Association of physical activity and sedentary behavior with type 2 diabetes and glycemic traits: a two-sample Mendelian randomization study

Physical activity and the risk of developing 8 age-related diseases: epidemiological and Mendelian randomization studies

BACKGROUND

We aimed to characterize the associations between physical activity levels and the risk of developing age-related diseases in the Coronary Artery Risk Development in Young Adults (CARDIA) study and used Mendelian randomization (MR) to assess whether there are causal relationships between physical activity levels and the risk of developing 8 age-related diseases (coronary atherosclerosis, ischemic heart disease, angina, Alzheimer's disease, hypertension, type 2 diabetes, hyperlipidemia, and venous thromboembolism).

METHODS

Based on the data available in the CARDIA, we obtained data related to five disease states: coronary heart disease, hypertension, diabetes, hyperlipidemia, and venous thromboembolism. Binary logistic regression analysis estimated the multivariable-adjusted associations between different physical activity statuses and diseases. For the MR study, we used summary-level data from a recently published genome-wide association study on physical activity (including vigorous physical activity and accelerometer-based physical activity) conducted with participants from the UK Biobank study. We selected the above 8 age-related diseases as our outcomes.

RESULTS

In the CARDIA-based analysis, the risk of developing coronary heart disease [OR (95% CI): 0.562 (0.397-0.795)], hypertension [OR (95% CI): 0.703 (0.601-0.821)], diabetes [OR (95% CI): 0.783 (0.620-0.988)], and hyperlipidemia [OR (95% CI): 0.792 (0.662-0.949)] was negatively related to physical activity status when participants achieved the physical activity target. Our MR results support a negative causal association between genetically determined vigorous physical activity levels and the risk of developing 3 age-related diseases, namely, angina, hypertension and type 2 diabetes. Moreover, our results also support a negative causal association between genetically determined accelerometer-based physical activity levels and the risk of developing angina.

CONCLUSIONS

Promotion of physical activity is likely to prevent specific age-related diseases.

Causal Association Between Sedentary Behaviors and Health Outcomes: A Systematic Review and Meta-Analysis of Mendelian Randomization Studies

BACKGROUND

Different types of sedentary behavior are associated with several health outcomes, but the causality of these associations remains unclear.

OBJECTIVES

To conduct a systematic review and meta-analysis of Mendelian randomization (MR) studies investigating the associations between sedentary behaviors and health outcomes.

METHODS

A systematic search on PubMed, Embase, Web of Science, Scopus, and PsycINFO up to August 2023 was conducted to identify eligible MR studies. We selected studies that assessed associations of genetically determined sedentary behaviors and health outcomes. A meta-analysis was conducted to examine the causal associations when two or more MR studies were available. We graded the evidence level of each MR association based on the results of the main method and sensitivity analyses in MR studies.

RESULTS

A total of 31 studies with 168 MR associations between six types of sedentary behavior and 47 health outcomes were included. Results from meta-analyses suggested a total of 47 significant causal associations between sedentary behaviors and health outcomes. Notably, more leisure TV watching is robustly correlated with increased risks of myocardial infarction, coronary artery disease, all-cause ischemic stroke, and type 2 diabetes. Conversely, robust inverse associations were observed between leisure computer use and risks of rheumatoid arthritis, Alzheimer's disease, and gastroesophageal reflux disease.

CONCLUSION

These findings suggest that different types of sedentary behavior have distinct causal effects on health outcomes. Therefore, interventions should focus not only on reducing sedentary time but also on promoting healthier types of sedentary behavior.

PROSPERO REGISTRATION

CRD42023453828.

Iron, copper, zinc and magnesium on rheumatoid arthritis: a two-sample Mendelian randomization study

This study aimed to elucidate the causal genetic relationships between iron, copper, zinc, magnesium, and rheumatoid arthritis (RA). A two-sample Mendelian randomization (MR) analysis was conducted using the "TwoSampleMR" and "MendelianRandomization" packages in R. The random-effects inverse variance-weighted (IVW) method was used as the primary approach. We performed sensitivity analyses to test the reliability of the results. The random-effects IVW analysis revealed that there was no genetic causal relationship between iron (P = 0.429, odds ratio [OR] 95% confidence interval [CI] = 0.919 [0.746-1.133]), copper (P = 0.313, OR 95% CI = 0.973 [0.921-1.027]), zinc (P = 0.633, OR 95% CI = 0.978 [0.891-1.073]), or magnesium (P = 0.218, OR 95% CI = 0.792 [0.546-1.148]) and RA. Sensitivity analysis verified the reliability of the results. Therefore, there is no evidence to support a causal relationship between iron, copper, zinc, and magnesium intake at the genetic level and the development of RA.

Rheumatoid arthritis increases the risk of malignant neoplasm of bone and articular cartilage: a two-sample bidirectional mendelian randomization study

OBJECTIVE

Prior research has revealed a heightened prevalence of neoplasms in individuals diagnosed with rheumatoid arthritis (RA). The primary objective of this study is to delve into the causal association between RA and two distinct types of neoplasms: benign neoplasm of bone and articular cartilage (BNBAC) and malignant neoplasm of bone and articular cartilage (MNBAC).

METHODS

We employed summary data from genome-wide association analyses (GWAS) to investigate the causal relationship between RA and two neoplasms, BNBAC and MNBAC, using a two-sample bidirectional Mendelian randomization (MR) study design. The IEU OpenGWAS database provided the GWAS summary data for RA, while the Finnish consortium supplied the GWAS summary data for BNBAC and MNBAC. Our analysis involved the utilization of eight distinct MR methods, namely random-effects inverse variance weighted (IVW), MR Egger, weighted median, simple mode, weighted mode, maximum likelihood, penalized weighted median, and fixed effects IVW. Subsequently, we conducted assessments to evaluate heterogeneity, horizontal pleiotropy, outliers, the impact of a single-nucleotide polymorphism (SNP), and adherence to the assumption of normal distribution in the MR analysis.

RESULTS

The results from the MR analysis revealed that there was no significant genetic association between RA and BNBAC (P = 0.427, odds ratio [OR] 95% confidence interval [CI] = 0.971 [0.904-1.044]). However, a positive genetic association was observed between RA and MNBAC (P = 0.001, OR 95% CI = 1.413 [1.144-1.745]). Conducting a reverse MR analysis, we found no evidence to support a genetic causality between BNBAC (P = 0.088, OR 95% CI = 1.041 [0.994-1.091]) or MNBAC (P = 0.168, OR 95% CI = 1.013 [0.995-1.031]) and RA. Our MR analysis demonstrated the absence of heterogeneity, horizontal pleiotropy, and outliers and confirmed that the effect was not driven by a single SNP. Additionally, the data exhibited a normal distribution.

CONCLUSION

The findings of this study demonstrate that RA constitutes a significant risk factor for MNBAC. In the context of clinical application, it is advisable to conduct MNBAC screening in RA patients and remain vigilant regarding its potential manifestation. Importantly, the outcomes of this investigation introduce a fresh vantage point into the understanding of the tumorigenesis associated with RA.

Causal association of physical activity with low back pain, intervertebral disc degeneration and sciatica: a two-sample mendelian randomization analysis study

Objective: Previous studies are insufficient to confirm a causal association between physical activity (PA) and low back pain (LBP), intervertebral disc degeneration (IDD), and sciatica. The present study used a two-sample Mendelian randomization (MR) analysis method to demonstrate whether or not there was a causal connection. Methods: First, four PA phenotypes were selected [accelerometer-based PA (average acceleration), accelerometer-based PA (acceleration fraction >425 mg), self-reported moderate-to-vigorous PA, and self-reported vigorous PA], setting thresholds for single nucleotide polymorphisms (SNPs) significantly concerned with PA p < 5 × 10-8, linkage disequilibrium (LD) r 2 < 0.01, genetic distance >5,000 kb, and F-value >10. SNPs associated with the outcome and confounding factors were then excluded using the PhenoScanncer database. Finally, after coordinating the genetic instruments from genome-wide association studies (GWAS) effect alleles for exposure and outcomes, multiplicative random effects inverse variance weighting (IVW), MR-Egger, weighted median method (WMM), and weighted mode method were used to assess exposure-outcome causality and perform sensitivity analysis on the estimated results. Results: The current study's IVW findings revealed proof of a causal connection between PA and LBP. While there was a positive causal tie between accelerometer-based PA (acceleration fraction >425 mg) and LBP [OR: 1.818, 95% CI:1.129-2.926, p = 0.012], there was a negative causal link between accelerometer-based PA (average acceleration) and LBP [OR: 0.945, 95% CI: 0.909-0.984, p = 0.005]. However causal relationship between PA and IDD or sciatica was not found. Conclusion: Increasing average PA but needing to avoid high-intensity PA may be an effective means of preventing low back pain. Although PA is not directly causally related to disc degeneration and sciatica, it can act through indirect pathways.

Systematic comparison of Mendelian randomisation studies and randomised controlled trials using electronic databases

OBJECTIVE

To scope the potential for (semi)-automated triangulation of Mendelian randomisation (MR) and randomised controlled trials (RCTs) evidence since the two methods have distinct assumptions that make comparisons between their results invaluable.

METHODS

We mined ClinicalTrials.Gov, PubMed and EpigraphDB databases and carried out a series of 26 manual literature comparisons among 54 MR and 77 RCT publications.

RESULTS

We found that only 13% of completed RCTs identified in ClinicalTrials.Gov submitted their results to the database. Similarly low coverage was revealed for Semantic Medline (SemMedDB) semantic triples derived from MR and RCT publications -36% and 12%, respectively. Among intervention types that can be mimicked by MR, only trials of pharmaceutical interventions could be automatically matched to MR results due to insufficient annotation with Medical Subject Headings ontology. A manual survey of the literature highlighted the potential for triangulation across a number of exposure/outcome pairs if these challenges can be addressed.

CONCLUSIONS

We conclude that careful triangulation of MR with RCT evidence should involve consideration of similarity of phenotypes across study designs, intervention intensity and duration, study population demography and health status, comparator group, intervention goal and quality of evidence.

Physical Activity, Sedentary Behavior, and Type 2 Diabetes: Mendelian Randomization Analysis

Context

The causality and pathways of the associations between physical activity and inactivity and the risk of type 2 diabetes remain inconclusive.

Objective

We conducted an updated mendelian randomization (MR) study to explore the associations of moderate-to-vigorous physical activity (MVPA) and leisure screen time (LST) with type 2 diabetes mellitus (T2DM).

Methods

Genetic variants strongly associated with MVPA or LST with low linkage disequilibrium were selected as instrumental variables from a genome-wide meta-analysis including more than 600 000 individuals. Summary-level data on T2DM were obtained from the DIAbetes Genetics Replication And Meta-analysis consortium including 898 130 individuals. Data on possible intermediates (adiposity indicators, lean mass, glycemic traits, and inflammatory biomarkers) were extracted from large-scale genome-wide association studies (n = 21 758-681 275). Univariable and multivariable MR analyses were performed to estimate the total and direct effects of MVPA and LST on T2DM. Methylation MR analysis was performed for MVPA in relation to diabetes.

Results

The odds ratio of T2DM was 0.70 (95% CI, 0.55-0.88; P = .002) per unit increase in the log-odds ratio of having MVPA and 1.45 (95% CI, 1.30-1.62; P = 7.62 × 10-11) per SD increase in genetically predicted LST. These associations attenuated in multivariable MR analyses adjusted for genetically predicted waist-to-hip ratio, body mass index, lean mass, and circulating C-reactive protein. The association between genetically predicted MVPA and T2DM attenuated after adjusting for genetically predicted fasting insulin levels. Two physical activity-related methylation biomarkers (cg17332422 in ADAMTS2 and cg09531019) were associated with the risk of T2DM (P < .05).

Conclusion

The study suggests causal associations of MVPA and LST with T2DM that appear to be mediated by obesity, lean mass, and chronic low-grade inflammation.

Causal factors underlying diabetes risk informed by Mendelian randomisation analysis: evidence, opportunities and challenges

Diabetes and its complications cause a heavy disease burden globally. Identifying exposures, risk factors and molecular processes causally associated with the development of diabetes can provide important evidence bases for disease prevention and spur novel therapeutic strategies. Mendelian randomisation (MR), an epidemiological approach that uses genetic instruments to infer causal associations between an exposure and an outcome, can be leveraged to complement evidence from observational and clinical studies. This narrative review aims to summarise the evidence on potential causal risk factors for diabetes by integrating published MR studies on type 1 and 2 diabetes, and to reflect on future perspectives of MR studies on diabetes. Despite the genetic influence on type 1 diabetes, few MR studies have been conducted to identify causal exposures or molecular processes leading to increased disease risk. In type 2 diabetes, MR analyses support causal associations of somatic, mental and lifestyle factors with development of the disease. These studies have also identified biomarkers, some of them derived from the gut microbiota, and molecular processes leading to increased disease risk. These studies provide valuable data to better understand disease pathophysiology and explore potential therapeutic targets. Because genetic association studies have mostly been restricted to participants of European descent, multi-ancestry cohorts are needed to examine the role of different types of physical activity, dietary components, metabolites, protein biomarkers and gut microbiome in diabetes development.

Association of physical activity with metabolic profile from adolescence to adulthood

OBJECTIVE

Physical activity benefits cardiometabolic health, but little is known about its detailed links with serum lipoproteins, amino acids, and glucose metabolism at young age. We therefore studied the association of physical activity with a comprehensive metabolic profile measured repeatedly in adolescence.

METHODS

The cohort is derived from the longitudinal Special Turku Coronary Risk Factor Intervention Project. At ages 13, 15, 17, and 19 years, data on physical activity were collected by a questionnaire, and circulating metabolic measures were quantified by nuclear magnetic resonance metabolomics from repeatedly assessed serum samples (age 13: n = 503, 15: n = 472, 17: n = 466, and 19: n = 361).

RESULTS

Leisure-time physical activity (LTPA;MET h/wk) was directly associated with concentrations of polyunsaturated fatty acids, and inversely with the ratio of monounsaturated fatty acids to total fatty acids (-0.006SD; [-0.008, -0.003]; p < 0.0001). LTPA was inversely associated with very-low-density lipoprotein (VLDL) particle concentration (-0.003SD; [-0.005, -0.001]; p = 0.002) and VLDL particle size (-0.005SD; [-0.007, -0.003]; p < 0.0001). LTPA showed direct association with the particle concentration and size of high-density lipoprotein (HDL), and HDL cholesterol concentration (0.004SD; [0.002, 0.006]; p < 0.0001). Inverse associations of LTPA with triglyceride and total lipid concentrations in large to small sized VLDL subclasses were found. Weaker associations were seen for other metabolic measures including inverse associations with concentrations of lactate, isoleucine, glycoprotein acetylation, and a direct association with creatinine concentration. The results remained after adjusting for body mass index and proportions of energy intakes from macronutrients.

CONCLUSIONS

Physical activity during adolescence is beneficially associated with the metabolic profile including novel markers. The results support recommendations on physical activity during adolescence to promote health and possibly reduce future disease risks.

Genetic causal relationship between age at menarche and benign oesophageal neoplasia identified by a Mendelian randomization study

OBJECTIVE

The occurrence and development of oesophageal neoplasia (ON) is closely related to hormone changes. The aim of this study was to investigate the causal relationships between age at menarche (AAMA) or age at menopause (AAMO) and benign oesophageal neoplasia (BON) or malignant oesophageal neoplasia (MON) from a genetic perspective.

METHODS

Genome-wide association study (GWAS) summary data of exposures (AAMA and AAMO) and outcomes (BON and MON) were obtained from the IEU OpenGWAS database. We performed a two-sample Mendelian randomization (MR) study between them. The inverse variance weighted (IVW) was used as the main analysis method, while the MR Egger, weighted median, simple mode, and weighted mode were supplementary methods. The maximum likelihood, penalized weighted median, and IVW (fixed effects) were validation methods. We used Cochran's Q statistic and Rucker's Q statistic to detect heterogeneity. The intercept test of the MR Egger and global test of MR pleiotropy residual sum and outlier (MR-PRESSO) were used to detect horizontal pleiotropy, and the distortion test of the MR-PRESSO analysis was used to detect outliers. The leave-one-out analysis was used to detect whether the MR analysis was affected by single nucleotide polymorphisms (SNPs). In addition, the MR robust adjusted profile score (MR-RAPS) method was used to assess the robustness of MR analysis.

RESULTS

The random-effects IVW results showed that AAMA had a negative genetic causal relationship with BON (odds ratio [OR] = 0.285 [95% confidence interval [CI]: 0.130-0.623], P = 0.002). The weighted median, maximum likelihood, penalized weighted median, and IVW (fixed effects) were consistent with random-effects IVW (P < 0.05). The MR Egger, simple mode and weighted mode results showed that AAMA had no genetic causal relationship with BON (P > 0.05). However, there were no causal genetic relationships between AAMA and MON (OR = 1.132 [95%CI: 0.621-2.063], P = 0.685), AAMO and BON (OR = 0.989 [95%CI: 0.755-1.296], P = 0.935), or AAMO and MON (OR = 1.129 [95%CI: 0.938-1.359], P = 0.200). The MR Egger, weighted median, simple mode, weighted mode, maximum likelihood, penalized weighted median, and IVW (fixed effects) were consistent with a random-effects IVW (P > 0.05). MR analysis results showed no heterogeneity, the horizontal pleiotropy and outliers (P > 0.05). They were not driven by a single SNP, and were normally distributed (P > 0.05).

CONCLUSION

Only AAMA has a negative genetic causal relationship with BON, and no genetic causal relationships exist between AAMA and MON, AAMO and BON, or AAMO and MON. However, it cannot be ruled out that they are related at other levels besides genetics.

Exercise sustains the hallmarks of health

Exercise has long been known for its active role in improving physical fitness and sustaining health. Regular moderate-intensity exercise improves all aspects of human health and is widely accepted as a preventative and therapeutic strategy for various diseases. It is well-documented that exercise maintains and restores homeostasis at the organismal, tissue, cellular, and molecular levels to stimulate positive physiological adaptations that consequently protect against various pathological conditions. Here we mainly summarize how moderate-intensity exercise affects the major hallmarks of health, including the integrity of barriers, containment of local perturbations, recycling and turnover, integration of circuitries, rhythmic oscillations, homeostatic resilience, hormetic regulation, as well as repair and regeneration. Furthermore, we summarize the current understanding of the mechanisms responsible for beneficial adaptations in response to exercise. This review aimed at providing a comprehensive summary of the vital biological mechanisms through which moderate-intensity exercise maintains health and opens a window for its application in other health interventions. We hope that continuing investigation in this field will further increase our understanding of the processes involved in the positive role of moderate-intensity exercise and thus get us closer to the identification of new therapeutics that improve quality of life.

Diet, Lifestyle Behaviours and Other Risk Factors Associated With Type 2 Diabetes Beyond Body Mass Index: A Mendelian Randomization Study

OBJECTIVES

Our aim in this study was to identify promising targets for the prevention of type 2 diabetes in addition to weight loss. We conducted a Mendelian randomization (MR) study to investigate the body mass index (BMI)-independent associations of 16 risk factors, including diet, lifestyle behaviours and others, with type 2 diabetes.

METHODS

We selected genetic variants as instrumental variables for diet, sleep traits, smoking, physical activity, education and blood pressure (BP) from European-descent genome-wide association studies (GWASs). Summary statistics for type 2 diabetes were derived from a recent GWAS with 74,124 European cases and 824,006 European controls. The inverse-variance weighted MR method was used to assess the associations of the risk factors with type 2 diabetes, followed by validation of robustness using different MR methods in sensitivity analyses.

RESULTS

Genetically predicted insomnia (odds ratio [OR], 1.10; 95% confidence interval [CI], 1.06 to 1.15), smoking initiation (OR, 1.14; 95% CI, 1.06 to 1.21), educational level (OR, 0.69; 95% CI, 0.65 to 0.74), hypertension (OR, 6.50; 95% CI, 3.13 to 13.50), systolic BP (OR, 1.02; 95% CI, 1.02 to 1.03) and diastolic BP (OR, 1.03; 95% CI, 1.02 to 1.03) had BMI-independent effects on type 2 diabetes risk. In addition, alcohol dependence (OR, 1.10; 95% CI, 1.05 to 1.16; BMI-adjusted OR, 1.04; 95% CI, 0.98 to 1.09) and vegetarian diet (OR, 0.50; 95% CI, 0.33 to 0.74; BMI-adjusted OR, 0.78; 95% CI, 0.57 to 1.06) appeared to be correlated with type 2 diabetes via a BMI-mediated pathway. Sensitivity analyses further confirmed the relationship between these factors and type 2 diabetes.

CONCLUSIONS

In this systematic MR study, insomnia, smoking, education and BP had BMI-independent causal effects on the risk of type 2 diabetes, whereas alcohol dependence and vegetarian diet were associated with type 2 diabetes through BMI.

Effects of 12-week moderate aerobic exercise on ROCK2 activity, hs-CRP and glycemic index in obese patients with impaired glucose tolerance

BACKGROUND

Obesity is a chronic low-grade inflammatory state that is related to prediabetes, increased Rhoassociated kinase 2 (ROCK2) activity and concentration of high-sensitivity C-reactive protein (hs-CRP). Therefore, the study was conducted to investigate the effects of 12-week moderate aerobic exercise on ROCK2 activity, hs-CRP, glycosylated hemoglobin A1C (HbA1c), and glycemic index in obese patients with impaired glucose tolerance.

METHODS

In a quasi-experimental design with pre and post-test, 42 obese men with prediabetes [mean±SD, age: 44.73 ± 3.30 years, body mass index (BMI): 33.22 ± 2.05 kg/m², HbA1c: 6.29 % ± 0.75] were allocated into two randomized homogeneous groups: Aerobic training group (AT, n=22) or control group (C, n=20). Exercise group performed a moderate aerobic exercise program three sessions per week, 60 minutes per session for 12 weeks. Body mass, BMI, maximal oxygen consumption (VO₂max), serum levels of fasting blood glucose (FBG), insulin, insulin resistance (HOMA-IR), homeostasis model assessment of β-cell function (HOMA-B); HbA1c, hs-CRP, or ROCK2 activity were measured before and after the study period. The data were analyzed using repeated measures ANOVA 2×2 and paired sample t test at a significant level of p < 0.05.

RESULTS

AT caused a significant reduction in body mass (p≤ 0.001), BMI (p= 0.04), HOMA-B (p=0.003), serum levels of FBG (p= 0.002), HbA1c (p= 0.039), hs-CRP (p≤ 0.0001), and ROCK2 activity (p= 0.001). In contrast, in the same group, a significant increase was observed in VO₂max (p= 0.04).

CONCLUSION

The results of this study showed that moderate aerobic exercise was an effective and safe method to prevent type 2 diabetes and cardiovascular diseases in obese men with prediabetes by improving glucose metabolism, reduction of body mass, ROCK2 activity and serum levels of hs-CRP.

Causal Relationships Between Total Physical Activity and Ankylosing Spondylitis: A Mendelian Randomization Study

Background

Currently, there is little literature about the association between physical activity (PA) and the risk of ankylosing spondylitis (AS). The present study aimed to understand the causal relationships between PA and AS.

Methods

We performed two-sample Mendelian randomization (MR) using publicly released genome-wide association studies summary statistics to estimate the causal associations of PA with AS risk. The inverse variance weighted (IVW) method was utilized as primary MR analysis. Furthermore, sensitivity, pleiotropy, and heterogeneity analyses were then conducted to assess the robustness of the findings of the present study.

Results

Results of the IVW analysis suggested a protective relationship between accelerometer-based PA and AS (average acceleration, odds ratio [OR] = 0.9995, 95% CI, 0.9988-0.9999, P = 0.014). On the contrary, there was no causal relationship between accelerometer-based PA (acceleration fraction >425 mg; OR = 0.9981, 95% CI = 0.9936-1.0026, P = 0.402) and AS. Furthermore, there was no significant relationship between self-reported vigorous PA and AS (OR = 1.0005, 95% CI = 0.9875-1.0136, P = 0.943), or even between self-reported moderate-to-vigorous PA and AS (OR = 1.0000, 95% CI, 0.9947-1.0052; P = 0.990).

Conclusions

The use of genetic approach in the present study revealed that total physical activity (TPA) has a protective relationship with AS risk. Furthermore, it was evident that vigorous PA or moderate-to-vigorous physical levels are not causally associated with AS. Therefore, the present study evidently supports the hypothesis that enhancing TPA rather than PA intensity is an effective prevention strategy for AS.

Association between physical activity and insulin resistance using the homeostatic model assessment for insulin resistance independent of waist circumference

Only a few studies have evaluated the relationship between physical activity (PA) and Homeostatic model assessment for insulin resistance (HOMA-IR). Therefore, we aimed to analyze the association between HOMA-IR and PA. We included 280,194 Korean without diabetes who underwent health examinations. The short form of the International Physical Activity Questionnaire was completed. PA level was divided into sedentary, mild PA, and health-enhancing PA (HEPA). The HOMA-IR levels were calculated. Confounding factors including waist circumference were adjusted. The median follow-up duration was 4.13 years. A significant inverse relationship was observed between PA level and HOMA-IR (p < 0.001). Compared with the sedentary group, HOMA-IR was lower in the HEPA group (p < 0.001), even when HEPA group decreased PA level over time (p < 0.001). Mild PA (p < 0.001) or HEPA showed a lower risk of HOMA-IR progression (p < 0.001). Increasing PA or maintaining HEPA was significantly associated with a lower HOMA-IR (p < 0.001), HOMA-IR improvement (p < 0.001), and a lower risk of HOMA-IR progression (p < 0.001). Our findings support the inverse relationship between PA and HOMA-IR in a population without diabetes. PA might improve IR and prevent its progression among populations without diabetes, independent of the waist circumference.

Shared Genetic Basis and Causal Relationship Between Television Watching, Breakfast Skipping and Type 2 Diabetes: Evidence From a Comprehensive Genetic Analysis

Background

Epidemiological investigations have established unhealthy lifestyles, such as excessive leisurely sedentary behavior (especially TV/television watching) and breakfast skipping, increase the risk of type 2 diabetes (T2D), but the causal relationship is unclear. We aimed to understand how single nucleotide variants contribute to the co-occurrence of unhealthy lifestyles and T2D, thereby providing meaningful insights into disease mechanisms.

Methods

Combining summary statistics from genome-wide association studies (GWAS) on TV watching (N = 422218), breakfast skipping (N = 193860) and T2D (N = 159208) in European pedigrees, we conducted comprehensive pairwise genetic analysis, including high-definition likelihood (HDL-method), cross-phenotype association studies (CPASSOC), GWAS-eQTL colocalization analysis and transcriptome-wide association studies (TWAS), to understand the genetic overlap between them. We also performed bidirectional two-sample Mendelian randomization (MR) analysis for causal inference using genetic instrumental variables, and two-step MR mediation analysis was used to assess any effects explained by body mass index, lipid traits and glycemic traits.

Results

HDL-method showed that T2D shared a strong genetic correlation with TV watching (rg = 0.26; P = 1.63×10-29) and skipping breakfast (rg = 0.15; P =2.02×10-6). CPASSOC identifies eight independent SNPs shared between T2D and TV watching, including one novel shared locus. TWAS and CPASSOC showed that shared genes were enriched in lung, esophageal, adipose, and thyroid tissues and highlighted potential shared regulatory pathways for lipoprotein metabolism, pancreatic β-cell function, cellular senescence and multi-mediator factors. MR showed TV watching had a causal effect on T2D (βIVW = 0.629, PIVW = 1.80×10-10), but no significant results were observed between breakfast skipping and T2D. Mediation analysis provided evidence that body mass index, fasting glucose, hemoglobin A1c and high-density lipoprotein are potential factors that mediate the causal relationship between TV and T2D.

Conclusions

Our findings provide strong evidence of shared genetics and causation between TV watching and T2D and facilitate our identification of common genetic architectures shared between them.

Physical activity, sedentary behavior, and the risk of type 2 diabetes: A two-sample Mendelian Randomization analysis in the European population

Physical activity (PA) and sedentary behaviors (SB) have been linked to the risk of type 2 diabetes (T2DM) in observational studies; however, it is unclear whether these associations are causative or confounded. This study intends to use summary genetic data from the UK Biobank and other consortiums in conjunction with the two-sample Mendelian Randomization (MR) approach to solve this problem. The inverse variance weighted (IVW) technique was utilized as the primary analysis, with sensitivity analyses using the MR-Egger, weighted-median, and MR-Pleiotropy RESidual Sum and Outlier (PRESSO) techniques. Inverse associations between self-reported moderate PA (OR: 0.3096, 95% CI: 0.1782-0.5380) and vigorous PA (OR: 0.2747, 95% CI: 0.1390-0.5428) with T2DM risk were found, respectively. However, accelerometer-based PA measurement (average acceleration) was not associated with T2DM risk (OR: 1.0284, 95% CI: 0.9831-1.0758). The time (hours/day) spent watching TV was associated with T2DM risk (OR: 2.3490, 95% CI: 1.9084-2.8915), while the time (hours/day) spent using the computer (OR: 0.8496, 95% CI: 0.7178-1.0056), and driving (OR: 3.0679, 95% CI: 0.8448-11.1415) were not associated with T2DM risk. The sensitivity analysis revealed relationships of a similar magnitude. Our study revealed that more PA and less TV viewing were related to a decreased T2DM risk, and provided genetic support for a causal relationship between PA, TV viewing, and T2DM risk.

Exercise as a drug for glucose management and prevention in type 2 diabetes mellitus

Physical inactivity and sedentary behavior are risk factors for type 2 diabetes mellitus (T2DM). Therefore, physical exercise (PE) together with medical treatment might be considered as a key strategy to counteract T2DM. Glycemic control is a central objective in the prevention and management of T2DM, and PE might be able to substantially affect the processes that determine it. Just like a drug, exercise can be dosed based on the characteristics of the individual to increase its benefits and reduce side effects. In this brief review, the mechanisms underlying the effects of PE on glucose metabolism in muscle are illustrated, and the effects of modulation of the parameters characterizing this atypical "drug" on glucose homeostasis are described.