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An understanding of the molecular mechanism whereby an environmental chemical causes a disease is important for the purposes of future applications. In this study, a multiomics workflow was designed to combine several publicly available datasets in order to identify CpG sites and genes that mediate the impact of exposure to environmental chemicals on cardiometabolic traits. Organophosphate and prenatal lead exposure were previously reported to change methylation level at the cg23627948 site. The outcome of the analyses conducted in this study revealed that, as the cg23627948 site becomes methylated, the expression of the GNA12 gene decreases, which leads to a higher body fat percentage. Prenatal perfluorooctane sulfonate exposure was reported to increase the methylation level at the cg21153102 site. Findings of this study revealed that higher methylation at this site contributes to higher diastolic blood pressure by changing the expression of CHP1 and GCHFR genes. Moreover, HKR1 mediates the impact of B12 supplementation → cg05280698 hypermethylation on higher kidney function, while CTDNEP1 mediates the impact of air pollution → cg03186999 hypomethylation on higher systolic blood pressure. This study investigates CpG sites and genes that mediate the impact of environmental chemicals on cardiometabolic traits. Furthermore, the multiomics approach described in this study provides a convenient workflow with which to investigate the impact of an environmental factor on the body's biomarkers, and, consequently, on health conditions, using publicly available data. [ABSTRACT FROM AUTHOR]

Dyslipidemia is one of the cardiometabolic risk factors that influences mortality globally. Unraveling the causality between blood lipids and metabolites and the complex networks connecting lipids, metabolites, and other cardiometabolic traits can help to more accurately reflect the body’s metabolic disorders and even cardiometabolic diseases. We conducted targeted metabolomics of 248 metabolites in 437 twins from the Chinese National Twin Registry. Inference about Causation through Examination of FAmiliaL CONfounding (ICE FALCON) analysis was used for causal inference between metabolites and lipid parameters. Bidirectional mediation analysis was performed to explore the linkages between blood lipids, metabolites, and other seven cardiometabolic traits. We identified 44, 1, and 31 metabolites associated with triglyceride (TG), total cholesterol (TC), and high-density lipoprotein-cholesterol (HDL-C), most of which were gut microbiota-derived metabolites. There were 9, 1, and 14 metabolites that showed novel associations with TG, TC, and HDL-C, respectively. ICE FALCON analysis found that TG and HDL-C may have a predicted causal effect on 23 and six metabolites, respectively, and one metabolite may have a predicted causal effect on TG. Mediation analysis discovered 14 linkages connecting blood lipids, metabolites, and other cardiometabolic traits. Our study highlights the significance of gut microbiota-derived metabolites in lipid metabolism. Most of the identified cross-sectional associations may be due to the lipids having a predicted causal effect on metabolites, but not vice versa, nor are they due to family confounding. These findings shed new light on lipid metabolism and personalized management of cardiometabolic diseases.

Abstract Patients with type 1 diabetes (T1D) have a greater risk of cardiovascular disease. Proconvertase subtilisin-kexin 9 (PCSK9) is involved in the atherosclerosis process. This study aimed to determine the relationship between PCSK9 levels and epicardial adipose tissue (EAT) volume and cardiometabolic variables in patients with T1D. This was an observational cross-sectional study including 73 patients with T1D. Clinical, biochemical and imaging data were collected. We divided the patients into two groups according to their glycemic control and the EAT index (iEAT) percentile. We performed a correlation analysis between the collected variables and PCSK9 levels; subsequently, we performed a multiple regression analysis with the significant parameters. The mean age was 47.6 ± 8.5 years, 58.9% were men, and the BMI was 26.9 ± 4.6 kg/m2. A total of 31.5%, 49.3% and 34.2% of patients had hypertension, dyslipidemia and smoking habit, respectively. The PCSK9 concentration was 0.37 ± 0.12 mg/L, which was greater in patients with worse glycemic control (HbA1c > 7.5%), dyslipidemia and high EAT volume (iEAT > 75th percentile). The PCSK9 concentration was positively correlated with age (r = 0.259; p = 0.027), HbA1c (r = 0.300; p = 0.011), insulin dose (r = 0.275; p = 0.020), VLDL-C level (r = 0.331; p = 0.004), TG level (r = 0.328; p = 0.005), and iEAT (r = 0.438; p

Patients with type 1 diabetes (T1D) have a greater risk of cardiovascular disease. Proconvertase subtilisin-kexin 9 (PCSK9) is involved in the atherosclerosis process. This study aimed to determine the relationship between PCSK9 levels and epicardial adipose tissue (EAT) volume and cardiometabolic variables in patients with T1D. This was an observational cross-sectional study including 73 patients with T1D. Clinical, biochemical and imaging data were collected. We divided the patients into two groups according to their glycemic control and the EAT index (iEAT) percentile. We performed a correlation analysis between the collected variables and PCSK9 levels; subsequently, we performed a multiple regression analysis with the significant parameters. The mean age was 47.6 ± 8.5 years, 58.9% were men, and the BMI was 26.9 ± 4.6 kg/m2. A total of 31.5%, 49.3% and 34.2% of patients had hypertension, dyslipidemia and smoking habit, respectively. The PCSK9 concentration was 0.37 ± 0.12 mg/L, which was greater in patients with worse glycemic control (HbA1c > 7.5%), dyslipidemia and high EAT volume (iEAT > 75th percentile). The PCSK9 concentration was positively correlated with age (r = 0.259; p = 0.027), HbA1c (r = 0.300; p = 0.011), insulin dose (r = 0.275; p = 0.020), VLDL-C level (r = 0.331; p = 0.004), TG level (r = 0.328; p = 0.005), and iEAT (r = 0.438; p < 0.001). Multiple regression analysis revealed that 25% of the PCSK9 variability was explained by iEAT and HbA1c (p < 0.05). The PCSK9 concentration is associated with metabolic syndrome parameters, poor glycemic control and increased EAT volume in patients with T1D. [ABSTRACT FROM AUTHOR]

BackgroundBoth diabetic kidney disease (DKD) and chronic kidney disease (CKD) are more prevalent among individuals with lower levels of education in observational studies. To quantify the mediation effect of recognized cardiometabolic traits, we obtain causal estimates between education and DKD as well as CKD.Materials and methodsWe assessed the causal effect of education on DKD and CKD, separately estimated the causal effect of 26 cardiometabolic traits on DKD and CKD, and finally calculated the mediating effects and mediating proportions of each using two-step, two-sample multivariable Mendelian randomization (MVMR). Furthermore, the genetic association between exposure, mediators, and outcomes was investigated using linkage disequilibrium score (LDSC) regression analysis. Expression quantitative trait loci (eQTL) were retrieved from the Genotype-Tissue Expression Project (GTEx) v8 to serve as genetic instrumental variables. Transcriptome-wide association studies (TWAS), Bayesian colocalization analysis, and Summary-data-based Mendelian Randomization (SMR) analysis were performed to explore underlying susceptibility genes between education, mediators, and kidney diseases.ResultsHigher education with a genetically predicted 1-SD (4.2 years) was linked to a 48.64% decreased risk of DKD and a 29.08% decreased risk of CKD. After extensive evaluation of 26 cardiometabolic traits, 7 and 6 causal mediators were identified as mediating the effects of education on DKD and CKD, respectively. The largest mediating factor between education and DKD was BMI, which was followed by WHR, T2D, fasting insulin, SBP, fasting glucose, and DBP. In contrast, candidate mediators in the education-to-CKD pathway included BMI, followed by cigarettes smoked per day, WHR, SBP, T2D, and DBP. MR analysis revealed that TP53INP1 was found to be a shared susceptibility gene for cardiometabolic traits and DKD, while L3MBTL3 was found to be a shared susceptibility gene for cardiometabolic traits and CKD.ConclusionOur findings provide solid evidence that education has a causally protective effect on the development of DKD and CKD. We additionally reveal significant directions for intervention on cardiometabolic traits that mitigate the negative effects of educational inequities on the onset of DKD and CKD. Our work demonstrates a shared genetic basis between education, cardiometabolic traits, and kidney diseases. Future research aiming at lowering kidney risk may benefit from these findings.

Searching for positive selection signals across genomes has identified functional genetic variants responding to environmental change. In Native Americans of Mexico, we used the fixation index (Fst) and population branch statistic (PBS) to identify SNPs suggesting positive selection. The 103 most differentiated SNPs were tested for associations with metabolic traits, the most significant association was FADS2/rs174616 with body mass index (BMI). This variant lies within a linkage disequilibrium (LD) block independent of previously reported FADS selection signals and has not been clearly associated with metabolic phenotypes. We tested this variant in two independent cohorts with cardiometabolic data. In the Genetics of Atherosclerotic Disease (GEA) cohort, the derived allele (T) was associated with increased BMI, lower LDL-C levels and a decreased risk of subclinical atherosclerosis in women. Significant gene-diet interactions affected lipid, apolipoprotein and adiponectin levels with differences according to sex, involving mainly total and complex dietary carbohydrate%. In the Genotype-related Effects of PUFA trial, the derived allele was associated with lower Δ-6 desaturase activity and erythrocyte membrane dihomo-gamma-linolenic acid (DGLA) levels, and with increased Δ-5 desaturase activity and eicosapentaenoic acid levels. This variant interacted with dietary carbohydrate% affecting Δ-6 desaturase activity. Notably, the relationship of DGLA and other erythrocyte membrane LC-PUFA indices with HOMA-IR differed according to rs174616 genotype, which has implications regarding how these indices should be interpreted. In conclusion, this observational study identified rs174616 as a signal suggesting selection in an independent linkage disequilibrium block, was associated with cardiometabolic and erythrocyte measurements of LC-PUFA in two independent Mexican cohorts and showed significant gene-diet interactions.

Individuals with schizophrenia (SCZ) have, on average, a 10- to 20-year shorter expected life span than the rest of the population, primarily due to cardiovascular disease comorbidity. Genome-wide association studies (GWAS) have previously been used to separately identify common variants in SCZ and cardiometabolic traits. However, genetic variants jointly influencing both traits remain to be fully characterised. To assess overlaps (if any) between the genetic architecture of SCZ and cardiometabolic traits, we used conditional false discovery rate (FDR) and local genetic correlation statistical framework analyses. A conjunctional FDR was used to identify shared genetic traits between SCZ and cardiometabolic risk factors. We identified 144 genetic variants which were shared between SCZ and body mass index (BMI), and 15 variants shared between SCZ and triglycerides (TG). Furthermore, we discovered four novel single nucleotide polymorphisms (SNPs) (rs3865350, rs9860913, rs13307 and rs9614186) and four proximate genes (DERL2, SNX4, LY75 and EFCAB6) which were shared by SCZ and BMI. We observed that the novel genetic variant rs13307 and the most proximate gene LY75 exerted potential effects on SCZ and BMI comorbidity. Also, we observed a mixture of concordant and opposite direction associations with shared genetic variants. We demonstrated a moderate to high genetic overlap between SCZ and cardiometabolic traits associated with a pattern of bidirectional associations. Our data suggested a complex interplay between metabolism-related gene pathways in SCZ pathophysiology.

Objective: To evaluate the causal relationship between childhood body-mass index (BMI) at different ages and adult cardiometabolic traits. Methods: We retrieved genetic instrument variables (IVs) for exposures (standardized BMI at newborn, infant, toddler and late childhood), cardiometabolic traits and potential confounders or mediators (adult BMI, SHBG, testosterone and age at menarche) from the corresponding genomewide association analysis. We performed univariate and multivariable Mendelian randomization (MR) to dissect associations between age-specific childhood BMI and adult cardiometabolic outcomes. Odds ratio was used to present the direction of the causal association. Results: In univariate MR, higher newborn BMI was causally associated with reduced risk for type 2 diabetes in women. Late childhood BMI was associated with increased risk for female diabetes and coronary artery disease (CAD), myocardial infarction (MI), and chronic kidney disease (CKD) in general population. Among these associations, only association between late childhood BMI with MI remained significant after adjusting for adult male BMI and sex hormones, (OR = 1.120, 95% CI 1.023-1.226, p = 0.014). Besides, in multivariable MR, we found evidence for causal association between newborn BMI with reduced risk for CAD (OR = 0.862, 95% CI 0.751-0.989, p = 0.034) and MI (OR = 0.864, 95% CI 0.752-0.991, p = 0.037) in men. No obvious impact of infant or toddler BMI was identified on the above-mentioned diseases. For continuous cardiometabolic traits, in all age epochs except infant, higher BMI was associated with increased level of fasting glucose in women. Conclusion: BMI at birth and late childhood exerts different impact on adult cardiometabolic diseases, while BMI at infant and toddler ages is not causally associated with these outcomes. The effect of childhood BMI may be influenced by sex disparities. [ABSTRACT FROM AUTHOR]

Abstract Background It is unclear to what extent genetics explain the familial clustering and the co-occurrence of distinct cardiometabolic disorders in the general population. We therefore aimed to quantify the familial (co-)aggregation of various cardiometabolic disorders and to estimate the heritability of cardiometabolic traits and their genetic correlations using the large, multi-generational Lifelines Cohort Study. Methods We used baseline data of 162,416 participants from Lifelines. Cardiometabolic disorders including type 2 diabetes (T2D), cardiovascular diseases, hypertension, obesity, hypercholesterolemia, and metabolic syndrome (MetS), were defined in adult participants. Fifteen additional cardiometabolic traits indexing obesity, blood pressure, inflammation, glucose regulation, and lipid levels were measured in all included participants. Recurrence risk ratios (λR) for first-degree relatives (FDR) indexed familial (co-)aggregation of cardiometabolic disorders using modified conditional Cox proportional hazards models and were compared to those of spouses. Heritability (h2), shared environment, and genetic correlation (rg) were estimated using restricted maximum likelihood variance decomposition methods, adjusted for age, age2, and sex. Results Individuals with a first-degree relative with a cardiometabolic disorder had a higher risk of the same disorder, ranging from λFDR of 1.23 (95% CI 1.20–1.25) for hypertension to λFDR of 2.48 (95% CI 2.15–2.86) for T2D. Most of these were higher than in spouses (λSpouses

BackgroundIdentification of genetic risk factors that are shared between Alzheimer's disease (AD) and other traits, i.e., pleiotropy, can help improve our understanding of the etiology of AD and potentially detect new therapeutic targets. Previous epidemiological correlations observed between cardiometabolic traits and AD led us to assess the pleiotropy between these traits.MethodsWe performed a set of bivariate genome-wide association studies coupled with colocalization analysis to identify loci that are shared between AD and eleven cardiometabolic traits. For each of these loci, we performed colocalization with Genotype-Tissue Expression (GTEx) project expression quantitative trait loci (eQTL) to identify candidate causal genes.ResultsWe identified three previously unreported pleiotropic trait associations at known AD loci as well as four novel pleiotropic loci. One associated locus was tagged by a low-frequency coding variant in the gene DOCK4 and is potentially implicated in its alternative splicing. Colocalization with GTEx eQTL data identified additional candidate genes for the loci we detected, including ACE, the target of the hypertensive drug class of ACE inhibitors. We found that the allele associated with decreased ACE expression in brain tissue was also associated with increased risk of AD, providing human genetic evidence of a potential increase in AD risk from use of an established anti-hypertensive therapeutic.ConclusionOur results support a complex genetic relationship between AD and these cardiometabolic traits, and the candidate causal genes identified suggest that blood pressure and immune response play a role in the pleiotropy between these traits.

An understanding of the molecular mechanism whereby an environmental chemical causes a disease is important for the purposes of future applications. In this study, a multiomics workflow was designed to combine several publicly available datasets in order to identify CpG sites and genes that mediate the impact of exposure to environmental chemicals on cardiometabolic traits. Organophosphate and prenatal lead exposure were previously reported to change methylation level at the cg23627948 site. The outcome of the analyses conducted in this study revealed that, as the cg23627948 site becomes methylated, the expression of the GNA12 gene decreases, which leads to a higher body fat percentage. Prenatal perfluorooctane sulfonate exposure was reported to increase the methylation level at the cg21153102 site. Findings of this study revealed that higher methylation at this site contributes to higher diastolic blood pressure by changing the expression of CHP1 and GCHFR genes. Moreover, HKR1 mediates the impact of B12 supplementation → cg05280698 hypermethylation on higher kidney function, while CTDNEP1 mediates the impact of air pollution → cg03186999 hypomethylation on higher systolic blood pressure. This study investigates CpG sites and genes that mediate the impact of environmental chemicals on cardiometabolic traits. Furthermore, the multiomics approach described in this study provides a convenient workflow with which to investigate the impact of an environmental factor on the body’s biomarkers, and, consequently, on health conditions, using publicly available data.

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

Background: It is unclear to what extent genetics explain the familial clustering and the co-occurrence of distinct cardiometabolic disorders in the general population. We therefore aimed to quantify the familial (co-)aggregation of various cardiometabolic disorders and to estimate the heritability of cardiometabolic traits and their genetic correlations using the large, multi-generational Lifelines Cohort Study. Methods: We used baseline data of 162,416 participants from Lifelines. Cardiometabolic disorders including type 2 diabetes (T2D), cardiovascular diseases, hypertension, obesity, hypercholesterolemia, and metabolic syndrome (MetS), were defined in adult participants. Fifteen additional cardiometabolic traits indexing obesity, blood pressure, inflammation, glucose regulation, and lipid levels were measured in all included participants. Recurrence risk ratios (λR) for first-degree relatives (FDR) indexed familial (co-)aggregation of cardiometabolic disorders using modified conditional Cox proportional hazards models and were compared to those of spouses. Heritability (h2), shared environment, and genetic correlation (rg) were estimated using restricted maximum likelihood variance decomposition methods, adjusted for age, age2, and sex. Results: Individuals with a first-degree relative with a cardiometabolic disorder had a higher risk of the same disorder, ranging from λFDR of 1.23 (95% CI 1.20–1.25) for hypertension to λFDR of 2.48 (95% CI 2.15–2.86) for T2D. Most of these were higher than in spouses (λSpouses < λFDR), except for obesity which was slightly higher in spouses. We found moderate heritability for cardiometabolic traits (from h2CRP: 0.26 to h2HDL: 0.50). Cardiometabolic disorders showed positive familial co-aggregation, particularly between T2D, MetS, and obesity (from λFDR obesity-MetS: 1.28 (95% CI 1.24–1.32) to λFDR MetS-T2D: 1.61 (95% CI 1.52–1.70)), consistent with the genetic correlations between continuous intermediate traits (ranging from rg HDL-Triglycerides: − 0.53 to rg LDL-Apolipoprotein B: 0.94). Conclusions: There is positive familial (co-)aggregation of cardiometabolic disorder, moderate heritability of intermediate traits, and moderate genetic correlations between traits. These results indicate that shared genetics and common genetic architecture contribute to cardiometabolic disease. [ABSTRACT FROM AUTHOR]

Understanding the epigenome paths through which smoking contributes to cardiometabolic traits is important for downstream applications. In this study, an SNP-based analytical pipeline was used to integrate several publicly available datasets in order to identify CpG sites that mediate the impact of smoking on cardiometabolic traits and to investigate the underlying molecular mechanisms. After applying stringent statistical criteria, 11 CpG sites were detected that showed significant association (p < 5 × 10−8) with cardiometabolic traits at both the discovery and replication stages. By integrating eQTL data, I found genes behind a number of these associations. cg05228408 was hypomethylated in smokers and contributed to higher blood pressure by lowering the expression of the CLCN6 gene. cg08639339 was hypermethylated in smokers and lowered the metabolic rate by increasing the expression of RAB29; furthermore, I noted TMEM120A mediated the impact of smoking-cg17325771 on LDL, and LTBP3 mediated the smoking-cg07029024 effect on heart rate. The pathway analysis identified processes through which the identified genes impact their traits. This study provides a list of CpG sites that mediates the impact of smoking on cardiometabolic traits and a framework to investigate the underlying molecular paths using publicly available data. [ABSTRACT FROM AUTHOR]

Zinc (Zn) participates as a cofactor for many enzymes in the cellular metabolism, and its serum levels have been associated with different metabolic diseases, especially obesity (OB). Nevertheless, its associations are not clear in the children population. The objective of this study is to evaluate the association between serum Zn levels (SZn) with overweight/obesity status (OW/OB), as well as its cardiometabolic traits in a population of children in Mexico City. Anthropometrical data (body mass index z score (BMIz)), demographic variables (age and sex), and cardiometabolic traits (total cholesterol (TC), high-density lipoprotein cholesterol (HDLc), low-density lipoprotein cholesterol (LDLc), triglycerides (TG), fasting plasma glucose (FPG), and insulin) were analyzed in this cross-sectional study. SZn were measured by inductively coupled plasma mass spectrometry (ICP–MS). The population included 210 children from Mexico City (girls (n = 105) and boys (n = 105)) between ages 6 and 10 years. Normal-weight (NW) schoolchildren had higher SZn concentrations (66 µg/dL; IQR: 48 to 91) compared to OW or OB schoolchildren (61 µg/dL; IQR: 45 to 76). The data showed a significant negative association between SZn and BMIz without sex exclusion (r = − 0.181 and p = 0.009). The boy's population did not show an association between the SZn and BMIz compared to the girl's population which showed a significant negative association (r = − 0.277 and p = 0.004). In addition, other associations were found between SZn and TC (boys (r = 0.214 and p = 0.025), LDLc (boys (r = 0.213 and p = 0.029), and TG (girls (r = − 0.260 and p = 0.007)). Moreover, 38.6% of the total children in our population study had Zn deficiency (ZnD). NW schoolchildren had higher SZn concentrations compared to OW or OB schoolchildren. A diet low in Zn can be a factor to evaluate in the development of childhood OB in Mexico. However, further studies need to be performed on the children Mexican population to replicate and confirm our findings. [ABSTRACT FROM AUTHOR]

The contribution of genome structural variation (SV) to quantitative traits associated with cardiometabolic diseases remains largely unknown. Here, we present the results of a study examining genetic association between SVs and cardiometabolic traits in the Finnish population. We used sensitive methods to identify and genotype 129,166 high-confidence SVs from deep whole-genome sequencing (WGS) data of 4,848 individuals. We tested the 64,572 common and low-frequency SVs for association with 116 quantitative traits and tested candidate associations using exome sequencing and array genotype data from an additional 15,205 individuals. We discovered 31 genome-wide significant associations at 15 loci, including 2 loci at which SVs have strong phenotypic effects: (1) a deletion of the ALB promoter that is greatly enriched in the Finnish population and causes decreased serum albumin level in carriers (p = 1.47 × 10-54) and is also associated with increased levels of total cholesterol (p = 1.22 × 10-28) and 14 additional cholesterol-related traits, and (2) a multi-allelic copy number variant (CNV) at PDPR that is strongly associated with pyruvate (p = 4.81 × 10-21) and alanine (p = 6.14 × 10-12) levels and resides within a structurally complex genomic region that has accumulated many rearrangements over evolutionary time. We also confirmed six previously reported associations, including five led by stronger signals in single nucleotide variants (SNVs) and one linking recurrent HP gene deletion and cholesterol levels (p = 6.24 × 10-10), which was also found to be strongly associated with increased glycoprotein level (p = 3.53 × 10-35). Our study confirms that integrating SVs in trait-mapping studies will expand our knowledge of genetic factors underlying disease risk.

The vitamin D receptor (VDR) is vital for maintaining calcium and phosphate balance and regulating bone metabolism. Recent research has suggested that VDR also plays an essential role in metabolic diseases. Previous studies on non-Hispanic whites have shown that VDR single nucleotide polymorphisms (SNP) are associated with cardiometabolic phenotypes. However, the association between VDR SNPs and cardiometabolic traits in Hispanics remains unclear. This study investigated the association between VDR SNPs and cardiometabolic phenotypic data in self-reported Hispanics (n = 1610) from the Arizona Insulin Resistance registry and Sangre Por Salud Biobank. The study population was predominantly female (66.4%) with a mean age of 40 ± 14 years (n = 121 <18 years) and an average body mass index (BMI) of 29.8 ± 6.3 kg/m2. We performed a genotyping association analysis of VDR SNPs (Taq1-rs731236, Fok1-rs2228570 and Apa1-rs7975232) with cardiometabolic traits using linear regression models. The results showed that Taq1 and Apa1 were strongly associated with systolic blood pressure (SBP) in children (<18 years), while Fok1 was associated with measures of adiposity, including fat mass, waist circumference, and BMI. In age-stratified adult (≥18 years) models, Taq1 was strongly associated with hemoglobin A1c, while Apa1 was associated with BMI and fasting glucose. Fok1 had no significant associations in the adult models. In conclusion, the VDR SNPs were associated with several cardiometabolic phenotypes in this Hispanic sample, but the type and strength of the associations varied by age group. [ABSTRACT FROM AUTHOR]

Abstract Individuals with schizophrenia (SCZ) have, on average, a 10- to 20-year shorter expected life span than the rest of the population, primarily due to cardiovascular disease comorbidity. Genome-wide association studies (GWAS) have previously been used to separately identify common variants in SCZ and cardiometabolic traits. However, genetic variants jointly influencing both traits remain to be fully characterised. To assess overlaps (if any) between the genetic architecture of SCZ and cardiometabolic traits, we used conditional false discovery rate (FDR) and local genetic correlation statistical framework analyses. A conjunctional FDR was used to identify shared genetic traits between SCZ and cardiometabolic risk factors. We identified 144 genetic variants which were shared between SCZ and body mass index (BMI), and 15 variants shared between SCZ and triglycerides (TG). Furthermore, we discovered four novel single nucleotide polymorphisms (SNPs) (rs3865350, rs9860913, rs13307 and rs9614186) and four proximate genes (DERL2, SNX4, LY75 and EFCAB6) which were shared by SCZ and BMI. We observed that the novel genetic variant rs13307 and the most proximate gene LY75 exerted potential effects on SCZ and BMI comorbidity. Also, we observed a mixture of concordant and opposite direction associations with shared genetic variants. We demonstrated a moderate to high genetic overlap between SCZ and cardiometabolic traits associated with a pattern of bidirectional associations. Our data suggested a complex interplay between metabolism-related gene pathways in SCZ pathophysiology.

Background: Individuals with a diagnosis of schizophrenia are known to be at high risk of premature mortality due to poor physical health, especially cardiovascular disease, diabetes, and obesity. The reasons for these physical health outcomes within this patient population are complex. Despite well-documented cardiometabolic adverse effects of certain antipsychotic drugs and lifestyle factors, schizophrenia may have an independent effect.Aims: To investigate if there is evidence that schizophrenia is causally related to cardiometabolic traits (blood lipids, anthropometric traits, glycaemic traits, blood pressure) and vice versa using bi-directional two-sample Mendelian randomization (MR) analysis.Methods: We used 185 genetic variants associated with schizophrenia from the latest Psychiatric Genomics Consortium GWAS (n = 130,644) in the forward analysis (schizophrenia to cardiometabolic traits) and genetic variants associated with the cardiometabolic traits from various consortia in the reverse analysis (cardiometabolic traits to schizophrenia), both at genome-wide significance (5 × 10−8). The primary method was inverse-variance weighted MR, supported by supplementary methods such as MR-Egger, as well as median and mode-based methods.Results: In the forward analysis, schizophrenia was associated with slightly higher low-density lipoprotein (LDL) cholesterol levels (0.013 SD change in LDL per log odds increase in schizophrenia risk, 95% CI, 0.001–0.024 SD; p = 0.027) and total cholesterol levels (0.013 SD change in total cholesterol per log odds increase in schizophrenia risk, 95% CI, 0.002–0.025 SD; p = 0.023). However, these associations did not survive multiple testing corrections. There was no evidence of a causal effect of cardiometabolic traits on schizophrenia in the reverse analysis.Discussion: Dyslipidemia and obesity in schizophrenia patients are unlikely to be driven primarily by schizophrenia itself. Therefore, lifestyle, diet, antipsychotic drugs side effects, as well as shared mechanisms for metabolic dysfunction and schizophrenia such as low-grade systemic inflammation could be possible reasons for the apparent increased risk of metabolic disease in people with schizophrenia. Further research is needed to examine the shared immune mechanism hypothesis.

Objective: Present shift work has been associated with chronic disease. But influence of past shift work has not been established. This study is designed to investigate whether shift work in the past is associated with chronic kidney disease (CKD) in retired workers, and whether cardiometabolic traits affect the relationship. Methods: Overall, 15,775 retired workers (aged 62.3 ± 7.2 years) without CKD at baseline in the Dongfeng–Tongji cohort were included. Duration of past shift work was obtained through questionnaires, and divided into < 10.0, 10.0–20.0, and ≥ 20.0 years. CKD was diagnosed if individual's estimated glomerular filtration rate (eGFR) < 60 mL/min/1.73 m2. Logistic regression model was used to estimate the association between past shift work and CKD. Mediation analysis was conducted to analyze the mediating effects of cardiometabolic traits. Results: During the median follow-up of 4.7 years, 1072 (6.8%) incident CKD cases were recorded. Retired workers with past shift work had elevated CKD risk [ORs and 95% CIs for those with < 10.0, 10.0–20.0, and ≥ 20.0 years of past shift work were 1.61 (1.30, 2.00), 0.90 (0.72, 1.12), and 1.33 (1.11, 1.61)]. The associations were more evident among participants with poor or terrible sleep quality (P for interaction, 0.022). Mediation analysis showed that cardiometabolic traits including diastolic blood pressure and high density lipoprotein cholesterol mediated 7.02% and 10.05% of the relationship from past shift work to higher CKD risk. Conclusions: Past shift work was related with increased risk of incident CKD among retired workers, and this relationship was partly mediated by cardiometabolic traits. [ABSTRACT FROM AUTHOR]

Selenium (Se) is an essential trace element that by its antioxidant properties has been studied to elucidate its participation in the development of obesity and type 2 diabetes. We evaluated the association between cardiometabolic traits and serum Se levels in a sample of adults from southern Mexico. In 96 nondiabetic individuals, anthropometric data and clinical biochemistry measurements were analyzed. Serum total Se levels were measured with inductively coupled plasma mass spectrometry (ICP-MS). Serum Se level in the whole sample was 10.309 ± 3.031 μg mL−1 and no difference between the women and men was observed (p = 0.09). Additionally, fasting plasma glucose (FPG) was significantly associated with serum Se level (β = −0.07 ± 0.03, p = 0.02, analysis adjusted for age, sex and BMI). Furthermore, sex shows significant interaction with FPG on the serum Se levels (p = 0.01). A follow-up analysis revealed the particular association between FPG and Se levels in women (β = −0.10 ± 0.04, p = 0.01). In conclusion, our data evidenced a women-specific association between FPG and serum Se levels in a sample of adults from southern Mexico. [ABSTRACT FROM AUTHOR]

Dyslipidemia is one of the cardiometabolic risk factors that influences mortality globally. Unraveling the causality between blood lipids and metabolites and the complex networks connecting lipids, metabolites, and other cardiometabolic traits can help to more accurately reflect the body's metabolic disorders and even cardiometabolic diseases. We conducted targeted metabolomics of 248 metabolites in 437 twins from the Chinese National Twin Registry. Inference about Causation through Examination of FAmiliaL CONfounding (ICE FALCON) analysis was used for causal inference between metabolites and lipid parameters. Bidirectional mediation analysis was performed to explore the linkages between blood lipids, metabolites, and other seven cardiometabolic traits. We identified 44, 1, and 31 metabolites associated with triglyceride (TG), total cholesterol (TC), and high-density lipoprotein-cholesterol (HDL-C), most of which were gut microbiota-derived metabolites. There were 9, 1, and 14 metabolites that showed novel associations with TG, TC, and HDL-C, respectively. ICE FALCON analysis found that TG and HDL-C may have a predicted causal effect on 23 and six metabolites, respectively, and one metabolite may have a predicted causal effect on TG. Mediation analysis discovered 14 linkages connecting blood lipids, metabolites, and other cardiometabolic traits. Our study highlights the significance of gut microbiota-derived metabolites in lipid metabolism. Most of the identified cross-sectional associations may be due to the lipids having a predicted causal effect on metabolites, but not vice versa, nor are they due to family confounding. These findings shed new light on lipid metabolism and personalized management of cardiometabolic diseases., Competing Interests: Conflict of interest All the authors declare no conflicts of interest in this study., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Abstract Background A complex set of perturbations occur in cytokines and hormones in the etiopathogenesis of obesity and related cardiometabolic conditions such as type 2 diabetes (T2D). Evidence for the genetic regulation of these cytokines and hormones is limited, particularly in African-ancestry populations. In order to improve our understanding of the biology of cardiometabolic traits, we investigated the genetic architecture of a large panel of obesity- related cytokines and hormones among Africans with replication analyses in African Americans. Methods We performed genome-wide association studies (GWAS) in 4432 continental Africans, enrolled from Ghana, Kenya, and Nigeria as part of the Africa America Diabetes Mellitus (AADM) study, for 13 obesity-related cytokines and hormones, including adipsin, glucose-dependent insulinotropic peptide (GIP), glucagon-like peptide-1 (GLP-1), interleukin-1 receptor antagonist (IL1-RA), interleukin-6 (IL-6), interleukin-10 (IL-10), leptin, plasminogen activator inhibitor-1 (PAI-1), resistin, visfatin, insulin, glucagon, and ghrelin. Exact and local replication analyses were conducted in African Americans (n = 7990). The effects of sex, body mass index (BMI), and T2D on results were investigated through stratified analyses. Results GWAS identified 39 significant (P value

Understanding the epigenome paths through which smoking contributes to cardiometabolic traits is important for downstream applications. In this study, an SNP-based analytical pipeline was used to integrate several publicly available datasets in order to identify CpG sites that mediate the impact of smoking on cardiometabolic traits and to investigate the underlying molecular mechanisms. After applying stringent statistical criteria, 11 CpG sites were detected that showed significant association (p < 5 × 10−8) with cardiometabolic traits at both the discovery and replication stages. By integrating eQTL data, I found genes behind a number of these associations. cg05228408 was hypomethylated in smokers and contributed to higher blood pressure by lowering the expression of the CLCN6 gene. cg08639339 was hypermethylated in smokers and lowered the metabolic rate by increasing the expression of RAB29; furthermore, I noted TMEM120A mediated the impact of smoking-cg17325771 on LDL, and LTBP3 mediated the smoking-cg07029024 effect on heart rate. The pathway analysis identified processes through which the identified genes impact their traits. This study provides a list of CpG sites that mediates the impact of smoking on cardiometabolic traits and a framework to investigate the underlying molecular paths using publicly available data.

Early life exposure to famine was associated with adulthood metabolic syndrome and nonalcoholic fatty liver disease (NAFLD), and NAFLD was also affected by cardiometabolic traits. However, the role of cardiometabolic traits in the associations from famine exposure to NAFLD was largely unknown. This study aimed to investigate whether the relationship between early life famine exposure and adulthood NAFLD risk was mediated by cardiometabolic traits. Overall, 7578 subjects aged 56·0 (sd 3·7) years in the Dongfeng–Tongji cohort were included and classified into late-exposed (1952–1954), middle-exposed (1954–1956), early-childhood-exposed (1956–1958), fetal-exposed (1959–1961) and non-exposed (1962–1966, reference) group according to the birth year. NAFLD was diagnosed by experienced physicians via abdominal B-type ultrasound inspection. Mediation analysis was used to evaluate the mediating effects of cardiometabolic traits. Compared with those non-exposed, after multivariable adjustment, participants in fetal-exposed group (OR: 1·37; 95 % CI 1·08, 1·73) had 37 % higher risk to develop NAFLD, and the overall childhood-exposed group had marginally significant association with NAFLD (OR: 1·39; 95 % CI 0·99, 1·94). Stratification analysis found the famine–NAFLD associations more evident in women and those born in areas severely affected by famine. Mediation analysis showed that cardiometabolic traits such as total cholesterol, TAG glucose index, γ-glutamyl transpeptidase, alkaline phosphatase and alanine aminotransferase mediated 6·7–22·2 % of the relation from famine exposure to higher NAFLD risk. Early life exposure to famine was related to increased adulthood NAFLD risk, and this relationship was partly mediated by cardiometabolic traits. [ABSTRACT FROM AUTHOR]

Background and Aims: Observational studies reveal that different body fat measures are associated with cardiometabolic disease with different effects. However, causality is not reflected by such observations. To explore and compare the causal relationships of general obesity (measured by body mass index (BMI)), adipose obesity (measured by fat mass percentage (FMP)) and central obesity (measured by waist-to-height ratio (WHtR)) with cardiometabolic traits among children.Methods and Results: We conducted one sample Mendelian randomization (MR) analysis in 3266 children from Beijing Children and Adolescents Metabolic Syndrome Study. Genetic instruments based on 28 SNPs were performed to explore and compare the causal associations of genetically BMI, FMP and WHtR with cardiometabolic traits. The genetic instruments were robustly correlated with observed BMI, FMP and WHtR. Each genetically 1-SD increment in BMI, FMP and WHtR were causally associated with increment in systolic blood pressure (SBP), diastolic blood pressure (DBP), log-transformed fasting plasma glucose (FPG), log-transformed HOMA-β, and decrease in log-transformed high-density lipoprotein cholesterol (HDL), respectively (all P < 0.05 after Bonferroni correction). The receiver operating characteristic curve indicated that BMI and FMP showed stronger effects on SBP, DBP, HOMA-β and HDL than WHtR (all P < 0.05). We also observed causal associations of BMI and FMP with log-transformed fasting insulin and HOMA-IR.Conclusions: The MR analysis based on population-based cohort indicated a causal relationship of adiposity and body fat distribution with cardiometabolic traits. When compared with central obesity, general obesity and adipose obesity might own stronger effects on blood pressure and blood lipids among children. [ABSTRACT FROM AUTHOR]

The antibiotic resistance crisis underlies globally increasing failures in treating deadly bacterial infections, largely due to the selection of antibiotic resistance genes (ARG) collection, known as the resistome, in human gut microbiota. So far, little is known about the relationship between gut antibiotic resistome and host metabolic disorders such as type 2 diabetes (T2D). Here, metagenomic landscape of gut antibiotic resistome is profiled in a large multiomics human cohort (n = 1210). There is a significant overall shift in gut antibiotic resistome structure among healthy, prediabetes, and T2D groups. It is found that larger ARG diversity is associated with a higher risk of T2D. The novel diabetes ARG score is positively associated with glycemic traits. Longitudinal validation analysis confirms that the ARG score is associated with T2D progression, characterized by the change of insulin resistance. Collectively, the data describe the profiles of gut antibiotic resistome and support its close relationship with T2D progression. [ABSTRACT FROM AUTHOR]

To assess the burden of type 2 diabetes (T2D) and its genetic profile in endogamous populations of India given the paucity of data, we aimed to determine the prevalence of T2D and estimate its heritability using family-based cohorts from three distinct Endogamous Ethnic Groups (EEGs) representing Northern (Rajasthan [Agarwals: AG]) and Southern (Tamil Nadu [Chettiars: CH] and Andhra Pradesh [Reddys: RE]) states of India. For comparison, family-based data collected previously from another North Indian Punjabi Sikh (SI) EEG was used. In addition, we examined various T2D-related cardiometabolic traits and determined their heritabilities. These studies were conducted as part of the Indian Diabetes Genetic Studies in collaboration with US (INDIGENIUS) Consortium. The pedigree, demographic, phenotypic, covariate data and samples were collected from the CH, AG, and RE EEGs. The status of T2D was defined by ADA guidelines (fasting glucose ≥ 126 mg/dl or HbA1c ≥ 6.5% and/or use of diabetes medication/history). The prevalence of T2D in CH (N = 517, families = 21, mean age = 47y, mean BMI = 27), AG (N = 530, Families = 25, mean age = 43y, mean BMI = 27), and RE (N = 500, Families = 22, mean age = 46y, mean BMI = 27) was found to be 33%, 37%, and 36%, respectively, Also, the study participants from these EEGs were found to be at increased cardiometabolic risk (e.g., obesity and prediabetes). Similar characteristics for the SI EEG (N = 1,260, Families = 324, Age = 51y, BMI = 27, T2D = 75%) were obtained previously. We used the variance components approach to carry out genetic analyses after adjusting for covariate effects. The heritability (h2) estimates of T2D in the CH, RE, SI, and AG were found to be 30%, 46%, 54%, and 82% respectively, and statistically significant (P ≤ 0.05). Other T2D related traits (e.g., BMI, lipids, blood pressure) in AG, CH, and RE EEGs exhibited strong additive genetic influences (h2 range: 17% [triglycerides/AG and hs-CRP/RE] - 86% [glucose/non-T2D/AG]). Our findings highlight the high burden of T2D in Indian EEGs with significant and differential additive genetic influences on T2D and related traits. [ABSTRACT FROM AUTHOR]

Context: Observational studies have suggested that higher resting heart rate (RHR) may be associated with increased cardiometabolic risk. However, causal associations are not fully understood. Objective: We aimed to examine the direction, strength, and causality of the associations of RHR with cardiometabolic traits. Methods: We assessed the strength of associations between measured RHR and cardiometabolic traits in 506 211 and 372 452 participants from China Kadoorie Biobank (CKB) and UK Biobank (UKB). Mendelian randomization (MR) analyses were used to make causal inferences in 99 228 and 371 508 participants from CKB and UKB, respectively. Results: We identified significant directionally concordant observational associations between RHR and higher total cholesterol, triglycerides (TG), low-density lipoprotein, C-reactive protein (CRP), glucose, body mass index, waist-hip ratio (WHR), systolic blood pressure (SBP), and diastolic blood pressure (DBP) after the Bonferroni correction. MR analyses showed that 10 beat/min higher genetically predicted RHR was trans-ethnically associated with a higher DBP (beta 2.059 [95% CI 1.544, 2.574] mmHg in CKB; 2.037 [1.845, 2.229] mmHg in UKB), higher CRP (0.180 [0.057, 0.303] log mg/L in CKB; 0.154 [0.134, 0.174] log mg/L in UKB), higher TG (0.052 [−0.009, 0.113] log mmol/L in CKB; 0.020 [0.010, 0.030] log mmol/L in UKB) and higher WHR (0.218 [−0.033, 0.469] % in CKB; 0.225 [0.111, 0.339] % in UKB). In the opposite direction, higher genetically predicted SBP, TG, glucose, and WHR, and lower high-density lipoprotein, were associated with elevated RHR. Conclusion: Our large-scale analyses provide causal evidence for associations between RHR and cardiometabolic traits, highlighting the importance of monitoring heat rate as a means of alleviating the adverse effects of metabolic disorders. [ABSTRACT FROM AUTHOR]

Abstract Background Identification of genetic risk factors that are shared between Alzheimer’s disease (AD) and other traits, i.e., pleiotropy, can help improve our understanding of the etiology of AD and potentially detect new therapeutic targets. Previous epidemiological correlations observed between cardiometabolic traits and AD led us to assess the pleiotropy between these traits. Methods We performed a set of bivariate genome-wide association studies coupled with colocalization analysis to identify loci that are shared between AD and eleven cardiometabolic traits. For each of these loci, we performed colocalization with Genotype-Tissue Expression (GTEx) project expression quantitative trait loci (eQTL) to identify candidate causal genes. Results We identified three previously unreported pleiotropic trait associations at known AD loci as well as four novel pleiotropic loci. One associated locus was tagged by a low-frequency coding variant in the gene DOCK4 and is potentially implicated in its alternative splicing. Colocalization with GTEx eQTL data identified additional candidate genes for the loci we detected, including ACE, the target of the hypertensive drug class of ACE inhibitors. We found that the allele associated with decreased ACE expression in brain tissue was also associated with increased risk of AD, providing human genetic evidence of a potential increase in AD risk from use of an established anti-hypertensive therapeutic. Conclusion Our results support a complex genetic relationship between AD and these cardiometabolic traits, and the candidate causal genes identified suggest that blood pressure and immune response play a role in the pleiotropy between these traits.

Abstract The antibiotic resistance crisis underlies globally increasing failures in treating deadly bacterial infections, largely due to the selection of antibiotic resistance genes (ARG) collection, known as the resistome, in human gut microbiota. So far, little is known about the relationship between gut antibiotic resistome and host metabolic disorders such as type 2 diabetes (T2D). Here, metagenomic landscape of gut antibiotic resistome is profiled in a large multiomics human cohort (n = 1210). There is a significant overall shift in gut antibiotic resistome structure among healthy, prediabetes, and T2D groups. It is found that larger ARG diversity is associated with a higher risk of T2D. The novel diabetes ARG score is positively associated with glycemic traits. Longitudinal validation analysis confirms that the ARG score is associated with T2D progression, characterized by the change of insulin resistance. Collectively, the data describe the profiles of gut antibiotic resistome and support its close relationship with T2D progression.

To assess the burden of type 2 diabetes (T2D) and its genetic profile in endogamous populations of India given the paucity of data, we aimed to determine the prevalence of T2D and estimate its heritability using family-based cohorts from three distinct Endogamous Ethnic Groups (EEGs) representing Northern (Rajasthan [Agarwals: AG]) and Southern (Tamil Nadu [Chettiars: CH] and Andhra Pradesh [Reddys: RE]) states of India. For comparison, family-based data collected previously from another North Indian Punjabi Sikh (SI) EEG was used. In addition, we examined various T2D-related cardiometabolic traits and determined their heritabilities. These studies were conducted as part of the Indian Diabetes Genetic Studies in collaboration with US (INDIGENIUS) Consortium. The pedigree, demographic, phenotypic, covariate data and samples were collected from the CH, AG, and RE EEGs. The status of T2D was defined by ADA guidelines (fasting glucose ≥ 126 mg/dl or HbA1c ≥ 6.5% and/or use of diabetes medication/history). The prevalence of T2D in CH (N = 517, families = 21, mean age = 47y, mean BMI = 27), AG (N = 530, Families = 25, mean age = 43y, mean BMI = 27), and RE (N = 500, Families = 22, mean age = 46y, mean BMI = 27) was found to be 33%, 37%, and 36%, respectively, Also, the study participants from these EEGs were found to be at increased cardiometabolic risk (e.g., obesity and prediabetes). Similar characteristics for the SI EEG (N = 1,260, Families = 324, Age = 51y, BMI = 27, T2D = 75%) were obtained previously. We used the variance components approach to carry out genetic analyses after adjusting for covariate effects. The heritability (h2) estimates of T2D in the CH, RE, SI, and AG were found to be 30%, 46%, 54%, and 82% respectively, and statistically significant (P ≤ 0.05). Other T2D related traits (e.g., BMI, lipids, blood pressure) in AG, CH, and RE EEGs exhibited strong additive genetic influences (h2 range: 17% [triglycerides/AG and hs-CRP/RE] - 86% [glucose/non-T2D/AG]). Our findings highlight the high burden of T2D in Indian EEGs with significant and differential additive genetic influences on T2D and related traits.

Background: Both diabetic kidney disease (DKD) and chronic kidney disease (CKD) are more prevalent among individuals with lower levels of education in observational studies. To quantify the mediation effect of recognized cardiometabolic traits, we obtain causal estimates between education and DKD as well as CKD., Materials and Methods: We assessed the causal effect of education on DKD and CKD, separately estimated the causal effect of 26 cardiometabolic traits on DKD and CKD, and finally calculated the mediating effects and mediating proportions of each using two-step, two-sample multivariable Mendelian randomization (MVMR). Furthermore, the genetic association between exposure, mediators, and outcomes was investigated using linkage disequilibrium score (LDSC) regression analysis. Expression quantitative trait loci (eQTL) were retrieved from the Genotype-Tissue Expression Project (GTEx) v8 to serve as genetic instrumental variables. Transcriptome-wide association studies (TWAS), Bayesian colocalization analysis, and Summary-data-based Mendelian Randomization (SMR) analysis were performed to explore underlying susceptibility genes between education, mediators, and kidney diseases., Results: Higher education with a genetically predicted 1-SD (4.2 years) was linked to a 48.64% decreased risk of DKD and a 29.08% decreased risk of CKD. After extensive evaluation of 26 cardiometabolic traits, 7 and 6 causal mediators were identified as mediating the effects of education on DKD and CKD, respectively. The largest mediating factor between education and DKD was BMI, which was followed by WHR, T2D, fasting insulin, SBP, fasting glucose, and DBP. In contrast, candidate mediators in the education-to-CKD pathway included BMI, followed by cigarettes smoked per day, WHR, SBP, T2D, and DBP. MR analysis revealed that TP53INP1 was found to be a shared susceptibility gene for cardiometabolic traits and DKD, while L3MBTL3 was found to be a shared susceptibility gene for cardiometabolic traits and CKD., Conclusion: Our findings provide solid evidence that education has a causally protective effect on the development of DKD and CKD. We additionally reveal significant directions for intervention on cardiometabolic traits that mitigate the negative effects of educational inequities on the onset of DKD and CKD. Our work demonstrates a shared genetic basis between education, cardiometabolic traits, and kidney diseases. Future research aiming at lowering kidney risk may benefit from these findings., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Wang, Chen, Wang and Wu.)

Searching for positive selection signals across genomes has identified functional genetic variants responding to environmental change. In Native Americans of Mexico, we used the fixation index (F st ) and population branch statistic (PBS) to identify SNPs suggesting positive selection. The 103 most differentiated SNPs were tested for associations with metabolic traits, the most significant association was FADS2 /rs174616 with body mass index (BMI). This variant lies within a linkage disequilibrium (LD) block independent of previously reported FADS selection signals and has not been clearly associated with metabolic phenotypes. We tested this variant in two independent cohorts with cardiometabolic data. In the Genetics of Atherosclerotic Disease (GEA) cohort, the derived allele (T) was associated with increased BMI, lower LDL-C levels and a decreased risk of subclinical atherosclerosis in women. Significant gene-diet interactions affected lipid, apolipoprotein and adiponectin levels with differences according to sex, involving mainly total and complex dietary carbohydrate%. In the Genotype-related Effects of PUFA trial, the derived allele was associated with lower Δ-6 desaturase activity and erythrocyte membrane dihomo-gamma-linolenic acid (DGLA) levels, and with increased Δ-5 desaturase activity and eicosapentaenoic acid levels. This variant interacted with dietary carbohydrate% affecting Δ-6 desaturase activity. Notably, the relationship of DGLA and other erythrocyte membrane LC-PUFA indices with HOMA-IR differed according to rs174616 genotype, which has implications regarding how these indices should be interpreted. In conclusion, this observational study identified rs174616 as a signal suggesting selection in an independent linkage disequilibrium block, was associated with cardiometabolic and erythrocyte measurements of LC-PUFA in two independent Mexican cohorts and showed significant gene-diet interactions., Competing Interests: The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:Maria Elizabeth Tejero reports financial support was provided by Nestec Ltd. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors. Published by Elsevier Ltd.)

Background and Aims: Evidence on the association of maternal obesity with offspring cardiometabolic health is limited, particularly for the Asian population. We aimed to examine the associations of maternal body mass index (BMI) in early pregnancy and gestational weight gain (GWG) rate in mid- and late-pregnancy with childhood cardiometabolic traits., Methods and Results: We used data of 1452 mother-child pairs from a population-based prospective cohort study in China. Maternal BMI in early pregnancy and GWG rate in mid- and late-pregnancy were calculated. Childhood cardiometabolic traits were assessed at aged 4-7 years, including BMI, BMI-z, systolic blood pressure (SBP), diastolic blood pressure, high-density lipoprotein-cholesterol, low-density lipoprotein-cholesterol, total cholesterol, triglycerides, fasting glucose, and C-reactive protein. Each 1 kg/m 2 increase in maternal BMI in early pregnancy was associated with 0.46% (95% confidence interval, 0.19%-0.72%) higher children BMI, 0.05 (0.02-0.08) higher BMI-z, 0.41% (0.22%-0.59%) higher waist circumference, and 0.24% (0.03%-0.46%) higher SBP. Each 1 kg/week higher GWG rate in mid- and late-pregnancy was associated with higher children SBP (4.58% [1.46%-7.71%]), triglycerides (18.28% [3.13%-33.44%]), and fasting glucose (5.83% [2.64%-9.02%]) and lower BMI-z (-0.45 [-0.82 to -0.08]). Additional adjustment for offspring BMI attenuated the associations for maternal BMI but not for GWG rate., Conclusions: The increase in maternal BMI and GWG are associated with adverse cardiometabolic profiles in childhood. The association between maternal BMI and childhood cardiometabolic traits is likely mediated using the offspring BMI., Competing Interests: Declaration of competing interest The authors have no conflicts of interest to declare., (Copyright © 2024 The Italian Diabetes Society, the Italian Society for the Study of Atherosclerosis, the Italian Society of Human Nutrition and the Department of Clinical Medicine and Surgery, Federico II University. Published by Elsevier B.V. All rights reserved.)

Background: A complex set of perturbations occur in cytokines and hormones in the etiopathogenesis of obesity and related cardiometabolic conditions such as type 2 diabetes (T2D). Evidence for the genetic regulation of these cytokines and hormones is limited, particularly in African-ancestry populations. In order to improve our understanding of the biology of cardiometabolic traits, we investigated the genetic architecture of a large panel of obesity- related cytokines and hormones among Africans with replication analyses in African Americans. Methods: We performed genome-wide association studies (GWAS) in 4432 continental Africans, enrolled from Ghana, Kenya, and Nigeria as part of the Africa America Diabetes Mellitus (AADM) study, for 13 obesity-related cytokines and hormones, including adipsin, glucose-dependent insulinotropic peptide (GIP), glucagon-like peptide-1 (GLP-1), interleukin-1 receptor antagonist (IL1-RA), interleukin-6 (IL-6), interleukin-10 (IL-10), leptin, plasminogen activator inhibitor-1 (PAI-1), resistin, visfatin, insulin, glucagon, and ghrelin. Exact and local replication analyses were conducted in African Americans (n = 7990). The effects of sex, body mass index (BMI), and T2D on results were investigated through stratified analyses. Results: GWAS identified 39 significant (P value < 5 × 10−8) loci across all 13 traits. Notably, 14 loci were African-ancestry specific. In this first GWAS for adipsin and ghrelin, we detected 13 and 4 genome-wide significant loci respectively. Stratified analyses by sex, BMI, and T2D showed a strong effect of these variables on detected loci. Eight novel loci were successfully replicated: adipsin (3), GIP (1), GLP-1 (1), and insulin (3). Annotation of these loci revealed promising links between these adipocytokines and cardiometabolic outcomes as illustrated by rs201751833 for adipsin and blood pressure and locus rs759790 for insulin level and T2D in lean individuals. Conclusions: Our study identified genetic variants underlying variation in multiple adipocytokines, including the first loci for adipsin and ghrelin. We identified population differences in variants associated with adipocytokines and highlight the importance of stratification for discovery of loci. The high number of African-specific loci detected emphasizes the need for GWAS in African-ancestry populations, as these loci could not have been detected in other populations. Overall, our work contributes to the understanding of the biology linking adipocytokines to cardiometabolic traits. [ABSTRACT FROM AUTHOR]

Background: There is growing support for the use of genetic risk scores (GRS) in routine clinical settings. Due to the limited diversity of current genomic discovery samples, there are concerns that the predictive power of GRS will be limited in non-European ancestry populations. GRS for cardiometabolic traits were evaluated in sub-Saharan Africans in comparison with African Americans and European Americans.Methods: We evaluated the predictive utility of GRS for 12 cardiometabolic traits in sub-Saharan Africans (AF; n = 5200), African Americans (AA; n = 9139) and European Americans (EUR; n = 9594). GRS were constructed as weighted sums of the number of risk alleles. Predictive utility was assessed using the additional phenotypic variance explained and the increase in discriminatory ability over traditional risk factors [age, sex and body mass index (BMI)], with adjustment for ancestry-derived principal components.Results: Across all traits, GRS showed up to a 5-fold and 20-fold greater predictive utility in EUR relative to AA and AF, respectively. Predictive utility was most consistent for lipid traits, with percentage increase in explained variation attributable to GRS ranging from 10.6% to 127.1% among EUR, 26.6% to 65.8% among AA and 2.4% to 37.5% among AF. These differences were recapitulated in the discriminatory power, whereby the predictive utility of GRS was 4-fold greater in EUR relative to AA and up to 44-fold greater in EUR relative to AF. Obesity and blood pressure traits showed a similar pattern of greater predictive utility among EUR.Conclusions: This work demonstrates the poorer performance of GRS in AF and highlights the need to improve representation of multiple ethnic populations in genomic studies to ensure equitable clinical translation of GRS. [ABSTRACT FROM AUTHOR]

Identifying the molecular mechanisms by which genome-wide association study (GWAS) loci influence traits remains challenging. Chromatin accessibility quantitative trait loci (caQTLs) help identify GWAS loci that may alter GWAS traits by modulating chromatin structure, but caQTLs have been identified in a limited set of human tissues. Here we mapped caQTLs in human liver tissue in 20 liver samples and identified 3,123 caQTLs. The caQTL variants are enriched in liver tissue promoter and enhancer states and frequently disrupt binding motifs of transcription factors expressed in liver. We predicted target genes for 861 caQTL peaks using proximity, chromatin interactions, correlation with promoter accessibility or gene expression, and colocalization with expression QTLs. Using GWAS signals for 19 liver function and/or cardiometabolic traits, we identified 110 colocalized caQTLs and GWAS signals, 56 of which contained a predicted caPeak target gene. At the LITAF LDL-cholesterol GWAS locus, we validated that a caQTL variant showed allelic differences in protein binding and transcriptional activity. These caQTLs contribute to the epigenomic characterization of human liver and help identify molecular mechanisms and genes at GWAS loci. [ABSTRACT FROM AUTHOR]

MicroRNAs (miRNAs) are non-coding RNA molecules that regulate gene expression. Extensive research has explored the role of miRNAs in the risk for type 2 diabetes (T2D) and coronary heart disease (CHD) using single-omics data, but much less by leveraging population-based omics data. Here we aimed to conduct a multi-omics analysis to identify miRNAs associated with cardiometabolic risk factors and diseases. First, we used publicly available summary statistics from large-scale genome-wide association studies to find genetic variants in miRNA-related sequences associated with various cardiometabolic traits, including lipid and obesity-related traits, glycemic indices, blood pressure, and disease prevalence of T2D and CHD. Then, we used DNA methylation and miRNA expression data from participants of the Rotterdam Study to further investigate the link between associated miRNAs and cardiometabolic traits. After correcting for multiple testing, 180 genetic variants annotated to 67 independent miRNAs were associated with the studied traits. Alterations in DNA methylation levels of CpG sites annotated to 38 of these miRNAs were associated with the same trait(s). Moreover, we found that plasma expression levels of 8 of the 67 identified miRNAs were also associated with the same trait. Integrating the results of different omics data showed miR-10b-5p, miR-148a-3p, miR-125b-5p, and miR-100-5p to be strongly linked to lipid traits. Collectively, our multi-omics analysis revealed multiple miRNAs that could be considered as potential biomarkers for early diagnosis and progression of cardiometabolic diseases.

Background and Aims: Body mass index (BMI) and waist-to-hip ratio (WHR) have been reported to be causally associated with cardiometabolic diseases in adults in European populations. However, this causality was less explored in East Asian populations and in children. Our study aimed to explore and compare the causal associations of general obesity (measured by BMI) and central obesity (measured by WHR) with cardiometabolic traits.Methods and Results: We performed a Mendelian randomization (MR) analysis in 2030 unrelated children from two independent case-control studies in Beijing, China. BMI-associated single nucleotide polymorphisms (SNPs) and WHR-SNPs identified by previous genome-wide association studies were used as genetic instruments to examine the casual associations of BMI and WHR with cardiometabolic traits, including glycemic traits, blood lipids, and blood pressure. Each 1-SD increase in BMI and WHR were significantly associated with 0.111 mmol/L and 0.110 mmol/L increase in log-transformed fasting insulin (FINS), 0.049 and 0.060 increase in log-transformed HOMA-β, 0.112 and 0.108 increase in log-transformed HOMA-IR, 0.009 mmol/L and 0.015 mmol/L increase in log-transformed triglyceride, and 15.527 mmHg and 7.277 mmHg increase in systolic blood pressure, respectively (all P < 0.05). The receiver operating characteristic curves showed that WHR had a stronger effect on FINS, HOMA-β, HOMA-IR, and triglyceride than BMI (all P < 0.05).Conclusions: Using the MR method, we found that the genetic predisposition to higher BMI or WHR was associated with altered cardiometabolic traits in Chinese children. When compared with general obesity, central obesity might have stronger effects on glycemic traits and blood lipids among children. [ABSTRACT FROM AUTHOR]

Several studies on gene-diet interactions (nutrigenetics) have been performed in western populations; however, there are only a few studies to date in lower middle-income countries (LMIC). A large-scale collaborative project called gene-nutrient interactions (GeNuIne) Collaboration, the main objective of which is to investigate the effect of GeNuIne on cardiometabolic traits using population-based studies from various ethnic groups, has been initiated at the University of Reading, UK. While South Asians with higher genetic risk score (GRS) showed a higher risk of obesity in response to a high-carbohydrate diet, South East and Western Asian populations with higher GRS showed an increased risk of central obesity in response to a high-protein diet. The paper also provides a summary of other gene-diet interaction analyses that were performed in LMIC as part of this collaborative project and gives an overview of how these nutrigenetic findings can be translated to personalised and public health approaches for the prevention of cardiometabolic diseases such as obesity, type 2 diabetes and CVD. [ABSTRACT FROM AUTHOR]

MicroRNAs (miRNAs) are non-coding RNA molecules that regulate gene expression. Extensive research has explored the role of miRNAs in the risk for type 2 diabetes (T2D) and coronary heart disease (CHD) using single-omics data, but much less by leveraging population-based omics data. Here we aimed to conduct a multi-omics analysis to identify miRNAs associated with cardiometabolic risk factors and diseases. First, we used publicly available summary statistics from large-scale genome-wide association studies to find genetic variants in miRNA-related sequences associated with various cardiometabolic traits, including lipid and obesity-related traits, glycemic indices, blood pressure, and disease prevalence of T2D and CHD. Then, we used DNA methylation and miRNA expression data from participants of the Rotterdam Study to further investigate the link between associated miRNAs and cardiometabolic traits. After correcting for multiple testing, 180 genetic variants annotated to 67 independent miRNAs were associated with the studied traits. Alterations in DNA methylation levels of CpG sites annotated to 38 of these miRNAs were associated with the same trait(s). Moreover, we found that plasma expression levels of 8 of the 67 identified miRNAs were also associated with the same trait. Integrating the results of different omics data showed miR-10b-5p, miR-148a-3p, miR-125b-5p, and miR-100-5p to be strongly linked to lipid traits. Collectively, our multi-omics analysis revealed multiple miRNAs that could be considered as potential biomarkers for early diagnosis and progression of cardiometabolic diseases. [ABSTRACT FROM AUTHOR]

The rapid rise of obesity, type 2 diabetes mellitus (T2DM) and cardiovascular disease (CVD) during the last few decades among South Asians has been largely attributed to a major shift in lifestyles including physical inactivity, unhealthy dietary patterns, and an overall pattern of sedentary lifestyle. Genetic predisposition to these cardiometabolic risk factors may have interacted with these obesogenic environments in determining the higher cardiometabolic disease prevalence. Based on the premise that gene-environment interactions cause obesity and cardiometabolic diseases, we systematically searched the literature and considered the knowledge gaps that future studies might fulfill. We identified only seven published studies that focused specifically on gene-environment interactions for cardiometabolic traits in South Asians, most of which were limited by relatively small sample and lack of replication. Some studies reported that the differences in metabolic response to higher physical activity and low caloric diet might be modified by genetic risk related to these cardiometabolic traits. Although studies on gene lifestyle interactions in cardiometabolic traits report significant interactions, future studies must focus on more precise assessment of lifestyle factors, investigation of a larger set of genetic variants and the application of powerful statistical methods to facilitate translatable approaches. Future studies should also be integrated with findings both using mechanistic studies through laboratory settings and randomized clinical trials for clinical outcomes.

Objective: To evaluate the causal relationship between childhood body-mass index (BMI) at different ages and adult cardiometabolic traits., Methods: We retrieved genetic instrument variables (IVs) for exposures (standardized BMI at newborn, infant, toddler and late childhood), cardiometabolic traits and potential confounders or mediators (adult BMI, SHBG, testosterone and age at menarche) from the corresponding genome-wide association analysis. We performed univariate and multivariable Mendelian randomization (MR) to dissect associations between age-specific childhood BMI and adult cardiometabolic outcomes. Odds ratio was used to present the direction of the causal association., Results: In univariate MR, higher newborn BMI was causally associated with reduced risk for type 2 diabetes in women. Late childhood BMI was associated with increased risk for female diabetes and coronary artery disease (CAD), myocardial infarction (MI), and chronic kidney disease (CKD) in general population. Among these associations, only association between late childhood BMI with MI remained significant after adjusting for adult male BMI and sex hormones, (OR = 1.120, 95% CI 1.023-1.226, p = 0.014). Besides, in multivariable MR, we found evidence for causal association between newborn BMI with reduced risk for CAD (OR = 0.862, 95% CI 0.751-0.989, p = 0.034) and MI (OR = 0.864, 95% CI 0.752-0.991, p = 0.037) in men. No obvious impact of infant or toddler BMI was identified on the above-mentioned diseases. For continuous cardiometabolic traits, in all age epochs except infant, higher BMI was associated with increased level of fasting glucose in women., Conclusion: BMI at birth and late childhood exerts different impact on adult cardiometabolic diseases, while BMI at infant and toddler ages is not causally associated with these outcomes. The effect of childhood BMI may be influenced by sex disparities., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The author PF declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision., (Copyright © 2024 Yang, Kuang, Yang, Li, Qi, Fu and Zeng.)

Type 2 diabetes (T2D) and hypertension are common comorbidities and, along with hyperlipidemia, serve as risk factors for cardiovascular diseases. This study aimed to evaluate the predictive value of polygenic risk scores (PRSs) on cardiometabolic traits related to T2D, hypertension, and hyperlipidemia and the incidence of these three diseases in Taiwan Biobank samples. Using publicly available, large-scale genome-wide association studies summary statistics, we constructed cross-ethnic PRSs for T2D, hypertension, body mass index, and nine quantitative traits typically used to define the three diseases. A composite PRS (cPRS) for each of the nine traits was constructed by aggregating the significant PRSs of its genetically correlated traits. The associations of each of the nine traits at baseline as well as the change of trait values during a 3- to 6-year follow-up period with its cPRS were evaluated. The predictive performances of cPRSs in predicting future incidences of T2D, hypertension, and hyperlipidemia were assessed. The cPRSs had significant associations with baseline and changes of trait values in 3-6 years and explained a higher proportion of variance for all traits than individual PRSs. Furthermore, models incorporating disease-related cPRSs, along with clinical features and relevant trait measurements achieved area under the curve values of 87.8%, 83.7%, and 75.9% for predicting future T2D, hypertension, and hyperlipidemia in 3-6 years, respectively., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2023 The Author(s). Published by Elsevier Inc. All rights reserved.)

Aims To identify genetic variants that have a regulatory impact on circulating microRNAs (miRNAs) and to connect genetic risk to blood traits/biomarkers through the circulating miRNAs. Methods and results Leveraging miRNA-Seq data and the 1000 Genomes imputed genotypes, we carried out genome-wide association analysis for SNPs that regulate the expression of circulating miRNAs in a sample of 710 unrelated subjects of European ancestry. Wherever possible, we used data from the Framingham and the Geuvadis studies to replicate our findings. We found at least one genome-wide significant (P  < 5e−8) miRNA-eQTL (mirQTL) for 143 circulating miRNAs. Overall each mirQTL explained a small portion (<1%) of variation in miRNA levels; however, we identified a few mirQTLs that explained 4% to 20% of variation in miRNA levels in plasma. Unlike trans -mirQTLs (P  = 0.7), cis -mirQTLs tend to be also associated with their counterpart mature miRNAs (P  < 0.0001), this suggests trans -mirQTLs exert their effect through processes that affect the stability of mature miRNAs; whereas, cis -mirQTLs mainly regulate the expression of primary-miRNAs. Next, we used the identified mirQTLs to investigate the links between circulating miRNAs with blood traits/biomarkers through Mendelian randomization analysis. We found miR-1908-5p plays an important role in regulating low-density lipoprotein (LDL), total cholesterol (TC), fasting glucose, HbA1c, and several lipid-metabolites in blood, whereas, miR-10b-5p mediates the trans -regulatory effect of the ABO locus on several blood proteins, coronary artery disease, and TC. Moreover, we demonstrated that a higher plasma level of miR-199a is causally associated with lower levels of LDL and TC. Finally, we found miR-143-3p and miR-145-5p are functionally related and mediate the effect of ZFPM2 on a number of its protein targets in blood including VEGFA , SERPINE1 , and PDGFs. Conclusions This study identifies SNPs that have a regulatory impact on circulating miRNAs, and underlines the role of several circulating miRNAs in mediating the effect of a number of GWAS loci on cardiometabolic phenotypes. [ABSTRACT FROM AUTHOR]