) in both subcutaneous and visceral adipose tissues, which are associated with these SBs. Enrichment analysis further revealed that these genes are involved in crucial biological pathways, including cortisol synthesis, thyroid hormone synthesis, and insulin secretion.

CONCLUSIONS

Our findings support a causal relationship between four specific SBs (LST, television watching, computer use, driving) and obesity. These results provide valuable insights into potential interventions to address obesity effectively, supported by genetic associations in the eQTL and enrichment analysis. Further research and public health initiatives focusing on reducing specific SBs may be warranted.

Causal Relationships Between Screen Use, Reading, and Brain Development in Early Adolescents

The rise of new media has greatly changed the lifestyles, leading to increased time on these platforms and less time spent reading. This shift has particularly profound impacts on early adolescents, who are in a critical stage of brain development. Previous studies have found associations between screen use and mental health, but it remains unclear whether screen use is the direct cause of the outcomes. Here, the Adolescent Brain Cognitive Development (ABCD) dataset is utlized to examine the causal relationships between screen use and brain development. The results revealed adverse causal effects of screen use on language ability and specific behaviors in early adolescents, while reading has positive causal effects on their language ability and brain volume in the frontal and temporal regions. Interestingly, increased screen use is identified as a result, rather than a cause, of certain behaviors such as rule-breaking and aggressive behaviors. Furthermore, the analysis uncovered an indirect influence of screen use, mediated by changes in reading habits, on brain development. These findings provide new evidence for the causal influences of screen use on brain development and highlight the importance of monitoring media use and related habit change in children.

Physical Activity, Sedentary Behavior, and Pancreatic Cancer Risk: A Mendelian Randomization Study

Pancreatic cancer is currently the seventh leading cause of cancer death worldwide. Understanding whether modifiable factors increase or decrease the risk of this disease is central to facilitating primary prevention. Several epidemiological studies have described the benefits of physical activity, and the risks associated with sedentary behavior, in relation to cancer. This study aimed to assess evidence of causal effects of physical activity and sedentary behavior on pancreatic cancer risk. We conducted a two-sample Mendelian randomization study using publicly available data for genetic variants associated with physical activity and sedentary behavior traits and genetic data from the Pancreatic Cancer Cohort Consortium (PanScan), the Pancreatic Cancer Case-Control Consortium (PanC4), and the FinnGen study for a total of 10 018 pancreatic cancer cases and 266 638 controls. We also investigated the role of body mass index (BMI) as a possible mediator between physical activity and sedentary traits and risk of developing pancreatic cancer. We found evidence of a causal association between genetically determined hours spent watching television (hours per day) and increased risk of pancreatic cancer for each hour increment (PanScan-PanC4 odds ratio = 1.52, 95% confidence interval 1.17-1.98, P = .002). Additionally, mediation analysis showed that genetically determined television-watching time was strongly associated with BMI, and the estimated proportion of the effect of television-watching time on pancreatic cancer risk mediated by BMI was 54%. This study reports the first Mendelian randomization-based evidence of a causal association between a measure of sedentary behavior (television-watching time) and risk of pancreatic cancer and that this is strongly mediated by BMI. Summary: Pancreatic cancer is a deadly disease that is predicted to become the second leading cause of cancer-related deaths by 2030. Physical activity and sedentary behaviors have been linked to cancer risk and survival. However, there is limited research on their correlation with pancreatic cancer. To investigate this, we used a Mendelian randomization approach to examine the genetic predisposition to physical activity and sedentariness and their relation to pancreatic cancer risk, while excluding external confounders. Our findings revealed a causal link between the time spent watching television and an increased risk of pancreatic cancer. Additionally, we determined that over half of the effect of watching television on pancreatic risk is mediated by the individual's BMI.

Genomic predictors of physical activity and athletic performance

Physical activity and athletic performance are complex phenotypes influenced by environmental and genetic factors. Recent advances in lifestyle and behavioral genomics led to the discovery of dozens of DNA polymorphisms (variants) associated with physical activity and allowed to use them as genetic instruments in Mendelian randomization studies for identifying the causal links between physical activity and health outcomes. On the other hand, exercise and sports genomics studies are focused on the search for genetic variants associated with athlete status, sports injuries and individual responses to training and supplement use. In this review, the findings of studies investigating genetic markers and their associations with physical activity and athlete status are reported. As of the end of September 2023, a total of 149 variants have been associated with various physical activity traits (of which 42 variants are genome-wide significant) and 253 variants have been linked to athlete status (115 endurance-related, 96 power-related, and 42 strength-related).

The Rotterdam Study. Design update and major findings between 2020 and 2024

The Rotterdam Study is a population-based cohort study, started in 1990 in the district of Ommoord in the city of Rotterdam, the Netherlands, with the aim to describe the prevalence and incidence, unravel the etiology, and identify targets for prediction, prevention or intervention of multifactorial diseases in mid-life and elderly. The study currently includes 17,931 participants (overall response rate 65%), aged 40 years and over, who are examined in-person every 3 to 5 years in a dedicated research facility, and who are followed-up continuously through automated linkage with health care providers, both regionally and nationally. Research within the Rotterdam Study is carried out along two axes. First, research lines are oriented around diseases and clinical conditions, which are reflective of medical specializations. Second, cross-cutting research lines transverse these clinical demarcations allowing for inter- and multidisciplinary research. These research lines generally reflect subdomains within epidemiology. This paper describes recent methodological updates and main findings from each of these research lines. Also, future perspective for coming years highlighted.

Physical activity, sedentary behavior, and the risk of frailty and falling: A Mendelian randomization study

BACKGROUND

Due to inconclusive evidence from observational studies regarding the impact of physical activity (PA) and sedentary behavior on frailty and falling risk, we conducted a two-sample Mendelian randomization analysis to investigate the causal associations between PA, sedentary behavior, and frailty and falls.

METHODS

We extracted summary data from genome-wide association studies conducted among individuals of European ancestry, encompassing PA (n = 90 667-608 595), sedentary behavior (n = 372 609-526 725), frailty index (n = 175 226), and falling risk (n = 451 179). Single nucleotide polymorphisms associated with accelerometer assessed fraction >425 milligravities, self-reported vigorous activity, moderate to vigorous physical acticity (MVPA), leisure screen time (LST), and sedentary behavior at work were taken as instrumental variables. The causal effects were primarily estimated using inverse variance weighted methods, complemented by several sensitivity and validation analyses.

RESULTS

Genetically predicted higher levels of PA were significantly associated with a reduction in the frailty index (accelerometer assessed fraction >425 milligravities: β = -0.25, 95% CI = -0.36 to -0.14, p = 1.27 × 10-5 ; self-reported vigorous activity: β = -0.13, 95% CI = -0.20 to -0.05, p = 7.9 × 10-4 ; MVPA: β = -0.28, 95% CI = -0.40 to -0.16, p = 9.9 × 10-6 ). Besides, LST was significantly associated with higher frailty index (β = 0.18, 95% CI = 0.14-0.22, p = 5.2 × 10-20 ) and higher odds of falling (OR = 1.13, CI = 1.07-1.19, p = 6.9 × 10-6 ). These findings remained consistent throughout sensitivity and validation analyses.

CONCLUSIONS

Our study offers evidence supporting a causal relationship between PA and a reduced risk of frailty. Furthermore, it underscores the association between prolonged LST and an elevated risk of frailty and falls. Therefore, promoting PA and reducing sedentary behavior may be an effective strategy in primary frailty and falls prevention.

Assessing the genetic contribution of cumulative behavioral factors associated with longitudinal type 2 diabetes risk highlights adiposity and the brain-metabolic axis

While genetic factors, behavior, and environmental exposures form a complex web of interrelated associations in type 2 diabetes (T2D), their interaction is poorly understood. Here, using data from ~500K participants of the UK Biobank, we identify the genetic determinants of a "polyexposure risk score" (PXS) a new risk factor that consists of an accumulation of 25 associated individual-level behaviors and environmental risk factors that predict longitudinal T2D incidence. PXS-T2D had a non-zero heritability (h2 = 0.18) extensive shared genetic architecture with established clinical and biological determinants of T2D, most prominently with body mass index (genetic correlation [rg] = 0.57) and Homeostatic Model Assessment for Insulin Resistance (rg = 0.51). Genetic loci associated with PXS-T2D were enriched for expression in the brain. Biobank scale data with genetic information illuminates how complex and cumulative exposures and behaviors as a whole impact T2D risk but whose biology have been elusive in genome-wide studies of T2D.

Distinct genomic signatures and modifiable risk factors underly the comorbidity between major depressive disorder and cardiovascular disease

Major depressive disorder (MDD) and cardiovascular disease (CVD) are often comorbid, resulting in excess morbidity and mortality. Using genomic data, this study elucidates biological mechanisms, key risk factors, and causal pathways underlying their comorbidity. We show that CVDs share a large proportion of their genetic risk factors with MDD. Multivariate genome-wide association analysis of the shared genetic liability between MDD and atherosclerotic CVD (ASCVD) revealed seven novel loci and distinct patterns of tissue and brain cell-type enrichments, suggesting a role for the thalamus. Part of the genetic overlap was explained by shared inflammatory, metabolic, and psychosocial/lifestyle risk factors. Finally, we found support for causal effects of genetic liability to MDD on CVD risk, but not from most CVDs to MDD, and demonstrated that the causal effects were partly explained by metabolic and psychosocial/lifestyle factors. The distinct signature of MDD-ASCVD comorbidity aligns with the idea of an immunometabolic sub-type of MDD more strongly associated with CVD than overall MDD. In summary, we identify plausible biological mechanisms underlying MDD-CVD comorbidity, as well as key modifiable risk factors for prevention of CVD in individuals with MDD.

Investigating the causal relationship between physical activity and incident knee osteoarthritis: a two-sample Mendelian randomization study

There is evidence that physical activity (PA) has a long-term positive impact on disease. Whether PA is a risk factor for knee osteoarthritis (OA) is still controversial. The purpose of this study was to explore whether there is a causal relationship between PA and knee OA. We extracted PA and knee OA data from genome-wide association study (GWAS) databases. We used single-nucleotide polymorphisms (SNPs) as instrumental variables. We performed MR analysis by random-effects inverse-variance weighting (IVW), MR‒Egger, weighted median, simple mode, and weighted mode methods. We evaluated the stability and reliability of the results through sensitivity analysis. There was no significant association between PA and knee OA (p > 0.05). We did not detect any pleiotropy (MR‒Egger intercept test et al.: p > 0.05). The sensitivity analysis confirmed our results (p > 0.05). There is no causal relationship between PA and knee OA.

The Role of Endocrine Disruptors Bisphenols and Phthalates in Obesity: Current Evidence, Perspectives and Controversies

Excess body weight constitutes one of the major health challenges for societies and healthcare systems worldwide. Besides the type of diet, calorie intake and the lack of physical exercise, recent data have highlighted a possible association between endocrine-disrupting chemicals (EDCs), such as bisphenol A, phthalates and their analogs, and obesity. EDCs represent a heterogeneous group of chemicals that may influence the hormonal regulation of body mass and adipose tissue morphology. Based on the available data from mechanistic, animal and epidemiological studies including meta-analyses, the weight of evidence points towards the contribution of EDCs to the development of obesity, associated disorders and obesity-related adipose tissue dysfunction by (1) impacting adipogenesis; (2) modulating epigenetic pathways during development, enhancing susceptibility to obesity; (3) influencing neuroendocrine signals responsible for appetite and satiety; (4) promoting a proinflammatory milieu in adipose tissue and inducing a state of chronic subclinical inflammation; (5) dysregulating gut microbiome and immune homeostasis; and (6) inducing dysfunction in thermogenic adipose tissue. Critical periods of exposure to obesogenic EDCs are the prenatal, neonatal, pubertal and reproductive periods. Interestingly, EDCs even at low doses may promote epigenetic transgenerational inheritance of adult obesity in subsequent generations. The aim of this review is to summarize the available evidence on the role of obesogenic EDCs, specifically BPA and phthalate plasticizers, in the development of obesity, taking into account in vitro, animal and epidemiologic studies; discuss mechanisms linking EDCs to obesity; analyze the effects of EDCs on obesity in critical chronic periods of exposure; and present interesting perspectives, challenges and preventive measures in this research area.

Causal Roles of Lifestyle, Psychosocial Characteristics, and Sleep Status in Sarcopenia: A Mendelian Randomization Study

BACKGROUND

Many studies reported that lifestyle, psychosocial characteristics, and sleep status related to sarcopenia, although few studies provided evidence of causal relationships between them.

METHODS

The data used in our study were from UK Biobank, FinnGen Release 8, and large genome-wide association study meta-analyses. Two-sample Mendelian randomization was conducted to identify the causal associations of 21 traits of lifestyle, psychosocial characteristics, and sleep status with 6 traits of sarcopenia. Benjamini-Hochberg correction was performed to reduce the bias caused by multiple tests. Risk factor analyses were performed to explore the potential mechanism behind the exposures.

RESULTS

Mendelian randomization analyses after adjustment proved the causal roles of coffee intake, education years, smoking, leisure screen time, and moderate-to-vigorous intensity physical activity during leisure time in sarcopenia was proven although providing no significant evidence for causal roles for carbohydrates intake, protein intake, alcohol, and sleep status in sarcopenia.

CONCLUSIONS

Our results strongly support that coffee intake, education years, smoking, leisure screen time, and moderate-to-vigorous intensity physical activity during leisure time played significantly causal roles in sarcopenia, which may provide new intervention strategies for preventing the development of sarcopenia.

Harnessing Passive Pulsatile Shear Stress for Alzheimer's Disease Prevention and Intervention

 Alzheimer's disease (AD) affects more than 40 million people worldwide and is the leading cause of dementia. This disease is a challenge for both patients and caregivers and puts a significant strain on the global healthcare system. To address this issue, the Lancet Commission recommends focusing on reducing modifiable lifestyle risk factors such as hypertension, diabetes, and physical inactivity. Passive pulsatile shear stress (PPSS) interventions, which use devices like whole-body periodic acceleration, periodic acceleration along the Z-axis (pGz), and the Jogging Device, have shown significant systemic and cellular effects in preclinical and clinical models which address these modifiable risks factors. Based on this, we propose that PPSS could be a potential non-pharmacological and non-invasive preventive or therapeutic strategy for AD. We perform a comprehensive review of the biological basis based on all publications of PPSS using these devices and demonstrate their effects on the various aspects of AD. We draw from this comprehensive analysis to support our hypothesis. We then delve into the possible application of PPSS as an innovative intervention. We discuss how PPSS holds promise in ameliorating hypertension and diabetes while mitigating physical inactivity, potentially offering a holistic approach to AD prevention and management.

Causal effects of body mass index, education, and lifestyle behaviors on intervertebral disc disorders: Mendelian randomization study

This study aimed to investigate the causal risk factors for intervertebral disc disorders (IVDD) to help establish prevention strategies for IVDD-related diseases. We performed two-sample Mendelian randomization analyses to investigate the causal effects of body mass index (BMI), education, and lifestyle behaviors (sedentary behavior, smoking, and sleeping) on thoracic/thoracolumbar/lumbosacral IVDD (TTL-IVDD) and cervical IVDD. The inverse-variance weighted (IVW) method was conducted as the primary model to pool effect sizes using odds ratio and 95% confidence interval. The strength of causal evidence was evaluated from the effect size and different Mendelian randomization methods (MR-Egger/weighted median/weighted mode method, Cochran's Q test, leave-one-out analysis, MR Steiger, MR-PRESSO and radial IVW analyses). We found strong evidence for the causal associations between IVDD and BMI (TTL-IVDD, 1.27 [1.18, 1.37], p = 2.40 × 10-10 ; cervical IVDD, 1.24 [1.12, 1.37, p = 6.58 × 10-5 ), educational attainment (TTL-IVDD, 0.57 [0.51, 0.64], p = 9.64 × 10-21 ; cervical IVDD, 0.58 [0.49, 0.68], p = 1.78 × 10-10 ), leisure television watching (TTL-IVDD, 1.54 [1.29, 1.84], p = 7.80 × 10-6 ; cervical IVDD, 1.65 [1.29, 2.11], p = 0.0001), smoking initiation (TTL-IVDD, 1.37 [1.25, 1.50], p = 1.78 × 10-10 ; cervical IVDD, 1.32 [1.16, 1.51], p = 6.49 × 10-5 ), short sleep (TTL-IVDD, 1.28 [1.09, 1.49], p = 0.0027; cervical IVDD, 1.53 [1.21, 1.94], p = 0.0008), or frequent insomnia (TTL-IVDD, 1.20 [1.11, 1.30], p = 1.54 × 10-5 ; cervical IVDD, 1.37 [1.20, 1.57], p = 7.80 × 10-6 ). This study provided genetic evidence that increased BMI, low educational attainment, sedentary behavior by leisure television watching, smoking initiation, short sleep, and frequent insomnia were causal risk factors for IVDD. More efforts should be directed toward increasing public awareness of these modifiable risk factors and mobilizing individuals to adopt healthy lifestyles.

Dose-response associations, physical activity intensity and mortality risk: A narrative review

Physical activity is consistently associated with reduced mortality, decreased risk for non-communicable diseases, and improved mental health in observational studies. Randomized controlled trials and observational Mendelian randomization studies support causal links between physical activity and health outcomes. However, the scarcity of evidence from randomized controlled trials, along with their inherent challenges like exposure contrasts, healthy volunteer biases, loss to follow-up, and limited real-world dose-response data, warrants a comprehensive approach. This review advocates synthesizing insights from diverse study designs to better understand the causal relationship between physical activity, mortality risk, and other health outcomes. Additionally, it summarizes recent research since the publication of current physical activity recommendations. Novel observational studies utilizing device-measured physical activity underscore the importance of every minute of activity and suggest that all intensity levels confer health benefits, with vigorous-intensity potentially requiring lower volumes for substantial benefits. Future guidelines, informed by device-measured physical activity studies, may offer refined age-specific recommendations, emphasize vigorous-intensity physical activity, and include daily step counts as a simple, easily assessable metric using commercial wearables.

Mendelian randomization for cardiovascular diseases: principles and applications

Large-scale genome-wide association studies conducted over the last decade have uncovered numerous genetic variants associated with cardiometabolic traits and risk factors. These discoveries have enabled the Mendelian randomization (MR) design, which uses genetic variation as a natural experiment to improve causal inferences from observational data. By analogy with the random assignment of treatment in randomized controlled trials, the random segregation of genetic alleles when DNA is transmitted from parents to offspring at gamete formation is expected to reduce confounding in genetic associations. Mendelian randomization analyses make a set of assumptions that must hold for valid results. Provided that the assumptions are well justified for the genetic variants that are employed as instrumental variables, MR studies can inform on whether a putative risk factor likely has a causal effect on the disease or not. Mendelian randomization has been increasingly applied over recent years to predict the efficacy and safety of existing and novel drugs targeting cardiovascular risk factors and to explore the repurposing potential of available drugs. This review article describes the principles of the MR design and some applications in cardiovascular epidemiology.

Obesity, birth weight, and lifestyle factors for frailty: a Mendelian randomization study

Obesity, birth weight and lifestyle factors have been found associated with the risk of frailty in observational studies, but whether these associations are causal is uncertain. We conducted a two-sample Mendelian randomization study to investigate the associations. Genetic instruments associated with the exposures at the genome-wide significance level (p < 5 × 10-8) were selected from corresponding genome-wide association studies (n = 143,677 to 703,901 individuals). Summary-level data for the frailty index were obtained from the UK Biobank (n = 164,610) and Swedish TwinGene (n = 10,616). The β of the frailty index was 0.15 (p = 3.88 × 10-9) for 1 standard deviation increase in the prevalence of smoking initiation, 0.19 (p = 3.54 × 10-15) for leisure screen time, 0.13 (p = 5.26 × 10-7) for body mass index and 0.13 (p = 1.80 × 10-4) for waist circumference. There was a suggestive association between genetically predicted higher birth weight and moderate-to-vigorous intensity physical activity with the decreased risk of the frailty index. We observed no causal association between genetically predicted age of smoking initiation and alcoholic drinks per week with the frailty index. This study supports the causal roles of smoking initiation, leisure screen time, overall obesity, and abdominal obesity in frailty. The possible association between higher birth weight, proper physical activity and a decreased risk of frailty needs further confirmation.

Understanding the consequences of leisure sedentary behavior on periodontitis: A two-step, multivariate Mendelian randomization study

Background

The relationship between leisure sedentary behavior (LSB) and periodontitis risk remains unclear in terms of causality and the potential mediating effects of intermediate factors.

Materials and methods

Using the aggregate data of several large-scale genetic association studies from participants of European descent, we conducted a univariate, two-step, and multivariate Mendelian random (MR) analysis to infer the overall effect of LSB on periodontitis, and quantified the intermediary proportion of intermediary traits such as smoking.

Results

Our findings indicated that per 1-SD increase (1.87 h) in leisure screen time (LST), there was a 23 % increase in the risk of periodontitis. [odds ratios (95 % CI) = 1.23 (1.04-1.44), p = 0.013]. Smoking was found to partially mediate the overall causal effect of LST on periodontitis, with a mediation rate of 20.7 % (95 % CI: 4.9%-35.5 %). Multivariate MR analysis demonstrated that the causal effect of LST on periodontitis was weakened when adjusting for smoking, resulting in an odds ratio of 1.19 (95 % CI: 1.01-1.39, p = 0.049) for each 1 standard deviation increase in exposure.

Conclusion

The study provides evidence of a potential causal relationship between LSB characterized by LST and periodontitis, thereby further supporting the notion that reducing LSB is beneficial for health. Furthermore, it confirms the role of smoking as a mediator in this process, suggesting that inhibiting smoking behavior among individuals with long-term LSB may serve as a strategy to mitigate the risk of periodontitis.

Maternal upbringing and selective breeding for voluntary exercise behavior modify patterns of DNA methylation and expression of genes in the mouse brain

Selective breeding has been utilized to study the genetic basis of exercise behavior, but research suggests that epigenetic mechanisms, such as DNA methylation, also contribute to this behavior. In a previous study, we demonstrated that the brains of mice from a genetically selected high runner (HR) line have sex-specific changes in DNA methylation patterns in genes known to be genomically imprinted compared to those from a non-selected control (C) line. Through cross-fostering, we also found that maternal upbringing can modify the DNA methylation patterns of additional genes. Here, we identify an additional set of genes in which DNA methylation patterns and gene expression may be altered by selection for increased wheel-running activity and maternal upbringing. We performed bisulfite sequencing and gene expression assays of 14 genes in the brain and found alterations in DNA methylation and gene expression for Bdnf, Pde4d and Grin2b. Decreases in Bdnf methylation correlated with significant increases in Bdnf gene expression in the hippocampus of HR compared to C mice. Cross-fostering also influenced the DNA methylation patterns for Pde4d in the cortex and Grin2b in the hippocampus, with associated changes in gene expression. We also found that the DNA methylation patterns for Atrx and Oxtr in the cortex and Atrx and Bdnf in the hippocampus were further modified by sex. Together with our previous study, these results suggest that DNA methylation and the resulting change in gene expression may interact with early-life influences to shape adult exercise behavior.

Distilling causality between physical activity traits and obesity via Mendelian randomization

BACKGROUND

Whether obesity is a cause or consequence of low physical activity levels and more sedentary time has not yet been fully elucidated. Better instrumental variables and a more thorough consideration of potential confounding variables that may influence the causal inference between physical activity and obesity are needed.

METHODS

Leveraging results from our recent genome-wide association study for leisure time moderate-to-vigorous intensity (MV) physical activity and screen time, we here disentangle the causal relationships between physical activity, sedentary behavior, education-defined by years of schooling-and body mass index (BMI), using multiple univariable and multivariable Mendelian Randomization (MR) approaches.

RESULTS

Univariable MR analyses suggest bidirectional causal effects of physical activity and sedentary behavior with BMI. However, multivariable MR analyses that take years of schooling into account suggest that more MV physical activity causes a lower BMI, and a higher BMI causes more screen time, but not vice versa. In addition, more years of schooling causes higher levels of MV physical activity, less screen time, and lower BMI.

CONCLUSIONS

In conclusion, our results highlight the beneficial effect of education on improved health and suggest that a more physically active lifestyle leads to lower BMI, while sedentary behavior is a consequence of higher BMI.

Polygenic Risk Score for Cardiovascular Diseases in Artificial Intelligence Paradigm: A Review

Cardiovascular disease (CVD) related mortality and morbidity heavily strain society. The relationship between external risk factors and our genetics have not been well established. It is widely acknowledged that environmental influence and individual behaviours play a significant role in CVD vulnerability, leading to the development of polygenic risk scores (PRS). We employed the PRISMA search method to locate pertinent research and literature to extensively review artificial intelligence (AI)-based PRS models for CVD risk prediction. Furthermore, we analyzed and compared conventional vs. AI-based solutions for PRS. We summarized the recent advances in our understanding of the use of AI-based PRS for risk prediction of CVD. Our study proposes three hypotheses: i) Multiple genetic variations and risk factors can be incorporated into AI-based PRS to improve the accuracy of CVD risk predicting. ii) AI-based PRS for CVD circumvents the drawbacks of conventional PRS calculators by incorporating a larger variety of genetic and non-genetic components, allowing for more precise and individualised risk estimations. iii) Using AI approaches, it is possible to significantly reduce the dimensionality of huge genomic datasets, resulting in more accurate and effective disease risk prediction models. Our study highlighted that the AI-PRS model outperformed traditional PRS calculators in predicting CVD risk. Furthermore, using AI-based methods to calculate PRS may increase the precision of risk predictions for CVD and have significant ramifications for individualized prevention and treatment plans.

Causal associations between hand grip strength and pulmonary function: a two-sample Mendelian randomization study

BACKGROUND

Several observational studies have reported an association between hand grip strength (HGS) and pulmonary function (PF). However, causality is unclear. To investigate whether HGS and PF are causally associated, we performed Mendelian randomization (MR) analyses.

METHODS

We identified 110 independent single nucleotide polymorphisms (SNPs) for right-hand grip strength (RHGS) and 103 independent SNPs for left-hand grip strength (LHGS) at the genome-wide significant threshold (P < 5 × 10-8) from MRC-IEU Consortium and evaluated these related to PF. MR estimates were calculated using the inverse-variance weighted (IVW) method and multiple sensitivity analyses were further performed.

RESULTS

Genetical liability to HGS was positively causally associated with forced vital capacity (FVC) and forced expiratory volume in one second (FEV1), but not with FEV1/FVC. In addition, there was positive causal association between RHGS and FVC (OR=1.519; 95% CI, 1.418-1.627; P=8.96E-33), and FEV1 (OR=1.486; 95% CI, 1.390-1.589; P=3.19E-31); and positive causal association between LHGS and FVC (OR=1.464; 95% CI, 1.385-1.548; P=2.83E-41) and FEV1 (OR=1.419; 95% CI, 1.340-1.502; P=3.19E-33). Nevertheless, no associations were observed between RHGS and FEV1/FVC (OR=0.998; 95% CI, 0.902-1.103; P=9.62E-01) and between LHGS and FEV1/FVC (OR=0.966; 95% CI, 0.861-1.083; P=5.52E-01). Similar results were shown in several sensitivity analyses.

CONCLUSION

Our study provides support at the genetic level that HGS is positively causally associated with FVC and FEV1, but not with FEV1/FVC. Interventions for HGS in PF impairment deserve further exploration as potential indicators of PF assessment.

Trait selection strategy in multi-trait GWAS: Boosting SNPs discoverability

Since the first Genome-Wide Association Studies (GWAS), thousands of variant-trait associations have been discovered. However, the sample size required to detect additional variants using standard univariate association screening is increasingly prohibitive. Multi-trait GWAS offers a relevant alternative: it can improve statistical power and lead to new insights about gene function and the joint genetic architecture of human phenotypes. Although many methodological hurdles of multi-trait testing have been discussed, the strategy to select trait, among overwhelming possibilities, has been overlooked. In this study, we conducted extensive multi-trait tests using JASS (Joint Analysis of Summary Statistics) and assessed which genetic features of the analysed sets were associated with an increased detection of variants as compared to univariate screening. Our analyses identified multiple factors associated with the gain in the association detection in multi-trait tests. Together, these factors of the analysed sets are predictive of the gain of the multi-trait test (Pearson's ρ equal to 0.43 between the observed and predicted gain, P < 1.6 × 10-60). Applying an alternative multi-trait approach (MTAG, multi-trait analysis of GWAS), we found that in most scenarios but particularly those with larger numbers of traits, JASS outperformed MTAG. Finally, we benchmark several strategies to select set of traits including the prevalent strategy of selecting clinically similar traits, which systematically underperformed selecting clinically heterogenous traits or selecting sets that issued from our data-driven models. This work provides a unique picture of the determinant of multi-trait GWAS statistical power and outline practical strategies for multi-trait testing.

Assessment of causal effects of physical activity on the risk of osteoarthritis: a two-sample Mendelian randomization study

BACKGROUND

Growing evidence supports an association between physical activity (PA) and the risk of osteoarthritis (OA), but this may be influenced by confounding and reverse causality. Therefore, we performed a two-sample Mendelian randomization (MR) analysis to reveal the causal relationship between PA and OA.

METHODS

MR was performed to explore the causation of PA and OA with genetic variants as instrumental variables. The genetic variants were derived from the summary statistics of a large genome-wide association study meta-analysis based on the European population (n = 661,399), including self-reported leisure screen time (LST) and moderate-to-vigorous physical activity (MVPA), and Arthritis Research UK Osteoarthritis Genetics Consortium cohorts (417,596, 393,873 and 403,124 for overall, hip and knee OA, respectively). The major MR analysis used in this work was the inverse variance weighted (IVW) approach, and sensitivity, pleiotropy, and heterogeneity studies were performed to evaluate the validity of the findings.

RESULTS

IVW estimates indicated that LST had a risk effect on overall OA (odds ratio (OR) = 1.309, 95% confidence interval (CI): 1.198-1.430, P = 2.330 × 10-9), hip OA (OR = 1.132, 95% CI: 1.009-1.269, P = 0.034) and knee OA (OR = 1.435. 95% CI: 1.286-1.602, P = 1.225 × 10-10). In contrast, no causal relationship was found between MVPA and OA (overall OA: OR = 0.895, 95% CI: 0.664-1.205, P = 0.465; hip OA: OR = 1.189, 95% CI: 0.792-1.786, P = 0.404; knee OA: OR = 0.707, 95% CI: 0.490 -1.021, P = 0.064). In addition, we observed significant heterogeneity in instrumental variables, but no horizontal pleiotropy was detected.

CONCLUSIONS

Recent findings demonstrated a protective impact of reducing LST on OA, independent of MVPA. This provides valuable insights into the role of physical activity in OA and offers lifestyle recommendations, such as reducing recreational sedentary behaviors and promoting appropriate exercise, for individuals at risk of OA.

Physiology of sedentary behavior

Sedentary behaviors (SB) are characterized by low energy expenditure while in a sitting or reclining posture. Evidence relevant to understanding the physiology of SB can be derived from studies employing several experimental models: bed rest, immobilization, reduced step count, and reducing/interrupting prolonged SB. We examine the relevant physiological evidence relating to body weight and energy balance, intermediary metabolism, cardiovascular and respiratory systems, the musculoskeletal system, the central nervous system, and immunity and inflammatory responses. Excessive and prolonged SB can lead to insulin resistance, vascular dysfunction, shift in substrate use toward carbohydrate oxidation, shift in muscle fiber from oxidative to glycolytic type, reduced cardiorespiratory fitness, loss of muscle mass and strength and bone mass, and increased total body fat mass and visceral fat depot, blood lipid concentrations, and inflammation. Despite marked differences across individual studies, longer term interventions aimed at reducing/interrupting SB have resulted in small, albeit marginally clinically meaningful, benefits on body weight, waist circumference, percent body fat, fasting glucose, insulin, HbA1c and HDL concentrations, systolic blood pressure, and vascular function in adults and older adults. There is more limited evidence for other health-related outcomes and physiological systems and for children and adolescents. Future research should focus on the investigation of molecular and cellular mechanisms underpinning adaptations to increasing and reducing/interrupting SB and the necessary changes in SB and physical activity to impact physiological systems and overall health in diverse population groups.

Assessment of the bidirectional causal association between frailty and depression: A Mendelian randomization study

BACKGROUND

Observational studies have demonstrated a strong bidirectional association between frailty and depression, but it remains unclear whether this association reflects causality. This study aimed to examine the bidirectional causal relationship between frailty and depression.

METHODS

Using genome-wide association study summary data, two-sample Mendelian randomization was performed to test for the potential bidirectional causality between frailty, as defined by both the frailty index and the frailty phenotype, and depression. Several frailty-related traits were additionally investigated, including weaker hand grip strength, slower walking pace and physical inactivity. Findings were replicated using an independent depression data source and verified using multiple sensitivity analyses.

RESULTS

Genetically predicted higher frailty index (odds ratio [OR], 1.86; P < 0.001), higher frailty phenotype score (OR, 2.79; P < 0.001), lower grip strength (OR, 1.23; P = 0.003), slower walking pace (OR, 1.55; P = 0.027) and physical inactivity (OR, 1.44; P = 0.003) all were associated with a higher risk of depression. As for the reverse direction, genetic liability to depression showed consistent associations with a higher frailty index (beta, 0.167; P < 0.001) and a higher frailty phenotype score (beta, 0.067; P = 0.001), but not with other frailty-related traits that were investigated. The results were stable across sensitivity analyses and across depression datasets.

CONCLUSIONS

Our findings add novel evidence supporting the bidirectional causal association between frailty and depression. Improving balance and muscle strength and increasing physical activity may be beneficial in both depression and frailty.

The Association of Physical Activity with Glaucoma and Related Traits in the UK Biobank

PURPOSE

To examine the association of physical activity (PA) with glaucoma and related traits, to assess whether genetic predisposition to glaucoma modified these associations, and to probe causal relationships using Mendelian randomization (MR).

DESIGN

Cross-sectional observational and gene-environment interaction analyses in the UK Biobank. Two-sample MR experiments using summary statistics from large genetic consortia.

PARTICIPANTS

UK Biobank participants with data on self-reported or accelerometer-derived PA and intraocular pressure (IOP; n = 94 206 and n = 27 777, respectively), macular inner retinal OCT measurements (n = 36 274 and n = 9991, respectively), and glaucoma status (n = 86 803 and n = 23 556, respectively).

METHODS

We evaluated multivariable-adjusted associations of self-reported (International Physical Activity Questionnaire) and accelerometer-derived PA with IOP and macular inner retinal OCT parameters using linear regression and with glaucoma status using logistic regression. For all outcomes, we examined gene-PA interactions using a polygenic risk score (PRS) that combined the effects of 2673 genetic variants associated with glaucoma.

MAIN OUTCOME MEASURES

Intraocular pressure, macular retinal nerve fiber layer (mRNFL) thickness, macular ganglion cell-inner plexiform layer (mGCIPL) thickness, and glaucoma status.

RESULTS

In multivariable-adjusted regression models, we found no association of PA level or time spent in PA with glaucoma status. Higher overall levels and greater time spent in higher levels of both self-reported and accelerometer-derived PA were associated positively with thicker mGCIPL (P < 0.001 for trend for each). Compared with the lowest quartile of PA, participants in the highest quartiles of accelerometer-derived moderate- and vigorous-intensity PA showed a thicker mGCIPL by +0.57 μm (P < 0.001) and +0.42 μm (P = 0.005). No association was found with mRNFL thickness. High overall level of self-reported PA was associated with a modestly higher IOP of +0.08 mmHg (P = 0.01), but this was not replicated in the accelerometry data. No associations were modified by a glaucoma PRS, and MR analyses did not support a causal relationship between PA and any glaucoma-related outcome.

CONCLUSIONS

Higher overall PA level and greater time spent in moderate and vigorous PA were not associated with glaucoma status but were associated with thicker mGCIPL. Associations with IOP were modest and inconsistent. Despite the well-documented acute reduction in IOP after PA, we found no evidence that high levels of habitual PA are associated with glaucoma status or IOP in the general population.

FINANCIAL DISCLOSURE(S)

Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

A General Approach to Adjusting Genetic Studies for Assortative Mating

The effects of assortative mating (AM) on estimates from genetic studies has been receiving increasing attention in recent years. We extend existing AM theory to more general models of sorting and conclude that correct theory-based AM adjustments require knowledge of complicated, unknown historical sorting patterns. We propose a simple, general-purpose approach using polygenic indexes (PGIs). Our approach can estimate the fraction of genetic variance and genetic correlation that is driven by AM. Our approach is less effective when applied to Mendelian randomization (MR) studies for two reasons: AM can induce a form of selection bias in MR studies that remains after our adjustment; and, in the MR context, the adjustment is particularly sensitive to PGI estimation error. Using data from the UK Biobank, we find that AM inflates genetic correlation estimates between health traits and education by 14% on average. Our results suggest caution in interpreting genetic correlations or MR estimates for traits subject to AM.

GWAS of random glucose in 476,326 individuals provide insights into diabetes pathophysiology, complications and treatment stratification

Conventional measurements of fasting and postprandial blood glucose levels investigated in genome-wide association studies (GWAS) cannot capture the effects of DNA variability on 'around the clock' glucoregulatory processes. Here we show that GWAS meta-analysis of glucose measurements under nonstandardized conditions (random glucose (RG)) in 476,326 individuals of diverse ancestries and without diabetes enables locus discovery and innovative pathophysiological observations. We discovered 120 RG loci represented by 150 distinct signals, including 13 with sex-dimorphic effects, two cross-ancestry and seven rare frequency signals. Of these, 44 loci are new for glycemic traits. Regulatory, glycosylation and metagenomic annotations highlight ileum and colon tissues, indicating an underappreciated role of the gastrointestinal tract in controlling blood glucose. Functional follow-up and molecular dynamics simulations of lower frequency coding variants in glucagon-like peptide-1 receptor (GLP1R), a type 2 diabetes treatment target, reveal that optimal selection of GLP-1R agonist therapy will benefit from tailored genetic stratification. We also provide evidence from Mendelian randomization that lung function is modulated by blood glucose and that pulmonary dysfunction is a diabetes complication. Our investigation yields new insights into the biology of glucose regulation, diabetes complications and pathways for treatment stratification.

Associations of polygenic inheritance of physical activity with aerobic fitness, cardiometabolic risk factors and diseases: the HUNT study

Physical activity (PA), aerobic fitness, and cardiometabolic diseases (CMD) are highly heritable multifactorial phenotypes. Shared genetic factors may underlie the associations between higher levels of PA and better aerobic fitness and a lower risk for CMDs. We aimed to study how PA genotype associates with self-reported PA, aerobic fitness, cardiometabolic risk factors and diseases. PA genotype, which combined variation in over one million of gene variants, was composed using the SBayesR polygenic scoring methodology. First, we constructed a polygenic risk score for PA in the Trøndelag Health Study (N = 47,148) using UK Biobank single nucleotide polymorphism-specific weights (N = 400,124). The associations of the PA PRS and continuous variables were analysed using linear regression models and with CMD incidences using Cox proportional hazard models. The results showed that genotypes predisposing to higher amount of PA were associated with greater self-reported PA (Beta [B] = 0.282 MET-h/wk per SD of PRS for PA, 95% confidence interval [CI] = 0.211, 0.354) but not with aerobic fitness. These genotypes were also associated with healthier cardiometabolic profile (waist circumference [B = -0.003 cm, 95% CI = -0.004, -0.002], body mass index [B = -0.002 kg/m2, 95% CI = -0.004, -0.001], high-density lipoprotein cholesterol [B = 0.004 mmol/L, 95% CI = 0.002, 0.006]) and lower incidence of hypertensive diseases (Hazard Ratio [HR] = 0.97, 95% CI = 0.951, 0.990), stroke (HR = 0.94, 95% CI = 0.903, 0.978) and type 2 diabetes (HR = 0.94, 95 % CI = 0.902, 0.970). Observed associations were independent of self-reported PA. These results support earlier findings suggesting small pleiotropic effects between PA and CMDs and provide new evidence about associations of polygenic inheritance of PA and intermediate cardiometabolic risk factors.

Gene-Environment Interplay in the Development of Overweight

PURPOSE

Overweight in youth is influenced by genes and environment. Gene-environment interaction (G×E) has been demonstrated in twin studies and recent developments in genetics allow for studying G×E using individual genetic predispositions for overweight. We examine genetic influence on trajectories of overweight during adolescence and early adulthood and determine whether genetic predisposition is attenuated by higher socioeconomic status and having physically active parents.

METHODS

Latent class growth models of overweight were fitted using data from the TRacking Adolescents' Individual Lives Survey (n = 2720). A polygenic score for body mass index (BMI) was derived using summary statistics from a genome-wide association study of adult BMI (N = ∼700,000) and tested as predictor of developmental pathways of overweight. Multinomial logistic regression models were used to examine effects of interactions of genetic predisposition with socioeconomic status and parental physical activity (n = 1675).

RESULTS

A three-class model of developmental pathways of overweight fitted the data best ("non-overweight", "adolescent-onset overweight", and "persistent overweight"). The polygenic score for BMI and socioeconomic status distinguished the persistent overweight and adolescent-onset overweight trajectories from the non-overweight trajectory. Only genetic predisposition differentiated the adolescent-onset from the persistent overweight trajectory. There was no evidence for G×E.

DISCUSSION

Higher genetic predisposition increased the risk of developing overweight during adolescence and young adulthood and was associated with an earlier age at onset. We did not find that genetic predisposition was offset by higher socioeconomic status or having physically active parents. Instead, lower socioeconomic status and higher genetic predisposition acted as additive risk factors for developing overweight.

The causal effects of leisure screen time on irritable bowel syndrome risk from a Mendelian randomization study

Associations between leisure sedentary behavior (especially leisure screen time, LST) and irritable bowel syndrome (IBS) have been reported, but causality is unclear. Here, the two-sample Mendelian randomization was performed to investigate the causal association between LST and IBS. Two recently published genome-wide association studies (GWASs) including a total of 1,190,502 people from Europe were used as our data source. Inverse variance weighting (OR = 1.120, 95% CI 1.029-1.219) and weighted median (OR = 1.112, 95% CI 1.000-1.236) analyses revealed a causal effect between LST and IBS. There was no evidence of pleiotropy in the sensitive analysis (MR-Egger, p = 0.139). After removing potentially confounding single nucleotide polymorphisms (SNPs), similar results were found using inverse variance weighting (OR = 1.131, 95% CI 1.025-1.248) and weighted median (OR = 1.151, 95% CI 1.020-1.299), as well as in the validation analyses using inverse variance weighting (OR = 1.287, 95% CI 0.996-1.662). This study provided support for a possible causal relationship between leisure screen time and IBS.

Genetically predicted effects of physical activity and sedentary behavior on myasthenia gravis: evidence from mendelian randomization study

BACKGROUND

Myasthenia gravis (MG) is an autoimmune disorder affecting the neuromuscular junction. Despite the potential benefits of higher physical activity and lower sedentary behavior in MG patients, evidence from observational studies for the effect of physical activity on the risk of MG is limited and inconclusive.

METHODS

We employed linkage disequilibrium score (LDSC) regression, two-sample Mendelian randomization (MR), and its multivariable extension analyses (MVMR) to assess the relationship between leisure screen time (LST), moderate-to-vigorous intensity physical activity during leisure time (MVPA) and the risk of MG using genome-wide association studies (GWAS) summary datasets. MR analyses were performed using the inverse-variance-weighted (IVW), weighted-median, and MR-Egger regression. Sensitivity analyses were further performed using alternative instruments to test the robustness of our findings.

RESULTS

We found evidence of genetic overlap between LST (rg = 0.113, P = 0.023) and MG, as well as between MVPA (rg=-0.220, P = 0.0001) and MG, using LDSC method. The results of the MR suggested an association between genetic liability to LST and increased risk of MG (IVW OR = 1.609, 95% CI = 1.153 to 2.244; P = 0.005). This association was particularly notable for late-onset MG (IVW OR = 1.698, 95% CI = 1.145 to 2.518; P = 0.008), but not for early-onset MG. Consistent findings were obtained in the MVMR analysis using BMI as covariate (IVW OR = 1.593, 95% CI 1.167 to 2.173, P = 0.003). However, the MR analysis does not support a substantial causal effect of MVPA on the risk of MG.

CONCLUSION

Our findings support a causal effect of sedentary behavior as measured by LST on MG, indicating that lack of exercise may play a role in the development of MG. Longitudinal and interventional studies of this association are warranted.

Intersecting Pathways in Bioinformatics and Translational Informatics: A One Health Perspective on Key Contributions and Future Directions

OBJECTIVES

To identify and summarize the top bioinformatics and translational informatics (BTI) papers published in 2022 for the International Medical Informatics Association (IMIA) Yearbook 2023.

METHODS

We conducted a comprehensive literature search to identify the top BTI papers, resulting in a set of ten candidate papers. The candidates were reviewed by the section co-editors and external reviewers to select the top three papers from 2022.

RESULTS

From a total of 558 papers, we identified a final candidate list of ten BTI papers for peer-review. These papers apply new statistical frameworks and experimental designs to better capture individual variability in disease and incorporate data that captures differences between single cells and across environmental exposures. In addition, they highlight the importance of model generalization across diverse cohorts and scalability to large medical centers.

CONCLUSIONS

We note several important trends in the candidate top BTI papers this year, including a continued focus on developing accurate and scalable computational models to predict disease risk across diverse cohorts and new strategies to capture the molecular heterogeneity of disease.

The causality of physical activity status and intelligence: A bidirectional Mendelian randomization study

BACKGROUND

Observational studies suggest physical activity (PA) enhances intelligence, while sedentary behavior (SB) poses a risk. However, causality remains unclear.

METHODS

We extracted genetic instruments from large genome-wide association studies summary data and employed an inverse-variance weighted (IVW) approach within a random-effects model as the primary method of Mendelian randomization (MR) analysis to estimate the overall effect of various physical activity statuses on intelligence. To assess IVW stability and MR sensitivity, we also utilized supplementary methods including weighted median, MR-Egger, and MR-PRESSO. Furthermore, multivariable MR analysis was conducted to examine the independent effects of each physical activity trait on intelligence.

RESULTS

The MR primary results indicated that LST was negatively associated with intelligence (β = -0.133, 95%CI: -0.177 to -0.090, p = 1.34×10-9), while SBW (β = 0.261, 95% CI: 0.059 to 0.463, p = 0.011) may have a positive effect on intelligence; however, MVPA and SC did not show significant effects on intelligence. Inverse causality analyses demonstrated intelligence significantly influenced all physical activity states.

CONCLUSIONS

Our study highlights a bidirectional causal relationship between physical activity states and intelligence.

Physical Exercise and Appetite Regulation: New Insights

Physical exercise is considered an important physiological intervention able to prevent cardiovascular diseases, obesity, and obesity-related cardiometabolic imbalance. Nevertheless, basic molecular mechanisms that govern the metabolic benefits of physical exercise are poorly understood. Recent data unveil new mechanisms that potentially explain the link between exercise, feeding suppression, and obesity.