The trans-ancestral genomic architecture of glycemic traits

Genetic Underpinnings of Fasting and Oral Glucose-stimulated Based Insulin Sensitivity Indices

CONTEXT

Insulin sensitivity (IS) is an important factor in type 2 diabetes (T2D) and can be estimated by many different indices.

OBJECTIVE

We aimed to compare the genetic components underlying IS indices obtained from fasting and oral glucose-stimulated plasma glucose and serum insulin levels.

METHODS

We computed 21 IS indices, classified as fasting, OGTT0,120, and OGTT0,30,120 indices, using fasting and oral glucose tolerance test (OGTT) data in 2 cohorts. We used data from a family cohort (n = 313) to estimate the heritability and the genetic and phenotypic correlations of IS indices. The population cohort, Inter99 (n = 5343), was used to test for associations between IS indices and 426 genetic variants known to be associated with T2D.

RESULTS

Heritability estimates of IS indices ranged between 19% and 38%. Fasting and OGTT0,30,120 indices had high genetic (ρG) and phenotypic (ρP) pairwise correlations (ρG and ρP: 0.88 to 1) The OGTT0,120 indices displayed a wide range of pairwise correlations (ρG: 0.17-1.00 and ρP: 0.13-0.97). We identified statistically significant associations between IS indices and established T2D-associated variants. The PPARG rs11709077 variant was associated only with fasting indices and PIK3R rs4976033 only with OGTT0,30,120 indices. The variants in FAM63A/MINDY1, GCK, C2CD4A/B, and FTO loci were associated only with OGTT0,120 indices.

CONCLUSION

Even though the IS indices mostly share a common genetic background, notable differences emerged between OGTT0,120 indices. The fasting and OGTT-based indices have distinct associations with T2D risk variants. This work provides a basis for future large-scale genetic investigations into the differences between IS indices.

Expression of CLDN1 and EGFR in PTC

Papillary thyroid carcinoma (PTC) involves complex genetic mechanisms, notably involving CLDN1 and EGFR. This study investigates the expression and variations of these genes and their effects on tumor behavior and patient outcomes. Meta-analysis of CLDN1 and EGFR expression in TCGA-PTC patients and GEO datasets was conducted. cBioPortal was used for clinical analysis. GSEA, GO, KEGG, Hallmark pathways, and cibersort analysis were applied. Cell proliferation, migration, invasion, and apoptosis were assessed in vitro. Co-culturing with CD8+ T cells, MTT assay, ELISA, subcutaneous tumor models, and immunohistochemistry were performed. TGF-β pathway-related proteins were analyzed via Western blot. CLDN1 and EGFR were overexpressed in PTC tumors, correlating with higher-risk patients and reduced CD8+ T cell infiltration. Silencing these genes inhibited tumor cell functions and enhanced CD8+ T cell activity, both in vitro and in vivo. CLDN1 and EGFR are crucial in PTC, linked to tumor invasiveness, EMT, and immune suppression, presenting them as potential therapeutic targets.

Common pitfalls in drug target Mendelian randomization and how to avoid them

BACKGROUND

Drug target Mendelian randomization describes the use of genetic variants as instrumental variables for studying the effects of pharmacological agents. The paradigm can be used to inform on all aspects of drug development and has become increasingly popular over the last decade, particularly given the time- and cost-efficiency with which it can be performed even before commencing clinical studies.

MAIN BODY

In this review, we describe the recent emergence of drug target Mendelian randomization, its common pitfalls, how best to address them, as well as potential future directions. Throughout, we offer advice based on our experiences on how to approach these types of studies, which we hope will be useful for both practitioners and those translating the findings from such work.

CONCLUSIONS

Drug target Mendelian randomization is nuanced and requires a combination of biological, statistical, genetic, epidemiological, clinical, and pharmaceutical expertise to be utilized to its full potential. Unfortunately, these skillsets are relatively infrequently combined in any given study.

Association of dietary and circulating antioxidant vitamins with metabolic syndrome: an observational and Mendelian randomization study

Aims

The objective of this study was to investigate the associations of dietary and circulating antioxidant vitamins with metabolic syndrome (MetS), and to assess causality using Mendelian randomization (MR).

Methods

This study included 10,308 participants from the National Health and Nutrition Examination Survey. The associations of vitamins A, C, E and carotenoids with MetS were assessed using multivariable weighted logistic regression analysis. Subsequently, the MR approach was employed to test the causal associations, with inverse variance weighted (IVW) serving as the primary analysis.

Results

Observationally, dietary vitamin A (OR=0.852, 95%CI: 0.727-0.999), C (OR=0.802, 95%CI: 0.675-0.952), carotene (OR=0.832, 95%CI: 0.706-0.982), and β-carotene (OR=0.838, 95%CI: 0.706-0.995) in quartile 4 had lower incidents of MetS, when compared to quartile 1. Circulating vitamin C and carotene were also present inversely associated with MetS, while the vitamin A and E both increased this risk. IVW-MR confirmed the associations of dietary vitamin A (OR=0.920, 95%CI: 0.861-0.984), vitamin C (OR=0.905, 95%CI: 0.836-0.979) and carotene (OR=0.918, 95%CI: 0.865-0.974) with MetS. However, there was only circulating β-carotene (OR=0.909, 95%CI: 0.857-0.965) was found to be causally associated with MetS.

Conclusions

Observational and MR studies have shown that adequate dietary intake of vitamin A, C and carotenoids may help to reduce the risk of MetS.

Causal associations between type 2 diabetes mellitus, glycemic traits, dietary habits and the risk of pressure ulcers: univariable, bidirectional and multivariable Mendelian randomization

Objective

Previous research has established a connection between Type 2 Diabetes Mellitus (T2DM), glycemic traits, dietary habits, and the risk of Pressure Ulcers (PUs). The aim of our study is to disentangle any potential causal relationship between T2DM, glycemic traits, and dietary factors, and the risk of PUs.

Methods

The exposure and outcome datasets were sourced from the IEU Open GWAS project, the Meta-Analyses of Glucose and Insulin-related traits Consortium (MAGIC), and the FinnGen biobank, respectively. The primary MR analysis method employed was the inverse variance-weighted method. Furthermore, we employed multivariable MR (MVMR) adjusting for BMI. Then, we investigated the possibility of a reverse association between glycemic traits and PUs through bidirectional MR. Finally, Heterogeneity and pleiotropic analysis were conducted to ensure the accuracy and robustness of the results.

Results

The findings revealed that T2DM (OR = 1.282, 95% CI: 1.138-1.445, p < 0.001) and Fasting Glucose (FG; OR = 2.111, 95% CI: 1.080-4.129, p = 0.029) were associated with an increased risk of PUs, while salad/raw vegetable intake (OR: 0.014; 95% CI: 0.001-0.278; p = 0.005) was identified as a protective element. However, no other dietary elements demonstrated a statistically significant causality with PUs. In addition, in the reverse direction, there were positive correlation between genetic susceptibility to PUs and an increase in FG (OR: 1.007, 95% CI: 1.000-1.013, p = 0.048) and Fasting Insulin (FI; OR: 1.012, 95% CI: 1.003-1.022, p = 0.011). MVMR results indicated that the causal effect of T2DM on PUs was independent of BMI (OR: 1.260, 95% CI: 1.112-1.427, p < 0.001). These results remained robust when considering weak instrument bias, pleiotropy, and heterogeneity.

Conclusion

This study establishes a causal link between genetically predicted T2DM, FG and an increased risk of PUs. Conversely, Salad/raw vegetable intake is significantly inversely associated with PUs. Simultaneously, we identified two downstream effector factor (FG and FI) that were associated with PUs. These findings may have clinical implications for both prevention and treatment.

Mapping biological influences on the human plasma proteome beyond the genome

Broad-capture proteomic platforms now enable simultaneous assessment of thousands of plasma proteins, but most of these are not actively secreted and their origins are largely unknown. Here we integrate genomic with deep phenomic information to identify modifiable and non-modifiable factors associated with 4,775 plasma proteins in ~8,000 mostly healthy individuals. We create a data-driven map of biological influences on the human plasma proteome and demonstrate segregation of proteins into clusters based on major explanatory factors. For over a third (N = 1,575) of protein targets, joint genetic and non-genetic factors explain 10-77% of the variation in plasma (median 19.88%, interquartile range 14.01-31.09%), independent of technical factors (median 2.48%, interquartile range 0.78-6.41%). Together with genetically anchored causal inference methods, our map highlights potential causal associations between modifiable risk factors and plasma proteins for hundreds of protein-disease associations, for example, COL6A3, which possibly mediates the association between reduced kidney function and cardiovascular disease. We provide a map of biological and technical influences on the human plasma proteome to help contextualize findings from proteomic studies.

Genetic architecture of oral glucose-stimulated insulin release provides biological insights into type 2 diabetes aetiology

The genetics of β-cell function (BCF) offer valuable insights into the aetiology of type 2 diabetes (T2D)1,2. Previous studies have expanded the catalogue of BCF genetic associations through candidate gene studies3-7, large-scale genome-wide association studies (GWAS) of fasting BCF8,9 or functional islet studies on T2D risk variants10-14. Nonetheless, GWAS focused on BCF traits derived from oral glucose tolerance test (OGTT) data have been limited in sample size15,16 and have often overlooked the potential for related traits to capture distinct genetic features of insulin-producing β-cells17,18. We reasoned that investigating the genetic basis of multiple BCF estimates could provide a broader understanding of β-cell physiology. Here, we aggregate GWAS data of eight OGTT-based BCF traits from ~26,000 individuals of European descent, identifying 55 independent genetic associations at 44 loci. By examining the effects of BCF genetic signals on related phenotypes, we uncover diverse disease mechanisms whereby genetic regulation of BCF may influence T2D risk. Integrating BCF-GWAS data with pancreatic islet transcriptomic and epigenomic datasets reveals 92 candidate effector genes. Gene silencing in β-cell models highlights ACSL1 and FAM46C as key regulators of insulin secretion. Overall, our findings yield insights into the biology of insulin release and the molecular processes linking BCF to T2D risk, shedding light on the heterogeneity of T2D pathophysiology.

Hemoglobin A1c Genetics and Disparities in Risk of Diabetic Retinopathy in Individuals of Genetically Inferred African American/African British and European Ancestries

OBJECTIVE

Individuals with diabetes who carry genetic variants that lower hemoglobin A1c (HbA1c) independently of glycemia may have higher real, but undetected, hyperglycemia compared with those without these variants despite achieving similar HbA1c targets, potentially placing them at greater risk for diabetes-related complications. We sought to determine whether these genetic variants, aggregated in a polygenic score, and the large-effect African ancestry-specific missense variant in G6PD (rs1050828) that lower HbA1c were associated with higher retinopathy risk.

RESEARCH DESIGN AND METHODS

Using data from 29,828 type 2 diabetes cases of genetically inferred African American/African British and European ancestries, we calculated ancestry-specific nonglycemic HbA1c polygenic scores (ngA1cPS) composed of 122 variants associated with HbA1c at genome-wide significance, but not with glucose. We tested the association of the ngA1cPS and the G6PD variant with retinopathy, adjusting for measured HbA1c and retinopathy risk factors.

RESULTS

Participants in the bottom quintile of the ngA1cPS showed between 20% and 50% higher retinopathy prevalence, compared with those above this quintile, despite similar levels of measured HbA1c. The adjusted meta-analytic odds ratio for the bottom quintile was 1.31 (95% CI 1.0, 1.73; P = 0.05) in African ancestry and 1.31 (95% CI 1.15, 1.50; P = 6.5 × 10-5) in European ancestry. Among individuals of African ancestry with HbA1c below 7%, retinopathy prevalence was higher in individuals below, compared with above, the 50th percentile of the ngA1cPS regardless of sex or G6PD carrier status.

CONCLUSIONS

Genetic effects need to be considered to personalize HbA1c targets and improve outcomes of people with diabetes from diverse ancestries.

Adiposity and metabolic health in Asian populations: an epidemiological study using dual-energy x-ray absorptiometry in Singapore

BACKGROUND

Type 2 diabetes, cardiovascular disease, and related cardiometabolic disturbances are increasing rapidly in the Asia-Pacific region. We investigated the contribution of excess adiposity, a key determinant of type 2 diabetes and cardiovascular risk, to unfavourable cardiometabolic profiles among Asian ethnic subgroups.

METHODS

The Health for Life in Singapore (HELIOS) Study is a population-based cohort comprising multiethnic Asian men and women living in Singapore, aged 30-84 years. We performed a cross-sectional analysis of data from individuals who had assessment of body composition by dual-energy x-ray absorptiometry and metabolic characterisation. In a subset of participants on no medication for type 2 diabetes, hypertension, and hypercholesterolaemia, we tested the relationship of BMI and visceral fat mass index (vFMI) with cardiometabolic phenotypes (glycaemic indices, lipid levels, and blood pressure), disease outcomes (type 2 diabetes, hypercholesterolaemia, and hypertension), and metabolic syndrome score with multivariable regression analyses.

FINDINGS

Between April 2, 2018, and Jan 28, 2022, 10 004 individuals consented to be part of the HELIOS cohort, of whom 9067 were included in the study (5404 [59·6%] female, 3663 [40·4%] male; 6224 [68·6%] Chinese, 1169 [12·9%] Malay, 1674 [18·5%] Indian; mean age 52·8 years [SD 11·8]). The prevalence of type 2 diabetes, hypercholesterolaemia, and hypertension was 8·2% (n=744), 27·2% (n=2469), and 18·0% (n=1630), respectively. Malay and Indian participants had 3-4-times higher odds of obesity and type 2 diabetes, and showed adverse metabolic and adiposity profiles, compared with Chinese participants. Excess adiposity was associated with adverse cardiometabolic health indices including type 2 diabetes (p<0·0001). However, while vFMI explained the differences in triglycerides and blood pressure between the Asian ethnic groups, increased vFMI did not explain higher glucose levels, reduced insulin sensitivity, and increased risk of type 2 diabetes among Indian participants.

INTERPRETATION

Visceral adiposity is an independent risk factor for metabolic disease in Asian populations, and accounts for a large fraction of type 2 diabetes cases in each of the ethnic groups studied. However, the variation in insulin resistance and type 2 diabetes risk between Asian subgroups is not consistently explained by adiposity, indicating an important role for additional mechanisms underlying the susceptibility to cardiometabolic disease in Asian populations.

FUNDING

Nanyang Technological University-the Lee Kong Chian School of Medicine, National Healthcare Group, and National Medical Research Council, Singapore.

A Mendelian randomization study on causal relationship between metabolic factors and abnormal spermatozoa

Background

Male infertility is a global health problem. There is an increasing attention on the association of metabolic status with spermatogenesis. However, the impacts of metabolic factors on semen parameters are still unclear. To provide evidence for developing appropriate interventions on disease screening and prevention, we performed a Mendelian randomization (MR) analysis to assess causality between various metabolic factors and abnormal spermatozoa.

Methods

We conducted a two-sample MR study to appraise the causal effects of 16 metabolic factors (including indexes of metabolic traits, glucose metabolism, lipid profile, adipokines, uric acid and metabolic diseases) on abnormal spermatozoa from genome-wide association studies (GWASs). Filtering with strict criteria, eligible genetic instruments closely associated with each of the factors were extracted. We employed inverse variance weighted for major analysis, with supplement MR methods including MR-Egger and weighted median. Heterogeneity and pleiotropy tests were further used to detect the reliability of analysis.

Results

After rigorous quality control in this MR framework, we identified that body fat percentage [odds ratio (OR) =1.49, 95% confidence interval (CI): 1.01-2.20, P=0.046] and resistin (OR =1.55, 95% CI: 1.11-2.19, P=0.01) were causally associated with a higher risk of abnormal spermatozoa. In terms of other indexes of metabolic traits, glucose metabolism, serum lipid profile and uric acid and metabolic diseases including type 2 diabetes mellitus (T2DM) and non-alcoholic fatty liver disease (NAFLD), no causal effects were observed (P>0.05).

Conclusions

Our MR analysis provides robust evidence that body fat percentage and resistin are risk factors for abnormal spermatozoa, suggesting implications of identifying them for potential interventions and clinical therapies in male infertility. Further investigation in larger-scale GWASs on subgroups of abnormal spermatozoa will verify impacts of metabolic factors on spermatogenesis.

Causal effects of cardiovascular health on five epigenetic clocks

BACKGROUND

This work delves into the relationship between cardiovascular health (CVH) and aging. Previous studies have shown an association of ideal CVH with a slower aging rate, measured by epigenetic age acceleration (EAA). However, the causal relationship between CVH and EAA has remained unexplored.

METHODS AND RESULTS

We performed genome-wide association studies (GWAS) on the (12-point) CVH score and its components using the Taiwan Biobank data, in which weighted genetic risk scores were treated as instrumental variables. Subsequently, we conducted a one-sample Mendelian Randomization (MR) analysis with the two-stage least-squares method on 2383 participants to examine the causal relationship between the (12-point) CVH score and EAA. As a result, we observed a significant causal effect of the CVH score on GrimAge acceleration (GrimEAA) (β [SE]: - 0.993 [0.363] year; p = 0.0063) and DNA methylation-based plasminogen activator inhibitor-1 (DNAmPAI-1) (β [SE]: - 0.294 [0.099] standard deviation (sd) of DNAmPAI-1; p = 0.0030). Digging individual CVH components in depth, the ideal total cholesterol score (0 [poor], 1 [intermediate], or 2 [ideal]) was causally associated with DNAmPAI-1 (β [SE]: - 0.452 [0.150] sd of DNAmPAI-1; false discovery rate [FDR] q = 0.0102). The ideal body mass index (BMI) score was causally associated with GrimEAA (β [SE]: - 2.382 [0.952] years; FDR q = 0.0498) and DunedinPACE (β [SE]: - 0.097 [0.030]; FDR q = 0.0044). We also performed a two-sample MR analysis using the summary statistics from European GWAS. We observed that the (12-point) CVH score exhibits a significant causal effect on Horvath's intrinsic epigenetic age acceleration (β [SE]: - 0.389 [0.186] years; p = 0.036) and GrimEAA (β [SE]: - 0.526 [0.244] years; p = 0.031). Furthermore, we detected causal effects of BMI (β [SE]: 0.599 [0.081] years; q = 2.91E-12), never smoking (β [SE]: - 2.981 [0.524] years; q = 1.63E-7), walking (β [SE]: - 4.313 [1.236] years; q = 0.004), and dried fruit intake (β [SE]: - 1.523 [0.504] years; q = 0.013) on GrimEAA in the European population.

CONCLUSIONS

Our research confirms the causal link between maintaining an ideal CVH and epigenetic age. It provides a tangible pathway for individuals to improve their health and potentially slow aging.

Exploring the design of clinical research studies on the efficacy mechanisms in type 2 diabetes mellitus

This review examines the complexities of Type 2 Diabetes Mellitus (T2DM), focusing on the critical role of integrating omics technologies with traditional experimental methods. It underscores the advancements in understanding the genetic diversity of T2DM and emphasizes the evolution towards personalized treatment modalities. The paper analyzes a variety of omics approaches, including genomics, methylation, transcriptomics, proteomics, metabolomics, and intestinal microbiomics, delineating their substantial contributions to deciphering the multifaceted mechanisms underlying T2DM. Furthermore, the review highlights the indispensable role of non-omics experimental techniques in comprehending and managing T2DM, advocating for their integration in the development of tailored medicine and precision treatment strategies. By identifying existing research gaps and suggesting future research trajectories, the review underscores the necessity for a comprehensive, multidisciplinary approach. This approach synergistically combines clinical insights with cutting-edge biotechnologies, aiming to refine the management and therapeutic interventions of T2DM, and ultimately enhancing patient outcomes. This synthesis of knowledge and methodologies paves the way for innovative advancements in T2DM research, fostering a deeper understanding and more effective treatment of this complex condition.

Understanding the Genetic Landscape of Gestational Diabetes: Insights into the Causes and Consequences of Elevated Glucose Levels in Pregnancy

Background/Objectives: During pregnancy, physiological changes in maternal circulating glucose levels and its metabolism are essential to meet maternal and fetal energy demands. Major changes in glucose metabolism occur throughout pregnancy and consist of higher insulin resistance and a compensatory increase in insulin secretion to maintain glucose homeostasis. For some women, this change is insufficient to maintain normoglycemia, leading to gestational diabetes mellitus (GDM), a condition characterized by maternal glucose intolerance and hyperglycaemia first diagnosed during the second or third trimester of pregnancy. GDM is diagnosed in approximately 14.0% of pregnancies globally, and it is often associated with short- and long-term adverse health outcomes in both mothers and offspring. Although recent studies have highlighted the role of genetic determinants in the development of GDM, research in this area is still lacking, hindering the development of prevention and treatment strategies. Methods: In this paper, we review recent advances in the understanding of genetic determinants of GDM and glycaemic traits during pregnancy. Results/Conclusions: Our review highlights the need for further collaborative efforts as well as larger and more diverse genotyped pregnancy cohorts to deepen our understanding of the genetic aetiology of GDM, address research gaps, and further improve diagnostic and treatment strategies.

Deciphering the role of FOXP4 in long COVID: exploring genetic associations, evolutionary conservation, and drug identification through bioinformatics analysis

Long COVID (LC) refers to a condition characterized by a variety of lingering symptoms that persist for more than 4 to 12 weeks following the initial acute SARS-CoV-2 infection. Recent research has suggested that the FOXP4 gene could potentially be a significant factor contributing to LC. Owing to that, this study investigates FOXP4's role in LC by analyzing public datasets to understand its evolution and expression in diverse human populations and searching for drugs to reduce LC symptoms. Population genetic analysis of FOXP4 across human populations unmasks distinct genetic diversity patterns and positive selection signatures, suggesting potential population-specific susceptibilities to conditions like LC. Further, we also observed that FOXP4 experiences high expression during LC. To identify potential inhibitors, drug screening analysis identifies synthetic drugs like Glisoxepide, and natural compounds Kapurimycin A3 produced from Streptomyces sp, and Cucurbitacin B from Begonia nantoensis as promising candidates. Overall, our research contributes to understanding how FOXP4 may serve as a therapeutic target for mitigating the impact of LC.

Malignant Transformation of Normal Oral Tissue to Dysplasia and Early Oral Squamous Cell Carcinoma: An In Silico Transcriptomics Approach

Background: Oral squamous cell carcinoma (OSCC) is a prevalent and aggressive form of head and neck cancer, often diagnosed at advanced stages. Elucidating the molecular mechanisms involved in the malignant transformation from normal oral tissue to oral preinvasive lesions (OPL) and primary OSCC could facilitate early diagnosis and improve therapeutic strategies. Methods: Differentially expressed genes (DEGs) were identified from the GSE30784 dataset by comparing normal oral tissue, oral dysplasia, and primary OSCC samples. Cross-validation was performed using an independent RNA-seq dataset, GSE186775. Protein-protein interaction (PPI) network analysis, gene ontology annotation, and pathway enrichment analysis were conducted on the common DEGs. Hub genes were identified, and their prognostic significance was evaluated using survival analysis. Transcription factor (TF) enrichment analysis, cross-validation, and immunohistochemistry analyses were also performed. Results: A total of 226 proteins and 677 interactions were identified in the PPI network, with 34 hub genes, including FN1, SERPINE1, PLAUR, THBS1, and ITGA6. Pathways such as "Formation of the cornified envelope," "Keratinization," and "Developmental biology" were enriched. Overexpression of SERPINE1, PLAUR, THBS1, and ITGA6 correlated with poor prognosis, while upregulation of CALML5 and SPINK5 was associated with favorable outcomes. NFIB emerged as the most significant TF-regulating hub genes. Immunohistochemistry validated ITGA6 overexpression in primary OSCC. Cross-validation using the RNA-seq dataset supported the involvement of critical genes in the malignant transformation process. Conclusion: This study identified vital genes, pathways, and prognostic markers involved in the malignant transformation from normal oral tissue to OPL and primary OSCC, providing insights for early diagnosis and targeted therapy development. Cross-validation with an independent RNA-seq dataset and immunohistochemistry reinforced the findings, supporting the robustness of the identified molecular signatures.

Genome-wide discovery and integrative genomic characterization of insulin resistance loci using serum triglycerides to HDL-cholesterol ratio as a proxy

Insulin resistance causes multiple epidemic metabolic diseases, including type 2 diabetes, cardiovascular disease, and fatty liver, but is not routinely measured in epidemiological studies. To discover novel insulin resistance genes in the general population, we conducted genome-wide association studies in 382,129 individuals for triglyceride to HDL-cholesterol ratio (TG/HDL), a surrogate marker of insulin resistance calculable from commonly measured serum lipid profiles. We identified 251 independent loci, of which 62 were more strongly associated with TG/HDL compared to TG or HDL alone, suggesting them as insulin resistance loci. Candidate causal genes at these loci were prioritized by fine mapping with directions-of-effect and tissue specificity annotated through analysis of protein coding and expression quantitative trait variation. Directions-of-effect were corroborated in an independent cohort of individuals with directly measured insulin resistance. We highlight two phospholipase encoding genes, PLA2G12A and PLA2G6, which liberate arachidonic acid and improve insulin sensitivity, and VGLL3, a transcriptional co-factor that increases insulin resistance partially through enhanced adiposity. Finally, we implicate the anti-apoptotic gene TNFAIP8 as a sex-dimorphic insulin resistance factor, which acts by increasing visceral adiposity, specifically in females. In summary, our study identifies several candidate modulators of insulin resistance that have the potential to serve as biomarkers and pharmacological targets.

SMIM1 absence is associated with reduced energy expenditure and excess weight

BACKGROUND

Obesity rates have nearly tripled in the past 50 years, and by 2030 more than 1 billion individuals worldwide are projected to be obese. This creates a significant economic strain due to the associated non-communicable diseases. The root cause is an energy expenditure imbalance, owing to an interplay of lifestyle, environmental, and genetic factors. Obesity has a polygenic genetic architecture; however, single genetic variants with large effect size are etiological in a minority of cases. These variants allowed the discovery of novel genes and biology relevant to weight regulation and ultimately led to the development of novel specific treatments.

METHODS

We used a case-control approach to determine metabolic differences between individuals homozygous for a loss-of-function genetic variant in the small integral membrane protein 1 (SMIM1) and the general population, leveraging data from five cohorts. Metabolic characterization of SMIM1-/- individuals was performed using plasma biochemistry, calorimetric chamber, and DXA scan.

FINDINGS

We found that individuals homozygous for a loss-of-function genetic variant in SMIM1 gene, underlying the blood group Vel, display excess body weight, dyslipidemia, altered leptin to adiponectin ratio, increased liver enzymes, and lower thyroid hormone levels. This was accompanied by a reduction in resting energy expenditure.

CONCLUSION

This research identified a novel genetic predisposition to being overweight or obese. It highlights the need to investigate the genetic causes of obesity to select the most appropriate treatment given the large cost disparity between them.

FUNDING

This work was funded by the National Institute of Health Research, British Heart Foundation, and NHS Blood and Transplant.

Predictive Prioritization of Enhancers Associated with Pancreas Disease Risk

Genetic and epigenetic variations in regulatory enhancer elements increase susceptibility to a range of pathologies. Despite recent advances, linking enhancer elements to target genes and predicting transcriptional outcomes of enhancer dysfunction remain significant challenges. Using 3D chromatin conformation assays, we generated an extensive enhancer interaction dataset for the human pancreas, encompassing more than 20 donors and five major cell types, including both exocrine and endocrine compartments. We employed a network approach to parse chromatin interactions into enhancer-promoter tree models, facilitating a quantitative, genome-wide analysis of enhancer connectivity. With these tree models, we developed a machine learning algorithm to estimate the impact of enhancer perturbations on cell type-specific gene expression in the human pancreas. Orthogonal to our computational approach, we perturbed enhancer function in primary human pancreas cells using CRISPR interference and quantified the effects at the single-cell level through RNA FISH coupled with high-throughput imaging. Our enhancer tree models enabled the annotation of common germline risk variants associated with pancreas diseases, linking them to putative target genes in specific cell types. For pancreatic ductal adenocarcinoma, we found a stronger enrichment of disease susceptibility variants within acinar cell regulatory elements, despite ductal cells historically being assumed as the primary cell-of-origin. Our integrative approach-combining cell type-specific enhancer-promoter interaction mapping, computational models, and single-cell enhancer perturbation assays-produced a robust resource for studying the genetic basis of pancreas disorders.

Genetic estimation of causalities between educational attainment with common digestive tract diseases and the mediating pathways

BACKGROUND

The association between education, intelligence, and cognition with digestive tract diseases has been established. However, the specific contribution of each factor in the pathogenesis of these diseases are still uncertain.

METHOD

This study employed multivariable Mendelian randomization (MR) to assess the independent effects of education, intelligence, and cognition on gastrointestinal conditions in the FinnGen and UK Biobank European-ancestry populations. A two-step MR approach was employed to assess the mediating effects of the association.

RESULTS

Meta-analysis of MR estimates from FinnGen and UK Biobank showed that 1- SD (4.2 years) higher education was causally associated with lower risks of gastroesophageal reflux (OR: 0.58; 95% CI: 0.50, 0.66), peptic ulcer (OR: 0.57; 95% CI: 0.47, 0.69), irritable bowel syndrome (OR: 0.70; 95% CI: 0.56, 0.87), diverticular disease (OR: 0.69; 95% CI: 0.61, 0.78), cholelithiasis (OR: 0.68; 95% CI: 0.59, 0.79) and acute pancreatitis (OR: 0.54; 95% CI: 0.41, 0.72), independently of intelligence and cognition. These causal associations were mediating by body mass index (3.7-22.3%), waist-to-hip ratio (8.3-11.9%), body fat percentage (4.1-39.8%), fasting insulin (1.4-5.5%) and major depression (6.0-12.4%).

CONCLUSION

Our findings demonstrate a causal and independent association between education and six common digestive tract diseases. Additionally, our study highlights five mediators as crucial targets for preventing digestive tract diseases associated with lower education levels.

Association between Serum Glycated Hemoglobin Levels and Female Infertility: A Cross-Sectional Survey and Genetic Approach

Female infertility affects a significant portion of the population, and recent studies suggest a potential link between glycemic control and reproductive health. This study investigates the association between serum glycated hemoglobin (HbA1c) levels and female infertility, utilizing data from the NHANES 2017-2020 and Mendelian randomization (MR) analysis. A cross-sectional study was conducted with 1578 women aged 20-45 who attempted pregnancy for at least one year. Serum HbA1c levels were analyzed in relation to infertility status, with multivariable logistic regression models adjusting for covariates such as age, body mass index, race/ethnicity, education, marital status, hypertension, and hyperlipidemia. Higher HbA1c levels were significantly associated with increased infertility risk. Each 1% increase in HbA1c was linked to higher odds of infertility (adjusted OR: 1.40, 95% CI: 1.15-1.69, p = 0.003). HbA1c levels ≥ 6.5% showed the strongest association. MR analysis employed single-nucleotide polymorphisms as instrumental variables to assess the causal relationship between HbA1c and infertility, confirming a causal relationship between higher genetically predicted HbA1c levels and infertility (OR: 1.82, 95% CI: 1.33-2.49, p = 0.00018). Sensitivity analyses supported the robustness of these findings. Elevated HbA1c levels are associated with an increased risk of female infertility, suggesting the importance of glycemic control in reproductive health management.

Liver eQTL meta-analysis illuminates potential molecular mechanisms of cardiometabolic traits

Understanding the molecular mechanisms of complex traits is essential for developing targeted interventions. We analyzed liver expression quantitative-trait locus (eQTL) meta-analysis data on 1,183 participants to identify conditionally distinct signals. We found 9,013 eQTL signals for 6,564 genes; 23% of eGenes had two signals, and 6% had three or more signals. We then integrated the eQTL results with data from 29 cardiometabolic genome-wide association study (GWAS) traits and identified 1,582 GWAS-eQTL colocalizations for 747 eGenes. Non-primary eQTL signals accounted for 17% of all colocalizations. Isolating signals by conditional analysis prior to coloc resulted in 37% more colocalizations than using marginal eQTL and GWAS data, highlighting the importance of signal isolation. Isolating signals also led to stronger evidence of colocalization: among 343 eQTL-GWAS signal pairs in multi-signal regions, analyses that isolated the signals of interest resulted in higher posterior probability of colocalization for 41% of tests. Leveraging allelic heterogeneity, we predicted causal effects of gene expression on liver traits for four genes. To predict functional variants and regulatory elements, we colocalized eQTL with liver chromatin accessibility QTL (caQTL) and found 391 colocalizations, including 73 with non-primary eQTL signals and 60 eQTL signals that colocalized with both a caQTL and a GWAS signal. Finally, we used publicly available massively parallel reporter assays in HepG2 to highlight 14 eQTL signals that include at least one expression-modulating variant. This multi-faceted approach to unraveling the genetic underpinnings of liver-related traits could lead to therapeutic development.

Associations between blood glucose and early- and late-onset colorectal cancer: evidence from two prospective cohorts and Mendelian randomization analyses

Background

The incidence of early-onset colorectal cancer (EOCRC), which exhibits differential clinical, pathological, and molecular features compared to late-onset CRC (LOCRC), is rising globally. The potential differential effects of blood glucose on EOCRC compared to LOCRC have not been investigated.

Methods

This study analyzed 374,568 participants from the UK Biobank cohort and 172,809 participants from the Kailuan cohort. The linear associations between blood glucose and EOCRC/LOCRC were estimated using Cox regression models. Restricted cubic spline (RCS) analysis and non-linear Mendelian randomization (MR) analysis using a 70-SNPs genetic instrument for fasting glucose were used to explore the potential non-linear associations.

Results

Participants in the highest quintile of blood glucose had higher overall CRC risk compared to the lowest quintile (HR = 1.10 in the UK Biobank cohort, 95% CI: 1.01-1.21, P-trend = 0.012; HR = 1.23 in the Kailuan cohort, 95% CI: 1.01-1.51, P-trend = 0.036). Elevated glucose (>7.0 mmol/L) was more strongly associated with increased risk of EOCRC (HR = 1.61, 95% CI: 1.07-2.44) than with LOCRC (HR = 1.14, 95% CI: 1.02-1.27) in the UK Biobank cohort (P-heterogeneity = 0.014). Elevated glucose (>7.0 mmol/L) was associated with increased risk of LOCRC (HR = 1.25, 95% CI: 1.04-1.65) in the Kailuan cohort as well. There was no evidence for non-linear associations between blood glucose and risks of EOCRC/LOCRC.

Conclusions

This study showed a positive association between blood glucose and CRC risk in a dose-response manner, particularly for EOCRC, suggesting that tighter glucose control should be a priority for younger age groups.

Individual cereals intake is associated with progression of diabetes and diabetic chronic complications

BACKGROUND AND AIMS

The relationship between cereals intake and diabetes is unclear. We aimed to explore associations between individual cereals intake and risks of incident and progression of diabetes.

METHODS

We included 502,490 participants from UK Biobank at baseline. A single touchscreen food frequency questionnaire was used to estimate the intake of individual cereals (bran, biscuit, oat, muesli, and other cereals). Main outcomes included incident diabetes and diabetic complications of cardiovascular disease (CVD), chronic kidney disease (CKD) and diabetic retinopathy (DR). Polygenic risk score (PRS) of glycosylated hemoglobin (HbA1c) was calculated for mediating effects analysis.

RESULTS

Among participants without diabetes, when compared to subjects who never had cereals, hazard ratios (95%CI) of developing diabetes in those who had ≥6 bowls/week were 0.72 (0.67-0.78) for bran, 0.86 (0.81-0.92) for biscuit, 0.75(0.66-0.84) for oat, and 0.57(0.53,0.61) for muesli. Among people with diabetes without CVD, a higher intake of aforementioned four individual cereals was associated with a 13%-32 % lower risk of developing CVD. Among people with diabetes without CKD, a higher intake of aforementioned four individual cereals was associated with a 9%-28 % lower risk of developing CKD. We observed a significant mediating effect of the PRS of HbA1c for the association between aforementioned four individual cereals and developing diabetes.

CONCLUSION

A higher consumption of cereals was significantly associated with lower risks of diabetes and diabetic complications. Polygenic of HbA1c mediates the effect of cereals on incident diabetes.

Characterizing Common and Rare Variations in Nontraditional Glycemic Biomarkers Using Multivariate Approaches on Multiancestry ARIC Study

Genetic studies of nontraditional glycemic biomarkers, glycated albumin and fructosamine, can shed light on unknown aspects of type 2 diabetes genetics and biology. We performed a multiphenotype genome-wide association study of glycated albumin and fructosamine from 7,395 White and 2,016 Black participants in the Atherosclerosis Risk in Communities (ARIC) study on common variants from genotyped/imputed data. We discovered two genome-wide significant loci, one mapping to a known type 2 diabetes gene (ARAP1/STARD10) and another mapping to a novel region (UGT1A complex of genes), using multiomics gene-mapping strategies in diabetes-relevant tissues. We identified additional loci that were ancestry- and sex-specific (e.g., PRKCA in African ancestry, FCGRT in European ancestry, TEX29 in males). Further, we implemented multiphenotype gene-burden tests on whole-exome sequence data from 6,590 White and 2,309 Black ARIC participants. Ten variant sets annotated to genes across different variant aggregation strategies were exome-wide significant only in multiancestry analysis, of which CD1D, EGFL7/AGPAT2, and MIR126 had notable enrichment of rare predicted loss of function variants in African ancestry despite smaller sample sizes. Overall, 8 of 14 discovered loci and genes were implicated to influence these biomarkers via glycemic pathways, and most of them were not previously implicated in studies of type 2 diabetes. This study illustrates improved locus discovery and potential effector gene discovery by leveraging joint patterns of related biomarkers across the entire allele frequency spectrum in multiancestry analysis. Future investigation of the loci and genes potentially acting through glycemic pathways may help us better understand the risk of developing type 2 diabetes.

ARTICLE HIGHLIGHTS

Current approaches in CRISPR-Cas systems for diabetes

In the face of advancements in health care and a shift towards healthy lifestyle, diabetes mellitus (DM) still presents as a global health challenge. This chapter explores recent advancements in the areas of genetic and molecular underpinnings of DM, addressing the revolutionary potential of CRISPR-based genome editing technologies. We delve into the multifaceted relationship between genes and molecular pathways contributing to both type1 and type 2 diabetes. We highlight the importance of how improved genetic screening and the identification of susceptibility genes are aiding in early diagnosis and risk stratification. The spotlight then shifts to CRISPR-Cas9, a robust genome editing tool capable of various applications including correcting mutations in type 1 diabetes, enhancing insulin production in T2D, modulating genes associated with metabolism of glucose and insulin sensitivity. Delivery methods for CRISPR to targeted tissues and cells are explored, including viral and non-viral vectors, alongside the exciting possibilities offered by nanocarriers. We conclude by discussing the challenges and ethical considerations surrounding CRISPR-based therapies for DM. These include potential off-target effects, ensuring long-term efficacy and safety, and navigating the ethical implications of human genome modification. This chapter offers a comprehensive perspective on how genetic and molecular insights, coupled with the transformative power of CRISPR, are paving the way for potential cures and novel therapeutic approaches for DM.

Causal associations between insulin and Lp(a) levels in Caucasian population: a Mendelian randomization study

BACKGROUND

Numerous observational studies have demonstrated that circulating lipoprotein(a) [Lp(a)] might be inversely related to the risk of type 2 diabetes (T2D). However, recent Mendelian randomization (MR) studies do not consistently support this association. The results of in vitro research suggest that high insulin concentrations can suppress Lp(a) levels by affecting apolipoprotein(a) [apo(a)] synthesis. This study aimed to identify the relationship between genetically predicted insulin concentrations and Lp(a) levels, which may partly explain the associations between low Lp(a) levels and increased risk of T2D.

METHODS

Independent genetic variants strongly associated with fasting insulin levels were identified from meta-analyses of genome-wide association studies in European populations (GWASs) (N = 151,013). Summary level data for Lp(a) in the population of European ancestry were acquired from a GWAS in the UK Biobank (N = 361,194). The inverse-variance weighted (IVW) method approach was applied to perform two-sample summary-level MR. Robust methods for sensitivity analysis were utilized, such as MR‒Egger, the weighted median (WME) method, MR pleiotropy residual sum and outlier (MR-PRESSO), leave-one-out analysis, and MR Steiger.

RESULTS

Genetically predicted fasting insulin levels were negatively associated with Lp(a) levels (β = - 0.15, SE = 0.05, P = 0.003). The sensitivity analysis revealed that WME (β = - 0.26, SE = 0.07, P = 0.0002), but not MR‒Egger (β = - 0.22, SE = 0.13, P = 0.11), supported a causal relationship between genetically predisposed insulin levels and Lp(a).

CONCLUSION

Our MR study provides robust evidence supporting the association between genetically predicted increased insulin concentrations and decreased concentrations of Lp(a). These findings suggest that hyperinsulinaemia, which typically accompanies T2D, can partially explain the inverse relationship between low Lp(a) concentrations and an increased risk of T2D.

Serum proteomic profiling of physical activity reveals CD300LG as a novel exerkine with a potential causal link to glucose homeostasis

Background

Physical activity has been associated with preventing the development of type 2 diabetes and atherosclerotic cardiovascular disease. However, our understanding of the precise molecular mechanisms underlying these effects remains incomplete and good biomarkers to objectively assess physical activity are lacking.

Methods

We analyzed 3072 serum proteins in 26 men, normal weight or overweight, undergoing 12 weeks of a combined strength and endurance exercise intervention. We estimated insulin sensitivity with hyperinsulinemic euglycemic clamp, maximum oxygen uptake, muscle strength, and used MRI/MRS to evaluate body composition and organ fat depots. Muscle and subcutaneous adipose tissue biopsies were used for mRNA sequencing. Additional association analyses were performed in samples from up to 47,747 individuals in the UK Biobank, as well as using two-sample Mendelian randomization and mice models.

Results

Following 12 weeks of exercise intervention, we observed significant changes in 283 serum proteins. Notably, 66 of these proteins were elevated in overweight men and positively associated with liver fat before the exercise regimen, but were normalized after exercise. Furthermore, for 19.7 and 12.1% of the exercise-responsive proteins, corresponding changes in mRNA expression levels in muscle and fat, respectively, were shown. The protein CD300LG displayed consistent alterations in blood, muscle, and fat. Serum CD300LG exhibited positive associations with insulin sensitivity, and to angiogenesis-related gene expression in both muscle and fat. Furthermore, serum CD300LG was positively associated with physical activity and negatively associated with glucose levels in the UK Biobank. In this sample, the association between serum CD300LG and physical activity was significantly stronger in men than in women. Mendelian randomization analysis suggested potential causal relationships between levels of serum CD300LG and fasting glucose, 2 hr glucose after an oral glucose tolerance test, and HbA1c. Additionally, Cd300lg responded to exercise in a mouse model, and we observed signs of impaired glucose tolerance in male, but not female, Cd300lg knockout mice.

Conclusions

Our study identified several novel proteins in serum whose levels change in response to prolonged exercise and were significantly associated with body composition, liver fat, and glucose homeostasis. Serum CD300LG increased with physical activity and is a potential causal link to improved glucose levels. CD300LG may be a promising exercise biomarker and a therapeutic target in type 2 diabetes.

Funding

South-Eastern Norway Regional Health Authority, Simon Fougners Fund, Diabetesforbundet, Johan Selmer Kvanes' legat til forskning og bekjempelse av sukkersyke. The UK Biobank resource reference 53641. Australian National Health and Medical Research Council Investigator Grant (APP2017942). Australian Research Council Discovery Early Career Award (DE220101226). Research Council of Norway (Project grant: 325640 and Mobility grant: 287198). The Medical Student Research Program at the University of Oslo. Novo Nordisk Fonden Excellence Emerging Grant in Endocrinology and Metabolism 2023 (NNF23OC0082123).

Clinical trial number

clinicaltrials.gov: NCT01803568.

The effect of SGLT2 inhibition on prostate cancer: Mendelian randomization and observational analysis using electronic healthcare and cohort data

We evaluated the effect of sodium-glucose cotransporter 2 (SGLT2) inhibition on prostate cancer by evidence triangulation. Using Mendelian randomization, we found that genetically proxied SGLT2 inhibition reduced the risk of overall (odds ratio = 0.56, 95% confidence interval [CI] = 0.38 to 0.82; 79,148 prostate cancer cases and 61,106 controls), advanced, and early-onset prostate cancer. Using electronic healthcare data (nSGLT2i = 24,155; nDPP4i = 24,155), we found that the use of SGLT2 inhibitors was associated with a 23% reduced risk of prostate cancer (hazard ratio = 0.77, 95% CI = 0.61 to 0.99) in men with diabetes. Using data from two prospective cohorts (n4C = 57,779; nUK_Biobank = 165,430), we found little evidence to support the association of HbA1c with prostate cancer, implying a non-glycemic effect of SGLT2 inhibition on prostate cancer. In summary, this study provides multiple layers of evidence to support the beneficial effect of SGLT2 inhibition on reducing prostate cancer risk. Future trials are warranted to investigate whether SGLT2 inhibitors can be recommended for prostate cancer prevention.

Causal link between metabolic related factors and osteoarthritis: a Mendelian randomization investigation

Introduction

Metabolic syndrome (MetS) is significantly associated with osteoarthritis (OA), especially in MetS patients with blood glucose abnormalities, such as elevated fasting blood glucose (FG), which may increase OA risk. Dietary modifications, especially the intake of polyunsaturated fatty acids (PUFAs), are regarded as a potential means of preventing MetS and its complications. However, regarding the effects of FG, Omega-3s, and Omega-6s on OA, the research conclusions are conflicting, which is attributed to the complexity of the pathogenesis of OA. Therefore, it is imperative to thoroughly evaluate multiple factors to fully understand their role in OA, which needs further exploration and clarification.

Methods

Two-sample univariable Mendelian randomization (UVMR) and multivariable Mendelian randomization (MVMR) were employed to examine the causal effect of metabolic related factors on hip OA (HOA) or knee OA (KOA). The exposure and outcome datasets were obtained from Open GWAS IEU. All cases were independent European ancestry data. Three MR methods were performed to estimate the causal effect: inverse-variance weighting (IVW), weighted median method (WMM), and MR-Egger regression. Additionally, the intercept analysis in MR-Egger regression is used to estimate pleiotropy, and the IVW method and MR-Egger regression are used to test the heterogeneity.

Results

The UVMR analysis revealed a causal relationship between FG and HOA. By MVMR analysis, the study discovered a significant link between FG (OR = 0.79, 95%CI: 0.64∼0.99, p = 0.036) and KOA after accounting for body mass index (BMI), age, and sex hormone-binding globulin (SHBG). However, no causal effects of FG on HOA were seen. Omega-3s and Omega-6s did not have a causal influence on HOA or KOA. No significant evidence of pleiotropy was identified.

Discussion

The MR investigation showed a protective effect of FG on KOA development but no causal relationship between FG and HOA. No causal effect of Omega-3s and Omega-6s on HOA and KOA was observed. Shared genetic overlaps might also exist between BMI and age, SHBG and PUFAs for OA development. This finding offers a novel insight into the treatment and prevention of KOA from glucose metabolism perspective. The FG cutoff value should be explored in the future, and consideration should be given to demonstrating the study in populations other than Europeans.

Effects of ACLY Inhibition on Body Weight Distribution: A Drug Target Mendelian Randomization Study

Background: Adenosine triphosphate-citrate lyase (ACLY) inhibition has proven clinically efficacious for low-density lipoprotein cholesterol (LDL-c) lowering and cardiovascular disease (CVD) risk reduction. Clinical and genetic evidence suggests that some LDL-c lowering strategies, such as 3-hydroxy-3-methylglutaryl-coenzyme A reductase (HMGCR) inhibition with statin therapy increase body weight and the risk of developing type 2 diabetes mellitus (T2DM). However, whether ACLY inhibition affects metabolic risk factors is currently unknown. We aimed to investigate the effects of ACLY inhibition on glycaemic and anthropometric traits using Mendelian randomization (MR). Methods: As genetic instruments for ACLY inhibition, we selected weakly correlated single-nucleotide polymorphisms at the ACLY gene associated with lower ACLY gene expression in the eQTLGen study (N = 31,684) and lower LDL-c levels in the Global Lipid Genetic Consortium study (N = 1.65 million). Two-sample Mendelian randomization was employed to investigate the effects of ACLY inhibition on T2DM risk, and glycaemic and anthropometric traits using summary data from large consortia, with sample sizes ranging from 151,013 to 806,834 individuals. Findings for genetically predicted ACLY inhibition were compared to those obtained for genetically predicted HMGCR inhibition using the same instrument selection strategy and outcome data. Results: Primary MR analyses showed that genetically predicted ACLY inhibition was associated with lower waist-to-hip ratio (β per 1 standard deviation lower LDL-c: -1.17; 95% confidence interval (CI): -1.61 to -0.73; p < 0.001) but not with risk of T2DM (odds ratio (OR) per standard deviation lower LDL-c: 0.74, 95% CI = 0.25 to 2.19, p = 0.59). In contrast, genetically predicted HMGCR inhibition was associated with higher waist-to-hip ratio (β = 0.15; 95%CI = 0.04 to 0.26; p = 0.008) and T2DM risk (OR = 1.73, 95% CI = 1.27 to 2.36, p < 0.001). The MR analyses considering secondary outcomes showed that genetically predicted ACLY inhibition was associated with a lower waist-to-hip ratio adjusted for body mass index (BMI) (β = -1.41; 95%CI = -1.81 to -1.02; p < 0.001). In contrast, genetically predicted HMGCR inhibition was associated with higher HbA1c (β = 0.19; 95%CI = 0.23 to 0.49; p < 0.001) and BMI (β = 0.36; 95%CI = 0.23 to 0.49; p < 0.001). Conclusions: Human genetic evidence supports the metabolically favourable effects of ACLY inhibition on body weight distribution, in contrast to HMGCR inhibition. These findings should be used to guide and prioritize ongoing clinical development efforts.

The role of the gluteofemoral adipose tissue in cerebrovascular disease risk: evidence from a mendelian randomization and mediation analysis

Objective

To explore causal associations between BMI-independent body fat distribution profiles and cerebrovascular disease risk, and to investigate potential mediators underlying these associations.

Methods

Leveraging data from genome wide association studies of BMI-independent gluteofemoral (GFAT), abdominal subcutaneous (ASAT), and visceral (VAT) adipose tissue volumes in UK Biobank, we selected variants associated with each trait, and performed univariable and multivariable mendelian randomization (MR) analyses on ischemic stroke and subtypes (large artery (LAS), cardioembolic (CES), small vessel (SVS)). We used coronary artery disease (CAD), carotid intima media thickness (cIMT), and an MRI-confirmed lacunar stroke as positive controls. For significant associations, we explored the mediatory role of four possible mediator categories in mediation MR analyses.

Results

Higher genetically proxied, BMI-independent GFAT volume was associated with decreased risk of ischemic stroke (FDR-p=0.0084), LAS (FDR-p=0.019), SVS (FDR-p<0.001), CAD (FDR-p<0.001), MRI-confirmed lacunar stroke (FDR-p=0.0053), and lower mean cIMT (FDR-p=0.0023), but not CES (FDR-p=0.749). Associations were largely consistent in pleiotropy- and sample structure-robust analyses. No association was observed between genetically proxied ASAT or VAT volumes and ischemic stroke/subtypes risk. In multivariable MR analyses, GFAT showed the most consistent independent association with ischemic stroke, LAS, and SVS. Common vascular risk factors were the predominant mediators in the GFAT-cerebrovascular disease axis, while adipose-tissue-specific adiponectin and leptin mediated a proportion of ischemic stroke and CAD risk.

Interpretation

Genetically proxied, BMI-independent higher GFAT volume is associated with reduced cerebrovascular disease risk. Although this is largely mediated by common vascular risk factor modification, targeting adipose-tissue specific pathways may provide additional cardiovascular benefit.

Single cell multiome profiling of pancreatic islets reveals physiological changes in cell type-specific regulation associated with diabetes risk

Physiological variability in pancreatic cell type gene regulation and the impact on diabetes risk is poorly understood. In this study we mapped gene regulation in pancreatic cell types using single cell multiomic (joint RNA-seq and ATAC-seq) profiling in 28 non-diabetic donors in combination with single cell data from 35 non-diabetic donors in the Human Pancreas Analysis Program. We identified widespread associations with age, sex, BMI, and HbA1c, where gene regulatory responses were highly cell type- and phenotype-specific. In beta cells, donor age associated with hypoxia, apoptosis, unfolded protein response, and external signal-dependent transcriptional regulators, while HbA1c associated with inflammatory responses and gender with chromatin organization. We identified 10.8K loci where genetic variants were QTLs for cis regulatory element (cRE) accessibility, including 20% with lineage- or cell type-specific effects which disrupted distinct transcription factor motifs. Type 2 diabetes and glycemic trait associated variants were enriched in both phenotype- and QTL-associated beta cell cREs, whereas type 1 diabetes showed limited enrichment. Variants at 226 diabetes and glycemic trait loci were QTLs in beta and other cell types, including 40 that were statistically colocalized, and annotating target genes of colocalized QTLs revealed genes with putatively novel roles in disease. Our findings reveal diverse responses of pancreatic cell types to phenotype and genotype in physiology, and identify pathways, networks, and genes through which physiology impacts diabetes risk.

Shared genetic architecture between periodontal disease and type 2 diabetes: a large scale genome-wide cross-trait analysis

PURPOSE

To investigate the relationship between abnormal glucose metabolism, type 2 diabetes (T2D), and periodontal disease (PER) independent of Body Mass Index (BMI), we employed a genome-wide cross-trait approach to clarify the association.

METHODS

Our study utilized the most extensive genome-wide association studies conducted for populations of European ancestry, including PER, T2D, fasting glucose, fasting insulin, 2-hour glucose after an oral glucose challenge, HOMA-β, HOMA-IR (unadjusted or adjusted for BMI) and HbA1c.

RESULTS

With this approach, we were able to identify pleiotropic loci, establish expression-trait associations, and quantify global and local genetic correlations. There was a significant positive global genetic correlation between T2D (rg = 0.261, p = 2.65 × 10-13), HbA1c (rg = 0.182, p = 4.14 × 10-6) and PER, as well as for T2D independent of BMI (rg = 0.158, p = 2.34 × 10-6). A significant local genetic correlation was also observed between PER and glycemic traits or T2D. We also identified 62 independent pleiotropic loci that impact both PER and glycemic traits, including T2D. Nine significant pathways were identified between the shared genes between T2D, glycemic traits and PER. Genetically liability of HOMA-βadjBMI was causally associated with the risk of PER.

CONCLUSION

Our research has revealed a genetic link between T2D, glycemic traits, and PER that is influenced by biological pleiotropy. Notably, some of these links are not related to BMI. Our research highlights an underlying link between patients with T2D and PER, regardless of their BMI.

Coeliac disease and type 2 diabetes risk: a nationwide matched cohort and Mendelian randomisation study

AIMS/HYPOTHESIS

While the association between coeliac disease and type 1 diabetes is well documented, the association of coeliac disease with type 2 diabetes risk remains undetermined. We conducted a nationwide cohort and Mendelian randomisation analysis to investigate this link.

METHODS

This nationwide matched cohort used data from the Swedish ESPRESSO cohort including 46,150 individuals with coeliac disease and 219,763 matched individuals in the comparator group selected from the general population, followed up from 1969 to 2021. Data from 9053 individuals with coeliac disease who underwent a second biopsy were used to examine the association between persistent villous atrophy and type 2 diabetes. Multivariable Cox regression was employed to estimate the associations. In Mendelian randomisation analysis, 37 independent genetic variants associated with clinically diagnosed coeliac disease at p<5×10-8 were used to proxy genetic liability to coeliac disease. Summary-level data for type 2 diabetes were obtained from the DIAGRAM consortium (80,154 cases) and the FinnGen study (42,593 cases).

RESULTS

Over a median 15.7 years' follow-up, there were 6132 (13.3%) and 30,138 (13.7%) incident cases of type 2 diabetes in people with coeliac disease and comparator individuals, respectively. Those with coeliac disease were not at increased risk of incident type 2 diabetes with an HR of 1.00 (95% CI 0.97, 1.03) compared with comparator individuals. Persistent villous atrophy was not associated with an increased risk of type 2 diabetes compared with mucosal healing among participants with coeliac disease (HR 1.02, 95% CI 0.90, 1.16). Genetic liability to coeliac disease was not associated with type 2 diabetes in DIAGRAM (OR 1.01, 95% CI 0.99, 1.03) or in FinnGen (OR 1.01, 95% CI 0.99-1.04).

CONCLUSIONS/INTERPRETATION

Coeliac disease was not associated with type 2 diabetes risk.

Metabolic factors are not the direct mediators of the association between type 2 diabetes and osteoporosis

Objective

The causal relationship between type 2 diabetes mellitus (T2DM) and osteoporosis (OS) remains unclear. This study aims to investigate the causal relationship and explore the potential metabolic mechanism and its mediating role.

Methods

We conducted a comprehensive study, gathering data on 490,089 T2DM patients from the genome-wide association study (GWAS) database and selecting OS data from FinnGen and MRC-IEU sources, including 212,778 and 463,010 patients, respectively, for causal analysis. Simultaneously, we explored the potential roles of three obesity traits and 30 metabolic and inflammation-related mediating variables in the causal relationship.

Results

There is a strong causal relationship between T2DM and OS. The data from our two different database sources appeared in the same direction, but after correcting for body mass index (BMI), waist circumference (WC), and waist-to-hip ratio (WHR), the direction became the same. T2DM may increase the risk of OS [odds ratio (OR) > 1.5, p < 0.001]. Steiger's test results show that there is no reverse causality. No risk factors related to glycolipid metabolism, amino acid metabolism, and inflammation were found to mediate the causal relationship.

Conclusion

This study's findings indicate a robust causal relationship between T2DM and OS, influenced by relevant factors such as BMI. Our results shed light on the pathogenesis of OS and underscore the importance for clinicians to treat metabolic disorders to prevent osteoporosis.

Unsupervised clustering identified clinically relevant metabolic syndrome endotypes in UK and Taiwan Biobanks

Metabolic syndrome (MetS) is a collection of cardiovascular risk factors; however, the high prevalence and heterogeneity impede effective clinical management. We conducted unsupervised clustering on individuals from UK Biobank to reveal endotypes. Five MetS subgroups were identified: Cluster 1 (C1): non-descriptive, Cluster 2 (C2): hypertensive, Cluster 3 (C3): obese, Cluster 4 (C4): lipodystrophy-like, and Cluster 5 (C5): hyperglycemic. For all of the endotypes, we identified the corresponding cardiometabolic traits and their associations with clinical outcomes. Genome-wide association studies (GWASs) were conducted to identify associated genotypic traits. We then determined endotype-specific genotypic traits and constructed polygenic risk score (PRS) models specific to each endotype. GWAS of each MetS clusters revealed different genotypic traits. C1 GWAS revealed novel findings of TRIM63, MYBPC3, MYLPF, and RAPSN. Intriguingly, C1, C3, and C4 were associated with genes highly expressed in brain tissues. MetS clusters with comparable phenotypic and genotypic traits were identified in Taiwan Biobank.

Multi-omics characterization of type 2 diabetes associated genetic variation

Discerning the mechanisms driving type 2 diabetes (T2D) pathophysiology from genome-wide association studies (GWAS) remains a challenge. To this end, we integrated omics information from 16 multi-tissue and multi-ancestry expression, protein, and metabolite quantitative trait loci (QTL) studies and 46 multi-ancestry GWAS for T2D-related traits with the largest, most ancestrally diverse T2D GWAS to date. Of the 1,289 T2D GWAS index variants, 716 (56%) demonstrated strong evidence of colocalization with a molecular or T2D-related trait, implicating 657 cis-effector genes, 1,691 distal-effector genes, 731 metabolites, and 43 T2D-related traits. We identified 773 of these cis- and distal-effector genes using either expression QTL data from understudied ancestry groups or inclusion of T2D index variants enriched in underrepresented populations, emphasizing the value of increasing population diversity in functional mapping. Linking these variants, genes, metabolites, and traits into a network, we elucidated mechanisms through which T2D-associated variation may impact disease risk. Finally, we showed that drugs targeting effector proteins were enriched in those approved to treat T2D, highlighting the potential of these results to prioritize drug targets for T2D. These results represent a leap in the molecular characterization of T2D-associated genetic variation and will aid in translating genetic findings into novel therapeutic strategies.

Assessment of glycemic susceptibility across multiple urological and reproductive disorders

OBJECTIVE

To test the glycemic susceptibility in three urological cancers and eight urological/reproductive diseases using the Mendelian randomization (MR) method.

MATERIALS AND METHODS

Two-sample MR was applied to investigate the causal role of three glycemic traits (type II diabetes, fasting glucose and glycated hemoglobin (HbA1c)) in eleven urological/reproductive diseases (kidney cancer, bladder cancer, prostate cancer, kidney/ureter stone, urinary incontinence, benign prostatic hyperplasia, erectile dysfunction, female infertility, male infertility, abnormal spermatozoa and polycystic ovary syndrome). Further multivariate MR (MVMR) and mediating analysis were performed to investigate the associations.

RESULTS

Among all the 11 diseases, type II diabetes was positively associated with erectile dysfunction, which was stable across both cohorts [odds ratio (OR): 1.59, 95% confidence interval (CI): 1.15-2.20, P = 0.005 for FinnGen Biobank and OR: 1.14, 95% CI: 1.08-1.21, P < 0.001 for the other cohort]. Also, type II diabetes was negatively associated with male infertility (OR: 0.57, 95% CI: 0.39-0.84, P = 0.005). In addition, all three glycemic traits were observed to be positively associated with polycystic ovary syndrome (OR: 2.36, 95% CI: 1.16-4.76, P = 0.017 for fasting glucose per mmol/L; OR: 3.04, 95% CI: 1.10-8.39, P = 0.032 for HbA1c per percentage; and OR: 1.21, 95% CI: 1.00-1.46, P = 0.046 for type II diabetes). Mediating analysis confirmed the effect of type II diabetes on these diseases.

CONCLUSIONS

There existed glycemic susceptibility in erectile dysfunction, male infertility and polycystic ovary syndrome. We could not conclude stable glycemic susceptibility in other urological/reproductive diseases.

Type 2 Diabetes, Circulating Metabolites, and Calcific Aortic Valve Stenosis: A Mendelian Randomization Study

Epidemiological studies have shown an association between type 2 diabetes (T2D) and calcific aortic valve stenosis (CAVS), but the potential causal relationship and underlying mechanisms remain unclear. Therefore, we conducted a two-sample and two-step Mendelian randomization (MR) analysis to evaluate the association of T2D with CAVS and the mediating effects of circulating metabolites and blood pressure using genome-wide association study (GWAS) summary statistics. The inverse variance weighted (IVW) method was used for the primary MR analysis, and comprehensive sensitivity analyses were performed to validate the robustness of the results. Our results showed that genetically predicted T2D was associated with increased CAVS risk (OR 1.153, 95% CI 1.096-1.214, p < 0.001), and this association persisted even after adjusting for adiposity traits in multivariable MR analysis. Furthermore, the two-step MR analysis identified 69 of 251 candidate mediators that partially mediated the effect of T2D on CAVS, including total branched-chain amino acids (proportion mediated: 23.29%), valine (17.78%), tyrosine (9.68%), systolic blood pressure (8.72%), the triglyceride group (6.07-11.99%), the fatty acid group (4.78-12.82%), and the cholesterol group (3.64-11.56%). This MR study elucidated the causal impact of T2D on CAVS risk independently of adiposity and identified potential mediators in this association pathways. Our findings shed light on the pathogenesis of CAVS and suggest additional targets for the prevention and intervention of CAVS attributed to T2D.

Impaired GK-GKRP interaction rather than direct GK activation worsens lipid profiles and contributes to long-term complications: a Mendelian randomization study

BACKGROUND

Glucokinase (GK) plays a key role in glucose metabolism. In the liver, GK is regulated by GK regulatory protein (GKRP) with nuclear sequestration at low plasma glucose level. Some GK activators (GKAs) disrupt GK-GKRP interaction which increases hepatic cytoplasmic GK level. Excess hepatic GK activity may exceed the capacity of glycogen synthesis with excess triglyceride formation. It remains uncertain whether hypertriglyceridemia associated with some GKAs in previous clinical trials was due to direct GK activation or impaired GK-GKRP interaction.

METHODS

Using publicly available genome-wide association study summary statistics, we selected independent genetic variants of GCKR and GCK associated with fasting plasma glucose (FPG) as instrumental variables, to mimic the effects of impaired GK-GKRP interaction and direct GK activation, respectively. We applied two-sample Mendelian Randomization (MR) framework to assess their causal associations with lipid-related traits, risks of metabolic dysfunction-associated steatotic liver disease (MASLD) and cardiovascular diseases. We verified these findings in one-sample MR analysis using individual-level statistics from the Hong Kong Diabetes Register (HKDR).

RESULTS

Genetically-proxied impaired GK-GKRP interaction increased plasma triglycerides, low-density lipoprotein cholesterol and apolipoprotein B levels with increased odds ratio (OR) of 14.6 (95% CI 4.57-46.4) per 1 mmol/L lower FPG for MASLD and OR of 2.92 (95% CI 1.78-4.81) for coronary artery disease (CAD). Genetically-proxied GK activation was associated with decreased risk of CAD (OR 0.69, 95% CI 0.54-0.88) and not with dyslipidemia. One-sample MR validation in HKDR showed consistent results.

CONCLUSIONS

Impaired GK-GKRP interaction, rather than direct GK activation, may worsen lipid profiles and increase risks of MASLD and CAD. Development of future GKAs should avoid interfering with GK-GKRP interaction.

The role of accelerometer-derived sleep traits on glycated haemoglobin and glucose levels: a Mendelian randomization study

Self-reported shorter/longer sleep duration, insomnia, and evening preference are associated with hyperglycaemia in observational analyses, with similar observations in small studies using accelerometer-derived sleep traits. Mendelian randomization (MR) studies support an effect of self-reported insomnia, but not others, on glycated haemoglobin (HbA1c). To explore potential effects, we used MR methods to assess effects of accelerometer-derived sleep traits (duration, mid-point least active 5-h, mid-point most active 10-h, sleep fragmentation, and efficiency) on HbA1c/glucose in European adults from the UK Biobank (UKB) (n = 73,797) and the MAGIC consortium (n = 146,806). Cross-trait linkage disequilibrium score regression was applied to determine genetic correlations across accelerometer-derived, self-reported sleep traits, and HbA1c/glucose. We found no causal effect of any accelerometer-derived sleep trait on HbA1c or glucose. Similar MR results for self-reported sleep traits in the UKB sub-sample with accelerometer-derived measures suggested our results were not explained by selection bias. Phenotypic and genetic correlation analyses suggested complex relationships between self-reported and accelerometer-derived traits indicating that they may reflect different types of exposure. These findings suggested accelerometer-derived sleep traits do not affect HbA1c. Accelerometer-derived measures of sleep duration and quality might not simply be 'objective' measures of self-reported sleep duration and insomnia, but rather captured different sleep characteristics.

Genome-wide association study identifies host genetic variants influencing oral microbiota diversity and metabolic health

The microbial communities of the oral cavity are important elements of oral and systemic health. With emerging evidence highlighting the heritability of oral bacterial microbiota, this study aimed to identify host genome variants that influence oral microbial traits. Using data from 16S rRNA gene amplicon sequencing, we performed genome-wide association studies with univariate and multivariate traits of the salivary microbiota from 610 unrelated adults from the Danish ADDITION-PRO cohort. We identified six single nucleotide polymorphisms (SNPs) in human genomes that showed associations with abundance of bacterial taxa at different taxonomical tiers (P < 5 × 10-8). Notably, SNP rs17793860 surpassed our study-wide significance threshold (P < 1.19 × 10-9). Additionally, rs4530093 was linked to bacterial beta diversity (P < 5 × 10-8). Out of these seven SNPs identified, six exerted effects on metabolic traits, including glycated hemoglobin A1c, triglyceride and high-density lipoprotein cholesterol levels, the risk of type 2 diabetes and stroke. Our findings highlight the impact of specific host SNPs on the composition and diversity of the oral bacterial community. Importantly, our results indicate an intricate interplay between host genetics, the oral microbiota, and metabolic health. We emphasize the need for integrative approaches considering genetic, microbial, and metabolic factors.

Do iron homeostasis biomarkers mediate the associations of liability to type 2 diabetes and glycemic traits in liver steatosis and cirrhosis: a two-step Mendelian randomization study

BACKGROUND

Previous studies, including Mendelian randomization (MR), have demonstrated type 2 diabetes (T2D) and glycemic traits are associated with increased risk of metabolic dysfunction-associated steatotic liver disease (MASLD). However, few studies have explored the underlying pathway, such as the role of iron homeostasis.

METHODS

We used a two-step MR approach to investigate the associations of genetic liability to T2D, glycemic traits, iron biomarkers, and liver diseases. We analyzed summary statistics from various genome-wide association studies of T2D (n = 933,970), glycemic traits (n ≤ 209,605), iron biomarkers (n ≤ 246,139), MASLD (n ≤ 972,707), and related biomarkers (alanine aminotransferase (ALT) and proton density fat fraction (PDFF)). Our primary analysis was based on inverse-variance weighting, followed by several sensitivity analyses. We also conducted mediation analyses and explored the role of liver iron in post hoc analysis.

RESULTS

Genetic liability to T2D and elevated fasting insulin (FI) likely increased risk of liver steatosis (ORliability to T2D: 1.14 per doubling in the prevalence, 95% CI: 1.10, 1.19; ORFI: 3.31 per log pmol/l, 95% CI: 1.92, 5.72) and related biomarkers. Liability to T2D also likely increased the risk of developing liver cirrhosis. Genetically elevated ferritin, serum iron, and liver iron were associated with higher risk of liver steatosis (ORferritin: 1.25 per SD, 95% CI 1.07, 1.46; ORliver iron: 1.15 per SD, 95% CI: 1.05, 1.26) and liver cirrhosis (ORserum iron: 1.31, 95% CI: 1.06, 1.63; ORliver iron: 1.34, 95% CI: 1.07, 1.68). Ferritin partially mediated the association between FI and liver steatosis (proportion mediated: 7%, 95% CI: 2-12%).

CONCLUSIONS

Our study provides credible evidence on the causal role of T2D and elevated insulin in liver steatosis and cirrhosis risk and indicates ferritin may play a mediating role in this association.

Exploring the mediating role of calcium homeostasis in the association between diabetes mellitus, glycemic traits, and vascular and valvular calcifications: a comprehensive Mendelian randomization analysis

BACKGROUND

The interplay between diabetes mellitus (DM), glycemic traits, and vascular and valvular calcifications is intricate and multifactorial. Exploring potential mediators may illuminate underlying pathways and identify novel therapeutic targets.

METHODS

We utilized univariable and multivariable Mendelian randomization (MR) analyses to investigate associations and mediation effects. Additionally, the multivariable MR analyses incorporated cardiometabolic risk factors, allowing us to account for potential confounders.

RESULTS

Type 2 diabetes mellitus (T2DM) and glycated hemoglobin (HbA1c) were positively associated with both coronary artery calcification (CAC) and calcific aortic valvular stenosis (CAVS). However, fasting glucose (FG) was only linked to CAVS and showed no association with CAC. Additionally, CAVS demonstrated a causal effect on FG. Calcium levels partially mediated the impact of T2DM on both types of calcifications. Specifically, serum calcium was positively associated with both CAC and CAVS. The mediation effects of calcium levels on the impact of T2DM on CAC and CAVS were 6.063% and 3.939%, respectively. The associations between T2DM and HbA1c with calcifications were influenced by body mass index (BMI) and smoking status. However, these associations were generally reduced after adjusting for hypertension.

CONCLUSION

Our findings suggest a genetically supported causal relationship between DM, glycemic traits, and vascular and valvular calcifications, with serum calcium playing a critical mediating role.

Comparing the effects of CETP in East Asian and European ancestries: a Mendelian randomization study

CETP inhibitors are a class of lipid-lowering drugs in development for treatment of coronary heart disease (CHD). Genetic studies in East Asian ancestry have interpreted the lack of CETP signal with low-density lipoprotein cholesterol (LDL-C) and lack of drug target Mendelian randomization (MR) effect on CHD as evidence that CETP inhibitors might not be effective in East Asian participants. Capitalizing on recent increases in sample size of East Asian genetic studies, we conducted a drug target MR analysis, scaled to a standard deviation increase in high-density lipoprotein cholesterol. Despite finding evidence for possible neutral effects of lower CETP levels on LDL-C, systolic blood pressure and pulse pressure in East Asians (interaction p-values < 1.6 × 10-3), effects on cardiovascular outcomes were similarly protective in both ancestry groups. In conclusion, on-target inhibition of CETP is anticipated to decrease cardiovascular disease in individuals of both European and East Asian ancestries.

A Mendelian randomization study between metabolic syndrome and its components with prostate cancer

Previous research has produced inconsistent findings concerning the connection between metabolic syndrome and prostate cancer. It is challenging for observational studies to establish a conclusive causal relationship between the two. However, Mendelian randomization can provide stronger evidence of causality in this context. To examine the causal link between a metabolic composite and its components with prostate cancer, we performed a two-sample Mendelian randomization (MR) study utilizing aggregated data from genome-wide association studies, followed by meta-analyses. In our study, we employed inverse variance weighting as the primary method for MR analysis. Additionally, we assessed potential sources of heterogeneity and horizontal pleiotropy through the Cochran's Q test and MR-Egger regression. Moreover, we used multivariate MR to determine whether smoking versus alcohol consumption had an effect on the outcomes. We found no causal relationship between metabolic syndrome and its components and prostate cancer(MetS, odds ratio [OR] = 0.95, 95% confidence interval [CI] = 0.738-1.223, p = 0.691; TG, [OR] = 1.02, 95%[CI] = 0.96-1.08, p = 0.59); HDL, [OR] = 1.02, 95% [CI] = 0.97-1.07, p = 0.47; DBP, [OR] = 1.00, 95%[CI] = 0.99-1.01, p = 0.87; SBP, [OR] = 1.00, 95%[CI] = 0.99-1.00, p = 0.26; FBG [OR] = 0.92, 95%[CI] = 0.81-1.05, p = 0.23; WC, [OR] = 0.93, 95%[CI] = 0.84-1.03, p = 0.16). Finally, the MVMR confirms that the metabolic syndrome and its components are independent of smoking and alcohol consumption in prostate cancer. We didn't find significant evidence to determine a causal relationship between the metabolic syndrome and its components and prostate cancer through MR analysis. Further research is necessary to explore the potential pathogenesis between the two diseases.

Assessing the causal association of pregnancy complications with diabetes and cardiovascular disease

Background

To the best of our knowledge, numerous observational studies have linked pregnancy complications to increased risks of diabetes and cardiovascular disease (CVD), causal evidence remains lacking. Our aim was to estimate the association of adverse pregnancy outcomes with diabetes and cardiovascular diseases.

Methods

A two-sample Mendelian randomization (MR) analysis was employed, which is not subject to potential reverse causality. Data for pregnancy complications were obtained from the FinnGen consortium. For primary analysis, outcome data on diabetes, related traits, stroke, and coronary heart disease (CHD) were extracted from the GWAS Catalog, MAGIC, MEGASTROKE, and CARDIoGRAMplusC4D consortium. The MAGIC and UKB consortium datasets were used for replication and meta-analysis. Causal effects were appraised using inverse variance weighted (IVW), weighted median (WM), and MR-Egger. Sensitivity analyses were implemented with Cochran's Q test, MR-Egger intercept test, MR-PRESSO, leave-one-out (LOO) analysis and the funnel plot.

Results

Genetically predicted gestational diabetes mellitus (GDM) was causally associated with an increased diabetes risk (OR=1.01, 95% CI=1-1.01, P<0.0001), yet correlated with lower 2-hour post-challenge glucose levels (OR=0.89, 95% CI=0.82-0.97, P=0.006). Genetic liability for pregnancy with abortive outcomes indicated decreased fasting insulin levels (OR=0.97, 95% CI=0.95-0.99, P=0.02), but potentially elevated glycated hemoglobin levels (OR=1.02, 95% CI=1.01-1.04, P=0.01). Additionally, hypertensive disorders in pregnancy was tentatively linked to increased risks of stroke (OR=1.11, 95% CI=1.04-1.18, P=0.002) and CHD (OR=1.3, 95% CI=1.2-1.4, P=3.11E-11). Gestational hypertension might have a potential causal association with CHD (OR=1.11, 95% CI=1.01-1.22, P=0.04). No causal associations were observed between preterm birth and diabetes, stroke, or CHD.

Conclusion

The findings of this study provide genetic evidence that gestational diabetes, pregnancy with abortive outcomes, and hypertensive disorders in pregnancy may serve as early indicators for metabolic and cardiovascular risks. These insights are pivotal for the development of targeted screening and preventive strategies.

Improved functional mapping of complex trait heritability with GSA-MiXeR implicates biologically specific gene sets

While genome-wide association studies are increasingly successful in discovering genomic loci associated with complex human traits and disorders, the biological interpretation of these findings remains challenging. Here we developed the GSA-MiXeR analytical tool for gene set analysis (GSA), which fits a model for the heritability of individual genes, accounting for linkage disequilibrium across variants and allowing the quantification of partitioned heritability and fold enrichment for small gene sets. We validated the method using extensive simulations and sensitivity analyses. When applied to a diverse selection of complex traits and disorders, including schizophrenia, GSA-MiXeR prioritizes gene sets with greater biological specificity compared to standard GSA approaches, implicating voltage-gated calcium channel function and dopaminergic signaling for schizophrenia. Such biologically relevant gene sets, often with fewer than ten genes, are more likely to provide insights into the pathobiology of complex diseases and highlight potential drug targets.

Noninvasive assessment of organ-specific and shared pathways in multi-organ fibrosis using T1 mapping

Fibrotic diseases affect multiple organs and are associated with morbidity and mortality. To examine organ-specific and shared biologic mechanisms that underlie fibrosis in different organs, we developed machine learning models to quantify T1 time, a marker of interstitial fibrosis, in the liver, pancreas, heart and kidney among 43,881 UK Biobank participants who underwent magnetic resonance imaging. In phenome-wide association analyses, we demonstrate the association of increased organ-specific T1 time, reflecting increased interstitial fibrosis, with prevalent diseases across multiple organ systems. In genome-wide association analyses, we identified 27, 18, 11 and 10 independent genetic loci associated with liver, pancreas, myocardial and renal cortex T1 time, respectively. There was a modest genetic correlation between the examined organs. Several loci overlapped across the examined organs implicating genes involved in a myriad of biologic pathways including metal ion transport (SLC39A8, HFE and TMPRSS6), glucose metabolism (PCK2), blood group antigens (ABO and FUT2), immune function (BANK1 and PPP3CA), inflammation (NFKB1) and mitosis (CENPE). Finally, we found that an increasing number of organs with T1 time falling in the top quintile was associated with increased mortality in the population. Individuals with a high burden of fibrosis in ≥3 organs had a 3-fold increase in mortality compared to those with a low burden of fibrosis across all examined organs in multivariable-adjusted analysis (hazard ratio = 3.31, 95% confidence interval 1.77-6.19; P = 1.78 × 10-4). By leveraging machine learning to quantify T1 time across multiple organs at scale, we uncovered new organ-specific and shared biologic pathways underlying fibrosis that may provide therapeutic targets.

Genetic association of glycemic traits and antihyperglycemic agent target genes with the risk of lung cancer: A Mendelian randomization study

AIMS

To evaluate the potential causal effect of glycemic traits on lung cancer and investigate the impact of antihyperglycemic agent-target genes on lung cancer risk.

METHODS

Genetic variants associated with glycemic traits, antihyperglycemic agent-target genes, and lung cancer were extracted from the Meta-Analyses of Glucose and Insulin-related traits Consortium (MAGIC), expression quantitative trait loci (eQTLs), protein quantitative trait loci (pQTLs), and the International Lung Cancer Consortium (ILCCO), respectively. Mendelian randomization (MR) analyses were performed to examine the associations of glycemic traits and antihyperglycemic agent-target genes with lung cancer. Mediation analysis was conducted to explore whether overweight operated as a mediator between antihyperglycemic agents and lung cancer outcomes.

RESULTS

Genetically determined glycated hemoglobin A1c levels were associated with squamous cell lung cancer (OR = 1.78; 95 % CI, 1.08-2.92; p = 0.023). The PRKAB1 gene (the target of metformin) was associated with a lower risk of developing lung adenocarcinoma (OR = 0.85; 95 % CI, 0.76-0.96; p = 0.006). Further mediation analyses did not support overweight as a mediator between PRKAB1 activation and lung adenocarcinoma.

CONCLUSION

Our analyses suggest an association of genetically determined abnormal glycemic traits with squamous cell lung cancer. The potential association between PRKAB1 activation and a reduced risk of developing lung adenocarcinoma appears to be independent of the anti-obesity effects of metformin, suggesting that PRKAB1 activation may have a direct protective effect on lung adenocarcinoma development.