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Background: Hypothyroidism and coronary heart disease are both common diseases in life and both are increasing in prevalence. Many studies have found a strong association between the two. However, they have not been able to prove a causal relationship. Furthermore, numerous studies have demonstrated that glycemic traits play a role in both. Consequently, the objective of this study was to ascertain the causal estimation of the association between hypothyroidism and coronary heart disease and to quantify the potential mediating role of glycemic traits in this relationship. Methods: We used two-sample Mendelian randomisation (UVMR) to explore causality between hypothyroidism and coronary heart disease. Additionally, multivariate Mendelian randomisation (MVMR) was applied to quantify the potential mediation of glycemic traits in this relationship. A variety of Mendelian randomization methods were employed in this study, including the inverse variance weighting (IVW) method, weighted median method, and MREgger test. Heterogeneity and horizontal pleiotropy were evaluated through MREgger intercept test, Cochran's Q test, and leave-one-out analysis to ensure the robustness of the study results. Results: The results of the MR analyses indicated that hypothyroidism was associated with an increased risk of coronary heart disease (IVW: OR=2.75, 95% CI: 1.53-4.94). In mediation analyses, the proportion of HbA1c-mediated effects of hypothyroidism on coronary heart disease was 7.3% (2.2%-12.5%). Conclusion: The results of our study indicate a causal relationship between hypothyroidism and coronary heart disease. Furthermore, HbA1c partially mediated the causal effect of hypothyroidism on coronary heart disease. Consequently, intervention in this factor may reduce the risk of coronary heart disease associated with hypothyroidism. [ABSTRACT FROM AUTHOR]

Background: Hypothyroidism and coronary heart disease are both common diseases in life and both are increasing in prevalence. Many studies have found a strong association between the two. However, they have not been able to prove a causal relationship. Furthermore, numerous studies have demonstrated that glycemic traits play a role in both. Consequently, the objective of this study was to ascertain the causal estimation of the association between hypothyroidism and coronary heart disease and to quantify the potential mediating role of glycemic traits in this relationship. Methods: We used two-sample Mendelian randomisation (UVMR) to explore causality between hypothyroidism and coronary heart disease. Additionally, multivariate Mendelian randomisation (MVMR) was applied to quantify the potential mediation of glycemic traits in this relationship. A variety of Mendelian randomization methods were employed in this study, including the inverse variance weighting (IVW) method, weighted median method, and MREgger test. Heterogeneity and horizontal pleiotropy were evaluated through MREgger intercept test, Cochran's Q test, and leave-one-out analysis to ensure the robustness of the study results. Results: The results of the MR analyses indicated that hypothyroidism was associated with an increased risk of coronary heart disease (IVW: OR=2.75, 95% CI: 1.53-4.94). In mediation analyses, the proportion of HbA1c-mediated effects of hypothyroidism on coronary heart disease was 7.3% (2.2%-12.5%). Conclusion: The results of our study indicate a causal relationship between hypothyroidism and coronary heart disease. Furthermore, HbA1c partially mediated the causal effect of hypothyroidism on coronary heart disease. Consequently, intervention in this factor may reduce the risk of coronary heart disease associated with hypothyroidism. [ABSTRACT FROM AUTHOR]

Clinical biomarkers such as fasting glucose, HbA1c, and fasting insulin, which gauge glycemic status in the body, are highly influenced by diet. Indians are genetically predisposed to type 2 diabetes and their carbohydrate-centric diet further elevates the disease risk. Despite the combined influence of genetic and environmental risk factors, Indians have been inadequately explored in the studies of glycemic traits. Addressing this gap, we investigate the genetic architecture of glycemic traits at genome-wide level in 4927 Indians (without diabetes). Our analysis revealed numerous variants of sub-genome-wide significance, and their credibility was thoroughly assessed by integrating data from various levels. This identified key effector genes, ZNF470, DPP6, GXYLT2, PITPNM3, BEND7, and LORICRIN-PGLYRP3. While these genes were weakly linked with carbohydrate intake or glycemia earlier in other populations, our findings demonstrated a much stronger association in the Indian population. Associated genetic variants within these genes served as expression quantitative trait loci (eQTLs) in various gut tissues essential for digestion. Additionally, majority of these gut eQTLs functioned as methylation quantitative trait loci (meth-QTLs) observed in peripheral blood samples from 223 Indians, elucidating the underlying mechanism of their regulation of target gene expression. Specific co-localized eQTLs-meth-QTLs altered the binding affinity of transcription factors targeting crucial genes involved in glucose metabolism. Our study identifies previously unreported genetic variants that strongly influence the diet-glycemia relationship. These findings set the stage for future research into personalized lifestyle interventions integrating genetic insights with tailored dietary strategies to mitigate disease risk based on individual genetic profiles. [ABSTRACT FROM AUTHOR]

Objective: To test the glycemic susceptibility in three urological cancers and eight urological/reproductive diseases using the Mendelian randomization (MR) method. Materials and methods: Two-sample MR was applied to investigate the causal role of three glycemic traits (type II diabetes, fasting glucose and glycated hemoglobin (HbA1c)) in eleven urological/reproductive diseases (kidney cancer, bladder cancer, prostate cancer, kidney/ureter stone, urinary incontinence, benign prostatic hyperplasia, erectile dysfunction, female infertility, male infertility, abnormal spermatozoa and polycystic ovary syndrome). Further multivariate MR (MVMR) and mediating analysis were performed to investigate the associations. Results: Among all the 11 diseases, type II diabetes was positively associated with erectile dysfunction, which was stable across both cohorts [odds ratio (OR): 1.59, 95% confidence interval (CI): 1.15–2.20, P = 0.005 for FinnGen Biobank and OR: 1.14, 95% CI: 1.08–1.21, P < 0.001 for the other cohort]. Also, type II diabetes was negatively associated with male infertility (OR: 0.57, 95% CI: 0.39–0.84, P = 0.005). In addition, all three glycemic traits were observed to be positively associated with polycystic ovary syndrome (OR: 2.36, 95% CI: 1.16–4.76, P = 0.017 for fasting glucose per mmol/L; OR: 3.04, 95% CI: 1.10–8.39, P = 0.032 for HbA1c per percentage; and OR: 1.21, 95% CI: 1.00-1.46, P = 0.046 for type II diabetes). Mediating analysis confirmed the effect of type II diabetes on these diseases. Conclusions: There existed glycemic susceptibility in erectile dysfunction, male infertility and polycystic ovary syndrome. We could not conclude stable glycemic susceptibility in other urological/reproductive diseases. [ABSTRACT FROM AUTHOR]

Epigenetic clocks based on DNA methylation have been known as biomarkers of aging, including principal component (PC) clocks representing the degree of aging and DunedinPACE representing the pace of aging. Prior studies have shown the associations between epigenetic aging and T2DM, but the results vary by epigenetic age metrics and people. This study explored the associations between epigenetic age metrics and T2DM or glycemic traits, based on 1070 twins (535 twin pairs) from the Chinese National Twin Registry. It also explored the temporal relationships of epigenetic age metrics and glycemic traits in 314 twins (157 twin pairs) who participated in baseline and follow‐up visits after a mean of 4.6 years. DNA methylation data were used to calculate epigenetic age metrics, including PCGrimAge acceleration (PCGrimAA), PCPhenoAge acceleration (PCPhenoAA), DunedinPACE, and the longitudinal change rate of PCGrimAge/PCPhenoAge. Mixed‐effects and cross‐lagged modelling assessed the cross‐sectional and temporal relationships between epigenetic age metrics and T2DM or glycemic traits, respectively. In the cross‐sectional analysis, positive associations were identified between DunedinPACE and glycemic traits, as well as between PCPhenoAA and fasting plasma glucose, which may be not confounded by shared genetic factors. Cross‐lagged models revealed that glycemic traits (fasting plasma glucose, HbA1c, and TyG index) preceded DunedinPACE increases, and TyG index preceded PCGrimAA increases. Glycemic traits are positively associated with epigenetic age metrics, especially DunedinPACE. Glycemic traits preceded the increases in DunedinPACE and PCGrimAA. Lowering the levels of glycemic traits may reduce DunedinPACE and PCGrimAA, thereby mitigating age‐related comorbidities. [ABSTRACT FROM AUTHOR]

Background : Previous studies, including Mendelian randomization (MR), have demonstrated type 2 diabetes (T2D) and glycemic traits are associated with increased risk of metabolic dysfunction-associated steatotic liver disease (MASLD). However, few studies have explored the underlying pathway, such as the role of iron homeostasis. Methods: We used a two-step MR approach to investigate the associations of genetic liability to T2D, glycemic traits, iron biomarkers, and liver diseases. We analyzed summary statistics from various genome-wide association studies of T2D (n = 933,970), glycemic traits (n ≤ 209,605), iron biomarkers (n ≤ 246,139), MASLD (n ≤ 972,707), and related biomarkers (alanine aminotransferase (ALT) and proton density fat fraction (PDFF)). Our primary analysis was based on inverse-variance weighting, followed by several sensitivity analyses. We also conducted mediation analyses and explored the role of liver iron in post hoc analysis. Results: Genetic liability to T2D and elevated fasting insulin (FI) likely increased risk of liver steatosis (ORliability to T2D: 1.14 per doubling in the prevalence, 95% CI: 1.10, 1.19; ORFI: 3.31 per log pmol/l, 95% CI: 1.92, 5.72) and related biomarkers. Liability to T2D also likely increased the risk of developing liver cirrhosis. Genetically elevated ferritin, serum iron, and liver iron were associated with higher risk of liver steatosis (ORferritin: 1.25 per SD, 95% CI 1.07, 1.46; ORliver iron: 1.15 per SD, 95% CI: 1.05, 1.26) and liver cirrhosis (ORserum iron: 1.31, 95% CI: 1.06, 1.63; ORliver iron: 1.34, 95% CI: 1.07, 1.68). Ferritin partially mediated the association between FI and liver steatosis (proportion mediated: 7%, 95% CI: 2–12%). Conclusions: Our study provides credible evidence on the causal role of T2D and elevated insulin in liver steatosis and cirrhosis risk and indicates ferritin may play a mediating role in this association. Highlights: • Ferritin possibly mediates the association of insulin resistance in liver steatosis. Targeting the reduction of ferritin may mitigate the risk of liver steatosis arising from elevated insulin. • Liver iron is likely to be positively associated with liver steatosis and the irreversible stage, liver cirrhosis, and mediates the association of ferritin and liver steatosis. • Genetically elevated HbA1c is shown to decrease the risk of liver steatosis due to its erythrocytic property. Caution should be applied when using HbA1c values for MASLD management. [ABSTRACT FROM AUTHOR]

Background: The interplay between diabetes mellitus (DM), glycemic traits, and vascular and valvular calcifications is intricate and multifactorial. Exploring potential mediators may illuminate underlying pathways and identify novel therapeutic targets. Methods: We utilized univariable and multivariable Mendelian randomization (MR) analyses to investigate associations and mediation effects. Additionally, the multivariable MR analyses incorporated cardiometabolic risk factors, allowing us to account for potential confounders. Results: Type 2 diabetes mellitus (T2DM) and glycated hemoglobin (HbA1c) were positively associated with both coronary artery calcification (CAC) and calcific aortic valvular stenosis (CAVS). However, fasting glucose (FG) was only linked to CAVS and showed no association with CAC. Additionally, CAVS demonstrated a causal effect on FG. Calcium levels partially mediated the impact of T2DM on both types of calcifications. Specifically, serum calcium was positively associated with both CAC and CAVS. The mediation effects of calcium levels on the impact of T2DM on CAC and CAVS were 6.063% and 3.939%, respectively. The associations between T2DM and HbA1c with calcifications were influenced by body mass index (BMI) and smoking status. However, these associations were generally reduced after adjusting for hypertension. Conclusion: Our findings suggest a genetically supported causal relationship between DM, glycemic traits, and vascular and valvular calcifications, with serum calcium playing a critical mediating role. [ABSTRACT FROM AUTHOR]

Background: Several recent observational studies have associated obesity, lifestyle factors (smoking, sleep duration, and alcohol drinking), and glycemic traits with facial aging. However, whether this relationship is causal due to confounding and reverse causation is yet to be substantiated. Aims: We aimed to assess these relationships using Mendelian randomization (MR). Methods: For the instrumental variables, this paper selected independent single nucleotide polymorphisms (SNPs) linked to the exposures at a genome-wide state (P < 5 × 10−8) in equivalent genome-wide association studies (GWAS). Using the UK Biobank, we obtained summary-level data for facial aging on 423,999 individuals. The primary assessments were performed through the combination of complementing techniques (simple method approaches, weighted model, MR-Egger, and weighted median) and the inverse-variance-weighted method. Along with that, we examined the heterogeneity and horizontal pleiotropy through different types of sensitivity analyses. Results: The correlations were (a) facial aging for body mass index (BMI, OR = 1.054, 95% CI 1.044–1.64), (b) waist/hip ratio (OR = 1.056, 95% CI 1.023–1.091), and (c) smoking (OR = 1.023, 95% CI 1.007–1.039). Equally important, the correlations for waist/hip ratio remained robust after adjusting for the genetically predicted BMI (OR = 1.028, 95% CI 1.003–1.054). However, no causal effects of alcoholic drinking, glycemic traits, and sleep duration on facial aging were observed. Conclusions: The outcomes shed light on the potential correlation of obesity and cigarette smoking with facial aging while putting forward a more comprehensive and credible foundation for the optimization of facial aging strategies. No Level Assigned: This journal requires that authors assign a level of evidence to each submission to which Evidence-Based Medicine rankings are applicable. This excludes Review Articles, Book Reviews, and manuscripts that concern Basic Science, Animal Studies, Cadaver Studies, and Experimental Studies. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266. [ABSTRACT FROM AUTHOR]

The current state of knowledge on the relationship between lifestyle factors, glycemic traits, lipoprotein traits with liver cancer risk is still uncertain despite some attempts made by observational studies. This study aims to investigate the causal genetic relationship between factors highly associated with liver cancer incidence by using Mendelian randomization (MR) analysis. Employing MR analysis, this study utilized previously published GWAS datasets to investigate whether lifestyle factors, glycemic traits, and lipoprotein traits would affect the risk of liver cancer. The study utilized three MR methods, including inverse variance-weighted model (IVW), MR Egger, and weighted median. Furthermore, MR-Egger analyses were performed to detect heterogeneity in the MR results. The study also conducted a leave-one-out analysis to assess the potential influence of individual SNPs on the MR analysis results. MR-PRESSO was used to identify and remove SNP outliers associated with liver cancer. MR analyses revealed that 2-h glucose (odds ratio, OR 2.33, 95% confidence interval, CI 1.28–4.21), type 2 diabetes mellitus (T2DM, OR 1.67, 95% CI 1.18–2.37), body mass index (BMI, OR 1.67, 95% CI 1.18–2.37), waist circumference (OR 1.78, 95% CI 1.18–2.37) were associated with increased risk of liver cancer. On the contrary, apolipoproteins B (APOB, OR 0.67, 95% CI 0.47–0.97), and low-density lipoprotein (LDL, OR 0.62, 95% CI 0.42–0.92) were negatively related to liver cancer risk. Additionally, after adjusting for BMI, apolipoproteins A-I (APOA-I, OR 0.56, 95% CI, 0.38–0.81), total cholesterol (TC, OR 0.72, 95% CI, 0.54–0.94), and total triglycerides (TG, OR 0.57, 95% CI, 0.40–0.78) exhibited a significant inverse correlation with the risk of liver cancer. This study supports a causal relationship between 2-h glucose, T2DM, BMI, and waist circumference with the increased risk of liver cancer. Conversely, the study reveals a cause-effect relationship between TC, TG, LDL, APOA-I, and APOB with a decreased risk of liver cancer. [ABSTRACT FROM AUTHOR]

Objective: To investigate the genetic underpinnings of the association between type 2 diabetes (T2D), glycemic indicators such as fasting glucose (FG), fasting insulin (FI), and glycated hemoglobin (GH), and venous thromboembolism (VTE), encompassing deep vein thrombosis (DVT) and pulmonary embolism (PE), thereby contributing novel insights to the scholarly discourse within this domain. Methods: Genome-wide association study (GWAS) summary data pertaining to exposures (T2D, FG, FI, GH) and outcomes (VTE, DVT, PE) were acquired from the IEU Open GWAS database, encompassing participants of European descent, including both male and female individuals. Two-sample Mendelian randomization (MR) analyses were conducted utilizing the TwoSampleMR and MRPRESSO packages within the R programming environment. The primary analytical approach employed was the random-effects inverse variance weighted (IVW) method. Heterogeneity was assessed via Cochran's Q statistic for MR-IVW and Rucker's Q statistic for MR-Egger. Horizontal pleiotropy was evaluated using the intercept test of MR Egger and MR pleiotropy residual sum and outlier (MR-PRESSO) analysis, with the latter also employed for outlier detection. Additionally, a "Leave one out" analysis was conducted to ascertain the influence of individual single nucleotide polymorphisms (SNPs) on MR results. Results: The random-effects IVW analysis revealed a negative genetic causal association between T2D) and VTE (P = 0.008, Odds Ratio [OR] 95% confidence interval [CI] = 0.896 [0.827–0.972]), as well as between FG and VTE (P = 0.002, OR 95% CI = 0.655 [0.503–0.853]), GH and VTE (P = 0.010, OR 95% CI = 0.604 [0.412–0.884]), and GH and DVT (P = 0.002, OR 95% CI = 0.413 [0.235–0.725]). Conversely, the random-effects IVW analysis did not detect a genetic causal relationship between FI and VTE (P > 0.05), nor between T2D, FG, or FI and DVT (P > 0.05), or between T2D, FG, FI, or GH and PE (P > 0.05). Both the Cochran's Q statistic for MR-IVW and Rucker's Q statistic for MR-Egger indicated no significant heterogeneity (P > 0.05). Moreover, the intercept tests of MR Egger and MR-PRESSO suggested the absence of horizontal pleiotropy (P > 0.05). MR-PRESSO analysis identified no outliers, while the "Leave one out" analysis underscored that the MR analysis was not influenced by any single SNP. Conclusion: Our investigation revealed that T2D, FG, and GH exhibit negative genetic causal relationships with VTE at the genetic level, while GH demonstrates a negative genetic causal relationship with DVT at the genetic level. These findings furnish genetic-level evidence warranting further examination of VTE, DVT, and PE, thereby making a contribution to the advancement of related research domains. [ABSTRACT FROM AUTHOR]

Background: Observational studies have suggested an association between endometriosis and glycemic traits, but causality remains unclear. We used bidirectional and multivariate Mendelian randomization (MR) to examine the causal effect of glycemic traits on endometriosis and vice versa. Methods: We obtained genome-wide association studies summary data of endometriosis and glycemic traits in our study. Inverse variance weighted (IVW), Weighted median, MR-Egger and Mendelian randomization pleiotropy residual sum and outlier (MR-PRESSO) were applied in bidirectional two-sample MR analyses. MVMR was implemented to estimate the causal effect for fasting insulin (FI), fasting glucose (FG), and glycosylated hemoglobin A1c (HbA1c) on endometriosis. To test the validity of our findings, a number of sensitivity analyses were conducted. Results: The risk of endometriosis was significantly increased by genetically predicted T1DM (OR = 1.02, 95% CI 1.00-1.04, p = 0.0171, q = 0.0556) and GDM (OR = 1.01, 95% CI 1.01–1.02, p = 1.34 × 10− 8, q = 1.74 × 10− 7). Endometriosis had a suggestive association with HbA1c (Beta = 0.04, 95% CI 0.00-0.08, p = 0.0481, q = 0.1251). Using multivariate Mendelian randomization (MVMR), a significant causal effect of FI on genetically predicted endometriosis was found (OR = 2.18, 95% CI 1.16–4.09, p = 0.0154, q = 0.0547). Moreover, no causal associations between endometriosis and other glycemic traits were detected. Conclusion: Our findings supported the significant causal associations of T1DM, GDM and FI with endometriosis, respectively. Additionally, a suggestive association was found of endometriosis on HbA1c. Importantly, our study may shed light on etiology studies and clinical management of endometriosis. [ABSTRACT FROM AUTHOR]

Background: Clinical diabetic traits have been reported to be associated with increased colorectal cancer (CRC) risk in observational studies. Using the Mendelian randomization (MR) analysis method, we examined the causal association between glycemic traits, such as fasting glucose (FG), fasting insulin (FI), and glycosylated hemoglobin A1c (HbA1c), and survival in a cohort of CRC patients. Methods: We conducted a two‐sample MR analysis among a cohort of patients with locally advanced CRC at Seoul National University Hospital. Single‐nucleotide polymorphisms robustly associated (p < 5 × 10−8) with the three glycemic traits were obtained from the Meta‐Analyses of Glucose and Insulin‐related traits Consortium, Asian Genetic Epidemiology Network, and Korea Biobank Array. Three‐year and 5‐year overall survival (OS) and progression‐free survival (PFS) were used as outcomes. Survival analysis was conducted using subgroup analysis by cancer stage and subsite in a multivariate Cox proportional hazards model adjusted for age and sex to examine whether glycemic traits affected survival. Results: A total of 509 patients were included in our final analysis. MR analysis showed that HbA1c levels were associated with poor 3‐year OS (β = 4.20, p = 0.02). Sensitivity analyses did not show evidence of any violations of the MR assumptions. In the cancer subgroup analysis of the Cox proportional hazards model, pooled hazard ratios for FG were significantly associated with poor 3‐year OS and PFS regardless of cancer stage. FI was not significantly associated with any 3‐year survival endpoints. Among Stage III patients, three glycemic traits were significantly associated with both 5‐year OS and PFS. Location‐specific subgroup analysis showed a significant association between three glycemic traits and 5‐year PFS in patients with left‐sided colon cancer. FG was associated with poor 3‐year survival for colon cancer but not rectal cancer. Conclusions: Our results suggest that FG and HbA1c could be used to predict prognosis in CRC patients. Lifestyle and/or pharmacological interventions targeting glycemic traits could help improve survival for CRC patients. [ABSTRACT FROM AUTHOR]

Objective To explore the causal relationship between the characteristics of glycemic traits (fasting blood glucose, fasting insulin, glycosylated hemoglobin, and insulin resistance) and benign colorectal neoplasm (colorectal adenomas, benign rectal neoplasm, and benign colon neoplasm). Methods The instrumental variables of blood glucose characteristics were extracted from MAGIC and GLGCL alliance, and the genome-wide data of colorectal benign tumors came from Finn-Gen alliance. In this study, random effect inverse-variance weighted method (IVW), MR-Egger regression, and weighted median method (WMM) were used to analyze the causal relationship between four glycemic traits and benign colorectal neoplasm. Results The results of IVW model showed that there was no causal relationship between fasting blood glucose (OA =0.999, 95%CI: 0.997-1.001), fasting insulin (OA=1.002, 95&lowbar;CI: 0.998-1.006), glycosylated hemoglobin (CI=1.001, 95%CI: 0.999-1.004), insulin resistance (OA=0.999, 95%CI: 0.997-1.002), and colorectal adenoma. There was no causal relationship between fasting blood glucose (OA =0.909, 95%CI: 0.684-1.209), fasting insulin (OA=1.220, 95%CI: 0.706-2.107), glycosylated hemoglobin (0A=0.678, 95&lowbar;CI: 0.440-1.046), insulin resistance (OA=1.161, 95 CI: 0.810-1.663) and rectal benign tumor. There was no causal relationship between fasting blood glucose (OA =0.966, 95%CI: 0.836-1.116), fasting insulin (OA=1.318, 95%CI: 0.906-1.916), glycosylated hemoglobin (OA=1.124, 95%CI: 0.882-1.431), insulin resistance (OA=1.071, 95%CI: 0.875-1.311) and benign tumors of colon. Conclusion There is no evidence of causal relationships of fasting blood glucose, fasting insulin, glycosy- lated hemoglobin, and insulin resistance with colorectal adenomas, benign rectal neoplasm, and benign colon neoplasm. [ABSTRACT FROM AUTHOR]

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

Introduction: Previous research has confirmed that patients with type 2 diabetes mellitus tend to have higher bone mineral density (BMD), but it is unknown whether this pattern holds true for individuals without diabetes. This Mendelian randomization (MR) study aims to investigate the potential causal relationship between various glycemic trait (including fasting glucose, fasting insulin, 2-h postprandial glucose, and glycated hemoglobin) and BMD in non-diabetic individuals. The investigation focuses on different age groups (15–30, 30–45, 45–60, and 60 + years) and various skeletal sites (forearm, lumbar spine, and hip). Materials and methods: We utilized genome-wide association study data from large population-based cohorts to identify robust instrumental variables for each glycemic traits parameter. Our primary analysis employed the inverse-variance weighted method, with sensitivity analyses conducted using MR-Egger, weighted median, MR-PRESSO, and multivariable MR methods to assess the robustness and potential horizontal pleiotropy of the study results. Results: Fasting insulin showed a negative modulating relationship on both lumbar spine and forearm. However, these associations were only nominally significant. No significant causal association was observed between blood glucose traits and BMD across the different age groups. The direction of fasting insulin's causal effects on BMD showed inconsistency between genders, with potentially decreased BMD in women with high fasting insulin levels and an increasing trend in BMD in men. Conclusions: In the non-diabetic population, currently available evidence does not support a causal relationship between glycemic traits and BMD. However, further investigation is warranted considering the observed gender differences. [ABSTRACT FROM AUTHOR]

Background: The effects of diabetes on the cardiac and aortic structure and function remain unclear. Detecting and intervening these variations early is crucial for the prevention and management of complications. Cardiovascular magnetic resonance imaging-derived traits are established endophenotypes and serve as precise, early-detection, noninvasive clinical risk biomarkers. We conducted a Mendelian randomization (MR) study to examine the association between two types of diabetes, four glycemic traits, and preclinical endophenotypes of cardiac and aortic structure and function. Methods: Independent genetic variants significantly associated with type 1 diabetes, type 2 diabetes, fasting insulin (FIns), fasting glucose (FGlu), 2 h-glucose post-challenge (2hGlu), and glycated hemoglobin (HbA1c) were selected as instrumental variables. The 96 cardiovascular magnetic resonance imaging traits came from six independent genome-wide association studies. These traits serve as preclinical endophenotypes and offer an early indication of the structure and function of the four cardiac chambers and two aortic sections. The primary analysis was performed using MR with the inverse-variance weighted method. Confirmation was achieved through Steiger filtering and testing to determine the causal direction. Sensitivity analyses were conducted using the weighted median, MR-Egger, and MR-PRESSO methods. Additionally, multivariable MR was used to adjust for potential effects associated with body mass index. Results: Genetic susceptibility to type 1 diabetes was associated with increased ascending aortic distensibility. Conversely, type 2 diabetes showed a correlation with a reduced diameter and areas of the ascending aorta, as well as decreased distensibility of the descending aorta. Genetically predicted higher levels of FGlu and HbA1c were correlated with a decrease in diameter and areas of the ascending aorta. Furthermore, higher 2hGlu levels predominantly showed association with a reduced diameter of both the ascending and descending aorta. Higher FIns levels corresponded to increased regional myocardial-wall thicknesses at end-diastole, global myocardial-wall thickness at end-diastole, and regional peak circumferential strain of the left ventricle. Conclusions: This study provides evidence that diabetes and glycemic traits have a causal relationship with cardiac and aortic structural and functional remodeling, highlighting the importance of intensive glucose-lowering for primary prevention of cardiovascular diseases. [ABSTRACT FROM AUTHOR]

Objective: To investigate the causal relationships between linoleic acid and type 2 diabetes, and between linoleic acid and glycemic traits in European populations. Methods: This study employed a two-sample Mendelian randomization approach to infer causality between linoleic acid and type 2 diabetes, as well as between linoleic acid and glycemic traits, leveraging genetic variations. Data were sourced from genome-wide association study summary datasets. Random-effects inverse-variance weighted, weighted median, and MR-Egger methods were used for the two-sample Mendelian randomization analyses. Results were presented as odds ratios with a 95% confidence interval. Multiple sensitivity analyses were conducted to assess result robustness. Results: MR findings indicated a correlation between linoleic acid levels and the risk of type 2 diabetes, fasting blood glucose, and glycated hemoglobin (HbA1c), but not with fasting insulin. Specifically: type 2 diabetes (OR: 0.811, 95% CI: 0.688-0.956, P=0.013<0.05), fasting blood glucose β_IVW): -0.056, 95% CI: (-0.091, -0.021), P=0.002< 0.0125), glycated hemoglobin (β_IVW: -0.032, 95% CI: (-0.048,-0.015), P=0.0002< 0.0125) and Fasting insulin (β_IVW: -0.024, 95% CI: (-0.056,-0.008), P=0.136 >0.05). Reverse MR analyses showed a correlation between type 2 diabetes and reduced levels of linoleic acid (β_IVW: -0.033, 95% CI: (-0.059,-0.006), P=0.014<0.05). Multiple sensitivity analyses also detected study heterogeneity but found no evidence of horizontal pleiotropy. Conclusion: High levels linoleic acid can reduce the risk of type 2 diabetes, fasting blood glucose, and glycated hemoglobin, but has no significant relation with fasting insulin. Type 2 diabetes can lower linoleic acid levels; however, no significant causal relationship was observed between the three glycemic traits and reduced levels of linoleic acid. [ABSTRACT FROM AUTHOR]

Purpose: Utilize Mendelian randomization (MR) to examine the impact of leisure sedentary behavior (LSB) on the prevalence of type 2 diabetes mellitus (T2D) and glycemic homeostasis impairment, as well as to identify potential mediating pathways involved in these associations. Methods: We chose genetic variants linked to LSB from a large genome-wide association study (GWAS) to use as instrumental variables (IVs). Then, we used a two-sample MR study to investigate the link between LSB and T2D and glycemic homeostasis. Multivariate MR (MVMR) and mediation analysis were also used to look at possible mediating paths. Results: MR analysis showed a genetical link between leisure TV watching and T2D (OR 1.64, 95% CI 1.39-1.93, P< 0.001) and impaired Glycemic Homeostasis, while leisure computer use seemed to protect against T2D prevalence (OR 0.65, 95% CI 0.50-0.84, P< 0.001). It was found that leisure TV watching increases the risk of T2D through higher BMI (mediation effect 0.23, 95% CI 0.11-0.35, P< 0.001), higher triglycerides (mediation effect 0.07, 95% CI 0.04-0.11, P< 0.001), and less education (mediation effect 0.16, 95% CI 0.08-0.24, P< 0.001). Sensitivity and heterogeneity analyses further substantiated the robustness of these findings. Reverse MR analysis did not yield significant results. Conclusion: This study shows LSB is linked to a higher rate of T2D and impaired glycemic homeostasis through obesity, lipid metabolism disorders, and reduced educational attainment. [ABSTRACT FROM AUTHOR]

Background: Regarding past epidemiological studies, there has been disagreement over whether type 1 diabetes (T1DM) is one of the risk factors for dental caries. The purpose of this study was to determine the causative links between genetic susceptibility to T1DM, glycemic traits, and the risk of dental caries using Mendelian randomization (MR) approaches. Methods: Summary-level data were collected on genome-wide association studies (GWAS) of T1DM, fasting glucose (FG), glycated hemoglobin (HbA1c), fasting insulin (FI), and dental caries. MR was performed using the inversevariance weighting (IVW) method, and sensitivity analyses were conducted using the MR-Egger method, weighted median, weighted mode, replication cohort, and multivariable MR conditioning on potential mediators. Results: The risk of dental caries increased as a result of genetic susceptibility to T1DM [odds ratio (OR) = 1.044; 95% confidence interval (CI) = 1.015-1.074; p = 0.003], with consistent findings in the replication cohort. The relationship between T1DM and dental caries was stable when adjusted for BMI, smoking, alcohol intake, and type 2 diabetes (T2DM) in multivariable MR. However, no significant correlations between the risk of dental caries and FG, HbA1c, or FI were found. Conclusion: These results indicate that T1DM has causal involvement in the genesis of dental caries. Therefore, periodic reinforcement of oral hygiene instructions must be added to the management and early multidisciplinary intervention of T1DM patients, especially among adolescents and teenagers, who are more susceptible to T1DM. [ABSTRACT FROM AUTHOR]

Objective: Type 2 diabetes mellitus (T2DM) is an endocrine-related disease with an increasing incidence worldwide. Male sexual dysfunction is common in diabetic patients. Therefore, we designed a Mendelian randomization (MR) study to investigate the association of type 2 diabetes and 3 glycemic traits with testosterone levels. Methods: Uncorrelated single nucleotide polymorphisms (SNPs) associated with T2DM (N = 228), fasting insulin (N = 38), fasting glucose (N = 71), and HbA1c (N = 75) at the genome-wide significance were selected as instrument variables. Genetic associations with testosterone levels (total testosterone, TT, bioavailable testosterone, BT, and sex hormone-binding globulin, SHBG) were obtained from the UK Biobank studies and other large consortia. Two-sample MR analysis was used to minimize the bias caused by confounding factors and response causality. Multivariable MR analysis was performed using Body mass index (BMI), Triglycerides (TG), LDL cholesterol (LDL), and adiponectin to adjust for the effects of potential confounders. Results: Type 2 diabetes mellitus was associated with the decrease of total testosterone (b: -0.021,95%CI: -0.032, -0.010, p<0.001) and sex hormone binding globulin (b: -0.048,95%CI: -0.065, -0.031, p<0.001). In males, total testosterone (b: 0.058, 95% CI: 0.088, 0.028, p < 0.001) decreased. In females, it was associated with an increase in bioavailable testosterone (b: 0.077,95%CI: 0.058,0.096, p<0.001). Each unit (pmol/L) increase in fasting insulin was associated with 0.283nmol/L decrease in sex hormone-binding globulin (95% CI: -0.464, -0.102, p=0.002) and 0.260nmol/L increase in bioavailable testosterone (95%CI: -0.464, -0.102, p= 0.002). In males, sex hormone binding globulin decreased by 0.507nmol/L (95%CI: -0.960, -0.054, p= 0.028) and bioavailable testosterone increased by 0.216nmol/L (95%CI: 0.087,0.344, p= 0.001). In females, sex hormone binding globulin decreased by 0.714 nmol/L (95%CI: -1.093, -0.335, p<0.001) and bioavailable testosterone increased by 0.467nmol/L (95%CI: 0.286,0.648, p<0.001). Each unit (%) increase in HbA1c was associated with 0.060nmol/L decrease in sex hormone-binding globulin (95%CI: -0.113, -0.007, p= 0.026). In males, total testosterone decreased by 0.171nmol/L (95%CI: -0.288, -0.053, p=0.005) and sex hormone binding globulin decreased by 0.206nmol/L (95%CI: -0.340, -0.072, p=0.003). Total testosterone increased by 0.122nmol/L (95%CI: 0.012,0.233, p=0.029) and bioavailable testosterone increased by 0.163nmol/L (95%CI: 0.042,0.285, p=0.008) in females. Conclusions: Using MR Analysis, we found independent effects of type 2 diabetes, fasting insulin, and HbA1c on total testosterone and sex hormonebinding globulin after maximum exclusion of the effects of obesity, BMI, TG, LDL and Adiponectin. [ABSTRACT FROM AUTHOR]

Context: Statins and possibly other lipid modifiers increase type 2 diabetes risk and body mass index (BMI). However, to what extent BMI mediates the diabetogenic effects of lipid modifiers remains unclear. Objective: We used Mendelian randomization (MR) to investigate the effects of commonly used lipid modifiers on type 2 diabetes risk and glycemic traits, and any mediation by BMI. Methods: Using established genetic variants to mimic commonly used lipid modifiers (ie, statins, PCSK9 inhibitors, and ezetimibe), we assessed their associations with type 2 diabetes risk, glycated hemoglobin (HbA1c), fasting insulin, fasting glucose, and BMI in the largest relevant genome-wide association studies (GWAS) in people of European ancestry, and where possible, in East Asians. We used multivariable MR to examine the role of lipid modifiers independent of BMI. Results: Genetically mimicked effects of statins and ezetimibe, but not PCSK9 inhibitors were associated with higher risk of type 2 diabetes (odds ratio [OR] 1.74 [95% CI, 1.49 to 2.03]; 1.92 [1.22 to 3.02]; 1.06 [0.87 to 1.29] per SD reduction in low-density lipoprotein (LDL)-cholesterol). Of these lipid modifiers, only genetic mimics of statins were associated with higher BMI (0.33 SD [0.29 to 0.38] per SD reduction in LDL-cholesterol), which explained 54% of the total effect of statins on type 2 diabetes risk. Conclusion: Higher BMI mediated more than half of the diabetogenic effects of statins, which did not extend to other commonly used lipid modifiers. Further investigations are needed to clarify drug-specific mechanisms underlying the effects of lipid modifiers on type 2 diabetes. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Objective: To assess the causal associations of plasma levels of metabolites with type 2 diabetes mellitus (T2DM) and glycemic traits.Methods: Two-sample mendelian randomization (MR) was conducted to assess the causal associations. Genetic variants strongly associated with metabolites at genome-wide significance level (P < 5 × 10-8) were selected from public genome-wide association studies, and single-nucleotide polymorphisms of outcomes were obtained from the Diabetes Genetics Replication and Meta-analysis consortium for T2DM and from the Meta-Analyses of Glucose and Insulin-related Traits Consortium for fasting glucose, insulin, and glycated hemoglobin (HbA1c). The Wald ratio and inverse-variance weighted methods were used for analyses, and MR-Egger was used for sensitivity analysis.Results: The β estimates per 1-SD increase of arachidonic acid (AA) level was 0.16 (95% CI, 0.078-0.242; P < 0.001). Genetic predisposition to higher plasma AA levels were associated with higher fasting glucose levels (β 0.10 [95% CI, 0.064-0.134], P < 0.001), higher HbA1c levels (β 0.04 [95% CI, 0.027-0.061]), and lower fasting insulin levels (β -0.025 [95% CI, -0.047 to -0.002], P = 0.033). Besides, 2-hydroxybutyric acid (2-HBA) might have a positive causal effect on glycemic traits.Conclusions: Our findings suggest that AA and 2-HBA may have causal associations on T2DM and glycemic traits. This is beneficial for clarifying the pathogenesis of T2DM, which would be valuable for early identification and prevention for T2DM. [ABSTRACT FROM AUTHOR]

Background: Observational studies have shown possible bidirectional association between type 2 diabetes (T2D) and pulmonary function, but the causality is not well defined. The purpose of this study is to investigate genetic correlation and causal relationship of T2D and glycemic traits with pulmonary function. Methods: By leveraging summary statistics from large-scale genome-wide association studies, linkage disequilibrium score regression was first implemented to quantify genetic correlations between T2D, glycemic traits, and several spirometry indices. Then both univariable and multivariable Mendelian randomization analyses along with multiple pleiotropy-robust methods were performed in two directions to assess the causal nature of these relationships. Results: Forced expiratory volume in 1 s (FEV1) and forced vital capacity (FVC) showed significant genetic correlations with T2D and fasting insulin levels and suggestive genetic correlations with fasting glucose and hemoglobin A1c. In Mendelian randomization analyses, genetically predicted higher FEV1 (OR = 0.77; 95% CI = 0.63, 0.94) and FVC (OR = 0.82; 95% CI = 0.68, 0.99) were significantly associated with lower risk of T2D. Conversely, genetic predisposition to higher risk of T2D exhibited strong association with reduced FEV1 (beta = −0.062; 95% CI = −0.100, −0.024) and FEV1 (beta = −0.088; 95% CI = −0.126, −0.050) and increased FEV1/FVC ratio (beta = 0.045; 95% CI = 0.012, 0.078). We also found a suggestive causal effect of fasting glucose on pulmonary function and of pulmonary function on fasting insulin and proinsulin. Conclusions: The present study provided supportive evidence for genetic correlation and bidirectional causal association between T2D and pulmonary function. Further studies are warranted to clarify possible mechanisms related to lung dysfunction and T2D, thus offering a new strategy for the management of the two comorbid diseases. [ABSTRACT FROM AUTHOR]

Purpose: Whether the association between fruit and type 2 diabetes (T2D) is modified by the genetic predisposition of T2D was yet elucidated. The current study is meant to examine the gene–dietary fruit intake interactions in the risk of T2D and related glycemic traits. Methods: We performed a cross-sectional study in 11,657 participants aged ≥ 40 years from a community-based population in Shanghai, China. Fruit intake information was collected by a validated food frequency questionnaire by asking the frequency of consumption of typical food items over the previous 12 months. T2D-genetic risk score (GRS) was constructed by 34 well established T2D common variants in East Asians. The risk of T2D, fasting, 2 h-postprandial plasma glucose, and glycated hemoglobin A1c associated with T2D-GRS and each individual single nucleotide polymorphisms (SNPs) were tested. Results: The risk of T2D associated with each 1-point of T2D-GRS was gradually decreased from the lower fruit intake level (< 1 times/week) [the odds ratio (OR) and 95% confidence interval (CI) was 1.10 (1.07–1.13)], to higher levels (1–3 and > 3 times/week) [the corresponding ORs and 95% CIs were 1.08 (1.05–1.10) and 1.07 (1.05–1.08); P for interaction = 0.04]. Analyses for associations with fasting, 2 h-postprandial plasma glucose and glycated hemoglobin A1c demonstrated consistent tendencies (all P for interaction ≤ 0.03). The inverse associations of fruit intake with risk of T2D and glucose traits were more prominent in the higher T2D-GRS tertile. Conclusions: Fruit intakes interact with the genetic predisposition of T2D on the risk of diabetes and related glucose metabolic traits. Fruit intake alleviates the association between genetic predisposition of T2D and the risk of diabetes; the association of fruit intake with a lower risk of diabetes was more prominent in population with a stronger genetic predisposition of T2D. [ABSTRACT FROM AUTHOR]

Purpose: Previous epidemiological evidence showed that type 2 diabetes (T2D) is related with gout. However, the causality and the direction of this association are still not definitely elucidated. We investigated bidirectional associations of T2D and glycemic traits with serum urate concentrations and gout using a Mendelian randomization approach.Methods: Summary statistics from the large-scale genomewide association studies conducted for T2D (Ncase = 62 892, Ncontrol = 596 424), fasting glucose (N = 133 010), fasting insulin (N = 133 010), hemoglobin A1c (N = 123 665), homeostasis model assessment of insulin resistance (N = 46 186), urate (N = 110 347), and gout (Ncase = 2115, Ncontrol = 67 259) among participants of European ancestry were analyzed. For each trait of interest, independent genomewide significant (P < 5 × 10-8) single nucleotide polymorphisms were selected as instrumental variables. The inverse-variance weighted method was used for the primary analyses.Results: Genetic predisposition to higher risk of T2D [beta = 0.042; 95% confidence interval (CI) = 0.016-0.068; P = 0.002] and higher levels of fasting insulin (beta = 0.756; 95% CI = 0.408-1.102; P = 1.96e-05) were significantly associated with increased serum urate concentrations. Moreover, we found suggestively significant evidence supporting a causal role of fasting insulin on risk of developing gout (odds ratio = 3.06; 95% CI = 0.88-10.61; P = 0.078). In the reverse direction analysis, genetic predisposition to both urate and gout were not associated with T2D or any of 4 glycemic traits being investigated.Conclusions: This study provides supportive evidence on causal associations of T2D and fasting insulin with serum urate concentrations and a suggestive association of fasting insulin with risk of gout. Future research is required to examine the underlying biological mechanisms on such relationships. [ABSTRACT FROM AUTHOR]

Purpose: Obesity is a heterogeneous condition and distinct adiposity subtypes may differentially affect type 2 diabetes risk. We assessed relations between genetically determined subtypes of adiposity and changes in glycemic traits in a dietary intervention trial. Methods: The four genetic subtypes of adiposity including waist–hip ratio-increase only (WHRonly+), body mass index-increase only (BMIonly+), WHR-increase and BMI-increase (BMI+WHR+), and WHR-decrease and BMI-increase (BMI+WHR−) were assessed by polygenetic scores (PGSs), calculated based on 159 single nucleotide polymorphisms related to BMI and/or WHR. We examined the associations between the four PGSs and changes in fasting glucose, insulin, β-cell function (HOMA-B) and insulin resistance (HOMA-IR) in 692 overweight participants (84% white Americans) who were randomly assigned to one of four weight-loss diets in a 2-year intervention trial. Results: Higher BMI+WHR−PGS was associated with a greater decrease in 2-year changes in waist circumference in white participants (P = 0.002). We also found significant interactions between WHRonly+PGS and dietary protein in 2-year changes in fasting glucose and HOMA-B (P = 0.0007 and < 0.0001, respectively). When consuming an average-protein diet, participants with higher WHRonly+PGS showed less increased fasting glucose (β = − 0.46, P = 0.006) and less reduction in HOMA-B (β = 0.02, P = 0.005) compared with lower WHRonly+PGS. Conversely, eating high-protein diet was associated with less decreased HOMA-B among individuals with lower than higher WHRonly+PGS (β = − 0.02, P = 0.006). Conclusions: Distinct genetically determined adiposity subtypes may differentially modify the effects of weight-loss diets on improving glucose metabolism in white Americans. This trial was registered at clinicaltrials.gov as NCT00072995. [ABSTRACT FROM AUTHOR]

Genetic variants associated with disease outcomes can be used to develop personalized treatment. To reach this precision medicine goal, hundreds of large‐scale genome‐wide association studies (GWAS) have been conducted in the past decade to search for promising genetic variants associated with various traits. They have successfully identified tens of thousands of disease‐related variants. However, in total these identified variants explain only part of the variation for most complex traits. There remain many genetic variants with small effect sizes to be discovered, which calls for the development of (a) GWAS with more samples and more comprehensively genotyped variants, for example, the NHLBI Trans‐Omics for Precision Medicine (TOPMed) Program is planning to conduct whole genome sequencing on over 100 000 individuals; and (b) novel and more powerful statistical analysis methods. The current dominating GWAS analysis approach is the "single trait" association test, despite the fact that many GWAS are conducted in deeply phenotyped cohorts including many correlated and well‐characterized outcomes, which can help improve the power to detect novel variants if properly analyzed, as suggested by increasing evidence that pleiotropy, where a genetic variant affects multiple traits, is the norm in genome‐phenome associations. We aim to develop pleiotropy informed powerful association test methods across multiple traits for GWAS. Since it is generally very hard to access individual‐level GWAS phenotype and genotype data for those existing GWAS, due to privacy concerns and various logistical considerations, we develop rigorous statistical methods for pleiotropy informed adaptive multitrait association test methods that need only summary association statistics publicly available from most GWAS. We first develop a pleiotropy test, which has powerful performance for truly pleiotropic variants but is sensitive to the pleiotropy assumption. We then develop a pleiotropy informed adaptive test that has robust and powerful performance under various genetic models. We develop accurate and efficient numerical algorithms to compute the analytical P‐value for the proposed adaptive test without the need of resampling or permutation. We illustrate the performance of proposed methods through application to joint association test of GWAS meta‐analysis summary data for several glycemic traits. Our proposed adaptive test identified several novel loci missed by individual trait based GWAS meta‐analysis. All the proposed methods are implemented in a publicly available R package. [ABSTRACT FROM AUTHOR]

Background: Seasonal variation in glucose metabolism might be driven by changes in daylight. Melatonin entrains circadian regulation and is directly associated with daylight. The relationship between melatonin receptor 1B gene variants with glycemic traits and type 2 diabetes is well established. We studied if daylight length was associated with glycemic traits and if it modified the relationship between melatonin receptor 1B gene rs10830963 variant and glycemic traits. Materials: A population-based sample of 3422 18–78-year-old individuals without diabetes underwent an oral glucose tolerance test twice, an average 6.8 years (SD = 0.9) apart and were genotyped for rs10830963. Daylight data was obtained from the Finnish Meteorological Institute. Results: Cross-sectionally, more daylight was associated with lower fasting glucose, but worse insulin sensitivity and secretion at follow-up. Longitudinally, individuals studied on lighter days at follow-up than at baseline showed higher glucose values during the oral glucose tolerance test and lower Corrected Insulin Response at follow-up. GG genotype carriers in the rs10830963 became more insulin resistant during follow-up if daylight length was shorter at follow-up than at baseline. Conclusions: Our study shows that individual glycemic profiles may vary according to daylight, MTNR1B genotype and their interaction. Future studies may consider taking daylight length into account. In Western Finland, the amount daylight follows an extensive annual variation ranging from 4 h 44 min to 20 h 17 min, making it ideal to study the associations between daylight and glycemic traits. Moreover, this allows researchers to explore if the relationship between the melatonin receptor 1B gene rs10830963 variant and glycemic traits is modified by the amount of daylight both cross-sectionally and longitudinally. This study shows that individuals, who participated in the study on lighter days at the follow-up than at the baseline, displayed to a greater extent worse glycemic profiles across the follow-up. Novel findings from the current study show that in the longitudinal analyses, each addition of the minor G allele of the melatonin receptor 1B gene rs10830963 was associated with worsening of fasting glucose values and insulin secretion across the 6.8-year follow-up. Importantly, this study shows that in those with the rs10830963 GG genotype, insulin sensitivity deteriorated the most significantly across the 6.8-year follow-up if the daylight length on the oral glucose tolerance testing date at the follow-up was shorter than at the baseline. Taken together, the current findings suggest that the amount of daylight may affect glycemic traits, especially fasting glucose and insulin secretion even though the effect size is small. The association can very according to the rs10830963 risk variant. Further research is needed to elucidate the mechanisms behind these associations. [ABSTRACT FROM AUTHOR]

Background: Coffee consumption has been associated with glucose metabolism and risk of type 2 diabetes. Objective: We examined whether the genetic variation determining habitual coffee consumption affected glycemic changes in response to weight-loss dietary intervention. Design: A genetic risk score (GRS) was calculated based on 8 habitual coffee consumption-associated single nucleotide polymorphisms. We used general linear models to test changes in glycemic traits in groups randomly assigned to high- and low-fat diets according to tertiles of the GRS. Results: We observed significant interactions between the GRS and low compared with high dietary fat intake on 6-mo changes in fasting insulin and homeostasis model assessment of insulin resistance (HOMA-IR) (P-interaction = 0.023 and 0.022, respectively), adjusting for age, sex, race, physical activity, smoking, alcohol, seasonal variation, and baseline values of the respective outcomes. Participants with a higher GRS of habitual coffee consumption showed a greater reduction in fasting insulin and a marginally greater decrease in HOMA-IR in the low-fat diet intervention group. Conclusions: Our data suggest that participants with genetically determined high coffee consumption may benefit more by eating a low-fat diet in improving fasting insulin and HOMA-IR in a short term. This trial was registered at clinicaltrials.gov as NCT00072995 and NCT03258203. [ABSTRACT FROM AUTHOR]

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