Large-scale association analyses identify new loci influencing glycemic traits and provide insight into the underlying biological pathways

A haplotype in the dipeptidyl peptidase 4 gene impacts glycemic-related traits of Brazilian older adults

Dipeptidyl peptidase 4 (DPP4) regulates various physiological pathways and has a pivotal role in glucose homeostasis. The objective of this study was to verify the association of a haplotype constituted by two single nucleotide polymorphisms (rs2268894 and rs6741949) in the DPP4 gene with type 2 diabetes mellitus (T2DM) and fasting glycemia-related variables in a sample of Brazilian older adults, taking serum levels and enzymatic activity of DPP4 into account. Clinical, biochemical, and anthropometric characteristics as well as DPP4 serum levels and enzymatic activity were determined in 800 elderly (≥60 years old) individuals. Assessment of polymorphic sites was performed by real-time PCR whereas haplotypes were inferred from genotypic frequencies. Statistical analyses compared measures and proportions according to T2DM diagnosis and DPP4 haplotypic groups. The most common haplotype consisted of the T-rs2268894/G-rs6741949 string, which was 20% more frequent among non-diabetics. Considering non-diabetic patients alone, carriers of the T/G haplotype had significantly lower levels of blood glucose, insulin, HOMA-IR index, and DPP4 activity. Among diabetic patients, the T/G haplotype was associated with lower DPP4 levels whereas glycemic scores were not affected by allelic variants. Our results suggested that the genetic architecture of DPP4 affects the glycemic profile and DPP4 serum levels and activity among elderly individuals according to the presence or absence of T2DM, with a possible implication of the T/G haplotype to the risk of T2DM onset.

Metabolic actions of the growth hormone-insulin growth factor-1 axis and its interaction with the central nervous system

The growth hormone/insulin growth factor-1 axis is a key endocrine system that exerts profound effects on metabolism by its actions on different peripheral tissues but also in the brain. Growth hormone together with insulin growth factor-1 perform metabolic adjustments, including regulation of food intake, energy expenditure, and glycemia. The dysregulation of this hepatic axis leads to different metabolic disorders including obesity, type 2 diabetes or liver disease. In this review, we discuss how the growth hormone/insulin growth factor-1 axis regulates metabolism and its interactions with the central nervous system. Finally, we state our vision for possible therapeutic uses of compounds based in the components of this hepatic axis.

Differentiating Associations of Glycemic Traits With Atherosclerotic and Thrombotic Outcomes: Mendelian Randomization Investigation

We conducted a Mendelian randomization analysis to differentiate associations of four glycemic indicators with a broad range of atherosclerotic and thrombotic diseases. Independent genetic variants associated with fasting glucose (FG), 2 h glucose after an oral glucose challenge (2hGlu), fasting insulin (FI), and glycated hemoglobin (HbA1c) at the genome-wide significance threshold were used as instrumental variables. Summary-level data for 12 atherosclerotic and 4 thrombotic outcomes were obtained from large genetic consortia and the FinnGen and UK Biobank studies. Higher levels of genetically predicted glycemic traits were consistently associated with increased risk of coronary atherosclerosis-related diseases and symptoms. Genetically predicted glycemic traits except HbA1c showed positive associations with peripheral artery disease risk. Genetically predicted FI levels were positively associated with risk of ischemic stroke and chronic kidney disease. Genetically predicted FG and 2hGlu were positively associated with risk of large artery stroke. Genetically predicted 2hGlu levels showed positive associations with risk of small vessel stroke. Higher levels of genetically predicted glycemic traits were not associated with increased risk of thrombotic outcomes. Most associations for genetically predicted levels of 2hGlu and FI remained after adjustment for other glycemic traits. Increase in glycemic status appears to increase risks of coronary and peripheral artery atherosclerosis but not thrombosis.

Multi-ancestry genome-wide association study of gestational diabetes mellitus highlights genetic links with type 2 diabetes

Gestational diabetes mellitus (GDM) is associated with increased risk of pregnancy complications and adverse perinatal outcomes. GDM often reoccurs and is associated with increased risk of subsequent diagnosis of type 2 diabetes (T2D). To improve our understanding of the aetiological factors and molecular processes driving the occurrence of GDM, including the extent to which these overlap with T2D pathophysiology, the GENetics of Diabetes In Pregnancy Consortium assembled genome-wide association studies of diverse ancestry in a total of 5485 women with GDM and 347 856 without GDM. Through multi-ancestry meta-analysis, we identified five loci with genome-wide significant association (P < 5 × 10-8) with GDM, mapping to/near MTNR1B (P = 4.3 × 10-54), TCF7L2 (P = 4.0 × 10-16), CDKAL1 (P = 1.6 × 10-14), CDKN2A-CDKN2B (P = 4.1 × 10-9) and HKDC1 (P = 2.9 × 10-8). Multiple lines of evidence pointed to the shared pathophysiology of GDM and T2D: (i) four of the five GDM loci (not HKDC1) have been previously reported at genome-wide significance for T2D; (ii) significant enrichment for associations with GDM at previously reported T2D loci; (iii) strong genetic correlation between GDM and T2D and (iv) enrichment of GDM associations mapping to genomic annotations in diabetes-relevant tissues and transcription factor binding sites. Mendelian randomization analyses demonstrated significant causal association (5% false discovery rate) of higher body mass index on increased GDM risk. Our results provide support for the hypothesis that GDM and T2D are part of the same underlying pathology but that, as exemplified by the HKDC1 locus, there are genetic determinants of GDM that are specific to glucose regulation in pregnancy.

Evidence of genetic overlap and causal relationships between blood-based biochemical traits and human cortical anatomy

Psychiatric disorders such as schizophrenia are commonly associated with structural brain alterations affecting the cortex. Recent genetic evidence suggests circulating metabolites and other biochemical traits play a causal role in many psychiatric disorders which could be mediated by changes in the cerebral cortex. Here, we leveraged publicly available genome-wide association study data to explore shared genetic architecture and evidence for causal relationships between a panel of 50 biochemical traits and measures of cortical thickness and surface area. Linkage disequilibrium score regression identified 191 genetically correlated biochemical-cortical trait pairings, with consistent representation of blood cell counts and other biomarkers such as C-reactive protein (CRP), haemoglobin and calcium. Spatially organised patterns of genetic correlation were additionally uncovered upon clustering of region-specific correlation profiles. Interestingly, by employing latent causal variable models, we found strong evidence suggesting CRP and vitamin D exert causal effects on region-specific cortical thickness, with univariable and multivariable Mendelian randomization further supporting a negative causal relationship between serum CRP levels and thickness of the lingual region. Our findings suggest a subset of biochemical traits exhibit shared genetic architecture and potentially causal relationships with cortical structure in functionally distinct regions, which may contribute to alteration of cortical structure in psychiatric disorders.

The Link between Three Single Nucleotide Variants of the GIPR Gene and Metabolic Health

Single nucleotide variants (SNVs) of the GIPR gene have been associated with BMI and type 2 diabetes (T2D), suggesting the role of the variation in this gene in metabolic health. To increase our understanding of this relationship, we investigated the association of three GIPR SNVs, rs11672660, rs2334255 and rs10423928, with anthropometric measurements, selected metabolic parameters, and the risk of excessive body mass and metabolic syndrome (MS) in the Polish population. Normal-weight subjects (n = 340, control group) and subjects with excessive body mass (n = 600, study group) participated in this study. For all participants, anthropometric measurements and metabolic parameters were collected, and genotyping was performed using the high-resolution melting curve analysis. We did not find a significant association between rs11672660, rs2334255 and rs10423928 variants with the risk of being overweight. Differences in metabolic and anthropometric parameters were found for investigated subgroups. An association between rs11672660 and rs10423928 with MS was identified. Heterozygous CT genotype of rs11672660 and AT genotype of rs10423928 were significantly more frequent in the group with MS (OR = 1.38, 95%CI: 1.03–1.85; p = 0.0304 and OR = 1.4, 95%CI: 1.05–1.87; p = 0.0222, respectively). Moreover, TT genotype of rs10423928 was less frequent in the MS group (OR = 0.72, 95%CI: 0.54–0.95; p = 0.0221).

Triangulating evidence for the causal impact of single-intervention zinc supplement on glycaemic control for type 2 diabetes: systematic review and meta-analysis of randomised controlled trial and two-sample Mendelian randomisation

Although previous studies suggested the protective effect of Zn for type 2 diabetes (T2D), the unitary causal effect remains inconclusive. We investigated the causal effect of Zn as a single intervention on glycaemic control for T2D, using a systematic review of randomised controlled trials and two-sample Mendelian randomisation (MR). Four primary outcomes were identified: fasting blood glucose/fasting glucose, HbA1c, homeostatic model assessment for insulin resistance (HOMA-IR) and serum insulin/fasting insulin level. In the systematic review, four databases were searched until June 2021. Studies, in which participants had T2D and intervention did not comprise another co-supplement, were included. Results were synthesised through the random-effects meta-analysis. In the two-sample MR, we used single-nucleotide polymorphisms (SNP) from MR-base, strongly related to Zn supplements, to infer the relationship causally, but not specified T2D. In the systematic review and meta-analysis, fourteen trials were included with overall 897 participants initially. The Zn supplement led to a significant reduction in the post-trial mean of fasting blood glucose (mean difference (MD): −26·52 mg/dl, 95 % CI (−35·13, −17·91)), HbA1c (MD: −0·52 %, 95 % CI: (−0·90, −0·13)) and HOMA-IR (MD: −1·65, 95 % CI (−2·62, −0·68)), compared to the control group. In the two-sample MR, Zn supplement with two SNP reduced the fasting glucose (inverse-variance weighted coefficient: −2·04 mmol/l, 95 % CI (−3·26, −0·83)). From the two methods, Zn supplementation alone may causally improve glycaemic control among T2D patients. The findings are limited by power from the small number of studies and SNP included in the systematic review and two-sample MR analysis, respectively.

Causal Association of Cardiovascular Risk Factors and Lifestyle Behaviors With Peripheral Artery Disease: A Mendelian Randomization Approach

Background

We investigated the causal associations between the genetic liability to cardiovascular and lifestyle risk factors and peripheral artery disease (PAD), using a Mendelian randomization approach.

Methods and Results

We performed a 2‐sample inverse‐variance weighted Mendelian randomization analysis, multiple sensitivity analyses to assess pleiotropy and multivariate Mendelian randomization analyses to assess mediating/confounding factors. European‐ancestry genomic summary data (P<5×10⁻⁸) for type 2 diabetes, lipid‐fractions, smoking, alcohol and coffee consumption, physical activity, sleep, and education level were selected. Genetic associations with PAD were extracted from the Million‐Veteran‐Program genome‐wide association studies (cases=31 307, controls=211 753, 72% European‐ancestry) and the GoLEAD‐SUMMIT genome‐wide association studies (11 independent genome‐wide association studies, European‐ancestry, cases=12 086, controls=449 548). Associations were categorized as robust (Bonferroni‐significant (P<0.00294), consistent over PAD‐cohorts/sensitivity analyses), suggestive (P value: 0.00294–0.05, associations in 1 PAD‐cohort/inconsistent sensitivity analyses) or not present. Robust evidence for genetic liability to type 2 diabetes, smoking, insomnia, and inverse associations for higher education level with PAD were found. Suggestive evidence for the genetic liability to higher low‐density lipoprotein cholesterol, triglyceride‐levels, alcohol consumption, and inverse associations for high‐density lipoprotein cholesterol, and increased sleep duration were found. No associations were found for physical activity and coffee consumption. However, effects fully attenuated for low‐density lipoprotein cholesterol and triglycerides after correcting for apoB, and for insomnia after correcting for body mass index and lipid‐fractions. Nonsignificant attenuation by potential mediators was observed for education level and type 2 diabetes.

Conclusions

Detrimental effects of smoking and type 2 diabetes, but not of low‐density lipoprotein cholesterol and triglycerides, on PAD were confirmed. Lower education level and insomnia were identified as novel risk factors for PAD; however, complete mediation for insomnia and incomplete mediation for education level by downstream risk factors was observed.

Genetics of Type 2 Diabetes: Past, Present, and Future

Diabetes has reached epidemic proportions worldwide. Currently, approximately 537 million adults (20–79 years) have diabetes, and the total number of people with diabetes is continuously increasing. Diabetes includes several subtypes. About 80% of all cases of diabetes are type 2 diabetes (T2D). T2D is a polygenic disease with an inheritance ranging from 30 to 70%. Genetic and environment/lifestyle factors, especially obesity and sedentary lifestyle, increase the risk of T2D. In this review, we discuss how studies on the genetics of diabetes started, how they expanded when genome-wide association studies and exome and whole-genome sequencing became available, and the current challenges in genetic studies of diabetes. T2D is heterogeneous with respect to clinical presentation, disease course, and response to treatment, and has several subgroups which differ in pathophysiology and risk of micro- and macrovascular complications. Currently, genetic studies of T2D focus on these subgroups to find the best diagnoses and treatments for these patients according to the principles of precision medicine.

Mendelian randomization analyses of 23 known and suspected risk factors and biomarkers for breast cancer overall and by molecular subtypes

Many risk factors have been identified for breast cancer. The potential causality for some of them remains uncertain, and few studies have comprehensively investigated these associations by molecular subtypes. We performed a two-sample Mendelian randomization (MR) study to evaluate potential causal associations of 23 known and suspected risk factors and biomarkers with breast cancer risk overall and by molecular subtypes using data from the Breast Cancer Association Consortium. The inverse-variance weighted method was used to estimate odds ratios (OR) and 95% confidence interval (CI) for association of each trait with breast cancer risk. Significant associations with breast cancer risk were found for 15 traits, including age at menarche, age at menopause, body mass index, waist-to-hip ratio, height, physical activity, cigarette smoking, sleep duration, and morning-preference chronotype, and six blood biomarkers (estrogens, insulin-like growth factor-1, sex hormone-binding globulin [SHBG], telomere length, HDL-cholesterol and fasting insulin). Noticeably, an increased circulating SHBG was associated with a reduced risk of estrogen receptor (ER)-positive cancer (OR = 0.83, 95% CI: 0.73-0.94), but an elevated risk of ER-negative (OR = 1.12, 95% CI: 0.93-1.36) and triple negative cancer (OR = 1.19, 95% CI: 0.92-1.54) (P_{heterogeneity}  = 0.01). Fasting insulin was most strongly associated with an increased risk of HER2-negative cancer (OR = 1.94, 95% CI: 1.18-3.20), but a reduced risk of HER2-enriched cancer (OR = 0.46, 95% CI: 0.26-0.81) (P_{heterogeneity}  = 0.006). Results from sensitivity analyses using MR-Egger and MR-PRESSO were generally consistent. Our study provides strong evidence supporting potential causal associations of several risk factors for breast cancer and suggests potential heterogeneous associations of SHBG and fasting insulin levels with subtypes of breast cancer.

Causal Graph Among Serum Lipids and Glycemic Traits: A Mendelian Randomization Study

We systematically investigated the bidirectional causality among HDL cholesterol (HDL-C), LDL cholesterol (LDL-C), triglycerides (TGs), fasting insulin (FI), and glycated hemoglobin A1c (HbA1c) based on genome-wide association summary statistics of Europeans (n = 1,320,016 for lipids, 151,013 for FI, and 344,182 for HbA1c). We applied multivariable Mendelian randomization (MR) to account for the correlation among different traits and constructed a causal graph with 13 significant causal effects after adjusting for multiple testing (P < 0.0025). Remarkably, we found that the effects of lipids on glycemic traits were through FI from TGs (β = 0.06 [95% CI 0.03, 0.08] in units of 1 SD for each trait) and HDL-C (β = -0.02 [-0.03, -0.01]). On the other hand, FI had a strong negative effect on HDL-C (β = -0.15 [-0.21, -0.09]) and positive effects on TGs (β = 0.22 [0.14, 0.31]) and HbA1c (β = 0.15 [0.12, 0.19]), while HbA1c could raise LDL-C (β = 0.06 [0.03, 0.08]) and TGs (β = 0.08 [0.06, 0.10]). These estimates derived from inverse-variance weighting were robust when using different MR methods. Our results suggest that elevated FI was a strong causal factor of high TGs and low HDL-C, which in turn would further increase FI. Therefore, early control of insulin resistance is critical to reduce the risk of type 2 diabetes, dyslipidemia, and cardiovascular complications.

Contribution of metabolic risk factors and lifestyle behaviors to cardiovascular disease: A mendelian randomization study

BACKGROUND AND AIMS

Etiologic associations between some modifiable factors (metabolic risk factors and lifestyle behaviors) and cardiovascular disease (CVD) remain unclear. To identify targets for CVD prevention, we evaluated the causal associations of these factors with coronary artery disease (CAD) and ischemic stroke using a two-sample Mendelian randomization (MR) method.

METHODS AND RESULTS

Previously published genome-wide association studies (GWASs) for blood pressure (BP), glucose, lipids, overweight, smoking, alcohol intake, sedentariness, and education were used to identify instruments for 15 modifiable factors. We extracted effects of the genetic variants used as instruments for the exposures on coronary artery disease (CAD) and ischemic stroke from large GWASs (N = 60 801 cases/123 504 controls for CAD and N = 40 585 cases/406 111 controls for ischemic stroke). Genetically predicted hypertension (CAD: OR, 5.19 [95% CI, 4.21-6.41]; ischemic stroke: OR, 4.92 [4.12-5.86]), systolic BP (CAD: OR, 1.03 [1.03-1.04]; ischemic stroke: OR, 1.03 [1.03-1.03]), diastolic BP (CAD: OR, 1.05 [1.05-1.06]; ischemic stroke: OR, 1.05 [1.04-1.05]), type 2 diabetes (CAD: OR, 1.11 [1.08-1.15]; ischemic stroke: OR, 1.07 [1.04-1.10]), smoking initiation (CAD: OR, 1.26 [1.18-1.35]; ischemic stroke: OR, 1.24 [1.16-1.33]), educational attainment (CAD: OR, 0.62 [0.58-0.66]; ischemic stroke: OR, 0.68 [0.63-0.72]), low-density lipoprotein cholesterol (CAD: OR, 1.55 [1.41-1.71]), high-density lipoprotein cholesterol (CAD: OR, 0.82 [0.74-0.91]), triglycerides (CAD: OR, 1.29 [1.14-1.45]), body mass index (CAD: OR, 1.25 [1.19-1.32]), and alcohol dependence (OR, 1.04 [1.03-1.06]) were causally related to CVD.

CONCLUSION

This systematic MR study identified 11 modifiable factors as causal risk factors for CVD, indicating that these factors are important targets for preventing CVD.

Whole genome sequence association analysis of fasting glucose and fasting insulin levels in diverse cohorts from the NHLBI TOPMed program

The genetic determinants of fasting glucose (FG) and fasting insulin (FI) have been studied mostly through genome arrays, resulting in over 100 associated variants. We extended this work with high-coverage whole genome sequencing analyses from fifteen cohorts in NHLBI's Trans-Omics for Precision Medicine (TOPMed) program. Over 23,000 non-diabetic individuals from five race-ethnicities/populations (African, Asian, European, Hispanic and Samoan) were included. Eight variants were significantly associated with FG or FI across previously identified regions MTNR1B, G6PC2, GCK, GCKR and FOXA2. We additionally characterize suggestive associations with FG or FI near previously identified SLC30A8, TCF7L2, and ADCY5 regions as well as APOB, PTPRT, and ROBO1. Functional annotation resources including the Diabetes Epigenome Atlas were compiled for each signal (chromatin states, annotation principal components, and others) to elucidate variant-to-function hypotheses. We provide a catalog of nucleotide-resolution genomic variation spanning intergenic and intronic regions creating a foundation for future sequencing-based investigations of glycemic traits.

Prediction of type 2 diabetes mellitus onset using logistic regression-based scorecards

Background

Type 2 diabetes (T2D) accounts for ~90% of all cases of diabetes, resulting in an estimated 6.7 million deaths in 2021, according to the International Diabetes Federation. Early detection of patients with high risk of developing T2D can reduce the incidence of the disease through a change in lifestyle, diet, or medication. Since populations of lower socio-demographic status are more susceptible to T2D and might have limited resources or access to sophisticated computational resources, there is a need for accurate yet accessible prediction models.

Methods

In this study, we analyzed data from 44,709 nondiabetic UK Biobank participants aged 40-69, predicting the risk of T2D onset within a selected time frame (mean of 7.3 years with an SD of 2.3 years). We started with 798 features that we identified as potential predictors for T2D onset. We first analyzed the data using gradient boosting decision trees, survival analysis, and logistic regression methods. We devised one nonlaboratory model accessible to the general population and one more precise yet simple model that utilizes laboratory tests. We simplified both models to an accessible scorecard form, tested the models on normoglycemic and prediabetes subcohorts, and compared the results to the results of the general cohort. We established the nonlaboratory model using the following covariates: sex, age, weight, height, waist size, hip circumference, waist-to-hip ratio, and body mass index. For the laboratory model, we used age and sex together with four common blood tests: high-density lipoprotein (HDL), gamma-glutamyl transferase, glycated hemoglobin, and triglycerides. As an external validation dataset, we used the electronic medical record database of Clalit Health Services.

Results

The nonlaboratory scorecard model achieved an area under the receiver operating curve (auROC) of 0.81 (95% confidence interval [CI] 0.77-0.84) and an odds ratio (OR) between the upper and fifth prevalence deciles of 17.2 (95% CI 5-66). Using this model, we classified three risk groups, a group with 1% (0.8-1%), 5% (3-6%), and the third group with a 9% (7-12%) risk of developing T2D. We further analyzed the contribution of the laboratory-based model and devised a blood test model based on age, sex, and the four common blood tests noted above. In this scorecard model, we included age, sex, glycated hemoglobin (HbA1c%), gamma glutamyl-transferase, triglycerides, and HDL cholesterol. Using this model, we achieved an auROC of 0.87 (95% CI 0.85-0.90) and a deciles' OR of ×48 (95% CI 12-109). Using this model, we classified the cohort into four risk groups with the following risks: 0.5% (0.4-7%); 3% (2-4%); 10% (8-12%); and a high-risk group of 23% (10-37%) of developing T2D. When applying the blood tests model using the external validation cohort (Clalit), we achieved an auROC of 0.75 (95% CI 0.74-0.75). We analyzed several additional comprehensive models, which included genotyping data and other environmental factors. We found that these models did not provide cost-efficient benefits over the four blood test model. The commonly used German Diabetes Risk Score (GDRS) and Finnish Diabetes Risk Score (FINDRISC) models, trained using our data, achieved an auROC of 0.73 (0.69-0.76) and 0.66 (0.62-0.70), respectively, inferior to the results achieved by the four blood test model and by the anthropometry models.

Conclusions

The four blood test and anthropometric models outperformed the commonly used nonlaboratory models, the FINDRISC and the GDRS. We suggest that our models be used as tools for decision-makers to assess populations at elevated T2D risk and thus improve medical strategies. These models might also provide a personal catalyst for changing lifestyle, diet, or medication modifications to lower the risk of T2D onset.

Funding

The funders had no role in study design, data collection, interpretation, or the decision to submit the work for publication.

Effects of glycemic traits on left ventricular structure and function: a mendelian randomization study

BACKGROUND

Adverse ventricular structure and function is a key pathogenic mechanism of heart failure. Observational studies have shown that both insulin resistance (IR) and glycemic level are associated with adverse ventricular structure and function. However, whether IR and glycemic level are causally associated with cardiac structure and function remains unclear.

METHODS

Genetic variants for IR, fasting insulin, HbA1c, and fasting glucose were selected based on published genome-wide association studies, which included 188,577, 108,557, 123,665, and 133,010 individuals of European ancestry, respectively. Outcome datasets for left ventricular (LV) parameters were obtained from UK Biobank Cardiovascular Magnetic Resonance sub-study (n = 16,923). Mendelian randomization (MR) analyses with the inverse-variance weighted (IVW) method were used for the primary analyses, while weighted median, MR-Egger, and MR-PRESSO were used for sensitivity analyses. Multivariable MR analyses were also conducted to examine the independent effects of glycemic traits on LV parameters.

RESULTS

In the primary IVW MR analyses, per 1-standard deviation (SD) higher IR was significantly associated with lower LV end-diastolic volume (β = - 0.31 ml, 95% confidence interval [CI] - 0.48 to - 0.14 ml; P = 4.20 × 10^-4), lower LV end-systolic volume (β = - 0.34 ml, 95% CI - 0.51 to - 0.16 ml; P = 1.43 × 10^-4), and higher LV mass to end-diastolic volume ratio (β = 0.50 g/ml, 95% CI 0.32 to 0.67 g/ml; P = 6.24 × 10^-8) after Bonferroni adjustment. However, no associations of HbA1c and fasting glucose were observed with any LV parameters. Results from sensitivity analyses were consistent with the main findings, but with a slightly attenuated estimate. Multivariable MR analyses provided further evidence for an independent effect of IR on the adverse changes in LV parameters after controlling for HbA1c.

CONCLUSIONS

Our study suggests that genetic liability to IR rather than those of glycemic levels are associated with adverse changes in LV structure and function, which may strengthen our understanding of IR as a risk factor for heart failure by providing evidence of direct impact on cardiac morphology.

Stbd1-deficient mice display insulin resistance associated with enhanced hepatic ER-mitochondria contact

Starch binding domain-containing protein 1 (STBD1) is an endoplasmic reticulum (ER)-resident, glycogen-binding protein. In addition to glycogen, STBD1 has been shown to interact with several proteins implicated in glycogen synthesis and degradation, yet its function in glycogen metabolism remains largely unknown. In addition to the bulk of the ER, STBD1 has been reported to localize at regions of physical contact between mitochondria and the ER, known as Mitochondria-ER Contact sites (MERCs). Given the emerging correlation between distortions in the integrity of hepatic MERCs and insulin resistance, our study aimed to delineate the role of STBD1 in vivo by addressing potential abnormalities in glucose metabolism and ER-mitochondria communication associated with insulin resistance in mice with targeted inactivation of Stbd1 (Stbd1KO). We show that Stbd1KO mice at the age of 24 weeks displayed reduced hepatic glycogen content and aberrant control of glucose homeostasis, compatible with insulin resistance. In line with the above, Stbd1-deficient mice presented with increased fasting blood glucose and insulin levels, attenuated activation of insulin signaling in the liver and skeletal muscle and elevated liver sphingomyelin content, in the absence of hepatic steatosis. Furthermore, Stbd1KO mice were found to exhibit enhanced ER-mitochondria association and increased mitochondrial fragmentation in the liver. Nevertheless, the enzymatic activity of hepatic respiratory chain complexes and ER stress levels in the liver were not altered. Our findings identify a novel important role for STBD1 in the control of glucose metabolism, associated with the integrity of hepatic MERCs.

Separating the direct effects of traits on atherosclerotic cardiovascular disease from those mediated by type 2 diabetes

AIMS/HYPOTHESIS

Type 2 diabetes and atherosclerotic CVD share many risk factors. This study aimed to systematically assess a broad range of continuous traits to separate their direct effects on coronary and peripheral artery disease from those mediated by type 2 diabetes.

METHODS

Our main analysis was a two-step Mendelian randomisation for mediation to quantify the extent to which the associations observed between continuous traits and liability to atherosclerotic CVD were mediated by liability to type 2 diabetes. To support this analysis, we performed several univariate Mendelian randomisation analyses to examine the associations between our continuous traits, liability to type 2 diabetes and liability to atherosclerotic CVD.

RESULTS

Eight traits were eligible for the two-step Mendelian randomisation with liability to coronary artery disease as the outcome and we found similar direct and total effects in most cases. Exceptions included fasting insulin and hip circumference where the proportion mediated by liability to type 2 diabetes was estimated as 56% and 52%, respectively. Six traits were eligible for the analysis with liability to peripheral artery disease as the outcome. Again, we found limited evidence to support mediation by liability to type 2 diabetes for all traits apart from fasting insulin (proportion mediated: 70%).

CONCLUSIONS/INTERPRETATION

Most traits were found to affect liability to atherosclerotic CVD independently of their relationship with liability to type 2 diabetes. These traits are therefore important for understanding atherosclerotic CVD risk regardless of an individual's liability to type 2 diabetes.

Causal Association of Type 2 Diabetes Mellitus and Glycemic Traits With Cardiovascular Diseases and Lipid Traits: A Mendelian Randomization Study

Objective

We aimed to evaluate the causal effect of type 2 diabetes mellitus (T2DM) and glycemic traits on the risk of a wide range of cardiovascular diseases (CVDs) and lipid traits using Mendelian randomization (MR).

Methods

Genetic variants associated with T2DM, fasting glucose, fasting insulin, and hemoglobin A1c were selected as instrumental variables to perform both univariable and multivariable MR analyses.

Results

In univariable MR, genetically predicted T2DM was associated with higher odds of peripheral artery disease (pooled odds ratio (OR) =1.207, 95% CI: 1.162-1.254), myocardial infarction (OR =1.132, 95% CI: 1.104-1.160), ischemic heart disease (OR =1.129, 95% CI: 1.105-1.154), heart failure (OR =1.050, 95% CI: 1.029-1.072), stroke (OR =1.087, 95% CI: 1.068-1.107), ischemic stroke (OR =1.080, 95% CI: 1.059-1.102), essential hypertension (OR =1.013, 95% CI: 1.010-1.015), coronary atherosclerosis (OR =1.005, 95% CI: 1.004-1.007), and major coronary heart disease event (OR =1.003, 95% CI: 1.002-1.004). Additionally, T2DM was causally related to lower levels of high-density lipoprotein cholesterol (OR =0.965, 95% CI: 0.958-0.973) and apolipoprotein A (OR =0.982, 95% CI: 0.977-0.987) but a higher level of triglycerides (OR =1.060, 95% CI: 1.036-1.084). Moreover, causal effect of glycemic traits on CVDs and lipid traits were also observed. Finally, most results of univariable MR were supported by multivariable MR.

Conclusion

We provided evidence for the causal effects of T2DM and glycemic traits on the risk of CVDs and dyslipidemia. Further investigations to elucidate the underlying mechanisms are warranted.

Identifying molecular mediators of the relationship between body mass index and endometrial cancer risk: a Mendelian randomization analysis

BACKGROUND

Endometrial cancer is the most common gynaecological cancer in high-income countries. Elevated body mass index (BMI) is an established modifiable risk factor for this condition and is estimated to confer a larger effect on endometrial cancer risk than any other cancer site. However, the molecular mechanisms underpinning this association remain unclear. We used Mendelian randomization (MR) to evaluate the causal role of 14 molecular risk factors (hormonal, metabolic and inflammatory markers) in endometrial cancer risk. We then evaluated and quantified the potential mediating role of these molecular traits in the relationship between BMI and endometrial cancer using multivariable MR.

METHODS

Genetic instruments to proxy 14 molecular risk factors and BMI were constructed by identifying single-nucleotide polymorphisms (SNPs) reliably associated (P < 5.0 × 10-8) with each respective risk factor in previous genome-wide association studies (GWAS). Summary statistics for the association of these SNPs with overall and subtype-specific endometrial cancer risk (12,906 cases and 108,979 controls) were obtained from a GWAS meta-analysis of the Endometrial Cancer Association Consortium (ECAC), Epidemiology of Endometrial Cancer Consortium (E2C2) and UK Biobank. SNPs were combined into multi-allelic models and odds ratios (ORs) and 95% confidence intervals (95% CIs) were generated using inverse-variance weighted random-effects models. The mediating roles of the molecular risk factors in the relationship between BMI and endometrial cancer were then estimated using multivariable MR.

RESULTS

In MR analyses, there was strong evidence that BMI (OR per standard deviation (SD) increase 1.88, 95% CI 1.69 to 2.09, P = 3.87 × 10-31), total testosterone (OR per inverse-normal transformed nmol/L increase 1.64, 95% CI 1.43 to 1.88, P = 1.71 × 10-12), bioavailable testosterone (OR per natural log transformed nmol/L increase: 1.46, 95% CI 1.29 to 1.65, P = 3.48 × 10-9), fasting insulin (OR per natural log transformed pmol/L increase: 3.93, 95% CI 2.29 to 6.74, P = 7.18 × 10-7) and sex hormone-binding globulin (SHBG, OR per inverse-normal transformed nmol/L increase 0.71, 95% CI 0.59 to 0.85, P = 2.07 × 10-4) had a causal effect on endometrial cancer risk. Additionally, there was suggestive evidence that total serum cholesterol (OR per mg/dL increase 0.90, 95% CI 0.81 to 1.00, P = 4.01 × 10-2) had an effect on endometrial cancer risk. In mediation analysis, we found evidence for a mediating role of fasting insulin (19% total effect mediated, 95% CI 5 to 34%, P = 9.17 × 10-3), bioavailable testosterone (15% mediated, 95% CI 10 to 20%, P = 1.43 × 10-8) and SHBG (7% mediated, 95% CI 1 to 12%, P = 1.81 × 10-2) in the relationship between BMI and endometrial cancer risk.

CONCLUSIONS

Our comprehensive MR analysis provides insight into potential causal mechanisms linking BMI with endometrial cancer risk and suggests targeting of insulinemic and hormonal traits as a potential strategy for the prevention of endometrial cancer.

Deciphering how early life adiposity influences breast cancer risk using Mendelian randomization

Studies suggest that adiposity in childhood may reduce the risk of breast cancer in later life. The biological mechanism underlying this effect is unclear but is likely to be independent of body size in adulthood. Using a Mendelian randomization framework, we investigate 18 hypothesised mediators of the protective effect of childhood adiposity on later-life breast cancer, including hormonal, reproductive, physical, and glycaemic traits. Our results indicate that, while most of the hypothesised mediators are affected by childhood adiposity, only IGF-1 (OR: 1.08 [1.03: 1.15]), testosterone (total/free/bioavailable ~ OR: 1.12 [1.05: 1.20]), age at menopause (OR: 1.05 [1.03: 1.07]), and age at menarche (OR: 0.92 [0.86: 0.99], direct effect) influence breast cancer risk. However, multivariable Mendelian randomization analysis shows that the protective effect of childhood body size remains unaffected when accounting for these traits (ORs: 0.59-0.67). This suggests that none of the investigated potential mediators strongly contribute to the protective effect of childhood adiposity on breast cancer risk individually. It is plausible, however, that several related traits could collectively mediate the effect when analysed together, and this work provides a compelling foundation for investigating other mediating pathways in future studies.

Multi-ethnic GWAS and fine-mapping of glycaemic traits identify novel loci in the PAGE Study

AIMS/HYPOTHESIS

Type 2 diabetes is a growing global public health challenge. Investigating quantitative traits, including fasting glucose, fasting insulin and HbA1c, that serve as early markers of type 2 diabetes progression may lead to a deeper understanding of the genetic aetiology of type 2 diabetes development. Previous genome-wide association studies (GWAS) have identified over 500 loci associated with type 2 diabetes, glycaemic traits and insulin-related traits. However, most of these findings were based only on populations of European ancestry. To address this research gap, we examined the genetic basis of fasting glucose, fasting insulin and HbA1c in participants of the diverse Population Architecture using Genomics and Epidemiology (PAGE) Study.

METHODS

We conducted a GWAS of fasting glucose (n = 52,267), fasting insulin (n = 48,395) and HbA1c (n = 23,357) in participants without diabetes from the diverse PAGE Study (23% self-reported African American, 46% Hispanic/Latino, 40% European, 4% Asian, 3% Native Hawaiian, 0.8% Native American), performing transethnic and population-specific GWAS meta-analyses, followed by fine-mapping to identify and characterise novel loci and independent secondary signals in known loci.

RESULTS

Four novel associations were identified (p < 5 × 10-9), including three loci associated with fasting insulin, and a novel, low-frequency African American-specific locus associated with fasting glucose. Additionally, seven secondary signals were identified, including novel independent secondary signals for fasting glucose at the known GCK locus and for fasting insulin at the known PPP1R3B locus in transethnic meta-analysis.

CONCLUSIONS/INTERPRETATION

Our findings provide new insights into the genetic architecture of glycaemic traits and highlight the continued importance of conducting genetic studies in diverse populations.

DATA AVAILABILITY

Full summary statistics from each of the population-specific and transethnic results are available at NHGRI-EBI GWAS catalog ( https://www.ebi.ac.uk/gwas/downloads/summary-statistics ).

Association between type 2 diabetes and amyotrophic lateral sclerosis

Type 2 diabetes (T2D) and amyotrophic lateral sclerosis (ALS) are associated consistently. However, it is currently unknown whether this association is causal. We aimed to estimate the unconfounded, causal association between T2D on ALS using a two-sample Mendelian randomization approach both in European and East Asian ancestry. Genetic variants strongly associated with T2D and each T2D markers were used to investigate the effect of T2D on ALS risk in European (involving 20,806 ALS cases and 59,804 controls) and East Asian (involving 1234 ALS cases and 2850 controls) ancestry. We found that the OR of ALS per 1 SD increase in T2D was estimated to be 0.96 [95% confidence interval (CI) 0.92–0.996; p = 0.03] in European populations. Similarly, all 8 SNPs were associated with T2D in East Asian ancestry, the OR of ALS per 1 SD increase in T2D was estimated to be 0.83 [95% CI 0.70–0.992; p = 0.04] in East Asian populations. Examining the intercept estimates from MR-Egger regression also leads to the same conclusion, in that horizontal pleiotropy unlikely influences the results in either population. We found that genetically predicted T2D was associated with significantly lower odds of amyotrophic lateral sclerosis both in European and East Asian populations. It is now critical to identify a clear molecular explanation for this association between T2D and ALS and to focus on its potential therapeutic implications.

Genomic legacy of migration in endangered caribou

Wide-ranging animals, including migratory species, are significantly threatened by the effects of habitat fragmentation and habitat loss. In the case of terrestrial mammals, this results in nearly a quarter of species being at risk of extinction. Caribou are one such example of a wide-ranging, migratory, terrestrial, and endangered mammal. In populations of caribou, the proportion of individuals considered as "migrants" can vary dramatically. There is therefore a possibility that, under the condition that migratory behavior is genetically determined, those individuals or populations that are migratory will be further impacted by humans, and this impact could result in the permanent loss of the migratory trait in some populations. However, genetic determination of migration has not previously been studied in an endangered terrestrial mammal. We examined migratory behavior of 139 GPS-collared endangered caribou in western North America and carried out genomic scans for the same individuals. Here we determine a genetic subdivision of caribou into a Northern and a Southern genetic cluster. We also detect >50 SNPs associated with migratory behavior, which are in genes with hypothesized roles in determining migration in other organisms. Furthermore, we determine that propensity to migrate depends upon the proportion of ancestry in individual caribou, and thus on the evolutionary history of its migratory and sedentary subspecies. If, as we report, migratory behavior is influenced by genes, caribou could be further impacted by the loss of the migratory trait in some isolated populations already at low numbers. Our results indicating an ancestral genetic component also suggest that the migratory trait and their associated genetic mutations could not be easily re-established when lost in a population.

Evidence for Shared Genetic Aetiology Between Schizophrenia, Cardiometabolic, and Inflammation-Related Traits: Genetic Correlation and Colocalization Analyses

BACKGROUND

Schizophrenia commonly co-occurs with cardiometabolic and inflammation-related traits. It is unclear to what extent the comorbidity could be explained by shared genetic aetiology.

METHODS

We used GWAS data to estimate shared genetic aetiology between schizophrenia, cardiometabolic, and inflammation-related traits: fasting insulin (FI), fasting glucose, glycated haemoglobin, glucose tolerance, type 2 diabetes (T2D), lipids, body mass index (BMI), coronary artery disease (CAD), and C-reactive protein (CRP). We examined genome-wide correlation using linkage disequilibrium score regression (LDSC); stratified by minor-allele frequency using genetic covariance analyzer (GNOVA); then refined to locus-level using heritability estimation from summary statistics (ρ-HESS). Regions with local correlation were used in hypothesis prioritization multi-trait colocalization to examine for colocalisation, implying common genetic aetiology.

RESULTS

We found evidence for weak genome-wide negative correlation of schizophrenia with T2D (r_g = -0.07; 95% C.I., -0.03,0.12; P = .002) and BMI (r_g = -0.09; 95% C.I., -0.06, -0.12; P = 1.83 × 10^-5). We found a trend of evidence for positive genetic correlation between schizophrenia and cardiometabolic traits confined to lower-frequency variants. This was underpinned by 85 regions of locus-level correlation with evidence of opposing mechanisms. Ten loci showed strong evidence of colocalization. Four of those (rs6265 (BDNF); rs8192675 (SLC2A2); rs3800229 (FOXO3); rs17514846 (FURIN)) are implicated in brain-derived neurotrophic factor (BDNF)-related pathways.

CONCLUSIONS

LDSC may lead to downwardly-biased genetic correlation estimates between schizophrenia, cardiometabolic, and inflammation-related traits. Common genetic aetiology for these traits could be confined to lower-frequency common variants and involve opposing mechanisms. Genes related to BDNF and glucose transport amongst others may partly explain the comorbidity between schizophrenia and cardiometabolic disorders.

Genetic variants for prediction of gestational diabetes mellitus and modulation of susceptibility by a nutritional intervention based on a Mediterranean diet

HYPOTHESIS

Gestational diabetes mellitus (GDM) entails a complex underlying pathogenesis, with a specific genetic background and the effect of environmental factors. This study examines the link between a set of single nucleotide polymorphisms (SNPs) associated with diabetes and the development of GDM in pregnant women with different ethnicities, and evaluates its potential modulation with a clinical intervention based on a Mediterranean diet.

METHODS

2418 women from our hospital-based cohort of pregnant women screened for GDM from January 2015 to November 2017 (the San Carlos Cohort, randomized controlled trial for the prevention of GDM ISRCTN84389045 and real-world study ISRCTN13389832) were assessed for evaluation. Diagnosis of GDM was made according to the International Association of Diabetes and Pregnancy Study Groups (IADPSG) criteria. Genotyping was performed by IPLEX MassARRAY PCR using the Agena platform (Agena Bioscience, SanDiego, CA). 110 SNPs were selected for analysis based on selected literature references. Statistical analyses regarding patients' characteristics were performed in SPSS (Chicago, IL, USA) version 24.0. Genetic association tests were performed using PLINK v.1.9 and 2.0 software. Bioinformatics analysis, with mapping of SNPs was performed using STRING, version 11.5.

RESULTS

Quality controls retrieved a total 98 SNPs and 1573 samples, 272 (17.3%) with GDM and 1301 (82.7%) without GDM. 1104 (70.2%) were Caucasian (CAU) and 469 (29.8%) Hispanic (HIS). 415 (26.4%) were from the control group (CG), 418 (26.6%) from the nutritional intervention group (IG) and 740 (47.0%) from the real-world group (RW). 40 SNPs (40.8%) presented some kind of significant association with GDM in at least one of the genetic tests considered. The nutritional intervention presented a significant association with GDM, regardless of the variant considered. In CAU, variants rs4402960, rs7651090, IGF2BP2; rs1387153, rs10830963, MTNR1B; rs17676067, GLP2R; rs1371614, DPYSL5; rs5215, KCNJ1; and rs2293941, PDX1 were significantly associated with an increased risk of GDM, whilst rs780094, GCKR; rs7607980, COBLL1; rs3746750, SLC17A9; rs6048205, FOXA2; rs7041847, rs7034200, rs10814916, GLIS3; rs3783347, WARS; and rs1805087, MTR, were significantly associated with a decreased risk of GDM, In HIS, variants significantly associated with increased risk of GDM were rs9368222, CDKAL1; rs2302593, GIPR; rs10885122, ADRA2A; rs1387153, MTNR1B; rs737288, BACE2; rs1371614, DPYSL5; and rs2293941, PDX1, whilst rs340874, PROX1; rs2943634, IRS1; rs7041847, GLIS3; rs780094, GCKR; rs563694, G6PC2; and rs11605924, CRY2 were significantly associated with decreased risk for GDM.

CONCLUSIONS

We identify a core set of SNPs in their association with diabetes and GDM in a large cohort of patients from two main ethnicities from a single center. Identification of these genetic variants, even in the setting of a nutritional intervention, deems useful to design preventive and therapeutic strategies.

The role of obesity, type 2 diabetes, and metabolic factors in gout: A Mendelian randomization study

BACKGROUND

Several epidemiological studies have reported a possible correlation between risk of gout and metabolic disorders including type 2 diabetes, insulin resistance, obesity, dyslipidemia, and hypertension. However, it is unclear if this association is causal.

METHODS

We used Mendelian randomization (MR) to evaluate the causal relation between metabolic conditions and gout or serum urate concentration by inverse-variance-weighted (conventional) and weighted median methods. Furthermore, MR-Egger regression and MR-pleiotropy residual sum and outlier (PRESSO) method were used to explore pleiotropy. Genetic instruments for metabolic disorders and outcome (gout and serum urate) were obtained from several genome-wide association studies on individuals of mainly European ancestry.

RESULTS

Conventional MR analysis showed a robust causal association of increasing obesity measured by body mass index (BMI), high-density lipoprotein cholesterol (HDL), and systolic blood pressure (SBP) with risk of gout. A causal relationship between fasting insulin, BMI, HDL, triglycerides (TG), SBP, alanine aminotransferase (ALT), and serum urate was also observed. These results were consistent in weighted median method and MR-PRESSO after removing outliers identified. Our analysis also indicated that HDL and serum urate as well as gout have a bidirectional causal effect on each other.

CONCLUSIONS

Our study suggested causal effects between glycemic traits, obesity, dyslipidemia, blood pressure, liver function, and serum urate as well as gout, which implies that metabolic factors contribute to the development of gout via serum urate, as well as potential benefit of sound management of increased serum urate in patients with obesity, dyslipidemia, hypertension, and liver dysfunction.

Mendelian randomization supports the causal role of fasting glucose on periodontitis

PURPOSE

The effect of hyperglycemia on periodontitis is mainly based on observational studies, and inconsistent results were found whether periodontal treatment favors glycemic control. The two-way relationship between periodontitis and hyperglycemia needs to be further elucidated. This study aims to evaluate the causal association of periodontitis with glycemic traits using bi-directional Mendelian randomization (MR) approach.

METHODS

Summary statistics were sourced from large-scale genome-wide association study conducted for fasting glucose (N = 133,010), HbA1c (N = 123,665), type 2 diabetes (T2D, N = 659,316), and periodontitis (N = 506,594) among European ancestry. The causal relationship was estimated using the inverse-variance weighted (IVW) model and further validated through extensive complementary and sensitivity analyses.

RESULTS

Overall, IVW showed that a genetically higher level of fasting glucose was significantly associated with periodontitis (OR = 1.119; 95% CI = 1.045-1.197; P_FDR= 0.007) after removing the outlying instruments. Such association was robust and consistent through other MR models. Limited evidence was found suggesting the association of HbA1C with periodontitis after excluding the outliers (IVW OR = 1.123; 95% CI = 1.026-1.229; P_FDR= 0.048). These linkages remained statistically significant in multivariate MR analyses, after adjusting for body mass index. The reverse direction MR analyses did not exhibit the causal association of genetic liability to periodontitis with any of the glycemic trait tested.

CONCLUSIONS

Our MR study reaffirms previous findings and extends evidence to substantiate the causal effect of hyperglycemia on periodontitis. Future studies with robust genetic instruments are needed to confirm the causal association of periodontitis with glycemic traits.

Hexokinase domain-containing protein-1 in metabolic diseases and beyond

Glucose phosphorylation by hexokinases (HKs) traps glucose in cells and facilitates its usage in metabolic processes dependent on cellular needs. HK domain-containing protein-1 (HKDC1) is a recently discovered protein with wide expression containing HK activity, first noted through a genome-wide association study (GWAS) to be linked with gestational glucose homeostasis during pregnancy. Since then, HKDC1 has been observed to be expressed in many human tissues. Moreover, studies have shown that HKDC1 plays a role in glucose homeostasis by which it may affect the progression of many pathophysiological conditions such as gestational diabetes mellitus (GDM), nonalcoholic steatohepatitis (NASH), and cancer. Here, we review the key studies contributing to our current understanding of the roles of HKDC1 in human pathophysiological conditions and potential therapeutic interventions.

The Association between Fasting Glucose and Sugar Sweetened Beverages Intake Is Greater in Latin Americans with a High Polygenic Risk Score for Type 2 Diabetes Mellitus

Chile is one of the largest consumers of sugar-sweetened beverages (SSB) world-wide. However, it is unknown whether the effects from this highly industrialized food will mimic those reported in industrialized countries or whether they will be modified by local lifestyle or population genetics. Our goal is to evaluate the interaction effect between SSB intake and T2D susceptibility on fasting glucose. We calculated a weighted genetic risk score (GRSw) based on 16 T2D risk SNPs in 2828 non-diabetic participants of the MAUCO cohort. SSB intake was categorized in four levels using a food frequency questionnaire. Log-fasting glucose was regressed on SSB and GRSw tertiles while accounting for socio-demography, lifestyle, obesity, and Amerindian ancestry. Fasting glucose increased systematically per unit of GRSw (β = 0.02 ± 0.006, p = 0.00002) and by SSB intake (β[cat4] = 0.04 ± 0.01, p = 0.0001), showing a significant interaction, where the strongest effect was observed in the highest GRSw-tertile and in the highest SSB consumption category (β = 0.05 ± 0.02, p = 0.02). SNP-wise, SSB interacted with additive effects of rs7903146 (TCF7L2) (β = 0.05 ± 0.01, p = 0.002) and with the G/G genotype of rs10830963 (MTNRB1B) (β = 0.19 ± 0.05, p = 0.001). Conclusions: The association between SSB intake and fasting glucose in the Chilean population without diabetes is modified by T2D genetic susceptibility.

The importance of increasing population diversity in genetic studies of type 2 diabetes and related glycaemic traits

Type 2 diabetes has a global prevalence, with epidemiological data suggesting that some populations have a higher risk of developing this disease. However, to date, most genetic studies of type 2 diabetes and related glycaemic traits have been performed in individuals of European ancestry. The same is true for most other complex diseases, largely due to use of 'convenience samples'. Rapid genotyping of large population cohorts and case-control studies from existing collections was performed when the genome-wide association study (GWAS) 'revolution' began, back in 2005. Although global representation has increased in the intervening 15 years, further expansion and inclusion of diverse populations in genetic and genomic studies is still needed. In this review, I discuss the progress made in incorporating multi-ancestry participants in genetic analyses of type 2 diabetes and related glycaemic traits, and associated opportunities and challenges. I also discuss how increased representation of global diversity in genetic and genomic studies is required to fulfil the promise of precision medicine for all.

Effect of dietary fat intake and genetic risk on glucose and insulin-related traits in Brazilian young adults

PURPOSE

The development of metabolic diseases such as type 2 diabetes (T2D) is closely linked to a complex interplay between genetic and dietary factors. The prevalence of abdominal obesity, hyperinsulinemia, dyslipidaemia, and high blood pressure among Brazilian adolescents is increasing and hence, early lifestyle interventions targeting these factors might be an effective strategy to prevent or slow the progression of T2D.

METHODS

We aimed to assess the interaction between dietary and genetic factors on metabolic disease-related traits in 200 healthy Brazilian young adults. Dietary intake was assessed using 3-day food records. Ten metabolic disease-related single nucleotide polymorphisms (SNPs) were used to construct a metabolic-genetic risk score (metabolic-GRS).

RESULTS

We found significant interactions between the metabolic-GRS and total fat intake on fasting insulin level (Pinteraction = 0.017), insulin-glucose ratio (Pinteraction = 0.010) and HOMA-B (Pinteraction = 0.002), respectively, in addition to a borderline GRS-fat intake interaction on HOMA-IR (Pinteraction = 0.051). Within the high-fat intake category [37.98 ± 3.39% of total energy intake (TEI)], individuals with ≥ 5 risk alleles had increased fasting insulin level (P = 0.021), insulin-glucose ratio (P = 0.010), HOMA-B (P = 0.001) and HOMA-IR (P = 0.053) than those with < 5 risk alleles.

CONCLUSION

Our study has demonstrated a novel GRS-fat intake interaction in young Brazilian adults, where individuals with higher genetic risk and fat intake had increased glucose and insulin-related traits than those with lower genetic risk. Large intervention and follow-up studies with an objective assessment of dietary factors are needed to confirm our findings.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s40200-021-00863-7.

Causal effect of insulin resistance on small vessel stroke and Alzheimer's disease: A Mendelian randomization analysis

BACKGROUND AND PURPOSE

The causal effect of insulin resistance on small vessel stroke and Alzheimer's disease (AD) was controversial in previous studies. We therefore applied Mendelian randomization (MR) analyses to identify the causal effect of insulin resistance on small vessel stroke and AD.

METHODS

We selected 12 single-nucleotide polymorphisms (SNPs) associated with fasting insulin levels and five SNPs associated with "gold standard" measures of insulin resistance as instrumental variables in MR analyses. Summary statistical data on SNP-small vessel stroke and on SNP-AD associations were derived from studies by the Multi-ancestry Genome-Wide Association Study of Stroke consortium (MEGASTROKE) and the Psychiatric Genomics Consortium-Alzheimer Disease Workgroup (PGC-ALZ) in individuals of European ancestry. Two-sample MR estimates were conducted with inverse-variance-weighted, robust inverse-variance-weighted, simple median, weighted median, weighted mode-based estimator, and MR pleiotropy residual sum and outlier (MR-PRESSO) methods.

RESULTS

Genetically predicted higher insulin resistance had a higher odds ratio (OR) of small vessel stroke (OR 1.23, 95% confidence interval [CI] 1.05-1.44, p = 0.01 using fasting insulin; OR 1.25, 95% CI 1.07-1.46, p = 0.006 using gold standard measures of insulin resistance) and AD (OR 1.13, 95% CI 1.04-1.23, p = 0.004 using fasting insulin; OR 1.02, 95% CI 1.00-1.03, p = 0.03 using gold standard measures of insulin resistance) using the inverse-variance-weighted method. No evidence of pleiotropy was found using MR-Egger regression.

CONCLUSION

Our findings provide genetic support for a potential causal effect of insulin resistance on small vessel stroke and AD.

Modifiable Risk Factors for Intracranial Aneurysm and Aneurysmal Subarachnoid Hemorrhage: A Mendelian Randomization Study

Background

The aim of this study was to assess the associations of modifiable lifestyle factors (smoking, coffee consumption, sleep, and physical activity) and cardiometabolic factors (body mass index, glycemic traits, type 2 diabetes, systolic and diastolic blood pressure, lipids, and inflammation and kidney function markers) with risks of any (ruptured or unruptured) intracranial aneurysm and aneurysmal subarachnoid hemorrhage using Mendelian randomization.

Methods and Results

Summary statistical data for the genetic associations with the modifiable risk factors and the outcomes were obtained from meta‐analyses of genome‐wide association studies. The inverse‐variance weighted method was used as the main Mendelian randomization analysis, with additional sensitivity analyses conducted using methods more robust to horizontal pleiotropy. Genetic predisposition to smoking, insomnia, and higher blood pressure was associated with an increased risk of both intracranial aneurysm and aneurysmal subarachnoid hemorrhage. For intracranial aneurysm, the odds ratios were 3.20 (95% CI, 1.93–5.29) per SD increase in smoking index, 1.24 (95% CI, 1.10–1.40) per unit increase in log‐odds of insomnia, and 2.92 (95% CI, 2.49–3.43) per 10 mm Hg increase in diastolic blood pressure. In addition, there was weak evidence for associations of genetically predicted decreased physical activity, higher triglyceride levels, higher body mass index, and lower low‐density lipoprotein cholesterol levels with higher risk of intracranial aneurysm and aneurysmal subarachnoid hemorrhage, with 95% CI overlapping the null for at least 1 of the outcomes. All results were consistent in sensitivity analyses.

Conclusions

This Mendelian randomization study suggests that smoking, insomnia, and high blood pressure are major risk factors for intracranial aneurysm and aneurysmal subarachnoid hemorrhage.

Palmitoylated small GTPase ARL15 is translocated within Golgi network during adipogenesis

The small GTPase ARF family member ARL15 gene locus is associated in population studies with increased risk of type 2 diabetes, lower adiponectin and higher fasting insulin levels. Previously, loss of ARL15 was shown to reduce insulin secretion in a human β-cell line and loss-of-function mutations are found in some lipodystrophy patients. We set out to understand the role of ARL15 in adipogenesis and showed that endogenous ARL15 palmitoylated and localised in the Golgi of mouse liver. Adipocyte overexpression of palmitoylation-deficient ARL15 resulted in redistribution to the cytoplasm and a mild reduction in expression of some adipogenesis-related genes. Further investigation of the localisation of ARL15 during differentiation of a human white adipocyte cell line showed that ARL15 was predominantly co-localised with a marker of the cis face of Golgi at the preadipocyte stage and then translocated to other Golgi compartments after differentiation was induced. Finally, co-immunoprecipitation and mass spectrometry identified potential interacting partners of ARL15, including the ER-localised protein ARL6IP5. Together, these results suggest a palmitoylation dependent trafficking-related role of ARL15 as a regulator of adipocyte differentiation via ARL6IP5 interaction.

This article has an associated First Person interview with the first author of the paper.

Summary: ARL15 (GTPase ARF family) is associated with adipose traits. ARL15 is palmitoylated, localised to Golgi in preadipocytes and translocated to other Golgi compartments during differentiation. ARL15 interacts with ER-localised ARL6IP5.

Assessing the Causal Relationships Between Insulin Resistance and Hyperuricemia and Gout Using Bidirectional Mendelian Randomization

OBJECTIVE

Hyperuricemia is closely associated with insulin resistance syndrome (and its many cardiometabolic sequelae); however, whether they are causally related has long been debated. We undertook this study to investigate the potential causal nature and direction between insulin resistance and hyperuricemia, along with gout, by using bidirectional Mendelian randomization (MR) analyses.

METHODS

We used genome-wide association data (n = 288,649 for serum urate [SU] concentration; n = 763,813 for gout risk; n = 153,525 for fasting insulin) to select genetic instruments for 2-sample MR analyses, using multiple MR methods to address potential pleiotropic associations. We then used individual-level, electronic medical record-linked data from the UK Biobank (n = 360,453 persons of European ancestry) to replicate our analyses via single-sample MR analysis.

RESULTS

Genetically determined SU levels, whether inferred from a polygenic score or strong individual loci, were not associated with fasting insulin concentrations. In contrast, genetically determined fasting insulin concentrations were positively associated with SU levels (0.37 mg/dl per log-unit increase in fasting insulin [95% confidence interval (95% CI) 0.15, 0.58]; P = 0.001). This persisted in outlier-corrected (β = 0.56 mg/dl [95% CI 0.45, 0.67]) and multivariable MR analyses adjusted for BMI (β = 0.69 mg/dl [95% CI 0.53, 0.85]) (P < 0.001 for both). Polygenic scores for fasting insulin were also positively associated with SU level among individuals in the UK Biobank (P < 0.001). Findings for gout risk were bidirectionally consistent with those for SU level.

CONCLUSION

These findings provide evidence to clarify core questions about the close association between hyperuricemia and insulin resistance syndrome: hyperinsulinemia leads to hyperuricemia but not the other way around. Reducing insulin resistance could lower the SU level and gout risk, whereas lowering the SU level (e.g., allopurinol treatment) is unlikely to mitigate insulin resistance and its cardiometabolic sequelae.

Association of mitochondrial DNA copy number with cardiometabolic diseases

Mitochondrial DNA (mtDNA) is present in multiple copies in human cells. We evaluated cross-sectional associations of whole blood mtDNA copy number (CN) with several cardiometabolic disease traits in 408,361 participants of multiple ancestries in TOPMed and UK Biobank. Age showed a threshold association with mtDNA CN: among younger participants (<65 years of age), each additional 10 years of age was associated with 0.03 standard deviation (s.d.) higher level of mtDNA CN (P = 0.0014) versus a 0.14 s.d. lower level of mtDNA CN (P = 1.82 × 10^-13) among older participants (≥65 years). At lower mtDNA CN levels, we found age-independent associations with increased odds of obesity (P = 5.6 × 10^-238), hypertension (P = 2.8 × 10^-50), diabetes (P = 3.6 × 10^-7), and hyperlipidemia (P = 6.3 × 10^-5). The observed decline in mtDNA CN after 65 years of age may be a key to understanding age-related diseases.

Synergistic Effects of Genetic Variants of Glucose Homeostasis and Lifelong Exposures to Cigarette Smoking, Female Hormones, and Dietary Fat Intake on Primary Colorectal Cancer Development in African and Hispanic/Latino American Women

BACKGROUND

Disparities in cancer genomic science exist among racial/ethnic minorities. Particularly, African American (AA) and Hispanic/Latino American (HA) women, the 2 largest minorities, are underrepresented in genetic/genome-wide studies for cancers and their risk factors. We conducted on AA and HA postmenopausal women a genomic study for insulin resistance (IR), the main biologic mechanism underlying colorectal cancer (CRC) carcinogenesis owing to obesity.

METHODS

With 780 genome-wide IR-specific single-nucleotide polymorphisms (SNPs) among 4,692 AA and 1,986 HA women, we constructed a CRC-risk prediction model. Along with these SNPs, we incorporated CRC-associated lifestyles in the model of each group and detected the topmost influential genetic and lifestyle factors. Further, we estimated the attributable risk of the topmost risk factors shared by the groups to explore potential factors that differentiate CRC risk between these groups.

RESULTS

In both groups, we detected IR-SNPs in PCSK1 (in AA) and IFT172, GCKR, and NRBP1 (in HA) and risk lifestyles, including long lifetime exposures to cigarette smoking and endogenous female hormones and daily intake of polyunsaturated fatty acids (PFA), as the topmost predictive variables for CRC risk. Combinations of those top genetic- and lifestyle-markers synergistically increased CRC risk. Of those risk factors, dietary PFA intake and long lifetime exposure to female hormones may play a key role in mediating racial disparity of CRC incidence between AA and HA women.

CONCLUSIONS

Our results may improve CRC risk prediction performance in those medically/scientifically underrepresented groups and lead to the development of genetically informed interventions for cancer prevention and therapeutic effort, thus contributing to reduced cancer disparities in those minority subpopulations.

Genetic Signatures of Glucose Homeostasis: Synergistic Interplay With Long-Term Exposure to Cigarette Smoking in Development of Primary Colorectal Cancer Among African American Women

INTRODUCTION

Insulin resistance (IR)/glucose intolerance is a critical biologic mechanism for the development of colorectal cancer (CRC) in postmenopausal women. Whereas IR and excessive adiposity are more prevalent in African American (AA) women than in White women, AA women are underrepresented in genome-wide studies for systemic regulation of IR and the association with CRC risk.

METHODS

With 780 genome-wide IR single-nucleotide polymorphisms (SNPs) among 4,692 AA women, we tested for a causal inference between genetically elevated IR and CRC risk. Furthermore, by incorporating CRC-associated lifestyle factors, we established a prediction model on the basis of gene-environment interactions to generate risk profiles for CRC with the most influential genetic and lifestyle factors.

RESUTLS

In the pooled Mendelian randomization analysis, the genetically elevated IR was associated with 9 times increased risk of CRC, but with lack of analytic power. By addressing the variation of individual SNPs in CRC in the prediction model, we detected 4 fasting glucose-specific SNPs in GCK, PCSK1, and MTNR1B and 4 lifestyles, including smoking, aging, prolonged lifetime exposure to endogenous estrogen, and high fat intake, as the most predictive markers of CRC risk. Our joint test for those risk genotypes and lifestyles with smoking revealed the synergistically increased CRC risk, more substantially in women with longer-term exposure to cigarette smoking.

DISCUSSION

Our findings may improve CRC prediction ability among medically underrepresented AA women and highlight genetically informed preventive interventions (e.g., smoking cessation; CRC screening to longer-term smokers) for those women at high risk with risk genotypes and behavioral patterns.

Relationship between glucose homeostasis and obesity in early life-A study of Italian children and adolescents

OBJECTIVES

Epidemic obesity is the most important risk factor for prediabetes and type 2 diabetes (T2D) in youth as it is in adults. Obesity shares pathophysiological mechanisms with T2D and is likely to share part of the genetic background. We aimed to test if weighted genetic risk scores (GRSs) for T2D, fasting glucose (FG) and fasting insulin (FI) predict glycaemic traits and if there is a causal relationship between obesity and impaired glucose metabolism in children and adolescents.

DESIGN AND PATIENTS

Genotyping of 42 SNPs established by genome-wide association studies for T2D, FG and FI was performed in 1660 Italian youths aged between 2 and 19 years. We defined GRS for T2D, FG and FI and tested their effects on glycaemic traits, including FG, FI, indices of insulin resistance/beta cell function, and body mass index (BMI). We evaluated causal relationships between obesity and FG/FI using one-sample Mendelian Randomization analyses in both directions.

RESULTS

GRS-FG associated with FG (beta = 0.075 mmol/l, SE = 0.011, P = 1.58 × 10-11) and beta cell function (beta = -0.041, SE = 0.0090 P = 5.13 × 10-6). GRS-T2D also demonstrated an association with beta cell function (beta = -0.020, SE = 0.021 P = 0.030). We detected a causal effect of increased BMI on levels of FI in Italian youths (beta = 0.31 ln (pmol/l), 95%CI [0.078, 0.54], P = 0.0085), while there was no effect of FG/FI levels on BMI.

CONCLUSION

Our results demonstrate that the glycaemic and T2D risk genetic variants contribute to higher FG and FI levels and decreased beta cell function in children and adolescents. The causal effects of adiposity on increased insulin resistance are detectable from childhood age.

Early Life Adversity and Polygenic Risk for High Fasting Insulin Are Associated With Childhood Impulsivity

While the co-morbidity between metabolic and psychiatric behaviors is well-established, the mechanisms are poorly understood, and exposure to early life adversity (ELA) is a common developmental risk factor. ELA is associated with altered insulin sensitivity and poor behavioral inhibition throughout life, which seems to contribute to the development of metabolic and psychiatric disturbances in the long term. We hypothesize that a genetic background associated with higher fasting insulin interacts with ELA to influence the development of executive functions (e.g., impulsivity in young children). We calculated the polygenic risk scores (PRSs) from the genome-wide association study (GWAS) of fasting insulin at different thresholds and identified the subset of single nucleotide polymorphisms (SNPs) that best predicted peripheral insulin levels in children from the Avon Longitudinal Study of Parents and Children (ALSPAC) cohort [N = 467; p_{t– initial} = 0.24 (10,296 SNPs), p_{t– refined} = 0.05 (57 SNPs)]. We then calculated the refined PRS (rPRS) for fasting insulin at this specific threshold in the children from the Maternal Adversity, Vulnerability and Neurodevelopment (MAVAN) cohort and investigated its interaction effect with adversity on an impulsivity task applied at 36 months. We found a significant effect of interaction between fasting insulin rPRS and adversity exposure predicting impulsivity measured by the Snack Delay Task at 36 months [β = −0.329, p = 0.024], such that higher PRS [β = −0.551, p = 0.009] was linked to more impulsivity in individuals exposed to more adversity. Enrichment analysis (MetaCore^TM) of the SNPs that compose the fasting insulin rPRS at this threshold was significant for certain nervous system development processes including dopamine D2 receptor signaling. Additional enrichment analysis (FUMA) of the genes mapped from the SNPs in the fasting insulin rPRS showed enrichment with the accelerated cognitive decline GWAS. Therefore, the genetic background associated with risk for adult higher fasting insulin moderates the impact of early adversity on childhood impulsivity.

Procollagen type III amino-terminal propeptide and insulin-like growth factor I as biomarkers of growth hormone administration

The acceptance in 2012 by the World Anti‐Doping Agency (WADA) of the biomarker test for human growth hormone (hGH) based on procollagen type III amino‐terminal propeptide (P‐III‐NP) and insulin‐like growth factor I (IGF‐I) was perhaps the first time that such a method has been used for forensic purposes. Developing a biomarker test to anti‐doping standards, where the strict liability principle applies, is discussed. An alternative WADA‐accepted approach is based on the measurement of different hGH isoforms, a method that suffers from the very short half‐life of hGH limiting the detection period. Modification or withdrawal of the immunoassays, on which the biomarker measurements largely depend, has necessitated revalidation of the assays, remeasurement of samples and adjustment of the decision limits above which an athlete will be assumed to have administered hGH. When a liquid chromatography coupled mass spectrometry (LC–MS) method became a reality for the measurement of IGF‐I, more consistency of results was assured. Measurement of P‐III‐NP is still dependent on immunoassays although work is underway to develop an LC–MS method. The promised long‐term detection time for the biomarker assay does not appear to have been realised in practice, and this is perhaps partly the result of decision limits being set too high. Nevertheless, more robust assays are needed before a further adjustment of the decision limit is warranted. In the meantime, WADA is considering using P‐III‐NP and IGF‐I as components of a biomarker passport system recording data from an individual athlete, rather than the population. Using this approach, smaller perturbations in the growth hormone (GH) score would mandate an investigation and possible action for hGH administration.

Genetically Predicted Insomnia in Relation to 14 Cardiovascular Conditions and 17 Cardiometabolic Risk Factors: A Mendelian Randomization Study

Background

This Mendelian randomization study aims to investigate causal associations between genetically predicted insomnia and 14 cardiovascular diseases (CVDs) as well as the potential mediator role of 17 cardiometabolic risk factors.

Methods and Results

Using genetic association estimates from large genome‐wide association studies and UK Biobank, we performed a 2‐sample Mendelian randomization analysis to estimate the associations of insomnia with 14 CVD conditions in the primary analysis. Then mediation analysis was conducted to explore the potential mediator role of 17 cardiometabolic risk factors using a network Mendelian randomization design. After correcting for multiple testing, genetically predicted insomnia was consistent significantly positively associated with 9 of 14 CVDs, those odds ratios ranged from 1.13 (95% CI, 1.08–1.18) for atrial fibrillation to 1.24 (95% CI, 1.16–1.32) for heart failure. Moreover, genetically predicted insomnia was consistently associated with higher body mass index, triglycerides, and lower high‐density lipoprotein cholesterol, each of which may act as a mediator in the causal pathway from insomnia to several CVD outcomes. Additionally, we found very little evidence to support a causal link between insomnia with abdominal aortic aneurysm, thoracic aortic aneurysm, total cholesterol, low‐density lipoprotein cholesterol, glycemic traits, renal function, and heart rate increase during exercise. Finally, we found no evidence of causal associations of genetically predicted body mass index, high‐density lipoprotein cholesterol, or triglycerides on insomnia.

Conclusions

This study provides evidence that insomnia is associated with 9 of 14 CVD outcomes, some of which may be partially mediated by 1 or more of higher body mass index, triglycerides, and lower high‐density lipoprotein cholesterol.

Obesity, Type 2 Diabetes, and the Risk of Carpal Tunnel Syndrome: A Two-Sample Mendelian Randomization Study

Some previous observational studies have reported an increased risk of carpal tunnel syndrome (CTS) in patients with obesity or type 2 diabetes (T2D), which was however, not observed in some other studies. In this study we performed a two-sample Mendelian randomization to assess the causal effect of obesity, T2D on the risk of CTS. Single nucleotide polymorphisms associated with the body mass index (BMI) and T2D were extracted from genome-wide association studies. Summary-level results of CTS were available through FinnGen repository. Univariable Mendelian randomization (MR) with inverse-variance-weighted method indicated a positive correlation of BMI with CTS risk [odds ratio (OR) 1.66, 95% confidence interval (CI), 1.39–1.97]. Genetically proxied T2D also significantly increased the risk of CTS [OR 1.17, 95% CI (1.07–1.29)]. The causal effect of BMI and T2D on CTS remained consistent after adjusting for each other with multivariable MR. Our mediation analysis indicated that 34.4% of BMI’s effect of CTS was mediated by T2D. We also assessed the effects of several BMI and glycemic related traits on CTS. Waist circumference and arm fat-free mass were also causally associated with CTS. However, the associations disappeared after adjusting for the effect of BMI. Our findings indicate that obesity and T2D are independent risk factors of CTS.

The Role of Hexokinase Domain Containing Protein-1 in Glucose Regulation During Pregnancy

PURPOSE OF REVIEW

Gestational diabetes mellitus (GDM) is a common pregnancy complication conferring an increased risk to the individual of developing type 2 diabetes. As such, a thorough understanding of the pathophysiology of GDM is warranted. Hexokinase domain containing protein-1 (HKDC1) is a recently discovered protein containing hexokinase activity which has been shown to be associated with glucose metabolism during pregnancy. Here, we discuss recent evidence suggesting roles for the novel HKDC1 in gestational glucose homeostasis and the development of GDM and overt diabetes.

RECENT FINDINGS

Genome-wide association studies identified variants of the HKDC1 gene associated with maternal glucose metabolism. Studies modulating HKDC1 protein expression in pregnant mice demonstrate that HKDC1 has roles in whole-body glucose utilization and nutrient balance, with liver-specific HKDC1 influencing insulin sensitivity, glucose tolerance, gluconeogenesis, and ketone production. HKDC1 has important roles in maintaining maternal glucose homeostasis extending beyond traditional hexokinase functions and may serve as a potential therapeutic target.

LDL-Cholesterol versus Glucose in Microvascular and Macrovascular Disease

BACKGROUND

The causal relationships between increased concentrations of low density lipoprotein (LDL)-cholesterol and glucose and risk of ischemic heart disease are well established. The causal contributions of LDL-cholesterol and glucose to risk of peripheral micro- and macrovascular diseases are less studied, especially in prediabetic stages and in a general population setting.

CONTENT

This review summarizes the current evidence for a causal contribution of LDL-cholesterol and glucose to risk of a spectrum of peripheral micro- and macrovascular diseases and reviews possible underlying disease mechanisms, including differences between vascular compartments, and finally discusses the clinical implications of these findings, including strategies for prevention and treatment.

SUMMARY

Combined lines of evidence suggest that LDL-cholesterol has a causal effect on risk of peripheral arterial disease and chronic kidney disease, both of which represent manifestations of macrovascular disease due to atherosclerosis and accumulation of LDL particles in the arterial wall. In contrast, there is limited evidence for a causal effect on risk of microvascular disease. Glucose has a causal effect on risk of both micro- and macrovascular disease. However, most evidence is derived from studies of individuals with diabetes. Further studies in normoglycemic and prediabetic individuals are warranted. Overall, LDL-cholesterol-lowering reduces risk of macrovascular disease, while evidence for a reduction in risk of microvascular disease is inconsistent. Glucose-lowering has a beneficial effect on risk of microvascular diseases and on risk of chronic kidney disease and estimated glomerular filtration rate (eGFR) in some studies, while results on risk of peripheral arterial disease are conflicting.

Multi-omics analysis identifies CpGs near G6PC2 mediating the effects of genetic variants on fasting glucose

AIMS/HYPOTHESIS

An elevated fasting glucose level in non-diabetic individuals is a key predictor of type 2 diabetes. Genome-wide association studies (GWAS) have identified hundreds of SNPs for fasting glucose but most of their functional roles in influencing the trait are unclear. This study aimed to identify the mediation effects of DNA methylation between SNPs identified as significant from GWAS and fasting glucose using Mendelian randomisation (MR) analyses.

METHODS

We first performed GWAS analyses for three cohorts (Taiwan Biobank with 18,122 individuals, the Healthy Aging Longitudinal Study in Taiwan with 1989 individuals and the Stanford Asia-Pacific Program for Hypertension and Insulin Resistance with 416 individuals) with individuals of Han Chinese ancestry in Taiwan, followed by a meta-analysis for combining the three GWAS analysis results to identify significant and independent SNPs for fasting glucose. We determined whether these SNPs were methylation quantitative trait loci (meQTLs) by testing their associations with DNA methylation levels at nearby CpG sites using a subsample of 1775 individuals from the Taiwan Biobank. The MR analysis was performed to identify DNA methylation with causal effects on fasting glucose using meQTLs as instrumental variables based on the 1775 individuals. We also used a two-sample MR strategy to perform replication analysis for CpG sites with significant MR effects based on literature data.

RESULTS

Our meta-analysis identified 18 significant (p < 5 × 10^-8) and independent SNPs for fasting glucose. Interestingly, all 18 SNPs were meQTLs. The MR analysis identified seven CpGs near the G6PC2 gene that mediated the effects of a significant SNP (rs2232326) in the gene on fasting glucose. The MR effects for two CpGs were replicated using summary data based on the European population, using an exonic SNP rs2232328 in G6PC2 as the instrument.

CONCLUSIONS/INTERPRETATION

Our analysis results suggest that rs2232326 and rs2232328 in G6PC2 may affect DNA methylation at CpGs near the gene and that the methylation may have downstream effects on fasting glucose. Therefore, SNPs in G6PC2 and CpGs near G6PC2 may reside along the pathway that influences fasting glucose levels. This is the first study to report CpGs near G6PC2, an important gene for regulating insulin secretion, mediating the effects of GWAS-significant SNPs on fasting glucose.

Genome-wide association study identifying novel variant for fasting insulin and allelic heterogeneity in known glycemic loci in Chilean adolescents: The Santiago Longitudinal Study

BACKGROUND

The genetic underpinnings of glycemic traits have been understudied in adolescent and Hispanic/Latino (H/L) populations in comparison to adults and populations of European ancestry.

OBJECTIVE

To identify genetic factors underlying glycemic traits in an adolescent H/L population.

METHODS

We conducted a genome-wide association study (GWAS) of fasting glucose (FG) and fasting insulin (FI) in H/L adolescents from the Santiago Longitudinal Study.

RESULTS

We identified one novel variant positioned in the CSMD1 gene on chromosome 8 (rs77465890, effect allele frequency = 0.10) that was associated with FI (β = -0.299, SE = 0.054, p = 2.72×10-8 ) and was only slightly attenuated after adjusting for body mass index z-scores (β = -0.252, SE = 0.047, p = 1.03×10-7 ). We demonstrated directionally consistent, but not statistically significant results in African and Hispanic adults of the Population Architecture Using Genomics and Epidemiology Consortium. We also identified secondary signals for two FG loci after conditioning on known variants, which demonstrate allelic heterogeneity in well-known glucose loci.

CONCLUSION

Our results exemplify the importance of including populations with diverse ancestral origin and adolescent participants in GWAS of glycemic traits to uncover novel risk loci and expand our understanding of disease aetiology.

Impact of high glucose levels and glucose lowering on risk of ischaemic stroke: a Mendelian randomisation study and meta-analysis

AIMS/HYPOTHESIS

It is unclear whether glucose per se has a causal impact on risk of stroke and whether glucose-lowering drugs reduce this risk. This is important for the choice of treatment for individuals at risk. We tested the hypotheses that high plasma glucose has a causal impact on increased risk of ischaemic stroke, and that glucose-lowering drugs reduce this risk.

METHODS

Using a Mendelian randomisation design, we examined 118,838 individuals from two Copenhagen cohorts, the Copenhagen General Population Study and the Copenhagen City Heart Study, and 440,328 individuals from the MEGASTROKE study. Effects of eight glucose-lowering drugs on risk of stroke were summarised by meta-analyses.

RESULTS

In genetic, causal analyses, a 1 mmol/l higher plasma glucose had a risk ratio of 1.48 (95% CI 1.04, 2.11) for ischaemic stroke in the Copenhagen studies. The corresponding risk ratio from the MEGASTROKE study combined with the Copenhagen studies was 1.74 (1.31, 2.18). In meta-analyses of glucose-lowering drugs, the risk ratio for stroke was 0.85 (0.77, 0.94) for glucagon-like peptide-1 receptor agonists and 0.82 (0.69, 0.98) for thiazolidinediones, while sulfonylureas, dipeptidyl peptidase-4 inhibitors, sodium-glucose cotransporter 2 inhibitors, α-glucosidase inhibitors, meglitinides and metformin individually lacked statistical evidence of an effect on stroke risk.

CONCLUSIONS/INTERPRETATION

Genetically high plasma glucose has a causal impact on increased risk of ischaemic stroke. Treatment with glucose-lowering glucagon-like peptide-1 receptor agonists and thiazolidinediones reduces this risk. These results may guide clinicians in the treatment of individuals at high risk of ischaemic stroke.

Type 2 Diabetes, Metabolic Traits, and Risk of Heart Failure: A Mendelian Randomization Study

OBJECTIVE

The aim of this study was to use Mendelian randomization (MR) techniques to estimate the causal relationships between genetic liability to type 2 diabetes (T2D), glycemic traits, and risk of heart failure (HF).

RESEARCH DESIGN AND METHODS

Summary-level data were obtained from genome-wide association studies of T2D, insulin resistance (IR), glycated hemoglobin, fasting insulin and glucose, and HF. MR was conducted using the inverse-variance weighted method. Sensitivity analyses included the MR-Egger method, weighted median and mode methods, and multivariable MR conditioning on potential mediators.

RESULTS

Genetic liability to T2D was causally related to higher risk of HF (odds ratio [OR] 1.13 per 1-log unit higher risk of T2D; 95% CI 1.11-1.14; P < 0.001); however, sensitivity analysis revealed evidence of directional pleiotropy. The relationship between T2D and HF was attenuated when adjusted for coronary disease, BMI, LDL cholesterol, and blood pressure in multivariable MR. Genetically instrumented higher IR was associated with higher risk of HF (OR 1.19 per 1-log unit higher risk of IR; 95% CI 1.00-1.41; P = 0.041). There were no notable associations identified between fasting insulin, glucose, or glycated hemoglobin and risk of HF. Genetic liability to HF was causally linked to higher risk of T2D (OR 1.49; 95% CI 1.01-2.19; P = 0.042), although again with evidence of pleiotropy.

CONCLUSIONS

These findings suggest a possible causal role of T2D and IR in HF etiology, although the presence of both bidirectional effects and directional pleiotropy highlights potential sources of bias that must be considered.

Dietary Acid Load and Its Interaction with IGF1 (rs35767 and rs7136446) and IL6 (rs1800796) Polymorphisms on Metabolic Traits among Postmenopausal Women

The objective of this study was to explore the effects of dietary acid load (DAL) and IGF1 and IL6 gene polymorphisms and their potential diet–gene interactions on metabolic traits. A total of 211 community-dwelling postmenopausal women were recruited. DAL was estimated using potential renal acid load (PRAL). Blood was drawn for biochemical parameters and DNA was extracted and Agena^® MassARRAY was used for genotyping analysis to identify the signalling of IGF1 (rs35767 and rs7136446) and IL6 (rs1800796) polymorphisms. Interactions between diet and genetic polymorphisms were assessed using regression analysis. The result showed that DAL was positively associated with fasting blood glucose (FBG) (β = 0.147, p < 0.05) and there was significant interaction effect between DAL and IL6 with systolic blood pressure (SBP) (β = 0.19, p = 0.041). In conclusion, these findings did not support the interaction effects between DAL and IGF1 and IL6 single nucleotide polymorphisms (rs35767, rs7136446, and rs1800796) on metabolic traits, except for SBP. Besides, higher DAL was associated with higher FBG, allowing us to postulate that high DAL is a potential risk factor for diabetes.