Genome-wide association analyses identify 143 risk variants and putative regulatory mechanisms for type 2 diabetes

Mendelian Randomization Analysis Supports Causal Effect of Type II Diabetes Mellitus on Onychomycosis

Introduction

Onychomycosis is common among adults with diabetes mellitus (DM). We used two-sample Mendelian randomization to estimate the causal effect of genetic risk for DM on onychomycosis and tinea skin infections in the All of Us Research Program.

Methods

Onychomycosis and tinea corporis, pedis, manus, and cruris cases were identified using electronic health record data, and genetic instrument variables and summary statistics were collected from a type II DM (T2DM) genome-wide association study (GWAS) meta-analysis.

Results

Inverse variance weighted regression showed positive effect of T2DM genetic risk on onychomycosis (beta = 0.135, p = 1.86E-2), and weighted median regression produced a comparable estimate of effect size (beta = 0.148). There was no significant effect of T2DM on skin dermatophytosis.

Conclusions

Our results suggest that T2DM has a positive causal effect on onychomycosis but not tinea skin infection risk. As onychomycosis may impair occupational function and increase risk for secondary soft tissue infections, patients with diabetes should be screened for onychomycosis and counseled on mitigating infection risk.

Management and Nursing Approaches to Low Back Pain: Investigating the Causal Association with Lifestyle-Related Risk Factors

BACKGROUND

Notwithstanding a plethora of observational studies, the causal implications of obesity, encompassing both body mass index (BMI) and waist circumference (WC), as well as type 2 diabetes (T2D), and lifestyle factors, in relation to the vulnerability to low back pain (LBP), remain enigmatic.

AIMS

This study was designed to investigate the related causal associations DESIGN: A two-sample Mendelian randomization (MR) analysis.

SETTINGS

By utilizing genetic variants associated with pertinent factors gleaned from genome-wide association studies (GWASs), We extracted independent genetic variants about exposures such as BMI, WC, T2D, smoking, alcohol consumption, and coffee intake from published GWASs, ensuring their genome-wide significance.

PARTICIPANTS/SUBJECTS

The GWASs were selected from the most up-to-date and largest publicly accessible databases.

METHODS

The summary data concerning LBP emanated from a GWAS of European cases and controls, which was based on the esteemed MRC-IEU (Medical Research Council Integrative Epidemiology Unit) consortium.

RESULTS

Heightened body mass index and waist circumference exhibited odds ratios of 1.003 (95% confidence interval [CI] = 1.002-1.004, p < 0.001) and 1.003 (95% CI = 1.002-1.004, p < 0.001) for LBP, respectively, per each standard deviation (SD) increase. As for smoking initiation and every SD increase in the frequency of alcohol intake, the odds ratios were 1.002 (95% CI = 1.001-1.003, p = 0.003) and 1.002 (95% CI = 1.000-1.003, p = 0.011), respectively, for LBP. Conversely, an increased log odds ratio for T2D, and prevalence of coffee intake, divulged no discernible causal effects on the risk of LBP.

CONCLUSION

This study provides suggestive evidence to support the causal involvement of obesity, smoking, and the frequency of alcohol intake in the development of LBP, which suggests that implementing measures to mitigate these risk factors may aid in preventing LBP.

Genetically identified mediators associated with increased risk of stroke and cardiovascular disease in individuals with autism spectrum disorder

Growing evidence suggested that individuals with autism spectrum disorder (ASD) associated with stroke and cardiovascular disease (CVD). However, the causal association between ASD and the risk of stroke and CVD remains unclear. To validate this, we performed two-sample Mendelian randomization (MR) and two-step mediation MR analyses, using relevant genetic variants sourced from the largest genome-wide association studies (GWASs). Two-sample MR evidence indicated causal relationships between ASD and any stroke (OR = 1.1184, 95% CI: 1.0302-1.2142, P < 0.01), ischemic stroke (IS) (OR = 1.1157, 95% CI: 1.0237-1.2160, P = 0.01), large-artery atherosclerotic stroke (LAS) (OR = 1.2902, 95% CI: 1.0395-1.6013, P = 0.02), atrial fibrillation (AF) (OR = 1.0820, 95% CI: 1.0019-1.1684, P = 0.04), and heart failure (HF) (OR = 1.1018, 95% CI: 1.0007-1.2132, P = 0.05). Additionally, two-step mediation MR suggested that type 2 diabetes mellitus (T2DM) partially mediated this effect (OR = 1.14, 95%CI: 1.02-1.28, P = 0.03). The mediated proportion were 10.96% (95% CI: 0.58%-12.10%) for any stroke, 11.77% (95% CI: 10.58%-12.97%) for IS, 10.62% (95% CI: 8.04%-13.20%) for LAS, and 7.57% (95% CI: 6.79%-8.36%) for HF. However, no mediated effect was observed between ASD and AF risk. These findings have implications for the development of prevention strategies and interventions for stroke and CVD in patients with ASD.

Genome-wide cross-disease analyses highlight causality and shared biological pathways of type 2 diabetes with gastrointestinal disorders

Studies suggest links between diabetes and gastrointestinal (GI) traits; however, their underlying biological mechanisms remain unclear. Here, we comprehensively assess the genetic relationship between type 2 diabetes (T2D) and GI disorders. Our study demonstrates a significant positive global genetic correlation of T2D with peptic ulcer disease (PUD), irritable bowel syndrome (IBS), gastritis-duodenitis, gastroesophageal reflux disease (GERD), and diverticular disease, but not inflammatory bowel disease (IBD). We identify several positive local genetic correlations (negative for T2D - IBD) contributing to T2D's relationship with GI disorders. Univariable and multivariable Mendelian randomisation analyses suggest causal effects of T2D on PUD and gastritis-duodenitis and bidirectionally with GERD. Gene-based analyses reveal a gene-level genetic overlap between T2D and GI disorders and identify several shared genes reaching genome-wide significance. Pathway-based study implicates leptin (T2D - IBD), thyroid, interferon, and notch signalling (T2D - IBS), abnormal circulating calcium (T2D - PUD), cardiovascular, viral, proinflammatory and (auto)immune-mediated mechanisms in T2D and GI disorders. These findings support a risk-increasing genetic overlap between T2D and GI disorders (except IBD), implicate shared biological pathways with putative causality for certain T2D - GI pairs, and identify targets for further investigation.

Genome-first evaluation with exome sequence and clinical data uncovers underdiagnosed genetic disorders in a large healthcare system

Population-based genomic screening may help diagnose individuals with disease-risk variants. Here, we perform a genome-first evaluation for nine disorders in 29,039 participants with linked exome sequences and electronic health records (EHRs). We identify 614 individuals with 303 pathogenic/likely pathogenic or predicted loss-of-function (P/LP/LoF) variants, yielding 644 observations; 487 observations (76%) lack a corresponding clinical diagnosis in the EHR. Upon further investigation, 75 clinically undiagnosed observations (15%) have evidence of symptomatic untreated disease, including familial hypercholesterolemia (3 of 6 [50%] undiagnosed observations with disease evidence) and breast cancer (23 of 106 [22%]). These genetic findings enable targeted phenotyping that reveals new diagnoses in previously undiagnosed individuals. Disease yield is greater with variants in penetrant genes for which disease is observed in carriers in an independent cohort. The prevalence of P/LP/LoF variants exceeds that of clinical diagnoses, and some clinically undiagnosed carriers are discovered to have disease. These results highlight the potential of population-based genomic screening.

Appendicular lean mass and the risk of stroke and Alzheimer's disease: a mendelian randomization study

BACKGROUND

Appendicular lean mass (ALM) is a good predictive biomarker for sarcopenia. And previous studies have reported the association between ALM and stroke or Alzheimer's disease (AD), however, the causal relationship is still unclear, The purpose of this study was to evaluate whether genetically predicted ALM is causally associated with the risk of stroke and AD by performing Mendelian randomization (MR) analyses.

METHODS

A two-sample MR study was designed. Genetic variants associated with the ALM were obtained from a large genome-wide association study (GWAS) and utilized as instrumental variables (IVs). Summary-level data for stroke and AD were generated from the corresponding GWASs. We used random-effect inverse-variance weighted (IVW) as the main method for estimating causal effects, complemented by several sensitivity analyses, including the weighted median, MR-Egger, and MR-pleiotropy residual sum and outlier (MR-PRESSO) methods. Multivariable analysis was further conducted to adjust for confounding factors, including body mass index (BMI), type 2 diabetes mellitus (T2DM), low density lipoprotein-C (LDL-C), and atrial fibrillation (AF).

RESULTS

The present MR study indicated significant inverse associations of genetically predicted ALM with any ischemic stroke ([AIS], odds ratio [OR], 0.93; 95% confidence interval [CI], 0.89-0.97; P = 0.002) and AD (OR, 090; 95% CI 0.85-0.96; P = 0.001). Regarding the subtypes of AIS, genetically predicted ALM was related to the risk of large artery stroke ([LAS], OR, 0.86; 95% CI 0.77-0.95; P = 0.005) and small vessel stroke ([SVS], OR, 0.80; 95% CI 0.73-0.89; P < 0.001). Regarding multivariable MR analysis, ALM retained the stable effect on AIS when adjusting for BMI, LDL-C, and AF, while a suggestive association was observed after adjusting for T2DM. And the estimated effect of ALM on LAS was significant after adjustment for BMI and AF, while a suggestive association was found after adjusting for T2DM and LDL-C. Besides, the estimated effects of ALM were still significant on SVS and AD after adjustment for BMI, T2DM, LDL-C, and AF.

CONCLUSIONS

The two-sample MR analysis indicated that genetically predicted ALM was negatively related to AIS and AD. And the subgroup analysis of AIS revealed a negative causal effect of genetically predicted ALM on LAS or SVS. Future studies are required to further investigate the underlying mechanisms.

AI-enhanced integration of genetic and medical imaging data for risk assessment of Type 2 diabetes

Type 2 diabetes (T2D) presents a formidable global health challenge, highlighted by its escalating prevalence, underscoring the critical need for precision health strategies and early detection initiatives. Leveraging artificial intelligence, particularly eXtreme Gradient Boosting (XGBoost), we devise robust risk assessment models for T2D. Drawing upon comprehensive genetic and medical imaging datasets from 68,911 individuals in the Taiwan Biobank, our models integrate Polygenic Risk Scores (PRS), Multi-image Risk Scores (MRS), and demographic variables, such as age, sex, and T2D family history. Here, we show that our model achieves an Area Under the Receiver Operating Curve (AUC) of 0.94, effectively identifying high-risk T2D subgroups. A streamlined model featuring eight key variables also maintains a high AUC of 0.939. This high accuracy for T2D risk assessment promises to catalyze early detection and preventive strategies. Moreover, we introduce an accessible online risk assessment tool for T2D, facilitating broader applicability and dissemination of our findings.

Causal relationship between type 2 diabetes mellitus and aortic dissection: insights from two-sample Mendelian randomization and mediation analysis

Objective

Some evidence suggests a reduced prevalence of type 2 diabetes mellitus (T2DM) in patients with aortic dissection (AD), a catastrophic cardiovascular illness, compared to general population. However, the conclusions were inconsistent, and the causal relationship between T2DM and AD remains unclear.

Methods

In this study, we aimed to explore the causal relationship between T2DM and AD using bidirectional Mendelian randomization (MR) analysis. Mediation MR analysis was conducted to explore and quantify the possible mediation effects of 1400 metabolites in T2DM and AD.

Results

The results of 26 datasets showed no causal relationship between T2DM and AD (P>0.05). Only one dataset (ebi-a-GCST90006934) showed that T2DM was a protective factor for AD (I9-AORTDIS) (OR=0.815, 95%CI: 0.692-0.960, P=0.014), and did not show horizontal pleiotropy (P=0.808) and heterogeneity (P=0.525). Vanillic acid glycine plays a mediator in the causal relationship between T2DM and AD. The mediator effect for vanillic acid glycine levels was -0.023 (95%CI: -0.066-0.021).

Conclusion

From the perspective of MR analysis, there might not be a causal relationship between T2DM and AD, and T2DM might not be a protective factor for AD. If a causal relationship does exist between T2DM and AD, with T2DM serving as a protective factor, vanillic acid glycine may act as a mediator and enhance such a protective effect.

Mitochondrial DNA: Inherent Complexities Relevant to Genetic Analyses

Mitochondrial DNA (mtDNA) exhibits distinct characteristics distinguishing it from the nuclear genome, necessitating specific analytical methods in genetic studies. This comprehensive review explores the complex role of mtDNA in a variety of genetic studies, including genome-wide, epigenome-wide, and phenome-wide association studies, with a focus on its implications for human traits and diseases. Here, we discuss the structure and gene-encoding properties of mtDNA, along with the influence of environmental factors and epigenetic modifications on its function and variability. Particularly significant are the challenges posed by mtDNA's high mutation rate, heteroplasmy, and copy number variations, and their impact on disease susceptibility and population genetic analyses. The review also highlights recent advances in methodological approaches that enhance our understanding of mtDNA associations, advocating for refined genetic research techniques that accommodate its complexities. By providing a comprehensive overview of the intricacies of mtDNA, this paper underscores the need for an integrated approach to genetic studies that considers the unique properties of mitochondrial genetics. Our findings aim to inform future research and encourage the development of innovative methodologies to better interpret the broad implications of mtDNA in human health and disease.

Leveraging functional genomic annotations and genome coverage to improve polygenic prediction of complex traits within and between ancestries

We develop a method, SBayesRC, that integrates genome-wide association study (GWAS) summary statistics with functional genomic annotations to improve polygenic prediction of complex traits. Our method is scalable to whole-genome variant analysis and refines signals from functional annotations by allowing them to affect both causal variant probability and causal effect distribution. We analyze 50 complex traits and diseases using ∼7 million common single-nucleotide polymorphisms (SNPs) and 96 annotations. SBayesRC improves prediction accuracy by 14% in European ancestry and up to 34% in cross-ancestry prediction compared to the baseline method SBayesR, which does not use annotations, and outperforms other methods, including LDpred2, LDpred-funct, MegaPRS, PolyPred-S and PRS-CSx. Investigation of factors affecting prediction accuracy identifies a significant interaction between SNP density and annotation information, suggesting whole-genome sequence variants with annotations may further improve prediction. Functional partitioning analysis highlights a major contribution of evolutionary constrained regions to prediction accuracy and the largest per-SNP contribution from nonsynonymous SNPs.

Enhanced resolution profiling in twins reveals differential methylation signatures of type 2 diabetes with links to its complications

BACKGROUND

Type 2 diabetes (T2D) susceptibility is influenced by genetic and environmental factors. Previous findings suggest DNA methylation as a potential mechanism in T2D pathogenesis and progression.

METHODS

We profiled DNA methylation in 248 blood samples from participants of European ancestry from 7 twin cohorts using a methylation sequencing platform targeting regulatory genomic regions encompassing 2,048,698 CpG sites.

FINDINGS

We find and replicate 3 previously unreported T2D differentially methylated CpG positions (T2D-DMPs) at FDR 5% in RGL3, NGB and OTX2, and 20 signals at FDR 25%, of which 14 replicated. Integrating genetic variation and T2D-discordant monozygotic twin analyses, we identify both genetic-based and genetic-independent T2D-DMPs. The signals annotate to genes with established GWAS and EWAS links to T2D and its complications, including blood pressure (RGL3) and eye disease (OTX2).

INTERPRETATION

The results help to improve our understanding of T2D disease pathogenesis and progression and may provide biomarkers for its complications.

FUNDING

Funding acknowledgements for each cohort can be found in the Supplementary Note.

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 underlying causes, treatment options of gut microbiota and food habits in type 2 diabetes mellitus: a narrative review

Type 2 diabetes mellitus is a long-lasting endocrine disorder characterized by persistent hyperglycaemia, which is often triggered by an entire or relative inadequacy of insulin production or insulin resistance. As a result of resistance to insulin (IR) and an overall lack of insulin in the body, type 2 diabetes mellitus (T2DM) is a metabolic illness that is characterized by hyperglycaemia. Notably, the occurrence of vascular complications of diabetes and the advancement of IR in T2DM are accompanied by dysbiosis of the gut microbiota. Due to the difficulties in managing the disease and the dangers of multiple accompanying complications, diabetes is a chronic, progressive immune-mediated condition that plays a significant clinical and health burden on patients. The frequency and incidence of diabetes among young people have been rising worldwide. The relationship between the gut microbiota composition and the physio-pathological characteristics of T2DM proposes a novel way to monitor the condition and enhance the effectiveness of therapies. Our knowledge of the microbiota of the gut and how it affects health and illness has changed over the last 20 years. Species of the genus Eubacterium, which make up a significant portion of the core animal gut microbiome, are some of the recently discovered 'generation' of possibly helpful bacteria. In this article, we have focused on pathogenesis and therapeutic approaches towards T2DM, with a special reference to gut bacteria from ancient times to the present day.

Genome-wide association study and trans-ethnic meta-analysis identify novel susceptibility loci for type 2 diabetes mellitus

BACKGROUND

The genetic basis of type 2 diabetes (T2D) is under-investigated in the Middle East, despite the rapidly growing disease prevalence. We aimed to define the genetic determinants of T2D in Qatar.

METHODS

Using whole genome sequencing of 11,436 participants (2765 T2D cases and 8671 controls) from the population-based Qatar Biobank (QBB), we conducted a genome-wide association study (GWAS) of T2D with and without body mass index (BMI) adjustment.

RESULTS

We replicated 93 known T2D-associated loci in a BMI-unadjusted model, while 96 known loci were replicated in a BMI-adjusted model. The effect sizes and allele frequencies of replicated SNPs in the Qatari population generally concurred with those from European populations. We identified a locus specific to our cohort located between the APOBEC3H and CBX7 genes in the BMI-unadjusted model. Also, we performed a transethnic meta-analysis of our cohort with a previous GWAS on T2D in multi-ancestry individuals (180,834 T2D cases and 1,159,055 controls). One locus in DYNC2H1 gene reached genome-wide significance in the meta-analysis. Assessing polygenic risk scores derived from European- and multi-ancestries in the Qatari population showed higher predictive performance of the multi-ancestry panel compared to the European panel.

CONCLUSION

Our study provides new insights into the genetic architecture of T2D in a Middle Eastern population and identifies genes that may be explored further for their involvement in T2D pathogenesis.

Causal Association Between Diabetes, Body Mass Index and Lichen Sclerosus: A Bidirectional Two-Sample Mendelian Randomization Analysis

Background

Previous observational studies have found that lichen sclerosus (LS) is associated with metabolic statuses, such as diabetes mellitus (DM) and body mass index (BMI). However, there are also some studies showing that LS is not related to DM and BMI. The mechanism behind observational results is still unclear. Therefore, the causality of this relationship remains unknown. In this study, a bidirectional two-sample Mendelian randomization (MR) was conducted to investigate the correlation between DM, BMI, and LS.

Methods

The instrumental variables related to DM (including type 1 and type 2 diabetes), and BMI were identified from genome-wide association studies (GWAS) and a GWAS meta-analysis. The GWAS data for LS was from obtained the eighth edition of the FinnGen biological database released in 2022. Inverse variance weighted (IVW), weighted median, and MR-Egger methods were used to conduct a bidirectional two-sample MR analysis. Thereafter, the heterogeneity and horizontal pleiotropy were examined to determine whether the results were affected by a single-nucleotide polymorphism (SNP).

Results

We found a lack of evidence for the causal association of DM, and BMI on LS in inverse variance weighted (type 1 diabetes, OR=0.97, 95% CI=0.91-1.04, p=0.429; type 2 diabetes, OR=0.91, 95% CI=0.82-1.00, p=0.0511; BMI, OR=0.92, 95% CI=0.73-1.15, p=0.4554). In the other direction, the results also showed that LS had no significant causal effect on DM and BMI.

Conclusion

This MR analysis demonstrated no significant causal relationship between DM and BMI with LS in both directions, which contradicts previous observational studies reporting a positive association. Potential confounding factors may contribute to previously observed associations, and further research is necessary.

Strengthening the Evidence for a Causal Link between Type 2 Diabetes Mellitus and Pancreatic Cancer: Insights from Two-Sample and Multivariable Mendelian Randomization

This two-sample Mendelian randomization (MR) study was conducted to investigate the causal associations between type 2 diabetes mellitus (T2DM) and the risk of pancreatic cancer (PaCa), as this causal relationship remains inconclusive in existing MR studies. The selection of instrumental variables for T2DM was based on two genome-wide association study (GWAS) meta-analyses from European cohorts. Summary-level data for PaCa were extracted from the FinnGen and UK Biobank databases. Inverse variance weighted (IVW) and four other robust methods were employed in our MR analysis. Various sensitivity analyses and multivariable MR approaches were also performed to enhance the robustness of our findings. In the IVW and Mendelian Randomization Pleiotropy RESidual Sum and Outlier (MR-PRESSO) analyses, the odds ratios (ORs) for each 1-unit increase in genetically predicted log odds of T2DM were approximately 1.13 for PaCa. The sensitivity tests and multivariable MR supported the causal link between T2DM and PaCa without pleiotropic effects. Therefore, our analyses suggest a causal relationship between T2DM and PaCa, shedding light on the potential pathophysiological mechanisms of T2DM's impact on PaCa. This finding underscores the importance of T2DM prevention as a strategy to reduce the risk of PaCa.

The causality between Type 2 diabetes and breast cancer: a bidirectional two-sample Mendelian randomization study

Objective: Observational studies showed that Type 2 diabetes increased the risk of breast cancer, and vice versa. However, it is uncertain whether the link is causal or just due to confounding factors. Using bidirectional Mendelian randomization analysis, we assessed the bidirectional causal relationship from a genetic level. Methods: Large genome-wide association studies yielded summary-level data for Type 2 diabetes and breast cancer. Results: Genetically predicted Type 2 diabetes presented no statistically significant association with overall breast cancer or its subtypes. Similarly, genetically predicted overall breast cancer or its subtypes had no causal effect on Type 2 diabetes. Sensitivity analyses yielded similar results. Conclusion: Our bidirectional Mendelian randomization studies revealed no causal links between Type 2 diabetes and breast cancer.

Polycystic ovary syndrome

Despite affecting ~11-13% of women globally, polycystic ovary syndrome (PCOS) is a substantially understudied condition. PCOS, possibly extending to men's health, imposes a considerable health and economic burden worldwide. Diagnosis in adults follows the International Evidence-based Guideline for the Assessment and Management of Polycystic Ovary Syndrome, requiring two out of three criteria - clinical or biochemical hyperandrogenism, ovulatory dysfunction, and/or specific ovarian morphological characteristics or elevated anti-Müllerian hormone. However, diagnosing adolescents omits ovarian morphology and anti-Müllerian hormone considerations. PCOS, marked by insulin resistance and hyperandrogenism, strongly contributes to early-onset type 2 diabetes, with increased odds for cardiovascular diseases. Reproduction-related implications include irregular menstrual cycles, anovulatory infertility, heightened risks of pregnancy complications and endometrial cancer. Beyond physiological manifestations, PCOS is associated with anxiety, depression, eating disorders, psychosexual dysfunction and negative body image, collectively contributing to diminished health-related quality of life in patients. Despite its high prevalence persisting into menopause, diagnosing PCOS often involves extended timelines and multiple health-care visits. Treatment remains ad hoc owing to limited understanding of underlying mechanisms, highlighting the need for research delineating the aetiology and pathophysiology of the syndrome. Identifying factors contributing to PCOS will pave the way for personalized medicine approaches. Additionally, exploring novel biomarkers, refining diagnostic criteria and advancing treatment modalities will be crucial in enhancing the precision and efficacy of interventions that will positively impact the lives of patients.

Genetic risk of type 2 diabetes modifies the association between lifestyle and glycemic health at 5 years postpartum among high-risk women

INTRODUCTION

Lifestyle interventions are effective in preventing type 2 diabetes, but genetic background may influence the individual response. In the Finnish gestational diabetes prevention study, RADIEL, lifestyle intervention during pregnancy and first postpartum year was effective in preventing gestational diabetes (GDM) and postpartum glycemic abnormalities only among women at highest genetic risk of type 2 diabetes. This study aimed to assess whether still 5 years postpartum the genetic risk modifies the association between lifestyle and glycemic health.

RESEARCH DESIGN AND METHODS

The RADIEL study (randomized controlled trial) aimed to prevent GDM with a lifestyle intervention among high-risk women (body mass index ≥30 kg/m2 and/or prior GDM). The follow-up study 5 years postpartum included anthropometric measurements, laboratory assessments, device-measured physical activity (PA), and questionnaires. A Healthy Lifestyle Score (HLS) indicated adherence to lifestyle goals (PA, diet, smoking) and a polygenic risk score (PRS) based on 50 type 2 diabetes risk alleles depicted the genetic risk.

RESULTS

Altogether 314 women provided genetic and glycemic data 5 years postpartum. The PRS for type 2 diabetes was not associated with glycemic abnormalities, nor was HLS in the total study sample. There was, however, an interaction between HLS and type 2 diabetes PRS on glycemic abnormalities (p=0.03). When assessing the association between HLS and glycemic abnormalities in PRS tertiles, HLS was associated with reduced risk of glycemic abnormalities only among women at the highest genetic risk (p=0.008).

CONCLUSIONS

These results extend our previous findings from pregnancy and first postpartum year demonstrating that still at 5 years postpartum, healthy lifestyle is associated with a lower risk of prediabetes/diabetes only among women at the highest genetic risk of type 2 diabetes.

Serum albumin and cardiovascular disease: a Mendelian randomization study

BACKGROUND

An increasing body of evidence suggests that serum albumin levels play a role in cardiovascular diseases. However, the specific causal relationship between serum albumin levels and cardiovascular disease remains partially unknown.

METHODS

Mendelian randomization (MR) was employed in this study to examine potential causal relationships between instrumental variables and cardiovascular diseases. Specifically, we utilized genetic variants of serum albumin levels within the reference range as our instrumental variables. To acquire data on genetic associations with cardiovascular diseases, we sourced information from renowned genome-wide association studies such as UK BioBank, EMBL-EBI, and FinnGen. Notably, our study leveraged summary statistics from large cohorts that have been previously described.

RESULTS

We explored the association between serum albumin levels and various conditions, including heart failure (HF), venous thromboembolism (VTE), stroke, atrial fibrillation (AF), coronary artery disease (CAD), type 2 diabetes (T2DM), and pulmonary heart disease (PHD). Genetically predicted serum albumin levels were associated with PHD (odds ratio = 0.737, 95% CI = 0.622 - 0.874, P < 0.001), AF (odds ratio = 0.922, 95% CI = 0.870 - 0.977, P = 0.006), VTE (odds ratio = 0.993, 95% CI = 0.991 - 0.995, P < 0.001), and Stroke (odds ratio = 0.997, 95% CI = 0.995 - 0.999, P = 0.002). However, genetically predicted serum albumin level traits were not associated with HF, CAD and T2DM.

CONCLUSION

Our study demonstrates a significant association between serum albumin levels and cardiovascular disease, underscoring the crucial role of low serum albumin as a predictive factor in patients with cardiovascular disease.

Role of CaMKII in diabetes induced vascular injury and its interaction with anti-diabetes therapy

Diabetes mellitus is a metabolic disorder denoted by chronic hyperglycemia that drives maladaptive structural changes and functional damage to the vasculature. Attenuation of this pathological remodeling of blood vessels remains an unmet target owing to paucity of information on the metabolic signatures of this process. Ca2+/calmodulin-dependent kinase II (CaMKII) is expressed in the vasculature and is implicated in the control of blood vessels homeostasis. Recently, CaMKII has attracted a special attention in view of its chronic upregulated activity in diabetic tissues, yet its role in the diabetic vasculature remains under investigation.This review highlights the physiological and pathological actions of CaMKII in the diabetic vasculature, with focus on the control of the dialogue between endothelial (EC) and vascular smooth muscle cells (VSMC). Activation of CaMKII enhances EC and VSMC proliferation and migration, and increases the production of extracellular matrix which leads to maladaptive remodeling of vessels. This is manifested by activation of genes/proteins implicated in the control of the cell cycle, cytoskeleton organization, proliferation, migration, and inflammation. Endothelial dysfunction is paralleled by impaired nitric oxide signaling, which is also influenced by CaMKII signaling (activation/oxidation). The efficiency of CaMKII inhibitors is currently being tested in animal models, with a focus on the genetic pathways involved in the regulation of CaMKII expression (microRNAs and single nucleotide polymorphisms). Interestingly, studies highlight an interaction between the anti-diabetic drugs and CaMKII expression/activity which requires further investigation. Together, the studies reviewed herein may guide pharmacological approaches to improve health-related outcomes in patients with diabetes.

Understanding the Impact of the Sirtuin 1 (SIRT1) Gene on Age-related Macular Degeneration: A Comprehensive Study

Age-related macular degeneration (AMD) is a prevalent and incurable condition affecting the central retina and posing a significant risk to vision, particularly in individuals over the age of 60. As the global population ages, the prevalence of AMD is expected to rise, leading to substantial socioeconomic impacts and increased healthcare costs. The disease manifests primarily in two forms, neovascular and non-neovascular, with genetic, environmental and lifestyle factors playing a pivotal role in disease susceptibility and progression. This review article involved conducting an extensive search across various databases, including Google Scholar, PubMed, Web of Science, ScienceDirect, Scopus and EMBASE, to compile relevant case-control studies and literature reviews from online published articles extracted using search terms related to the work. SIRT1, a key member of the sirtuin family, influences cellular processes such as ageing, metabolism, DNA repair and stress response. Its dysregulation is linked to retinal ageing and ocular conditions like AMD. This review discusses the role of SIRT1 in AMD pathology, its association with genetic variants and its potential as a biomarker, paving the way for targeted interventions and personalised treatment strategies. In addition, it highlights the findings of case-control studies investigating the relationship between SIRT1 gene polymorphisms and AMD risk. These studies collectively revealed a significant association between certain SIRT1 gene variants and AMD risk. Further studies with larger sample sizes are required to validate these findings. As the prevalence of AMD grows, understanding the role of SIRT1 and other biomarkers becomes increasingly vital for improving diagnosis, treatment and, ultimately, patient outcomes.

Obesity-related indicators and tuberculosis: A Mendelian randomization study

PURPOSE

Obesity is a strong risk factor for many diseases, with controversy regarding the cause(s) of tuberculosis (TB) reflected by contradictory findings. Therefore, a larger sample population is required to determine the relationship between obesity and TB, which may further inform treatment.

METHODS

Obesity-related indicators and TB mutation data were obtained from a genome-wide association study database, while representative instrumental variables (IVs) were obtained by screening and merging. Causal relationships between exposure factors and outcomes were determined using two-sample Mendelian randomization (MR) analysis. Three tests were used to determine the representativeness and stability of the IVs, supported by sensitivity analysis.

RESULTS

Initially, 191 single nucleotide polymorphisms were designated as IVs by screening, followed by two-sample MR analysis, which revealed the causal relationship between waist circumference [odds ratio (OR): 2.13 (95% confidence interval (CI): 1.19-3.80); p = 0.011] and TB. Sensitivity analysis verified the credibility of the IVs, none of which were heterogeneous or horizontally pleiotropic.

CONCLUSION

The present study determined the causal effect between waist circumference and TB by two-sample MR analysis and found both to be likely to be potential risk factors.

Risk prediction and interaction analysis using polygenic risk score of type 2 diabetes in a Korean population

Joint modelling of genetic and environmental risk factors can provide important information to predict the risk of type 2 diabetes (T2D). Therefore, to predict the genetic risk of T2D, we constructed a polygenic risk score (PRS) using genotype data of one Korean cohort, KARE (745 cases and 2549 controls), and the genome-wide association study summary statistics of Biobank Japan. We evaluated the performance of PRS in an independent Korean cohort, HEXA (5684 cases and 35,703 controls). Individuals with T2D had a significantly higher mean PRS than controls (0.492 vs. - 0.078, p ≈ 0 ). PRS predicted the risk of T2D with an AUC of 0.658 (95% CI 0.651-0.666). We also evaluated interaction between PRS and waist circumference (WC) in the HEXA cohort. PRS exhibited a significant sub-multiplicative interaction with WC (ORinteraction 0.991, 95% CI 0.987-0.995, pinteraction = 4.93 × 10-6) in T2D. The effect of WC on T2D decreased as PRS increased. The sex-specific analyses produced similar interaction results, revealing a decreased WC effect on T2D as the PRS increased. In conclusion, the risk of WC for T2D may differ depending on PRS and those with a high PRS might develop T2D with a lower WC threshold. Our findings are expected to improve risk prediction for T2D and facilitate the identification of individuals at an increased risk of T2D.

Diabetes mellitus and idiopathic pulmonary fibrosis: a Mendelian randomization study

BACKGROUND

The question as to whether or not diabetes mellitus increases the risk of idiopathic pulmonary fibrosis (IPF) remains controversial. This study aimed to investigate the causal association between type 1 diabetes (T1D), type 2 diabetes (T2D), and IPF using Mendelian randomization (MR) analysis.

METHODS

We used two-sample univariate and multivariate MR (MVMR) analyses to investigate the causal relationship between T1D or T2D and IPF. We obtained genome-wide association study (GWAS) data for T1D and T2D from the European Bioinformatics Institute, comprising 29,652 T1D samples and 101,101 T1D single nucleotide polymorphisms (SNPs) and 655,666 T2D samples and 5,030,727 T2D SNPs. We also used IPF GWAS data from the FinnGen Biobank comprising 198,014 IPF samples and 16,380,413 IPF SNPs. All cases and controls in these datasets were derived exclusively from European populations. In the univariate MR analysis, we employed inverse variance-weighted (IVW), weighted median (WM), and MR-Egger regression methods. For the MVMR analysis, we used the multivariate IVW method primarily, and supplemented it with multivariate MR-Egger and multivariate MR- least absolute shrinkage and selection operator methods. Heterogeneity tests were conducted using the MR-IVW and MR-Egger regression methods, whereas pleiotropic effects were assessed using the MR-Egger intercept. The results of MR and sensitivity analyses were visualized using forest, scatter, leave-one-out, and funnel plots.

RESULTS

Univariate MR revealed a significant causal relationship between T1D and IPF (OR = 1.118, 95% CI = 1.021-1.225, P = 0.016); however, no significant causal relationship was found between T2D and IPF (OR = 0.911, 95% CI = 0.796-1.043, P = 0.178). MVMR analysis further confirmed a causal association between T1D and IPF (OR = 1.133, 95% CI = 1.011-1.270, P = 0.032), but no causal relationship between T2D and IPF (OR = 1.009, 95% CI = 0.790-1.288, P = 0.950). Sensitivity analysis results validated the stability and reliability of our findings.

CONCLUSION

Univariate and multivariate analyses demonstrated a causal relationship between T1D and IPF, whereas no evidence was found to support a causal relationship between T2D and IPF. Therefore, in clinical practice, patients with T1D should undergo lung imaging for early detection of IPF.

The protective role of oily fish intake against type 2 diabetes: insights from a genetic correlation and Mendelian randomization study

Background and aims

Previous research has underscored the association between oily fish intake and type 2 diabetes (T2DM), yet the causality remains elusive.

Methods

A bidirectional univariable Mendelian Randomization (MR) analysis was employed to evaluate the causal effects of oily fish and non-oily fish intake on T2DM. Replication analysis and meta-analysis were conducted to ensure robust results. Multivariable MR analysis was utilized to assess confounders, and further mediation MR analysis discerned mediating effects. Linkage Disequilibrium Score (LDSC) analysis was undertaken to compute genetic correlations. Inverse variance weighted (IVW) was the primary method, complemented by a series of sensitivity analyses.

Results

The LDSC analysis unveiled a significant genetic correlation between oily fish intake and T2DM (Genetic correlation: -0.102, p = 4.43 × 10-4). For each standard deviation (SD) increase in genetically predicted oily fish intake, the risk of T2DM was reduced by 38.6% (OR = 0.614, 95% CI 0.504 ~ 0.748, p = 1.24 × 10-6, False Discovery Rate (FDR) = 3.72 × 10-6). The meta-analysis across three data sources highlighted a persistent causal association (OR = 0.728, 95% CI 0.593 ~ 0.895, p = 0.003). No other causal effects were identified (all p > 0.5, FDR > 0.5). The main outcomes remained consistent in most sensitivity analyses. Both MVMR and mediation MR analyses emphasized the mediating roles of triglycerides (TG), body mass index (BMI), and 25-hydroxyvitamin D (25OHD) levels.

Conclusion

To encapsulate, there's an inverse association between oily fish intake and T2DM risk, suggesting potential benefits of oily fish intake in T2DM prevention.

The clinical relevance of a polygenic risk score for type 2 diabetes mellitus in the Korean population

The clinical utility of a type 2 diabetes mellitus (T2DM) polygenic risk score (PRS) in the East Asian population remains underexplored. We aimed to examine the potential prognostic value of a T2DM PRS and assess its viability as a clinical instrument. We first established a T2DM PRS for 5490 Korean individuals using East Asian Biobank data (269,487 samples). Subsequently, we assessed the predictive capability of this T2DM PRS in a prospective longitudinal study with baseline data and data from seven additional follow-ups. Our analysis showed that the T2DM PRS could predict the transition of glucose tolerance stages from normal glucose tolerance to prediabetes and from prediabetes to T2DM. Moreover, T2DM patients in the top-decile PRS group were more likely to be treated with insulin (hazard ratio = 1.69, p value = 2.31E-02) than were those in the remaining PRS groups. T2DM PRS values were significantly high in the severe diabetes subgroup, characterized by insulin resistance and β -cell dysfunction (p value = 0.0012). The prediction models with the T2DM PRS had significantly greater Harrel's C-indices than did corresponding models without it. By utilizing prospective longitudinal study data and extensive clinical risk factor information, our analysis provides valuable insights into the multifaceted clinical utility of the T2DM PRS.

A Mendelian randomization analysis identifies causal association between sarcopenia and gastroesophageal reflux disease

The incidence of gastroesophageal reflux disease (GERD) is increasing with the advancement of world population aging, affecting the population health worldwide. Recently, there were several researches to suggest the association between GERD and sarcopenia, but evidence supporting the causal effect was absent. The purpose of this study is to determine the causal relationship between GERD and sarcopenia through a Mendelian randomization (MR) study. We conducted an MR analysis by using summary-level data of genome-wide association studies (GWASs) in the European population. The inverse variance weighted (IVW) method was used as the primary analytical method for evaluating causality. In addition, four other MR methods were performed to supplement the IVW results. We also used the Mendelian randomization pleiotropy residual sum and outlier (MR-PRESSO) and the multivariable Mendelian randomization (MVMR) to validate the robustness of our results. IVW analysis revealed a causally positive correlation between low hand grip strength (OR = 1.2358, 95% C.I.: 1.0521-1.4514, P = 0.0099), decreased walking pace (OR = 0.1181, 95% C.I.: 0.0838-0.1666, P = 4×10-34), and decreased appendicular lean mass (ALM) (OR = 0.8612, 95% C.I.: 0.8263-0.8975, P = 1×10-12) and GERD. MR-PRESSO and MVMR analysis confirmed the association evidence. In conclusion, this MR analysis supported the causal association between sarcopenia-related traits and GERD.

Effect of Household Income on Cardiovascular Diseases, Cardiovascular Biomarkers, and Socioeconomic Factors

PURPOSE

To examine whether household income is causally related to cardiovascular diseases and investigate the potential reasons.

METHODS

Using 2-sample Mendelian randomization analyses, we obtained summary statistics from genome-wide association studies of household income and a range of cardiovascular diseases, biomarkers, and socioeconomic factors.

FINDINGS

Higher household income was causally associated with lower risks of coronary heart disease (odd ratio [OR] = 0.63; 95% CI: 0.49-0.79; P = 0.0001), myocardial infarction (OR = 0.64; 95% CI: 0.50-0.82; P = 0.0003), and hypertension (OR = 0.71; 95% CI: 0.58-0.88; P = 0.0015). With increasing household income, the cardiovascular biomarkers including triglycerides, C-reactive protein, body mass index, fasting glucose were decreased whereas telomere length and high-density lipoprotein cholesterol were increased. Besides, individuals with higher household income were less likely to smoke (β = -0.34; 95% CI: -0.47 to -0.21; P = 1.91×10-07), intake salt (β = -0.14; 95% CI: -0.21 to -0.07; P = 0.0001), or be exposed to air pollution (β = -0.10; 95% CI: -0.15 to -0.06; P = 8.81×10-06) or depression state (β = -0.03; 95% CI: -0.04 to -0.02; P = 5.16×10-07). They were more likely to take physical activity (β = 0.06; 95% CI: 0.02 to 010; P = 0.0016) and have long years of schooling (β = 0.70; 95% CI: 0.62 to 0.78; P = 5.32×10-67).

IMPLICATIONS

Higher household income is causally associated with better socioeconomic factors and improved cardiovascular biomarkers, which translates into a reduced prevalence of cardiovascular diseases. Policies to improve income equality may result in a reduced burden of cardiovascular diseases.

Genotypes of the UCP1 gene polymorphisms and cardiometabolic diseases: A multifactorial study of association with disease probability

Cardiometabolic diseases (CMDs) are complex disorders with a heterogenous phenotype, which are caused by multiple factors including genetic factors. Single nucleotide polymorphisms (SNPs) rs45539933 (p.Ala64Thr), rs10011540 (c.-112A>C), rs3811791 (c.-1766A>G), and rs1800592 (c.-3826A>G) in the UCP1 gene have been analyzed for association with CMDs in many studies providing controversial results. However, previous studies only considered individual UCP1 SNPs and did not evaluate them in an integrated manner, which is a more powerful approach to uncover genetic component of complex diseases. This study aimed to investigate associations between UCP1 genotype combinations and CMDs or CMD risk factors in the context of non-genetic factors. We performed multiple logistic regression analysis and proposed new methodology of testing different combinations of SNP genotypes. We found that probability of CMDs increased in presence of the three-SNP combination of genotypes with minor alleles of c.-3826A>G and p.Ala64Thr and wild allele of c.-112A>C, with increasing age, body mass index (BMI), body fat percentage (BF%) and may differ between sexes and between countries. The combination of genotypes with c.-3826A>G minor allele and wild homozygotes of c.-112A>C and p.Ala64Thr was associated with increased probability of diabetes. While combination of genotypes with minor alleles of all three SNPs reduced the CMD probability. The present results suggest that age, BMI, sex, and UCP1 three-SNP combinations of genotypes significantly contribute to CMD probability. Varying of c.-112A>C alleles in the genotype combination with minor alleles of c.-3826A>G and p.Ala64Thr markedly changes CMD probability.

Causal Associations of Education Level With Cardiovascular Diseases, Cardiovascular Biomarkers, and Socioeconomic Factors

An inverse association of education level with cardiovascular diseases has been documented in observational studies, yet the causality and potential mechanisms remain to be determined. To systematically investigate the causal associations of education level with cardiovascular diseases, cardiovascular biomarkers, and socioeconomic factors, a 2-sample Mendelian randomization was performed. The results revealed that higher genetically determined education level was associated with lower risks of type 2 diabetes mellitus (odds ratio [OR] 0.54, 95% confidence interval [CI] 0.47 to 0.61, p = 3.04 × 10-23), peripheral artery disease (OR 0.62, 95% CI 0.51 to 0.76, p = 2.14 × 10-06), hypertension (OR 0.62, 95% CI 0.56 to 0.70, p = 4.22 × 10-16), coronary heart disease (OR 0.62, 95% CI 0.56 to 0.69, p = 3.50 × 10-19), myocardial infarction (OR 0.62, 95% CI 0.55 to 0.69, p = 2.58 × 10-16), ischemic stroke (OR 0.67, 95% CI 0.62 to 0.74, p = 6.00 × 10-19), deep vein thrombosis (OR 0.69, 95% CI 0.55 to 0.87, p = 0.0017), atrial fibrillation (OR 0.70, 95% CI 0.57 to 0.86, p = 0.0007), cardiac death (OR 0.71, 95% CI 0.60 to 0.86, p = 0.0003), heart failure (OR 0.72, 95% CI 0.65 to 0.79, p = 6.37 × 10-12), transient ischemic attack (OR 0.76, 95% CI 0.64 to 0.90, p = 0.0010), and venous thromboembolism (OR 0.79, 95% CI 0.67 to 0.92, p = 0.0028). Systolic blood pressure, diastolic blood pressure, C-reactive protein, body mass index, waist circumference, and triglycerides were decreased, whereas telomere length was increased. Subjects with higher education were less likely to smoke, intake salt, or be exposed to air pollution and depression state. They were more likely to take physical activity and possess more household income. In conclusion, higher education may causally decrease cardiovascular diseases through socioeconomic factors and cardiovascular biomarkers. Reducing education inequality is important in the management of cardiovascular diseases.

Association of type 2 Diabetes Mellitus and bone mineral density: a two-sample Mendelian randomization study

BACKGROUND

Observational studies have suggested that type 2 Diabetes Mellitus (DM2) is a potentially modifiable risk factor for lower BMD, but the causal relationship is unclear. This study aimed to examine whether the association of DM2 with lower BMD levels was causal by using Mendelian randomization (MR) analyses.

METHODS

We collected genome-wide association study data for DM2 and BMD of total body and different skeletal sites from the IEU database. Subsequently, we performed a two-sample Mendelian randomization analysis using the Two Sample MR package.

RESULTS

We identified a positive association between DM2 risk (61,714 DM2 cases and 596,424 controls) and total BMD, and other skeletal sites BMD, such as femoral neck BMD, ultra-distal forearm BMD and heel BMD. However, non-significant trends were observed for the effects of DM2 on lumbar-spine BMD.

CONCLUSION

In two-sample MR analyses, there was positive causal relationship between DM2 and BMD in both overall samples. In summary, while observational analyses consistently indicate a strong association between DM2 and low BMD, our MR analysis introduces a nuanced perspective. Contrary to the robust association observed in observational studies, our MR analysis suggests a significant link between DM2 and elevated BMD.

Predicting cell-type specific disease genes of diabetes with the biological network

Type 2 diabetes (T2D) is a chronic condition that can lead to significant harm, such as heart disease, kidney disease, nerve damage, and blindness. Although T2D-related genes have been identified through Genome-wide association studies (GWAS) and various computational methods, the biological mechanism of T2D at the cell type level remains unclear. Exploring cell type-specific genes related to T2D is essential to understand the cellular mechanisms underlying the disease. To address this issue, we introduce DiGCellNet (predicting Disease Genes with Cell type specificity based on biological Networks), a model that integrates graph convolutional network (GCN) and multi-task learning (MTL) to predict T2D-associated cell type-specific genes based on the biological network. Our work represents the first attempt to predict cell type-specific disease genes using GCN and MTL. We evaluate our approach by predicting genes specific to four cell types and demonstrate that the proposed DiGCellNet outperforms other models that combine node embeddings with traditional machine learning algorithms. Moreover, DiGCellNet successfully identifies CALM1 as a gene specific to beta cell type in T2D cases, and this association is confirmed using an independent dataset. The code is available at https://github.com/23AIBox/23AIBox-DiGCellNet.

Type 2 diabetes and fasting glycemic traits are causal factors of frozen shoulder: a 2-sample Mendelian randomization analysis

BACKGROUND

The causal relationship between type 2 diabetes (T2D) and frozen shoulder is unclear. This study aims to explore the genetic causal association between T2D and glycemic traits (fasting glucose [FG], fasting insulin [FI], glycated hemoglobin [HbA1c], and 2-hour postprandial glucose [2hGlu]) on frozen shoulder.

METHODS

Using 2-sample Mendelian randomization (MR), we analyzed nonconfounded estimates of the effects of T2D and glycemic traits on frozen shoulder. Single-nucleotide polymorphisms (SNPs) strongly associated (P < 5 × 10-8) with exposures from genome-wide association studies (GWAS) were identified. We employed fixed effect mode inverse variance weighting (IVW-FE), random effect mode IVW (IVW-MRE), MR-Egger, and weighted median to assess the association of exposures and outcome. Sensitivity analysis was conducted to test for heterogeneity and multidirectionality bias in MR.

RESULTS

We found a significant genetic causal correlation between T2D (IVW-MRE P = .007, odds ratio [OR] 1.093, 95% confidence interval [CI] 1.03-1.16), FG (IVW-FE P < .001, OR 1.455, 95% CI 1.173-1.806), and frozen shoulder, but no evidence for causal correlation between FI, HbA1c, and 2hGlu and frozen shoulder. Although there was certain heterogeneity, sensitivity analysis reveals no deviation from the MR assumptions.

CONCLUSION

This study supports a genetic causal relationship between T2D and FG and frozen shoulder.

Causations between obesity, diabetes, lifestyle factors and the risk of low back pain

BACKGROUND

Despite numerous observational studies, the causal relationship between obesity-measured by body mass index (BMI) and waist circumference (WC)-as well as type 2 diabetes (T2D), lifestyle habits, and susceptibility to low back pain (LBP) remains obscure.

METHODS

This investigation employed two-sample Mendelian randomization (MR) analysis to explore causality, using genetic variants linked to relevant factors from genome-wide association studies (GWASs). Specifically, we selected independent genetic variants related to BMI, WC, T2D, smoking, alcohol consumption, and coffee intake from established GWASs, all of which demonstrated genome-wide significance. The comparative data for LBP were derived from a GWAS involving European subjects, under the auspices of the renowned MRC-IEU (Medical Research Council Integrative Epidemiology Unit) consortium.

RESULTS

Elevated BMI and WC were associated with odds ratios of 1.002 (95% confidence interval [CI] = 1.001-1.004, p < 0.001) and 1.003 (95% CI = 1.002-1.004, p < 0.001) for LBP per standard deviation (SD) increase, respectively. Regarding smoking initiation and coffee consumption, the odds ratios stood at 1.002 (95% CI = 1.001-1.004, p = 0.001) and 1.004 (95% CI = 1.001-1.008, p = 0.034) for LBP, respectively. However, an augmented log odds ratio for T2D and each SD rise in alcohol consumption frequency revealed no significant causal impact on LBP risk.

CONCLUSION

Our findings indicate a potential causal link between obesity, smoking, and coffee intake in the genesis of LBP, suggesting that mitigating these factors could contribute to LBP prevention.

Causal associations between modifiable risk factors and intervertebral disc degeneration

BACKGROUND

Intervertebral disc degeneration (IVDD) is a common degenerative condition, which is thought to be a major cause of lower back pain (LBP). However, the etiology and pathophysiology of IVDD are not yet completely clear.

PURPOSE

To examine potential causal effects of modifiable risk factors on IVDD.

STUDY DESIGN

Bidirectional Mendelian randomization (MR) study.

PATIENT SAMPLE

Genome-wide association studies (GWAS) with sample sizes between 54,358 and 766,345 participants.

OUTCOME MEASURES

Outcomes included (1) modifiable risk factors associated with IVDD use in the forward MR; and (2) modifiable risk factors that were determined to have a causal association with IVDD in the reverse MR, including smoking, alcohol intake, standing height, education level, household income, sleeplessness, hypertension, hip osteoarthritis, HDL, triglycerides, apolipoprotein A-I, type 2 diabetes, fasting glucose, HbA1c, BMI and obesity trait.

METHODS

We obtained genetic variants associated with 33 exposure factors from genome-wide association studies. Summary statistics for IVDD were obtained from the FinnGen consortium. The risk factors of IVDD were analyzed by inverse variance weighting method, MR-Egger method, weighted median method, MR-PRESSO method and multivariate MR Method. Reverse Mendelian randomization analysis was performed on risk factors found to be caustically associated with IVDD in the forward Mendelian randomization analysis. The heterogeneity of instrumental variables was quantified using Cochran's Q statistic.

RESULTS

Genetic predisposition to smoking (OR=1.221, 95% CI: 1.068-1.396), alcohol intake (OR=1.208, 95% CI: 1.056-1.328) and standing height (OR=1.149, 95% CI: 1.072-1.231) were associated with increased risk of IVDD. In addition, education level (OR=0.573, 95%CI: 0.502-0.654)and household income (OR=0.614, 95%CI: 0.445-0.847) had a protective effect on IVDD. Sleeplessness (OR=1.799, 95%CI: 1.162-2.783), hypertension (OR=2.113, 95%CI: 1.132-3.944) and type 2 diabetes (OR=1.069, 95%CI: 1.024-1.115) are three important risk factors causally associated with the IVDD. In addition, we demonstrated that increased levels of triglycerides (OR=1.080, 95%CI:1.013-1.151), fasting glucose (OR=1.189, 95%CI:1.007-1.405), and HbA1c (OR=1.308, 95%CI:1.017-1.683) could significantly increase the odds of IVDD. Hip osteoarthritis, HDL, apolipoprotein A-I, BMI and obesity trait factors showed bidirectional causal associations with IVDD, therefore we considered the causal associations between these risk factors and IVDD to be uncertain.

CONCLUSIONS

This MR study provides evidence of complex causal associations between modifiable risk factors and IVDD. It is noteworthy that metabolic disturbances appear to have a more significant effect on IVDD than biomechanical alterations, as individuals with type 2 diabetes, elevated triglycerides, fasting glucose, and elevated HbA1c are at higher risk for IVDD, and the causal association of obesity-related characteristics with IVDD incidence is unclear. These findings provide new insights into potential therapeutic and prevention strategies. Further research is needed to clarify the mechanisms of these risk factors on IVDD.

Women's reproductive risk and genetic predisposition in type 2 diabetes: A prospective cohort study

OBJECTIVE

To assess synergistic effects of reproductive factors and gene-reproductive interaction on type 2 diabetes (T2D) risk, also the extent to which the genetic risk of T2D can be affected by reproductive risk.

METHODS

84,254 women with genetic data and reproductive factors were enrolled between 2006 and 2010 in the UK Biobank. The reproductive risk score (RRS) was conducted based on 17 reproductive items, and genetic risk score (GRS) was based on 149 genetic variants.

RESULTS

There were 2300 (2.8 %) T2D cases during an average follow-up of 4.49 years. We found a significant increase in T2D risk across RRS categories (Ptrend < 0.001). Compared with low reproductive risk, high-mediate (adjusted hazard ratio [aHR] 1.38, 95 % CI 1.20-1.58) and high (aHR 1.84, 95 % CI 1.54-2.19) reproductive risk could increase the risk of T2D. We further observed a significant additive interaction between reproductive risk and genetic predisposition. In the situation of high genetic predisposition, women with low reproductive risk had lower risk of T2D than those with high reproductive risk (aHR 0.47, 95 % CI 0.30-0.76), with an absolute risk reduction of 2.98 %.

CONCLUSIONS

Our novo developed RRS identified high reproductive risk is associated with elevated risk of women's T2D, which can be magnified by gene-reproductive interaction.

Large scale plasma proteomics identifies novel proteins and protein networks associated with heart failure development

Heart failure (HF) causes substantial morbidity and mortality but its pathobiology is incompletely understood. The proteome is a promising intermediate phenotype for discovery of novel mechanisms. We measured 4877 plasma proteins in 13,900 HF-free individuals across three analysis sets with diverse age, geography, and HF ascertainment to identify circulating proteins and protein networks associated with HF development. Parallel analyses in Atherosclerosis Risk in Communities study participants in mid-life and late-life and in Trøndelag Health Study participants identified 37 proteins consistently associated with incident HF independent of traditional risk factors. Mendelian randomization supported causal effects of 10 on HF, HF risk factors, or left ventricular size and function, including matricellular (e.g. SPON1, MFAP4), senescence-associated (FSTL3, IGFBP7), and inflammatory (SVEP1, CCL15, ITIH3) proteins. Protein co-regulation network analyses identified 5 modules associated with HF risk, two of which were influenced by genetic variants that implicated trans hotspots within the VTN and CFH genes.

FORGEdb: a tool for identifying candidate functional variants and uncovering target genes and mechanisms for complex diseases

The majority of disease-associated variants identified through genome-wide association studies are located outside of protein-coding regions. Prioritizing candidate regulatory variants and gene targets to identify potential biological mechanisms for further functional experiments can be challenging. To address this challenge, we developed FORGEdb ( https://forgedb.cancer.gov/ ; https://forge2.altiusinstitute.org/files/forgedb.html ; and https://doi.org/10.5281/zenodo.10067458 ), a standalone and web-based tool that integrates multiple datasets, delivering information on associated regulatory elements, transcription factor binding sites, and target genes for over 37 million variants. FORGEdb scores provide researchers with a quantitative assessment of the relative importance of each variant for targeted functional experiments.

Chronic Stress as a Risk Factor for Type 2 Diabetes: Endocrine, Metabolic, and Immune Implications

BACKGROUND

Chronic stress is a condition of pressure on the brain and whole body, which in the long term may lead to a frank disease status, even including type 2 diabetes (T2D). Stress activates the hypothalamus-pituitary-adrenal axis with release of glucocorticoids (GCs) and catecholamines, as well as activation of the inflammatory pathway of the immune system, which alters glucose and lipid metabolism, ultimately leading to beta-cell destruction, insulin resistance and T2D onset. Alteration of the glucose and lipid metabolism accounts for insulin resistance and T2D outcome. Furthermore, stress-related subversion of the intestinal microbiota leads to an imbalance of the gut-brain-immune axis, as evidenced by the stress-related depression often associated with T2D. A condition of generalized inflammation and subversion of the intestinal microbiota represents another facet of stress-induced disease. In fact, chronic stress acts on the gut-brain axis with multiorgan consequences, as evidenced by the association between depression and T2D. Oxidative stress with the production of reactive oxygen species and cytokine-mediated inflammation represents the main hallmarks of chronic stress. ROS production and pro-inflammatory cytokines represent the main hallmarks of stress-related disorders, and therefore, the use of natural antioxidant and anti-inflammatory substances (nutraceuticals) may offer an alternative therapeutic approach to combat stress-related T2D. Single or combined administration of nutraceuticals would be very beneficial in targeting the neuro-endocrine-immune axis, thus, regulating major pathways involved in T2D onset. However, more clinical trials are needed to establish the effectiveness of nutraceutical treatment, dosage, time of administration and the most favorable combinations of compounds. Therefore, in view of their antioxidant and anti-inflammatory properties, the use of natural products or nutraceuticals for the treatment of stress-related diseases, even including T2D, will be discussed. Several evidences suggest that chronic stress represents one of the main factors responsible for the outcome of T2D.

Causal associations of plasma omega-3 polyunsaturated fatty acids with sarcopenia-related traits: a two-sample Mendelian randomization study

OBJECTIVE

To evaluate the causal effect of plasma omega-3 polyunsaturated fatty acids (PUFAs) on sarcopenia-related traits (lean mass, grip strength and walking pace) utilizing two-sample Mendelian randomization (MR) approach.

METHODS

Based on genome-wide association study (GWAS) summary statistics, we performed two-sample MR applying the inverse variance weighted (IVW) as the primary method, supplemented with four additional sensitivity analyses. Furthermore, multivariable MR (MVMR) was applied to assess these associations independent of alcohol drinking, type 2 diabetes (T2D), triglycerides (TG), estimated glomerular filtration rate (eGFR) and C-reactive protein (CRP).

RESULTS

In univariable MR, the IVW analysis suggested no significant causal effect of genetically determined plasma omega-3 PUFAs on fat-free mass (right leg: β = 0.01, 95% CI = -0.02 to 0.05, P = 0.375; left leg: β = 0.01, 95% CI = -0.02 to 0.04, P = 0.446; right arm: β = 0.01, 95% CI = -0.02 to 0.05, P = 0.376; left arm: β = 0.01, 95% CI = -0.02 to 0.04, P = 0.384; trunk:β = 0.02, 95% CI = -0.02 to 0.06, P = 0.283; whole: β = 0.01, 95% CI = -0.03 to 0.04, P = 0.631), grip strength (right hand: β = -0.01, 95% CI = -0.03 to 0.01, P = 0.387; left hand: β = -0.01, 95% CI = -0.02 to 0.01, P = 0.553) and walking pace (β = 0.00, 95% CI = -0.01 to 0.02, P = 0.575), and sensitive analysis generated similar non-significant results. Furthermore, the MVMR revealed no independent causal association.

CONCLUSIONS

Genetically determined plasma omega-3 PUFAs have no causal effect on sarcopenia-related traits.

Association of clinical parameters and polygenic risk scores for body mass index, schizophrenia, and diabetes with antipsychotic-induced weight gain

Antipsychotic-induced weight gain (AIWG) is a common adverse event in schizophrenia. Genome-wide association studies (GWAS) and polygenic risk scores (PRS) for other diseases or traits are recent approaches to disentangling the genetic architecture of AIWG. 200 patients with schizophrenia treated monotherapeutically with antipsychotics were included in this study. A multiple linear regression analysis with ten-fold crossvalidation was performed to predict the percentage weight change after five weeks of treatment. Independent variables were sex, age, body mass index (BMI) at baseline, medication-associated risk, and PRSs (BMI, schizophrenia, diabetes, and metabolic syndrome). An explorative GWAS analysis was performed on the same subjects and traits. PRSs for BMI (β = 3.78; p = 0.0041), schizophrenia (β = 5.38; p = 0.021) and diabetes type 2 (β = 13.4; p = 0.046) were significantly associated with AIWG. Other significant factors were sex, baseline BMI and medication. Compared to the model without genetic factors, the addition of PRSs for BMI, schizophrenia, and diabetes type 2 increased the goodness of fit by 6.5 %. The GWAS identified the association of three variants (rs10668573, rs10249381 and rs1988834) with AIWG at a genome-wide level of p < 1 · 10-6. Using PRS for schizophrenia, BMI, and diabetes type 2 increased the explained variation of predicted weight gain, compared to a model without PRSs. For more precise results, PRSs derived from other traits (ideally AIWG) should be investigated. Potential risk variants identified in our GWAS need to be further investigated and replicated in independent samples.

Causal relationship between glycemic traits and bone mineral density in different age groups and skeletal sites: a Mendelian randomization analysis

INTRODUCTION

Previous research has confirmed that patients with type 2 diabetes mellitus tend to have higher bone mineral density (BMD), but it is unknown whether this pattern holds true for individuals without diabetes. This Mendelian randomization (MR) study aims to investigate the potential causal relationship between various glycemic trait (including fasting glucose, fasting insulin, 2-h postprandial glucose, and glycated hemoglobin) and BMD in non-diabetic individuals. The investigation focuses on different age groups (15-30, 30-45, 45-60, and 60 + years) and various skeletal sites (forearm, lumbar spine, and hip).

MATERIALS AND METHODS

We utilized genome-wide association study data from large population-based cohorts to identify robust instrumental variables for each glycemic traits parameter. Our primary analysis employed the inverse-variance weighted method, with sensitivity analyses conducted using MR-Egger, weighted median, MR-PRESSO, and multivariable MR methods to assess the robustness and potential horizontal pleiotropy of the study results.

RESULTS

Fasting insulin showed a negative modulating relationship on both lumbar spine and forearm. However, these associations were only nominally significant. No significant causal association was observed between blood glucose traits and BMD across the different age groups. The direction of fasting insulin's causal effects on BMD showed inconsistency between genders, with potentially decreased BMD in women with high fasting insulin levels and an increasing trend in BMD in men.

CONCLUSIONS

In the non-diabetic population, currently available evidence does not support a causal relationship between glycemic traits and BMD. However, further investigation is warranted considering the observed gender differences.

The first exome wide association study in Tunisia: identification of candidate loci and pathways with biological relevance for type 2 diabetes

Introduction

Type 2 diabetes (T2D) is a multifactorial disease involving genetic and environmental components. Several genome-wide association studies (GWAS) have been conducted to decipher potential genetic aberrations promoting the onset of this metabolic disorder. These GWAS have identified over 400 associated variants, mostly in the intronic or intergenic regions. Recently, a growing number of exome genotyping or exome sequencing experiments have identified coding variants associated with T2D. Such studies were mainly conducted in European populations, and the few candidate-gene replication studies in North African populations revealed inconsistent results. In the present study, we aimed to discover the coding genetic etiology of T2D in the Tunisian population.

Methods

We carried out a pilot Exome Wide Association Study (EWAS) on 50 Tunisian individuals. Single variant analysis was performed as implemented in PLINK on potentially deleterious coding variants. Subsequently, we applied gene-based and gene-set analyses using MAGMA software to identify genes and pathways associated with T2D. Potential signals were further replicated in an existing large in-silico dataset, involving up to 177116 European individuals.

Results

Our analysis revealed, for the first time, promising associations between T2D and variations in MYORG gene, implicated in the skeletal muscle fiber development. Gene-set analysis identified two candidate pathways having nominal associations with T2D in our study samples, namely the positive regulation of neuron apoptotic process and the regulation of mucus secretion. These two pathways are implicated in the neurogenerative alterations and in the inflammatory mechanisms of metabolic diseases. In addition, replication analysis revealed nominal associations of the regulation of beta-cell development and the regulation of peptidase activity pathways with T2D, both in the Tunisian subjects and in the European in-silico dataset.

Conclusions

The present study is the first EWAS to investigate the impact of single genetic variants and their aggregate effects on T2D risk in Africa. The promising disease markers, revealed by our pilot EWAS, will promote the understanding of the T2D pathophysiology in North Africa as well as the discovery of potential treatments.

Association of cardiovascular disease management drugs with Lewy body dementia: a case-control study

Lewy body dementia is the second most common neurodegenerative dementia after Alzheimer's disease. Disease-modifying therapies for this disabling neuropsychiatric condition are critically needed. To identify drugs associated with the risk of developing Lewy body dementia, we performed a population-based case-control study of 148 170 US Medicare participants diagnosed with Lewy body dementia between 1 January 2008 and 31 December 2014 and of 1 253 043 frequency-matched controls. We estimated odds ratios and 95% confidence intervals for the association of Lewy body dementia risk with 1017 prescription drugs overall and separately for the three major racial groups (Black, Hispanic and White Americans). We identified significantly reduced Lewy body dementia risk associated with drugs used to treat cardiovascular diseases (anti-hypertensives: odds ratio = 0.72, 95% confidence interval = 0.70-0.74, P-value = 0; cholesterol-lowering agents: odds ratio = 0.85, 95% confidence interval = 0.83-0.87, P-value = 0; anti-diabetics: odds ratio = 0.83, 95% confidence interval = 0.62-0.72, P-value = 0). Notably, anti-diabetic medications were associated with a larger risk reduction among Black Lewy body dementia patients compared with other racial groups (Black: odds ratio = 0.67, 95% confidence interval = 0.62-0.72, P-value = 0; Hispanic: odds ratio = 0.86, 95% = 0.80-0.92, P-value = 5.16 × 10-5; White: odds ratio = 0.85, 95% confidence interval = 0.82-0.88, P-value = 0). To independently confirm the epidemiological findings, we looked for evidence of genetic overlap between Lewy body dementia and cardiovascular traits using whole-genome sequence data generated for 2591 Lewy body dementia patients and 4027 controls. Bivariate mixed modelling identified shared genetic risk between Lewy body dementia and low-density lipoprotein cholesterol levels, Type 2 diabetes and hypertension. By combining epidemiological and genomic data, we demonstrated that drugs treating cardiovascular diseases are associated with reduced Lewy body dementia risk, and these associations varied across racial groups. Future randomized clinical trials need to confirm our findings, but our data suggest that assiduous management of cardiovascular diseases may be beneficial in this understudied form of dementia.

Identifying risk variants for embryo aneuploidy using ultra-low coverage whole-genome sequencing from preimplantation genetic testing

Aneuploidy frequently arises during human meiosis and is the primary cause of early miscarriage and in vitro fertilization (IVF) failure. Individuals undergoing IVF exhibit significant variability in aneuploidy rates, although the exact genetic causes of the variability in aneuploid egg production remain unclear. Preimplantation genetic testing for aneuploidy (PGT-A) using next-generation sequencing is a standard test for identifying and selecting IVF-derived euploid embryos. The wealth of embryo aneuploidy data and ultra-low coverage whole-genome sequencing (ulc-WGS) data from PGT-A have the potential to discover variants in parental genomes that are associated with aneuploidy risk in their embryos. Using ulc-WGS data from ∼10,000 PGT-A biopsies, we imputed genotype likelihoods of genetic variants in embryo genomes. We then used the imputed variants and embryo aneuploidy calls to perform a genome-wide association study of aneuploidy incidence. Finally, we carried out functional evaluation of the identified candidate gene in a mouse oocyte system. We identified one locus on chromosome 3 that is significantly associated with meiotic aneuploidy risk. One candidate gene, CCDC66, encompassed by this locus, is involved in chromosome segregation during meiosis. Using mouse oocytes, we showed that CCDC66 regulates meiotic progression and chromosome segregation fidelity, especially in older mice. Our work extended the research utility of PGT-A ulc-WGS data by allowing robust association testing and improved the understanding of the genetic contribution to maternal meiotic aneuploidy risk. Importantly, we introduce a generalizable method that has potential to be leveraged for similar association studies that use ulc-WGS data.

High-throughput screening of glucocorticoid-induced enhancer activity reveals mechanisms of stress-related psychiatric disorders

Exposure to stressful life events increases the risk for psychiatric disorders. Mechanistic insight into the genetic factors moderating the impact of stress can increase our understanding of disease processes. Here, we test 3,662 single nucleotide polymorphisms (SNPs) from preselected expression quantitative trait loci in massively parallel reporter assays to identify genetic variants that modulate the activity of regulatory elements sensitive to glucocorticoids, important mediators of the stress response. Of the tested SNP sequences, 547 were located in glucocorticoid-responsive regulatory elements of which 233 showed allele-dependent activity. Transcripts regulated by these functional variants were enriched for those differentially expressed in psychiatric disorders in the postmortem brain. Phenome-wide Mendelian randomization analysis in 4,439 phenotypes revealed potentially causal associations specifically in neurobehavioral traits, including major depression and other psychiatric disorders. Finally, a functional gene score derived from these variants was significantly associated with differences in the physiological stress response, suggesting that these variants may alter disease risk by moderating the individual set point of the stress response.

Effect of genetically determined BCAA levels on cardiovascular diseases and their risk factors: A Mendelian randomization study

BACKGROUND AND AIMS

Observational studies have demonstrated that serum branched-chain amino acids (BCAAs) are associated with the risk of various cardiovascular diseases (CVDs) and their risk factors. However, the causal effect is unclear. The aim of this study was to investigate the effect of genetically determined BCAA levels on CVDs and their risk factors using Mendelian randomization (MR).

METHODS AND RESULTS

We performed univariable and multivariable MR analyses using summary-level data from multiple GWASs and the FinnGen consortium to investigate the association between BCAA levels and the risk of CVDs (myocardial infarction, ischemic stroke, and intracerebral hemorrhage) and their risk factors (atrial fibrillation, hypertension, heart failure, and valvular heart disease). We used the random-effects IVW approach as the primary statistical method and incorporated MR estimates from different data sources using the fixed-effects model. We found genetically determined total and individual BCAA levels and a high risk of hypertension. However, there is no evidence of a causal relationship between BCAA levels and 3 cardiovascular diseases and other their risk factors. The odds of hypertension increased per 1-SD increase in BCAA levels (OR = 1.02 95% CI: 1.01, 1.04; P = 0.005), valine (OR = 1.02 95% CI: 1.01, 1.03; P<0.0001), leucine (OR = 1.02 95% CI: 1.01, 1.04; P＜0.01), and isoleucine (OR = 1.02 95% CI: 1.01, 1.03; P < 0.0001). This result was also significant in the multivariable MR.

CONCLUSIONS

This MR study suggests that total and individual BCAA levels could be associated with a high risk of hypertension.

Associations between modifiable risk factors and frailty: a Mendelian randomisation study

BACKGROUND

Early identification of modifiable risk factors is essential for the prevention of frailty. This study aimed to explore the causal relationships between a spectrum of genetically predicted risk factors and frailty.

METHODS

Univariable and multivariable Mendelian randomisation (MR) analyses were performed to explore the relationships between 22 potential risk factors and frailty, using summary genome-wide association statistics. Frailty was accessed by the frailty index.

RESULTS

Genetic liability to coronary artery disease (CAD), type 2 diabetes mellitus (T2DM), ischaemic stroke, atrial fibrillation and regular smoking history, as well as genetically predicted 1-SD increase in body mass index, systolic blood pressure, diastolic blood pressure, low-density lipoprotein cholesterol, triglycerides, alcohol intake frequency and sleeplessness were significantly associated with increased risk of frailty (all p<0.001). In addition, there was a significant inverse association between genetically predicted college or university degree with risk of frailty (beta -0.474; 95% CI (-0.561 to -0.388); p<0.001), and a suggestive inverse association between high-density lipoprotein cholesterol level with risk of frailty (beta -0.032; 95% CI (-0.055 to -0.010); p=0.004). However, no significant causal associations were observed between coffee consumption, tea consumption, serum level of total testosterone, oestradiol, 25-hydroxyvitamin D, C reactive protein or moderate to vigorous physical activity level with frailty (all p>0.05). Results of the reverse directional MR suggested bidirectional causal associations between T2DM and CAD with frailty.

CONCLUSIONS

This study provided genetic evidence for the causal associations between several modifiable risk factors with lifetime frailty risk. A multidimensional approach targeting these factors may hold a promising prospect for prevention frailty.