The trans-ancestral genomic architecture of glycemic traits

Hyperglycaemia, diabetes and risk of fragility fractures: observational and Mendelian randomisation studies

AIMS/HYPOTHESIS

Fragility fractures may be a complication of diabetes, partly caused by chronic hyperglycaemia. We hypothesised that: (1) individuals with hyperglycaemia and diabetes have increased risk of fragility fracture; (2) hyperglycaemia is causally associated with increased risk of fragility fracture; and (3) diabetes and fragility fracture jointly associate with the highest risk of all-cause mortality.

METHODS

In total, 117,054 individuals from the Copenhagen City Heart Study and the Copenhagen General Population Study (the Copenhagen studies) and 390,374 individuals from UK Biobank were included for observational and one-sample Mendelian randomisation (MR) analyses. Fragility fractures were defined as fractures at the hip, spine and arm (humerus/wrist), collected from national health registries. Summary data for fasting glucose and HbA1c concentrations from 196,743 individuals in the Meta-Analyses of Glucose and Insulin-related traits Consortium (MAGIC) were combined with data on fragility fractures from the Copenhagen studies in two-sample MR analyses.

RESULTS

Higher fasting and non-fasting glucose and HbA1c concentrations were associated with higher risk of any fragility fracture (p<0.001). Individuals with vs without diabetes had HRs for fragility fracture of 1.50 (95% CI 1.19, 1.88) in type 1 diabetes and 1.22 (1.13, 1.32) in type 2 diabetes. One-sample MR supported a causal association between high non-fasting glucose concentrations and increased risk of arm fracture in the Copenhagen studies and UK Biobank combined (RR 1.41 [1.11, 1.79], p=0.004), with similar results for fasting glucose and HbA1c in two-sample MR analyses (ORs 1.50 [1.03, 2.18], p=0.03; and 2.79 [1.12, 6.93], p=0.03, respectively). The corresponding MR estimates for any fragility fracture were 1.18 (1.00, 1.41), p=0.06; 1.36 (0.89, 2.09), p=0.15; and 2.47 (0.95, 6.43), p=0.06, respectively. At age 80 years, cumulative death was 27% in individuals with fragility fracture only, 54% in those with diabetes only, 67% in individuals with both conditions and 17% in those with neither.

CONCLUSIONS/INTERPRETATION

Hyperglycaemia and diabetes are risk factors for fragility fracture and one- and two-sample MR analyses supported a causal effect of hyperglycaemia on arm fractures. Diabetes and previous fragility fracture jointly conferred the highest risk of death in the general population.

Cardiovascular diseases consequences of type 1, type 2 diabetes mellitus and glycemic traits: A Mendelian randomization study

OBJECTIVE

This Mendelian randomization (MR) study aimed to investigate the relationships between type 1 diabetes (T1D), type 2 diabetes (T2D), and glycemic traits, including fasting insulin, fasting glucose, and HbA1c, with cardiovascular diseases (CVDs).

METHODS

We selected genetic instruments for predisposition to T1D, T2D, fasting insulin, fasting glucose, and HbA1c based on published genome-wide association studies. Using a 2-Sample MR approach, we assessed associations with 12 common CVDs sourced from the FinnGen and UK Biobank studies, along with stroke subtypes obtained from the GIGASTROKE and MEGASTROKE Consortium.

RESULTS

T1D was associated with SVS. T2D showed associations with AIS, LAA, CES, SVS, coronary heart disease, myocardial infarction, pulmonary embolism, DVT of lower extremities, peripheral vascular diseases. Genetically predicted higher HbA1c levels were associated with eight CVDs. The results of MVMR aligned with the primary findings for T1D and T2D.

CONCLUSIONS

T1D and T2D exhibit different genetic predisposition to CVDs. BMI, LDL, and HDL play intermediary roles in connecting TID and T2D to specific types of CVDs, providing insights into the potential underlying pathways and mechanisms involved in these relationships. Strategies aimed at achieving sustained reductions in HbA1c levels may offer potential for reducing the risk of various CVDs.

Effects of body mass index and blood pressure on atrioventricular block: Two-sample mendelian randomization

BACKGROUND

Observational studies have suggested associations between some atherogenic risk factors and atrioventricular (AV) block.

OBJECTIVE

The purpose of this study was to investigate the causal effects of several cardiometabolic exposures on AV block and evaluate the role of coronary artery disease (CAD) as a mediator on the causal pathway by mendelian randomization analysis.

METHODS

Two-sample bidirectional mendelian randomization was performed to assess the causal effects of cardiometabolic traits on AV block and examine causality inversely. The exposures of interest included body mass index (BMI), systolic blood pressure (SBP), diastolic blood pressure (DBP), fasting glucose, fasting insulin, low-density lipoprotein, high-density lipoprotein, and triglyceride. Multivariable mendelian randomization was then conducted to disentangle the effect of each significant exposure. Mediation effect of CAD on the causal pathways were estimated by two-step, two-sample mendelian randomization.

RESULTS

Genetically predicted elevation of BMI (odds ratio [OR] 1.40; 95% confidence interval [CI] 1.10-1.78; P = .006), SBP (OR 1.02; 95% CI 1.00-1.03; P = .015), and DBP (OR 1.04; 95% CI 1.01-1.07; P = .005) were significantly associated with increased AV block risk. Effects of the other exposures were insignificant. There were no reverse causal effects. Multivariable mendelian randomization showed causal effects of increased BMI, SBP, and DBP on AV block after mutual adjustment. CAD mediated 14.20% (8.82%, 16.46%), 26.32% (25.00%, 26.47,%) and 12.20% (7.69%, 15.94%) of AV block risk from BMI, SBP and DBP, respectively.

CONCLUSION

Elevated BMI, SBP, and DBP exhibited causal effects on AV block. The impacts were partly mediated by CAD.

Comprehensive genetic study of the insulin resistance marker TG:HDL-C in the UK Biobank

Insulin resistance (IR) is a well-established risk factor for metabolic disease. The ratio of triglycerides to high-density lipoprotein cholesterol (TG:HDL-C) is a surrogate marker of IR. We conducted a genome-wide association study of the TG:HDL-C ratio in 402,398 Europeans within the UK Biobank. We identified 369 independent SNPs, of which 114 had a false discovery rate-adjusted P value < 0.05 in other genome-wide studies of IR making them high-confidence IR-associated loci. Seventy-two of these 114 loci have not been previously associated with IR. These 114 loci cluster into five groups upon phenome-wide analysis and are enriched for candidate genes important in insulin signaling, adipocyte physiology and protein metabolism. We created a polygenic-risk score from the high-confidence IR-associated loci using 51,550 European individuals in the Michigan Genomics Initiative. We identified associations with diabetes, hyperglyceridemia, hypertension, nonalcoholic fatty liver disease and ischemic heart disease. Collectively, this study provides insight into the genes, pathways, tissues and subtypes critical in IR.

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.

Multi-ancestry genome-wide association study of major depression aids locus discovery, fine mapping, gene prioritization and causal inference

Most genome-wide association studies (GWAS) of major depression (MD) have been conducted in samples of European ancestry. Here we report a multi-ancestry GWAS of MD, adding data from 21 cohorts with 88,316 MD cases and 902,757 controls to previously reported data. This analysis used a range of measures to define MD and included samples of African (36% of effective sample size), East Asian (26%) and South Asian (6%) ancestry and Hispanic/Latin American participants (32%). The multi-ancestry GWAS identified 53 significantly associated novel loci. For loci from GWAS in European ancestry samples, fewer than expected were transferable to other ancestry groups. Fine mapping benefited from additional sample diversity. A transcriptome-wide association study identified 205 significantly associated novel genes. These findings suggest that, for MD, increasing ancestral and global diversity in genetic studies may be particularly important to ensure discovery of core genes and inform about transferability of findings.

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.

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

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

Observational and genetic analyses clarify the relationship between type 2 diabetes mellitus and gallstone disease

Background

The relationship between type 2 diabetes mellitus (T2DM) and gallstone disease (GSD) have been incompletely understood. We aimed to investigate their phenotypic and genetic associations and evaluate the biological mechanisms underlying these associations.

Methods

We first evaluated the phenotypic association between T2DM and GSD using data from the UK Biobank (n>450,000) using a prospective observational design. We then conducted genetic analyses using summary statistics from a meta-analysis of genome-wide association studies of T2DM, with and without adjusting for body mass index (BMI) (Ncase=74,124, Ncontrol=824,006; T2DMadjBMI: Ncase=50,409, Ncontrol=523,897) and GSD (Ncase=43,639, Ncontrol=506,798).

Results

A unidirectional phenotypic association was observed, where individuals with T2DM exhibited a higher GSD risk (hazard ratio (HR)=1.39, P<0.001), but not in the reverse direction (GSD→T2DM: HR=1.00, P=0.912). The positive T2DM-GSD genetic correlation (rg=0.35, P=7.71×10-23) remained even after adjusting for BMI (T2DMadjBMI: rg=0.22, P=4.48×10-10). Mendelian randomization analyses provided evidence of a unidirectional causal relationship (T2DM→GSD: odds ratio (OR)=1.08, P=4.6×10-8; GSD→T2DM: OR=1.02, P=0.48), even after adjusting for important metabolic confounders (OR=1.02, P=0.02). This association was further corroborated through a comprehensive functional analysis reflected by 23 pleiotropic single nucleotide polymorphisms, as well as multiple neural and motor-enriched tissues.

Conclusion

Through comprehensive observational and genetic analyses, our study clarified the causal relationship between T2DM and GSD, but not in the reverse direction. These findings might provide new insights into prevention and treatment strategies for T2DM and GSD.

Association between Type 1 Diabetes Mellitus and Parkinson's Disease: A Mendelian Randomization Study

While much evidence suggests that type 2 diabetes mellitus increases the risk of Parkinson's disease (PD), the relationship between type 1 diabetes mellitus (T1DM) and PD is unclear. To study their association, we performed a two-sample Mendelian randomization (MR) using the following statistical methods: inverse variance weighting (IVW), MR-Egger, weight median, and weighted mode. Independent datasets with no sample overlap were retrieved from the IEU GWAS platform. All the MR methods found a lower risk of PD in T1DM (IVW-OR 0.93, 95% CI 0.91-0.96, p = 3.12 × 10-5; MR-Egger-OR 0.93, 95% CI 0.88-0.98, p = 1.45 × 10-2; weighted median-OR 0.93, 95% CI 0.89-0.98, p = 2.76 × 10-3; and weighted mode-OR 0.94, 95% CI 0.9-0.98, p = 1.58 × 10-2). The findings were then replicated with another independent GWAS dataset on T1DM (IVW-OR 0.97, 95% CI 0.95-0.99, p = 3.10 × 10-3; MR-Egger-OR 0.96, 95% CI 0.93-0.99, p = 1.08 × 10-2; weighted median-OR 0.97, 95% CI 0.94-0.99, p = 1.88 × 10-2; weighted mode-OR 0.97, 95% CI 0.94-0.99, p = 1.43 × 10-2). Thus, our study provides evidence that T1DM may have a protective effect on PD risk, though further studies are needed to clarify the underlying mechanisms.

Metabolic syndrome and risk of colorectal cancer: A Mendelian randomization study

Background

Observational studies have previously demonstrated a significant relationship among both metabolic syndrome (Mets) and colorectal cancer (CRC). Whether there is a causal link remains controversial.

Objective

To clarify whether Mets and their components have a causal effect on colorectal cancer, we have carried out a bidirectional Mendelian randomization analysis (MR).

Methods

This study started from genome-wide association data for Mets and its 5 components (hypertension, waist circumference, fasting blood glucose, serum triglycerides, and serum high-density lipoprotein cholesterol) and colorectal cancer. Mendelian randomization (MR) techniques were used in the study to examine their associations.

Results

After Benjamini-Hochberg multiple corrections, genetically predicted significant causal link exists between WC (waist circumference) and CRC. The OR was 1.35 (95 % CI: 1.08-1.69; p = 0.0096). Other Mets components (HBP, FBG, TG, HDL), on the other hand, found no evidence of a genetic link between CRC and Mets. In addition, MR results showed that CRC was not causally related to either Mets or the components. We get the same result in the validated dataset.

Conclusion

According to the bidirectional MR investigation shows a significant causal relationship among obesity and CRC in the Mets component but no causal relationship in the opposite direction.

Evaluating polygenic risk scores for predicting cardiometabolic traits and disease risks in the Taiwan Biobank

Type 2 diabetes (T2D) and hypertension are common comorbidities and, along with hyperlipidemia, serve as risk factors for cardiovascular diseases. This study aimed to evaluate the predictive value of polygenic risk scores (PRSs) on cardiometabolic traits related to T2D, hypertension, and hyperlipidemia and the incidence of these three diseases in Taiwan Biobank samples. Using publicly available, large-scale genome-wide association studies summary statistics, we constructed cross-ethnic PRSs for T2D, hypertension, body mass index, and nine quantitative traits typically used to define the three diseases. A composite PRS (cPRS) for each of the nine traits was constructed by aggregating the significant PRSs of its genetically correlated traits. The associations of each of the nine traits at baseline as well as the change of trait values during a 3- to 6-year follow-up period with its cPRS were evaluated. The predictive performances of cPRSs in predicting future incidences of T2D, hypertension, and hyperlipidemia were assessed. The cPRSs had significant associations with baseline and changes of trait values in 3-6 years and explained a higher proportion of variance for all traits than individual PRSs. Furthermore, models incorporating disease-related cPRSs, along with clinical features and relevant trait measurements achieved area under the curve values of 87.8%, 83.7%, and 75.9% for predicting future T2D, hypertension, and hyperlipidemia in 3-6 years, respectively.

Parental and child genetic burden of glycaemic dysregulation and early-life cognitive development: an Asian and European prospective cohort study

Insulin resistance and glucose metabolism have been associated with neurodevelopmental disorders. However, in the metabolically more susceptible Asian populations, it is not clear whether the genetic burden of glycaemic dysregulation influences early-life neurodevelopment. In a multi-ethnic Asian prospective cohort study in Singapore (Growing Up in Singapore Towards healthy Outcomes (GUSTO)), we constructed child and parental polygenic risk scores (PRS) for glycaemic dysregulation based on the largest genome-wide association studies of type 2 diabetes and fasting glucose among Asians. We found that child PRS for HOMA-IR was associated with a lower perceptual reasoning score at ~7 years (β = -0. 141, p-value = 0.024, 95% CI -0. 264 to -0. 018) and a lower WIAT-III mean score at ~9 years (β = -0.222, p-value = 0.001, 95% CI -0.357 to -0.087). This association were consistent in direction among boys and girls. These inverse associations were not influenced by parental PRS and were likely mediated via insulin resistance rather than mediators such as birth weight and childhood body mass index. Higher paternal PRS for HOMA-IR was suggestively associated with lower child perceptual reasoning at ~7 years (β = -0.172, p-value = 0.002, 95% CI -0.280 to -0.064). Replication analysis in a European cohort, the Avon Longitudinal Study of Parents and Children (ALSPAC) birth cohort, showed that higher child PRS for fasting glucose was associated with lower verbal IQ score while higher maternal PRS for insulin resistance was associated with lower performance IQ score in their children at ~8.5 years. In summary, our findings suggest that higher child PRS for HOMA-IR was associated with lower cognitive scores in both Asian and European replication cohorts. Differential findings between cohorts may be attributed to genetic and environmental factors. Further investigation of the functions of the genetic structure and ancestry-specific PRS and a more comprehensive investigation of behavioural mediators may help to understand these findings better.

A Bayesian approach to Mendelian randomization using summary statistics in the univariable and multivariable settings with correlated pleiotropy

Mendelian randomization uses genetic variants as instrumental variables to make causal inferences on the effect of an exposure on an outcome. Due to the recent abundance of high-powered genome-wide association studies, many putative causal exposures of interest have large numbers of independent genetic variants with which they associate, each representing a potential instrument for use in a Mendelian randomization analysis. Such polygenic analyses increase the power of the study design to detect causal effects; however, they also increase the potential for bias due to instrument invalidity. Recent attention has been given to dealing with bias caused by correlated pleiotropy, which results from violation of the "instrument strength independent of direct effect" assumption. Although methods have been proposed that can account for this bias, a number of restrictive conditions remain in many commonly used techniques. In this paper, we propose a Bayesian framework for Mendelian randomization that provides valid causal inference under very general settings. We propose the methods MR-Horse and MVMR-Horse, which can be performed without access to individual-level data, using only summary statistics of the type commonly published by genome-wide association studies, and can account for both correlated and uncorrelated pleiotropy. In simulation studies, we show that the approach retains type I error rates below nominal levels even in high-pleiotropy scenarios. We demonstrate the proposed approaches in applied examples in both univariable and multivariable settings, some with very weak instruments.

A genome-wide association meta-analysis implicates Hedgehog and Notch signaling in Dupuytren's disease

Dupuytren's disease (DD) is a highly heritable fibrotic disorder of the hand with incompletely understood etiology. A number of genetic loci, including Wnt signaling members, have been previously identified. Our overall aim was to identify novel genetic loci, to prioritize genes within the loci for functional studies, and to assess genetic correlation with associated disorders. We performed a meta-analysis of six DD genome-wide association studies from three European countries and extensive bioinformatic follow-up analyses. Leveraging 11,320 cases and 47,023 controls, we identified 85 genome-wide significant single nucleotide polymorphisms in 56 loci, of which 11 were novel, explaining 13.3-38.1% of disease variance. Gene prioritization implicated the Hedgehog and Notch signaling pathways. We also identified a significant genetic correlation with frozen shoulder. The pathways identified highlight the potential for new therapeutic targets and provide a basis for additional mechanistic studies for a common disorder that can severely impact hand function.

Multi-tissue transcriptome-wide association study reveals susceptibility genes and drug targets for insulin resistance-relevant phenotypes

AIM

Genome-wide association studies (GWAS) have identified multiple susceptibility loci associated with insulin resistance (IR)-relevant phenotypes. However, the genes responsible for these associations remain largely unknown. We aim to identify susceptibility genes for IR-relevant phenotypes via a transcriptome-wide association study.

MATERIALS AND METHODS

We conducted a large-scale multi-tissue transcriptome-wide association study for IR (Insulin Sensitivity Index, homeostasis model assessment-IR, fasting insulin) and lipid-relevant traits (high-density lipoprotein cholesterol, triglycerides, low-density lipoprotein cholesterol and total cholesterol) using the largest GWAS summary statistics and precomputed gene expression weights of 49 human tissues. Conditional and joint analyses were implemented to identify significantly independent genes. Furthermore, we estimated the causal effects of independent genes by Mendelian randomization causal inference analysis.

RESULTS

We identified 1190 susceptibility genes causally associated with IR-relevant phenotypes, including 58 genes that were not implicated in the original GWAS. Among them, 11 genes were further supported in differential expression analyses or a gene knockout mice database, such as KRIT1 showed both significantly differential expression and IR-related phenotypic effects in knockout mice. Meanwhile, seven proteins encoded by susceptibility genes were targeted by clinically approved drugs, and three of these genes (H6PD, CACNB2 and DRD2) have been served as drug targets for IR-related diseases/traits. Moreover, drug repurposing analysis identified four compounds with profiles opposing the expression of genes associated with IR risk.

CONCLUSIONS

Our study provided new insights into IR aetiology and avenues for therapeutic development.

Identification of molecular mediators of renal sarcopenia risk: a mendelian randomization analysis

BACKGROUND

Observational studies have shown an association between reduced renal function and the risk of sarcopenia. However, the causal relationship and the underlying biological mechanisms remain uncertain. Using a Mendelian randomization (MR) framework, we investigated the causal role of 27 hypothetical risk mediators, including metabolites, hormones, inflammation, and stress traits, on the risk of sarcopenia.

METHODS

Instrumental variables (IVs) to proxy renal function were identified by selecting single nucleotide polymorphisms (SNPs) reliably associated with creatinine and cystatin C-based glomerular filtration rate (GFR) in CKDGen summary data. IVs for putative risk traits and sarcopenia traits were constructed from relevant genome-wide association studies (GWAS). MR estimated effects were obtained using an inverse-variance weighted effects model, and various sensitivity analyses were performed. The mediating role of hypothetical risk factors in the relationship between GFR and sarcopenia was assessed through multivariate MR.

RESULTS

Genetically predicted reduced GFRcrea was associated with higher odds of appendicular lean mass (ALM) (odds ratio (OR): 0.64, 95% confidence interval (CI) 0.37 to 0.68) and grip strength (OR: 0.67; 95% CI 0.58 to 0.78). Likewise, GFRcys highlighted a causal relationship with ALM (OR: 0.52; 95% CI 0.42 to 0.65) and grip strength (OR: 0.66; 95% CI 0.59 to 0.74). Both estimated GFR (eGFR) were negatively associated with IGF-1, IL-16, 25(OH)D, triglycerides (range of effect size per standard deviation: -0.81 to -0.30), and positively correlated with HDL cholesterol (0.62, 0.31). There was a positive correlation between IGF-1, fasting insulin and ALM as well as grip strength (OR range: 1.04-1.67) and a negative correlation between serum CRP and ALM (OR: 0.95) as well as grip strength (OR: 0.98). Additionally, genetically predicted IL-1β (OR: 0.95) and total cholesterol (OR: 0.96) were negatively associated with ALM. We found evidence that IGF-1 mediates the relationship between eGFR and risk for muscle mass and strength.

CONCLUSIONS

This MR study provides insight into the potential causal mechanisms between renal function and the risk of sarcopenia and proposes IGF-1 as a potential target for the prevention of renal sarcopenia.

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.

Causality of Diabetic Nephropathy and Age-Related Macular Degeneration: A Mendelian Randomization Study

PURPOSE

Age-related macular degeneration (AMD) currently stands as the leading cause of irreversible vision loss in the present era. The primary objective of this study was to investigate the causal relationships between diabetic nephropathy (DN), its associated risk factors, and AMD among participants of European descent.

METHODS

Genetic variants associated with DN and its risk factors, encompassing glycemic traits, lipidemic traits, systolic/diastolic blood pressure, obesity, and urate, were obtained from previously published genome-wide association studies. Summary-level statistics for AMD were acquired from the FinnGen database. Univariable and multivariable Mendelian randomization (MR) were employed to conduct this investigation.

RESULTS

Our MR analyses indicated that per 1-standard deviation (SD) increase of DN heightened the risk of overall AMD (p = 1.03 × 10-8, OR = 1.24). And these findings remained consistent when examining both dry AMD (p = 2.27 × 10-4, OR = 1.17) and wet AMD (p = 5.15 × 10-6, OR = 1.33). Additionally, there was a causal association between high-density lipoprotein-cholesterol (HDL-C) levels and an increased risk of AMD (p = 2.69 × 10-3, OR = 1.23), while triglycerides were found to mitigate the risk (p = 0.02, OR = 0.83). Notably, no significant associations were observed between other risk factors of DN and AMD.

CONCLUSIONS

These findings suggest that the impact of DN on the development of AMD may be more substantial than previously believed. Furthermore, elevated HDL-C levels appear to heighten the risk of AMD, whereas triglycerides may provide a protective effect.

Association of iron homeostasis biomarkers in type 2 diabetes and glycaemic traits: a bidirectional two-sample Mendelian randomization study

BACKGROUND

Mendelian randomization (MR) studies show iron positively associated with type 2 diabetes (T2D) but included potentially biasing hereditary haemochromatosis variants and did not assess reverse causality.

METHODS

We assessed the relation of iron homeostasis with T2D and glycaemic traits bidirectionally, using genome-wide association studies (GWAS) of iron homeostasis biomarkers [ferritin, serum iron, total iron-binding capacity (TIBC), transferrin saturation (TSAT) (n ≤ 246 139)], T2D (DIAMANTE n = 933 970 and FinnGen n = 300 483), and glycaemic traits [fasting glucose (FG), 2-h glucose, glycated haemoglobin (HbA1c) and fasting insulin (FI) (n ≤ 209 605)]. Inverse variance weighting (IVW) was the main analysis, supplemented with sensitivity analyses and assessment of mediation by hepcidin.

RESULTS

Iron homeostasis biomarkers were largely unrelated to T2D, although serum iron was potentially associated with higher T2D [odds ratio: 1.07 per standard deviation; 95% confidence interval (CI): 0.99 to 1.16; P-value: 0.078) in DIAMANTE only. Higher ferritin, serum iron, TSAT and lower TIBC likely decreased HbA1c, but were not associated with other glycaemic traits. Liability to T2D likely increased TIBC (0.03 per log odds; 95% CI: 0.01 to 0.05; P-value: 0.005), FI likely increased ferritin (0.29 per log pmol/L; 95% CI: 0.12 to 0.47; P-value: 8.72 x 10-4). FG likely increased serum iron (0.06 per mmol/L; 95% CI: 0.001 to 0.12; P-value: 0.046). Hepcidin did not mediate these associations.

CONCLUSION

It is unlikely that ferritin, TSAT and TIBC cause T2D although an association for serum iron could not be excluded. Glycaemic traits and liability to T2D may affect iron homeostasis, but mediation by hepcidin is unlikely. Corresponding mechanistic studies are warranted.

Association between glycemic traits and melanoma: a mendelian randomization analysis

Background: The causation of Glycemic Traits and risks of Melanoma remains unknown. We used Mendelian Randomization (MR) to assess the links between Glycemic Traits and Melanoma. Method: Pooled data from Genome-Wide Association Studies (GWAS) were utilized to examine the relationships that exist between Fasting Insulin (n = 26), 2-h Glucose (n = 10), Fasting Glucose (n = 47), HbA1c (n = 68), and Type-2 Diabetes (n = 105) and Melanoma. We evaluated the correlation of these variations with melanoma risk using Two-Samples MR. Result: In the IVW model, Fasting Glucose (OR = 0.99, 95%CI = 0.993-0.998, p < 0.05, IVW), Type-2 Diabetes (OR = 0.998, 95%CI = 0.998-0.999, p < 0.01, IVW) and HbA1c (OR = 0.19, 95%CI = 0.0415-0.8788, p < 0.05, IVW) was causally associated with a lower risk of Melanoma. In all models analyzed, there was no apparent causal relationship between Fasting Insulin and Melanoma risk. There was no obvious causal difference in the IVW analysis of 2-h Glucose and Melanoma, but its p < 0.05 in MR Egger (OR = 0.99, 95%CI = 0.9883-0.9984, p < 0.05, MR Egger), and the direction was consistent in other MR analyses, suggesting that there may be a causal relationship. Conclusion: The results of this study suggest that a higher risk of Fasting Glucose, Type-2 Diabetes, 2-h Glucose, and HbA1c may be associated with a lower risk of Melanoma. However, no causal relationship between fasting insulin and melanoma was found. These results suggest that pharmacological or lifestyle interventions that regulate plasma glucose levels in the body may be beneficial in the prevention of melanoma.

Causal effects of potential risk factors on postpartum depression: a Mendelian randomization study

Background

Postpartum depression (PPD) is a type of depressive episode related to parents after childbirth, which causes a variety of symptoms not only for parents but also affects the development of children. The causal relationship between potential risk factors and PPD remains comprehensively elucidated.

Methods

Linkage disequilibrium score regression (LDSC) analysis was conducted to screen the heritability of each instrumental variant (IV) and to calculate the genetic correlations between effective causal factors and PPD. To search for the causal effect of multiple potential risk factors on the incidence of PPD, random effects of the inverse variance weighted (IVW) method were applied. Sensitivity analyses, including weighted median, MR-Egger regression, Cochrane's Q test, and MR Pleiotropy Residual Sum and Outlier (MR-PRESSO), were performed to detect potential Mendelian randomization (MR) assumption violations. Multivariable MR (MVMR) was conducted to control potential multicollinearity.

Results

A total of 40 potential risk factors were investigated in this study. LDSC regression analysis reported a significant genetic correlation of potential traits with PPD. MR analysis showed that higher body mass index (BMI) (Benjamini and Hochberg (BH) corrected p = 0.05), major depression (MD) (BH corrected p = 5.04E-19), and schizophrenia (SCZ) (BH corrected p = 1.64E-05) were associated with the increased risk of PPD, whereas increased age at first birth (BH corrected p = 2.11E-04), older age at first sexual intercourse (BH corrected p = 3.02E-15), increased average total household income before tax (BH corrected p = 4.57E-02), and increased years of schooling (BH corrected p = 1.47E-11) led to a decreased probability of PPD. MVMR analysis suggested that MD (p = 3.25E-08) and older age at first birth (p = 8.18E-04) were still associated with an increased risk of PPD.

Conclusion

In our MR study, we found multiple risk factors, including MD and younger age at first birth, to be deleterious causal risk factors for PPD.

Mendelian randomization study supports the causal effects of air pollution on longevity via multiple age-related diseases

Growing evidence suggests that exposure to fine particulate matter (PM2.5) may reduce life expectancy; however, the causal pathways of PM2.5 exposure affecting life expectancy remain unknown. Here, we assess the causal effects of genetically predicted PM2.5 concentration on common chronic diseases and longevity using a Mendelian randomization (MR) statistical framework based on large-scale genome-wide association studies (GWAS) (>400,000 participants). After adjusting for other types of air pollution and smoking, we find significant causal relationships between PM2.5 concentration and angina pectoris, hypercholesterolaemia and hypothyroidism, but no causal relationship with longevity. Mediation analysis shows that although the association between PM2.5 concentration and longevity is not significant, PM2.5 exposure indirectly affects longevity via diastolic blood pressure (DBP), hypertension, angina pectoris, hypercholesterolaemia and Alzheimer's disease, with a mediated proportion of 31.5, 70.9, 2.5, 100, and 24.7%, respectively. Our findings indicate that public health policies to control air pollution may help improve life expectancy.

The citrate transporter SLC13A5 as a therapeutic target for kidney disease: evidence from Mendelian randomization to inform drug development

BACKGROUND

Solute carrier family 13 member 5 (SLC13A5) is a Na+-coupled citrate co-transporter that mediates entry of extracellular citrate into the cytosol. SLC13A5 inhibition has been proposed as a target for reducing progression of kidney disease. The aim of this study was to leverage the Mendelian randomization paradigm to gain insight into the effects of SLC13A5 inhibition in humans, towards prioritizing and informing clinical development efforts.

METHODS

The primary Mendelian randomization analyses investigated the effect of SLC13A5 inhibition on measures of kidney function, including creatinine and cystatin C-based measures of estimated glomerular filtration rate (creatinine-eGFR and cystatin C-eGFR), blood urea nitrogen (BUN), urine albumin-creatinine ratio (uACR), and risk of chronic kidney disease and microalbuminuria. Secondary analyses included a paired plasma and urine metabolome-wide association study, investigation of secondary traits related to SLC13A5 biology, a phenome-wide association study (PheWAS), and a proteome-wide association study. All analyses were compared to the effect of genetically predicted plasma citrate levels using variants selected from across the genome, and statistical sensitivity analyses robust to the inclusion of pleiotropic variants were also performed. Data were obtained from large-scale genetic consortia and biobanks, with sample sizes ranging from 5023 to 1,320,016 individuals.

RESULTS

We found evidence of associations between genetically proxied SLC13A5 inhibition and higher creatinine-eGFR (p = 0.002), cystatin C-eGFR (p = 0.005), and lower BUN (p = 3 × 10-4). Statistical sensitivity analyses robust to the inclusion of pleiotropic variants suggested that these effects may be a consequence of higher plasma citrate levels. There was no strong evidence of associations of genetically proxied SLC13A5 inhibition with uACR or risk of CKD or microalbuminuria. Secondary analyses identified evidence of associations with higher plasma calcium levels (p = 6 × 10-13) and lower fasting glucose (p = 0.02). PheWAS did not identify any safety concerns.

CONCLUSIONS

This Mendelian randomization analysis provides human-centric insight to guide clinical development of an SLC13A5 inhibitor. We identify plasma calcium and citrate as biologically plausible biomarkers of target engagement, and plasma citrate as a potential biomarker of mechanism of action. Our human genetic evidence corroborates evidence from various animal models to support effects of SLC13A5 inhibition on improving kidney function.

Genetic estimation of correlations between circulating glutamine and cancer

The controversy regarding the causal relationship between circulating glutamine and cancer risk remains unresolved. Here, we aim to assess the causal impact of glutamine on the risk of six prevalent cancer types and their respective subtypes including breast, lung, ovarian, thyroid, prostate, and endometrial cancers. A Mendelian randomization (MR) analysis was conducted to evaluate the causal effect of circulating glutamine on cancers risk. Data on circulating glutamine were extracted from the UK Biobank (UKB), comprising 114,750 European patients. To ensure the validity of our findings, we employed several analytical approaches, such as inverse variance weighting, weighted median, weighted mode test, MR-Egger regression, and MR-PRESSO method. Both univariable and multivariable MR analyses were conducted. Additionally, we employed a large-scale summary-level study on circulating glutamine involving 24,925 European participants for validation purposes. Our MR analysis reveals a causal association between circulating glutamine and thyroid cancer in both the UKB cohort (IVW: OR = 0.667, 95% CI [0.541-0.822], P = 1.52×10-4) and the validated cohort (IVW: OR = 0.577, 95% CI [0.421-0.790], P = 6.14×10-4). Sensitivity analysis, including multivariable MR analyses, consistently supports this finding (P < 0.05), affirming the reliability and robustness of our study. Our findings indicate an inverse correlation between circulating glutamine and the incidence of thyroid cancer in European populations. However, further research encompassing diverse ancestries is necessary to validate this causal relationship.

Mendelian randomization for cardiovascular diseases: principles and applications

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

Analysis across Taiwan Biobank, Biobank Japan, and UK Biobank identifies hundreds of novel loci for 36 quantitative traits

Genome-wide association studies (GWASs) have identified tens of thousands of genetic loci associated with human complex traits. However, the majority of GWASs were conducted in individuals of European ancestries. Failure to capture global genetic diversity has limited genomic discovery and has impeded equitable delivery of genomic knowledge to diverse populations. Here we report findings from 102,900 individuals across 36 human quantitative traits in the Taiwan Biobank (TWB), a major biobank effort that broadens the population diversity of genetic studies in East Asia. We identified 968 novel genetic loci, pinpointed novel causal variants through statistical fine-mapping, compared the genetic architecture across TWB, Biobank Japan, and UK Biobank, and evaluated the utility of cross-phenotype, cross-population polygenic risk scores in disease risk prediction. These results demonstrated the potential to advance discovery through diversifying GWAS populations and provided insights into the common genetic basis of human complex traits in East Asia.

Effect of Genetic and Dietary Perturbation of Glycine Metabolism on Atherosclerosis in Humans and Mice

Objective

Epidemiological and genetic studies have reported inverse associations between circulating glycine levels and risk of coronary artery disease (CAD). However, these findings have not been consistently observed in all studies. We sought to evaluate the causal relationship between circulating glycine levels and atherosclerosis using large-scale genetic analyses in humans and dietary supplementation experiments in mice.

Methods

Serum glycine levels were evaluated for association with prevalent and incident CAD in the UK Biobank. A multi-ancestry genome-wide association study (GWAS) meta-analysis was carried out to identify genetic determinants for circulating glycine levels, which were then used to evaluate the causal relationship between glycine and risk of CAD by Mendelian randomization (MR). A glycine feeding study was carried out with atherosclerosis-prone apolipoprotein E deficient (ApoE-/-) mice to determine the effects of increased circulating glycine levels on amino acid metabolism, metabolic traits, and aortic lesion formation.

Results

Among 105,718 subjects from the UK Biobank, elevated serum glycine levels were associated with significantly reduced risk of prevalent CAD (Quintile 5 vs. Quintile 1 OR=0.76, 95% CI 0.67-0.87; P<0.0001) and incident CAD (Quintile 5 vs. Quintile 1 HR=0.70, 95% CI 0.65-0.77; P<0.0001) in models adjusted for age, sex, ethnicity, anti-hypertensive and lipid-lowering medications, blood pressure, kidney function, and diabetes. A meta-analysis of 13 GWAS datasets (total n=230,947) identified 61 loci for circulating glycine levels, of which 26 were novel. MR analyses provided modest evidence that genetically elevated glycine levels were causally associated with reduced systolic blood pressure and risk of type 2 diabetes, but did provide evidence for an association with risk of CAD. Furthermore, glycine-supplementation in ApoE-/- mice did not alter cardiometabolic traits, inflammatory biomarkers, or development of atherosclerotic lesions.

Conclusions

Circulating glycine levels were inversely associated with risk of prevalent and incident CAD in a large population-based cohort. While substantially expanding the genetic architecture of circulating glycine levels, MR analyses and in vivo feeding studies in humans and mice, respectively, did not provide evidence that the clinical association of this amino acid with CAD represents a causal relationship, despite being associated with two correlated risk factors.

The association of psychological stress with metabolic syndrome and its components: cross-sectional and bidirectional two-sample Mendelian randomization analyses

Background

Metabolic syndrome (MetS) is a group of co-occurring conditions that increase the risk of cardiovascular disease, which include the conditions of hypertension, overweight or obesity, hyperglycemia, and dyslipidemia. Psychological stress is gradually being taken seriously, stemming from the imbalance between environmental demands and individual perceptions. However, the potential causal relationship between psychological stress and MetS remains unclear.

Method

We conducted cross-sectional and bidirectional Mendelian randomization (MR) analyses to clarify the potential causal relationship of psychological stress with MetS and its components. Multivariable logistic regression models were used to adjust for potential confounders in the cross-sectional study of the Chinese population, including 4,933 individuals (70.1% men; mean age, 46.13 ± 8.25). Stratified analyses of sexual characteristics were also performed. Bidirectional MR analyses were further carried out to verify causality based on summary-level genome-wide association studies in the European population, using the main analysis of the inverse variance-weighted method.

Results

We found that higher psychological stress levels were cross-sectionally associated with an increased risk of hypertension in men (odds ratio (OR), 1.341; 95% confidence interval (CI), 1.023-1.758; p = 0.034); moreover, higher levels of hypertension were cross-sectionally associated with an increased risk of psychological stress in men and the total population (men: OR, 1.545 (95% CI, 1.113-2.145); p = 0.009; total population: OR, 1.327 (95% CI, 1.025-1.718); p = 0.032). Genetically predicted hypertension was causally associated with a higher risk of psychological stress in the inverse-variance weighted MR model (OR, 2.386 (95% CI, 1.209-4.710); p = 0.012). However, there was no association between psychological stress and MetS or the other three risk factors (overweight or obesity, hyperglycemia, and dyslipidemia) in cross-sectional and MR analyses.

Conclusion

Although we did not observe an association between psychological stress and MetS, we found associations between psychological stress and hypertension both in cross-sectional and MR studies, which may have implications for targeting hypertension-related factors in interventions to improve mental and metabolic health. Further study is needed to confirm our findings.

Effects of diabetes mellitus and glycemic traits on cardiovascular morpho-functional phenotypes

BACKGROUND

The effects of diabetes on the cardiac and aortic structure and function remain unclear. Detecting and intervening these variations early is crucial for the prevention and management of complications. Cardiovascular magnetic resonance imaging-derived traits are established endophenotypes and serve as precise, early-detection, noninvasive clinical risk biomarkers. We conducted a Mendelian randomization (MR) study to examine the association between two types of diabetes, four glycemic traits, and preclinical endophenotypes of cardiac and aortic structure and function.

METHODS

Independent genetic variants significantly associated with type 1 diabetes, type 2 diabetes, fasting insulin (FIns), fasting glucose (FGlu), 2 h-glucose post-challenge (2hGlu), and glycated hemoglobin (HbA1c) were selected as instrumental variables. The 96 cardiovascular magnetic resonance imaging traits came from six independent genome-wide association studies. These traits serve as preclinical endophenotypes and offer an early indication of the structure and function of the four cardiac chambers and two aortic sections. The primary analysis was performed using MR with the inverse-variance weighted method. Confirmation was achieved through Steiger filtering and testing to determine the causal direction. Sensitivity analyses were conducted using the weighted median, MR-Egger, and MR-PRESSO methods. Additionally, multivariable MR was used to adjust for potential effects associated with body mass index.

RESULTS

Genetic susceptibility to type 1 diabetes was associated with increased ascending aortic distensibility. Conversely, type 2 diabetes showed a correlation with a reduced diameter and areas of the ascending aorta, as well as decreased distensibility of the descending aorta. Genetically predicted higher levels of FGlu and HbA1c were correlated with a decrease in diameter and areas of the ascending aorta. Furthermore, higher 2hGlu levels predominantly showed association with a reduced diameter of both the ascending and descending aorta. Higher FIns levels corresponded to increased regional myocardial-wall thicknesses at end-diastole, global myocardial-wall thickness at end-diastole, and regional peak circumferential strain of the left ventricle.

CONCLUSIONS

This study provides evidence that diabetes and glycemic traits have a causal relationship with cardiac and aortic structural and functional remodeling, highlighting the importance of intensive glucose-lowering for primary prevention of cardiovascular diseases.

Genetic effect of metformin use on risk of cancers: evidence from Mendelian randomization analysis

BACKGROUND

Increasing number of studies reported the positive effect of metformin on the prevention and treatment of cancers. However, the genetic causal effect of metformin utilization on the risk of common cancers was not completely demonstrated.

METHODS

Two-sample Mendelian Randomization (two-sample MR) analysis was conducted to uncover the genetically predicted causal association between metformin use and 26 kinds of cancers. Besides, two-step Mendelian Randomization (two-step MR) assessment was applied to clarify the mediators which mediated the causal effect of metformin on certain cancer. We utilized five robust analytical methods, in which the inverse variance weighting (IVW) method served as the major one. Sensitivity, pleiotropy, and heterogeneity were assessed. The genetic statistics of exposure, outcomes, and mediators were downloaded from publicly available datasets, including the Open Genome-Wide Association Study (GWAS), FinnGen consortium (FinnGen), and UK Biobank (UKB).

RESULTS

Among 26 kinds of common cancers, HER-positive breast cancer was presented with a significant causal relationship with metformin use [Beta: - 4.0982; OR: 0.0166 (95% CI: 0.0008, 0.3376); P value: 0.0077], which indicated metformin could prevent people from HER-positive breast cancer. Other cancers only showed modest associations with metformin use. Potential mediators were included in two-step MR, among which total testosterone levels (mediating effect: 24.52%) displayed significant mediating roles. Leave-one-out, MR-Egger, and MR-PRESSO analyses produced consistent outcomes.

CONCLUSION

Metformin use exhibited a genetically protective effect on HER-positive breast cancer, which was partially mediated by total testosterone levels.

Central Adiposity Increases Risk of Kidney Stone Disease through Effects on Serum Calcium Concentrations

SIGNIFICANCE STATEMENT

Kidney stone disease is a common disorder with poorly understood pathophysiology. Observational and genetic studies indicate that adiposity is associated with an increased risk of kidney stone disease. However, the relative contribution of general and central adipose depots and the mechanisms by which effects of adiposity on kidney stone disease are mediated have not been defined. Using conventional and genetic epidemiological techniques, we demonstrate that general and central adiposity are independently associated with kidney stone disease. In addition, one mechanism by which central adiposity increases risk of kidney stone disease is by increasing serum calcium concentration. Therapies targeting adipose depots may affect calcium homeostasis and help to prevent kidney stone disease.

BACKGROUND

Kidney stone disease affects approximately 10% of individuals in their lifetime and is frequently recurrent. The disease is linked to obesity, but the mechanisms mediating this association are uncertain.

METHODS

Associations of adiposity and incident kidney stone disease were assessed in the UK Biobank over a mean of 11.6 years/person. Genome-wide association studies and Mendelian randomization (MR) analyses were undertaken in the UK Biobank, FinnGen, and in meta-analyzed cohorts to identify factors that affect kidney stone disease risk.

RESULTS

Observational analyses on UK Biobank data demonstrated that increasing central and general adiposity is independently associated with incident kidney stone formation. Multivariable MR, using meta-analyzed UK Biobank and FinnGen data, established that risk of kidney stone disease increases by approximately 21% per one standard deviation increase in body mass index (BMI, a marker of general adiposity) independent of waist-to-hip ratio (WHR, a marker of central adiposity) and approximately 24% per one standard deviation increase of WHR independent of BMI. Genetic analyses indicate that higher WHR, but not higher BMI, increases risk of kidney stone disease by elevating adjusted serum calcium concentrations (β=0.12 mmol/L); WHR mediates 12%-15% of its effect on kidney stone risk in this way.

CONCLUSIONS

Our study indicates that visceral adipose depots elevate serum calcium concentrations, resulting in increased risk of kidney stone disease. These findings highlight the importance of weight loss in individuals with recurrent kidney stones and suggest that therapies targeting adipose depots may affect calcium homeostasis and contribute to prevention of kidney stone disease.

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

Background

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

Materials and methods

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

Results

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

Conclusion

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

SparsePro: An efficient fine-mapping method integrating summary statistics and functional annotations

Identifying causal variants from genome-wide association studies (GWAS) is challenging due to widespread linkage disequilibrium (LD) and the possible existence of multiple causal variants in the same genomic locus. Functional annotations of the genome may help to prioritize variants that are biologically relevant and thus improve fine-mapping of GWAS results. Classical fine-mapping methods conducting an exhaustive search of variant-level causal configurations have a high computational cost, especially when the underlying genetic architecture and LD patterns are complex. SuSiE provided an iterative Bayesian stepwise selection algorithm for efficient fine-mapping. In this work, we build connections between SuSiE and a paired mean field variational inference algorithm through the implementation of a sparse projection, and propose effective strategies for estimating hyperparameters and summarizing posterior probabilities. Moreover, we incorporate functional annotations into fine-mapping by jointly estimating enrichment weights to derive functionally-informed priors. We evaluate the performance of SparsePro through extensive simulations using resources from the UK Biobank. Compared to state-of-the-art methods, SparsePro achieved improved power for fine-mapping with reduced computation time. We demonstrate the utility of SparsePro through fine-mapping of five functional biomarkers of clinically relevant phenotypes. In summary, we have developed an efficient fine-mapping method for integrating summary statistics and functional annotations. Our method can have wide utility in understanding the genetics of complex traits and increasing the yield of functional follow-up studies of GWAS. SparsePro software is available on GitHub at https://github.com/zhwm/SparsePro.

Association of Bone Mineral Density and Bone Turnover Markers with the Risk of Diabetes: Hong Kong Osteoporosis Study and Mendelian Randomization

Preclinical studies demonstrated that bone plays a central role in energy metabolism. However, how bone metabolism is related to the risk of diabetes in humans is unknown. We investigated the association of bone health (bone mineral density [BMD] and bone turnover markers) with incident type-2 diabetes mellitus (T2DM) based on the Hong Kong Osteoporosis Study (HKOS). A total of 993 and 7160 participants from the HKOS were studied for the cross-sectional and prospective analyses, respectively. The cross-sectional study evaluated the association of BMD and bone biomarkers with fasting glucose and glycated hemoglobin (HbA1c ) levels, whereas the prospective study examined the associations between BMD at study sites and the risk of T2DM by following subjects a median of 16.8 years. Body mass index (BMI) was adjusted in all full models. Mendelian randomization (MR) was conducted for causal inference. In the cross-sectional analysis, lower levels of circulating bone turnover markers and higher BMD were significantly associated with increased fasting glucose and HbA1c levels. In the prospective analysis, higher BMD (0.1 g/cm2 ) at the femoral neck and total hip was associated with increased risk of T2DM with hazard ratios (HRs) of 1.10 (95% confidence interval [CI], 1.03 to 1.18) and 1.14 (95% CI, 1.08 to 1.21), respectively. The presence of osteoporosis was associated with a 30% reduction in risk of T2DM compared to those with normal BMD (HR = 0.70; 95% CI, 0.55 to 0.90). The MR results indicate a robust genetic causal association of estimated BMD (eBMD) with 2-h glucose level after an oral glucose challenge test (estimate = 0.043; 95% CI, 0.007 to 0.079) and T2DM (odds ratio = 1.064; 95% CI, 1.036 to 1.093). Higher BMD and lower levels of circulating bone biomarkers were cross-sectionally associated with poor glycemic control. Moreover, higher BMD was associated with a higher risk of incident T2DM and the association is probably causal. © 2023 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR).

Genetic risk converges on regulatory networks mediating early type 2 diabetes

Type 2 diabetes mellitus (T2D), a major cause of worldwide morbidity and mortality, is characterized by dysfunction of insulin-producing pancreatic islet β cells1,2. T2D genome-wide association studies (GWAS) have identified hundreds of signals in non-coding and β cell regulatory genomic regions, but deciphering their biological mechanisms remains challenging3-5. Here, to identify early disease-driving events, we performed traditional and multiplexed pancreatic tissue imaging, sorted-islet cell transcriptomics and islet functional analysis of early-stage T2D and control donors. By integrating diverse modalities, we show that early-stage T2D is characterized by β cell-intrinsic defects that can be proportioned into gene regulatory modules with enrichment in signals of genetic risk. After identifying the β cell hub gene and transcription factor RFX6 within one such module, we demonstrated multiple layers of genetic risk that converge on an RFX6-mediated network to reduce insulin secretion by β cells. RFX6 perturbation in primary human islet cells alters β cell chromatin architecture at regions enriched for T2D GWAS signals, and population-scale genetic analyses causally link genetically predicted reduced RFX6 expression with increased T2D risk. Understanding the molecular mechanisms of complex, systemic diseases necessitates integration of signals from multiple molecules, cells, organs and individuals, and thus we anticipate that this approach will be a useful template to identify and validate key regulatory networks and master hub genes for other diseases or traits using GWAS data.

Role of leisure sedentary behavior on type 2 diabetes and glycemic homeostasis: a Mendelian randomization analysis

Purpose

Utilize Mendelian randomization (MR) to examine the impact of leisure sedentary behavior (LSB) on the prevalence of type 2 diabetes mellitus (T2D) and glycemic homeostasis impairment, as well as to identify potential mediating pathways involved in these associations.

Methods

We chose genetic variants linked to LSB from a large genome-wide association study (GWAS) to use as instrumental variables (IVs). Then, we used a two-sample MR study to investigate the link between LSB and T2D and glycemic homeostasis. Multivariate MR (MVMR) and mediation analysis were also used to look at possible mediating paths.

Results

MR analysis showed a genetical link between leisure TV watching and T2D (OR 1.64, 95% CI 1.39-1.93, P< 0.001) and impaired Glycemic Homeostasis, while leisure computer use seemed to protect against T2D prevalence (OR 0.65, 95% CI 0.50-0.84, P< 0.001). It was found that leisure TV watching increases the risk of T2D through higher BMI (mediation effect 0.23, 95% CI 0.11-0.35, P< 0.001), higher triglycerides (mediation effect 0.07, 95% CI 0.04-0.11, P< 0.001), and less education (mediation effect 0.16, 95% CI 0.08-0.24, P< 0.001). Sensitivity and heterogeneity analyses further substantiated the robustness of these findings. Reverse MR analysis did not yield significant results.

Conclusion

This study shows LSB is linked to a higher rate of T2D and impaired glycemic homeostasis through obesity, lipid metabolism disorders, and reduced educational attainment.

Circulating sex hormone-binding globulin levels and ischemic stroke risk: a Mendelian randomization study

PURPOSE

Previous studies have presented conflicting findings regarding the protective effects of circulating sex hormone-binding globulin (SHBG) on ischemic stroke (IS). This study aimed to assess the causal effect of SHBG on IS using Mendelian randomization (MR) analysis and to identify potential mediators.

METHODS

First, the causal effect of SHBG on any IS (AIS), cardioembolic stroke (CES), large artery stroke (LAS), and small vessel stroke (SVS) was assessed by inverse variance weighed (IVW) method. Two additional MR methods (weighted median and MR-Egger) were used to supplement the IVW results. Subsequently, a two-step MR was further performed to assess whether three glycemic profiles [fasting glucose, fasting insulin, and glycated hemoglobin (HbA1c)] and five lipid profiles (high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, non-HDL cholesterol, total cholesterol, and triglycerides) mediated the causal effect. Furthermore, Cochrane's Q test, MR-Egger intercept test, MR-PRESSO global test, and leave-one-out analysis were performed for sensitivity analyses.

RESULTS

The IVW results showed that SHBG significantly reduced SVS risk (odds ratio= 0.60, 95% confidence interval: 0.47-0.77, P = 4.60E-05). The weighted median and MR-Egger results were parallel to IVW. However, no significant associations were found between SHBG and AIS, CES, and LAS. Mediation analysis indicated that HbA1c may be involved in SHBG reducing SVS risk. Sensitivity tests demonstrated the reliability of causal estimates.

CONCLUSIONS

Circulating SHBG levels may decrease SVS risk by lowering HbA1c levels. Therefore, individuals with low circulating SHBG levels should focus on glycemic control to reduce future SVS risk.

Thyroid Function and Metabolic Syndrome: A Two-Sample Bidirectional Mendelian Randomization Study

CONTEXT

Thyroid function has been associated with metabolic syndrome (MetS) in a number of observational studies but the direction of effects and the exact causal mechanism of this relationship is still unknown.

OBJECTIVE

To examine genetically predicted effects of thyroid function on MetS risk and its components, and vice versa, using large-scale summary genetic association data.

METHODS

We performed a two-sample bidirectional Mendelian randomization (MR) study using summary statistics from the most comprehensive genome-wide association studies (GWAS) of thyroid-stimulating hormone (TSH, n = 119 715), free thyroxine (fT4, n = 49 269), MetS (n = 291 107), and components of MetS: waist circumference (n = 462 166), fasting blood glucose (n = 281 416), hypertension (n = 463 010), triglycerides (TG, n = 441 016) and high-density lipoprotein cholesterol (HDL-C, n = 403 943). We chose the multiplicative random effects inverse variance weighted (IVW) method as the main analysis. Sensitivity analysis included weighted median and mode analysis, as well as MR-Egger and Causal Analysis Using Summary Effect estimates (CAUSE).

RESULTS

Our results suggest that higher fT4 levels lower the risk of developing MetS (OR = 0.96, P = .037). Genetically predicted fT4 was also positively associated with HDL-C (β = 0.02, P = .008), while genetically predicted TSH was positively associated with TG (β = 0.01, P = .044). These effects were consistent across different MR analyses and confirmed with the CAUSE analysis. In the reverse direction MR analysis, genetically predicted HDL-C was negatively associated with TSH (β = -0.03, P = .046) in the main IVW analysis.

CONCLUSION

Our study suggests that variations in normal-range thyroid function are causally associated with the diagnosis of MetS and with lipid profile, while in the reverse direction, HDL-C has a plausible causal effect on reference-range TSH levels.

Precision Medicine in Type 2 Diabetes Mellitus: Utility and Limitations

Type 2 diabetes mellitus (T2DM) is one of the most widespread diseases in Western countries, and its incidence is constantly increasing. Epidemiological studies have shown that in the next 20 years. The number of subjects affected by T2DM will double. In recent years, owing to the development and improvement in methods for studying the genome, several authors have evaluated the association between monogenic or polygenic genetic alterations and the development of metabolic diseases and complications. In addition, sedentary lifestyle and socio-economic and pandemic factors have a great impact on the habits of the population and have significantly contributed to the increase in the incidence of metabolic disorders, obesity, T2DM, metabolic syndrome, and liver steatosis. Moreover, patients with type 2 diabetes appear to respond to antihyperglycemic drugs. Only a minority of patients could be considered true non-responders. Thus, it appears clear that the main aim of precision medicine in T2DM is to identify patients who can benefit most from a specific drug class more than from the others. Precision medicine is a discipline that evaluates the applicability of genetic, lifestyle, and environmental factors to disease development. In particular, it evaluated whether these factors could affect the development of diseases and their complications, response to diet, lifestyle, and use of drugs. Thus, the objective is to find prevention models aimed at reducing the incidence of pathology and mortality and therapeutic personalized approaches, to obtain a greater probability of response and efficacy. This review aims to evaluate the applicability of precision medicine for T2DM, a healthcare burden in many countries.

High-frequency variants in PKA signaling-related genes within a large pediatric cohort with obesity or metabolic abnormalities

Introduction

Pediatric obesity has steadily increased in recent decades. Large-scale genome-wide association studies (GWAS) conducted primarily in Eurocentric adult populations have identified approximately 100 loci that predispose to obesity and type II diabetes. GWAS in children and individuals of non-European descent, both disproportionately affected by obesity, are fewer. Rare syndromic and monogenic obesities account for only a small portion of childhood obesity, so understanding the role of other genetic variants and their combinations in heritable obesities is key to developing targeted and personalized therapies. Tight and responsive regulation of the cAMP-dependent protein kinase (PKA) signaling pathway is crucial to maintaining healthy energy metabolism, and mutations in PKA-linked genes represent the most common cause of monogenic obesity.

Methods

For this study, we performed targeted exome sequencing of 53 PKA signaling-related genes to identify variants in genomic DNA from a large, ethnically diverse cohort of obese or metabolically challenged youth.

Results

We confirmed 49 high-frequency variants, including a novel variant in the PDE11A gene (c.152C>T). Several other variants were associated with metabolic characteristics within ethnic groups.

Discussion

We conclude that a PKA pathway-specific variant search led to the identification of several new genetic associations with obesity in an ethnically diverse population.

Leveraging information between multiple population groups and traits improves fine-mapping resolution

Statistical fine-mapping helps to pinpoint likely causal variants underlying genetic association signals. Its resolution can be improved by (i) leveraging information between traits; and (ii) exploiting differences in linkage disequilibrium structure between diverse population groups. Using association summary statistics, MGflashfm jointly fine-maps signals from multiple traits and population groups; MGfm uses an analogous framework to analyse each trait separately. We also provide a practical approach to fine-mapping with out-of-sample reference panels. In simulation studies we show that MGflashfm and MGfm are well-calibrated and that the mean proportion of causal variants with PP > 0.80 is above 0.75 (MGflashfm) and 0.70 (MGfm). In our analysis of four lipids traits across five population groups, MGflashfm gives a median 99% credible set reduction of 10.5% over MGfm. MGflashfm and MGfm only require summary level data, making them very useful fine-mapping tools in consortia efforts where individual-level data cannot be shared.

Unraveling the associations and causalities between glucose metabolism and multiple sleep traits

Purpose

The aim of our study is to estimate the associations and causalities of glucose metabolism traits of fasting blood glucose (FBG), fasting insulin (FINS), glycosylated hemoglobin (HbA1c), and 2-h glucose post-challenge (2hGlu) with sleep traits consisting of excessive daytime sleepiness (EDS), insomnia, and sleep duration.

Methods

We employed standard quantitative analysis procedures to assess the associations between sleep traits and glucose metabolism. Moreover, we acquired published genome-wide association studies (GWAS) summary statistics for these traits and conducted Mendelian randomization (MR) analyses to estimate their causal directions and effects. Inverse variance weighting (IVW) was employed as the primary approach, followed by sensitivity analyses.

Results

A total of 116 studies with over 840,000 participants were included in the quantitative analysis. Our results revealed that participants with abnormal glucose metabolism had higher risks for EDS (OR [95% CI] = 1.37 [1.10,1.69]), insomnia (OR [95% CI] = 1.65 [1.24,2.20]), and both short and long sleep duration (OR [95% CI] = 1.35 [1.12,1.63]; OR [95% CI] = 1.38 [1.13,1.67] respectively). In addition, individuals with these sleep traits exhibited alterations in several glycemic traits compared with non-affected controls. In MR analysis, the primary analysis demonstrated causal effects of 2hGlu on risks of EDS (OR [95% CI] = 1.022 [1.002,1.042]) and insomnia (OR [95% CI] = 1.020[1.001,1.039]). Furthermore, FINS was associated with short sleep duration (OR [95% CI] = 1.043 [1.018,1.068]), which reversely presented a causal influence on HbA1c (β [95% CI] = 0.131 [0.022,0.239]). These results were confirmed by sensitivity analysis.

Conclusion

Our results suggested mutual risk and causal associations between the sleep traits and glycemic traits, shedding new light on clinical strategies for preventing sleep disorders and regulating glucose metabolism. Future studies targeting these associations may hold a promising prospect for public health.

Genetic insights into the risk of metabolic syndrome and its components on stroke and its subtypes: Bidirectional Mendelian randomization

The role of metabolic syndrome (MetS) on stroke has been explored only in many observational studies. We conducted Mendelian randomization (MR) to clarify whether or not the genetically predicted MetS and its components are causally associated with stroke and its subtypes. Genetic instruments of MetS and its components and outcome data sets for stroke and its subtypes came from the gene-wide association study in the UK Biobank and MEGASTROKE consortium, respectively. Inverse variance weighting was utilized as the main method. Genetically predicted MetS, waist circumference (WC), and hypertension increase the risk of stroke. WC and hypertension are related to increased risk of ischemic stroke. MetS, WC, hypertension, and triglycerides (TG) are causally associated with the increasing of large artery stroke. Hypertension increased the risk of cardioembolic stroke. Hypertension and TG lead to 77.43- and 1.19-fold increases, respectively, in small vessel stroke (SVS) risk. The protective role of high-density lipoprotein cholesterol on SVS is identified. Results of the reverse MR analyses show that stroke is related to hypertension risk. From the genetical variants perspective, our study provides novel evidence that early management of MetS and its components are effective strategies to decrease the risk of stroke and its subtypes.

The case for precision medicine in the prevention, diagnosis, and treatment of cardiometabolic diseases in low-income and middle-income countries

Cardiometabolic diseases are the leading preventable causes of death in most geographies. The causes, clinical presentations, and pathogenesis of cardiometabolic diseases vary greatly worldwide, as do the resources and strategies needed to prevent and treat them. Therefore, there is no single solution and health care should be optimised, if not to the individual (ie, personalised health care), then at least to population subgroups (ie, precision medicine). This optimisation should involve tailoring health care to individual disease characteristics according to ethnicity, biology, behaviour, environment, and subjective person-level characteristics. The capacity and availability of local resources and infrastructures should also be considered. Evidence needed for equitable precision medicine cannot be generated without adequate data from all target populations, and the idea that research done in high-income countries will transfer adequately to low-income and middle-income countries (LMICs) is problematic, as many migration studies and transethnic comparisons have shown. However, most data for precision medicine research are derived from people of European ancestry living in high-income countries. In this Series paper, we discuss the case for precision medicine for cardiometabolic diseases in LMICs, the barriers and enablers, and key considerations for implementation. We focus on three propositions: first, failure to explore and implement precision medicine for cardiometabolic disease in LMICs will enhance global health disparities. Second, some LMICs might already be placed to implement cardiometabolic precision medicine under appropriate circumstances, owing to progress made in treating infectious diseases. Third, improvements in population health from precision medicine are most probably asymptotic; the greatest gains are more likely to be obtained in countries where health-care systems are less developed. We outline key recommendations for implementation of precision medicine approaches in LMICs.

The Associations of Genetically Predicted Plasma Alanine with Coronary Artery Disease and its Risk Factors: A Mendelian Randomization Study

BACKGROUND

Alanine is an amino acid commonly used as a nutritional supplement and plays a key role in the glucose-alanine cycle. Plasma alanine has been associated in observational studies with a higher risk of coronary artery disease (CAD) and unhealthier lipid profiles. However, evidence from large randomized controlled trials is lacking.

OBJECTIVES

Using Mendelian randomization (MR), we assessed the unconfounded associations of plasma alanine with CAD and CAD risk factors.

METHODS

We applied single nucleotide polymorphisms that were strongly (P < 5 ×10-8) associated with plasma alanine as genetic instruments to large genome-wide association studies of CAD (63,108 cases; 296,901 controls), diabetes (90,612 cases; 583,493 controls), glucose (515,538 participants), lipids (low-density lipoprotein [LDL] cholesterol, high-density lipoprotein [HDL] cholesterol, triglycerides, total cholesterol, and apolipoprotein B) (>1.1 million participants), blood pressure (BP) (757,601 participants), and body mass index (682,137 participants). Given the potential sex disparity, we also conducted sex-specific analyses. MR estimates per standard deviation increase in alanine concentrations were obtained using inverse variance weighting followed by sensitivity analyses using weighted median, MR-Egger, MR-Pleiotropy RESidual Sum and Outlier, and MR-Robust Adjusted Profile Score.

RESULTS

Genetically predicted plasma alanine was not associated with CAD but with a higher risk of diabetes (odds ratio [OR]: 1.35; 95% confidence interval [CI]: 1.06, 1.72), higher glucose (β: 0.11; 95% CI: 0.02, 0.19), LDL cholesterol (β: 0.08; 95% CI: 0.04, 0.12), triglycerides (β: 0.25; 95% CI: 0.13, 0.38), total cholesterol (β: 0.14; 95% CI: 0.08, 0.20), apolipoprotein B (β: 0.12; 95% CI: 0.03, 0.21), and BP (β: 1.17; 95% CI: 0.31, 2.04 for systolic BP: β: 0.97; 95% CI: 0.49, 1.45 for diastolic BP) overall. The positive associations of serum alanine with LDL cholesterol and triglycerides were more notable in women than in men.

CONCLUSIONS

Alanine or factors affecting alanine may have causal effects on diabetes, blood glucose, lipid profiles, and BP but not on CAD. Further studies are needed to clarify possible mechanisms.

Unraveling the pathogenesis of non-alcoholic fatty liver diseases through genome-wide association studies

Non-alcoholic fatty liver disease (NAFLD) is a significant health burden around the world, affecting approximately 25% of the population. Recent advances in human genetic databases have allowed for the identification of various single nucleotide polymorphisms associated with NAFLD-related traits. Investigating the functions of these genetic factors provides insight into the pathogenesis of NAFLD and potentially identifies novel therapeutic targets for NAFLD. In this review, we summarized current research on genes with NAFLD-associated mutations, highlighting phospholipid remodeling and spatially clustered loci as common pathological and genetic features of these mutations. These features suggest a complex yet intriguing mechanism of dissociated steatosis and insulin resistance, which is observed in a subset of patients and may lead to more precise therapy against NAFLD in the future.

Testing for associations between HbA1c levels, polygenic risk and brain health in UK Biobank (N = 39 283)

AIM

To investigate whether continuous HbA1c levels and HbA1c-polygenic risk scores (HbA1c-PRS) are significantly associated with worse brain health independent of type 2 diabetes (T2D) diagnosis (vs. not), by examining brain structure and cognitive test score phenotypes.

METHODS

Using UK Biobank data (n = 39 283), we tested whether HbA1c levels and/or HbA1c-PRS were associated with cognitive test scores and brain imaging phenotypes. We adjusted for confounders of age, sex, Townsend deprivation score, level of education, genotyping chip, eight genetic principal components, smoking, alcohol intake frequency, cholesterol medication, body mass index, T2D and apolipoprotein (APOE) e4 dosage.

RESULTS

We found an association between higher HbA1c levels and poorer performance on symbol digit substitution scores (standardized beta [β] = -0.022, P = .001) in the fully adjusted model. We also found an association between higher HbA1c levels and worse brain MRI phenotypes of grey matter (GM; fully-adjusted β = -0.026, P < .001), whole brain volume (β = -0.072, P = .0113) and a general factor of frontal lobe GM (β = -0.022, P < .001) in partially and fully adjusted models. HbA1c-PRS were significantly associated with GM volume in the fully adjusted model (β = -0.010, P = .0113); however, when adjusted for HbA1c levels, the association was not significant.

CONCLUSIONS

Our findings suggest that measured HbA1c is associated with poorer cognitive health, and that HbA1c-PRS do not add significant information to this.

eQTL mapping in fetal-like pancreatic progenitor cells reveals early developmental insights into diabetes risk

The impact of genetic regulatory variation active in early pancreatic development on adult pancreatic disease and traits is not well understood. Here, we generate a panel of 107 fetal-like iPSC-derived pancreatic progenitor cells (iPSC-PPCs) from whole genome-sequenced individuals and identify 4065 genes and 4016 isoforms whose expression and/or alternative splicing are affected by regulatory variation. We integrate eQTLs identified in adult islets and whole pancreas samples, which reveal 1805 eQTL associations that are unique to the fetal-like iPSC-PPCs and 1043 eQTLs that exhibit regulatory plasticity across the fetal-like and adult pancreas tissues. Colocalization with GWAS risk loci for pancreatic diseases and traits show that some putative causal regulatory variants are active only in the fetal-like iPSC-PPCs and likely influence disease by modulating expression of disease-associated genes in early development, while others with regulatory plasticity likely exert their effects in both the fetal and adult pancreas by modulating expression of different disease genes in the two developmental stages.

Adipose tissue eQTL meta-analysis reveals the contribution of allelic heterogeneity to gene expression regulation and cardiometabolic traits

Complete characterization of the genetic effects on gene expression is needed to elucidate tissue biology and the etiology of complex traits. Here, we analyzed 2,344 subcutaneous adipose tissue samples and identified 34K conditionally distinct expression quantitative trait locus (eQTL) signals in 18K genes. Over half of eQTL genes exhibited at least two eQTL signals. Compared to primary signals, non-primary signals had lower effect sizes, lower minor allele frequencies, and less promoter enrichment; they corresponded to genes with higher heritability and higher tolerance for loss of function. Colocalization of eQTL with conditionally distinct genome-wide association study signals for 28 cardiometabolic traits identified 3,605 eQTL signals for 1,861 genes. Inclusion of non-primary eQTL signals increased colocalized signals by 46%. Among 30 genes with ≥2 pairs of colocalized signals, 21 showed a mediating gene dosage effect on the trait. Thus, expanded eQTL identification reveals more mechanisms underlying complex traits and improves understanding of the complexity of gene expression regulation.