Large-scale genome-wide association studies in east Asians identify new genetic loci influencing metabolic traits

Identification of genetic loci enriched in obese or lean T2D cases in the Korean population

BACKGROUND

Obesity causes many complex diseases including type 2 diabetes (T2D). Obesity increases the risk of T2D in Europeans, but there are many non-obese (lean) T2D patients in East Asia.

OBJECTIVE

To discover genetic factors enriched in obese or lean T2D patients, we conducted a genome-wide association (GWA) analysis for T2D stratified by BMI in the Korean population.

METHODS

In the discovery stage, 654 and 247 individuals classified as obese (BMI > 25) and lean (BMI < 23) T2D patients, respectively, were compared with 3,842 control subjects for GWA analysis. Several BMI-stratified T2D variants detected in the discovery stage were further tested in the replication stage, which included 402 obese and 220 lean T2D cases, and 3,615 controls.

RESULTS

Meta-analysis combining the discovery and replication stages detected two variants with genome-wide significance: rs2356138 [P = 2.8 × 10-8, OR = 2.06 (1.59-2.65)] in obese T2D subjects and rs9295478 [P = 2.5 × 10-9, OR = 1.61 (1.38-1.88)] in lean ones. The SNP rs9295478 is located in CDKAL1, a well-known T2D gene previously identified in several GWA studies. Meanwhile, the SNP rs2356138 is a previously unknown variant located in PKP4.

CONCLUSION

We discovered genetic loci enriched in obese or lean T2D patients in the Korean population. Our findings should facilitate more effective control of T2D in Koreans.

Utilizing Machine Learning to Identify Biomarkers of Endoplasmic Reticulum Stress and Analyze Immune Cell Infiltration in Parkinson's Disease

The neurodegenerative disorder known as Parkinson's disease (PD) affects many people. The objective of this investigation was to examine the relationship between immune system infiltration, ATP-binding cassette transporter subfamily A member 7 (ABCA7) and TBL2 as well as potential therapeutic targets for the identification of PD associated to endoplasmic reticulum (ER) stress. First, we obtained PD data through GEO and divided it into two sets: a training set (GSE8397) plus a set for validation (GSE7621). Functional enrichment analysis was performed on a set of DEGs that overlapped with genes involved in endoplasmic reticulum stress. To identify genes of PD linked with endoplasmic reticulum stress, we employed random forest (RF) along with the least absolute shrinkage and selection operator (LASSO) logistic regression. Spearman's rank correlation analysis was then used to find associations among diagnostic markers with immune cell penetration. A grand total of 2 stress-related endoplasmic reticulum signature transcripts were identified. ABCA7 and TBL2 were shown to have diagnostic potential for PD and immune infiltrating cells have a role in the etiology of the disease. Additionally, resting CD4 memory, plasma cells, and NK cells overall exhibited positive associations with ABCA7, whereas triggered macrophages, T cells with active CD4 memory, activating NK cells, T cells with activated CD4 naive, engaged NK cells, and neutrophils all had adverse interactions with ABCA7. Overall, ABCA7 together with TBL2 have diagnostic utility for PD, and several types of immune cells, especially macrophages, may be involved in the development and progression of the disease.

Genome-wide association study of maternal plasma metabolites during pregnancy

Metabolites are key indicators of health and therapeutic targets, but their genetic underpinnings during pregnancy-a critical period for human reproduction-are largely unexplored. Using genetic data from non-invasive prenatal testing, we performed a genome-wide association study on 84 metabolites, including 37 amino acids, 24 elements, 13 hormones, and 10 vitamins, involving 34,394 pregnant Chinese women, with sample sizes ranging from 6,394 to 13,392 for specific metabolites. We identified 53 metabolite-gene associations, 23 of which are novel. Significant differences in genetic effects between pregnant and non-pregnant women were observed for 16.7%-100% of these associations, indicating gene-environment interactions. Additionally, 50.94% of genetic associations exhibited pleiotropy among metabolites and between six metabolites and eight pregnancy phenotypes. Mendelian randomization revealed potential causal relationships between seven maternal metabolites and 15 human traits and diseases. These findings provide new insights into the genetic basis of maternal plasma metabolites during pregnancy.

A comprehensive multi-task deep learning approach for predicting metabolic syndrome with genetic, nutritional, and clinical data

Metabolic syndrome (MetS) is a complex disorder characterized by a cluster of metabolic abnormalities, including abdominal obesity, hypertension, elevated triglycerides, reduced high-density lipoprotein cholesterol, and impaired glucose tolerance. It poses a significant public health concern, as individuals with MetS are at an increased risk of developing cardiovascular diseases and type 2 diabetes. Early and accurate identification of individuals at risk for MetS is essential. Various machine learning approaches have been employed to predict MetS, such as logistic regression, support vector machines, and several boosting techniques. However, these methods use MetS as a binary status and do not consider that MetS comprises five components. Therefore, a method that focuses on these characteristics of MetS is needed. In this study, we propose a multi-task deep learning model designed to predict MetS and its five components simultaneously. The benefit of multi-task learning is that it can manage multiple tasks with a single model, and learning related tasks may enhance the model's predictive performance. To assess the efficacy of our proposed method, we compared its performance with that of several single-task approaches, including logistic regression, support vector machine, CatBoost, LightGBM, XGBoost and one-dimensional convolutional neural network. For the construction of our multi-task deep learning model, we utilized data from the Korean Association Resource (KARE) project, which includes 352,228 single nucleotide polymorphisms (SNPs) from 7729 individuals. We also considered lifestyle, dietary, and socio-economic factors that affect chronic diseases, in addition to genomic data. By evaluating metrics such as accuracy, precision, F1-score, and the area under the receiver operating characteristic curve, we demonstrate that our multi-task learning model surpasses traditional single-task machine learning models in predicting MetS.

Identification of shared genetic risks underlying metabolic syndrome and its related traits in the Korean population

Introduction: Observational studies have demonstrated strong correlations between metabolic syndrome (MetS) and its related traits. To gain insight into the genetic architecture and molecular mechanism of MetS, we investigated the shared genetic basis of MetS and its related traits and further tested their causal relationships. Methods: Using summary statistics from genome-wide association analyses of about 72,000 subjects from the Korean Genome and Epidemiological Study (KoGES), we conducted genome-wide multi-trait analyses to quantify the overall genetic correlation and Mendelian randomization analyses to infer the causal relationships between traits of interest. Results: Genetic correlation analyses revealed a significant correlation of MetS with its related traits, such as obesity traits (body mass index and waist circumference), lipid traits (triglyceride and high-density lipoprotein cholesterol), glycemic traits (fasting plasma glucose and hemoglobin A1C), and blood pressure (systolic and diastolic). Mendelian randomization analyses further demonstrated that the MetS-related traits showing significant overall genetic correlation with MetS could be genetically determined risk factors for MetS. Discussion: Our study suggests a shared genetic basis of MetS and its related traits and provides novel insights into the biological mechanisms underlying these complex traits. Our findings further inform public health interventions by supporting the important role of the management of metabolic risk factors such as obesity, unhealthy lipid profiles, diabetes, and high blood pressure in the prevention of MetS.

The discovery of GGT1 as a novel gene for ischemic stroke conferring protection against disease risk in non-smokers and non-abusers of alcohol

OBJECTIVES

Increased plasma gamma-glutamyl transferase (GGT1) has been identified as a robust and independent risk factor for ischemic stroke (IS), but the molecular mechanisms of the enzyme-disease association are unclear. The present study investigated whether polymorphisms in the GGT1 gene contribute to IS susceptibility.

MATERIALS AND METHODS

DNA samples obtained from 1288 unrelated individuals (600 IS patients and 688 controls) were genotyped for common single nucleotide polymorphisms of GGT1 using the MassArray-4 platform.

RESULTS

The rs5751909 polymorphism was significantly associated with decreased risk of ischemic stroke regardless sex and age (Pperm ≤ 0.01, dominant genetic model). The haplotype rs4820599A-rs5760489A-rs5751909A showed strong protection against ischemic stroke (OR 0.53, 95 %CI 0.36 - 0.77, Pperm ≤ 0.0001). The protective effect of SNP rs5751909 in the stroke phenotype was successfully replicated in the UK Biobank, SiGN, and ISGC cohorts (P ≤ 0.01). GGT1 polymorphisms showed joint (epistatic) effects on the risk of ischemic stroke, with some known IS-associated GWAS loci (e.g., rs4322086 and rs12646447) investigated in our population. In addition, SNP rs5751909 was found to be strongly associated with a decreased risk of ischemic stroke in non-smokers (OR 0.54 95 %CI 0.39-0.75, Pperm = 0.0002) and non-alcohol abusers (OR 0.43 95 %CI 0.30-0.61, Pperm = 2.0 × 10-6), whereas no protective effects of this SNP against disease risk were observed in smokers and alcohol abusers (Pperm < 0.05).

CONCLUSIONS

We propose mechanisms underlying the observed associations between GGT1 polymorphisms and ischemic stroke risk. This pilot study is the first to demonstrate that GGT1 is a novel susceptibility gene for ischemic stroke and provides additional evidence of the genetic contribution to impaired redox homeostasis underlying disease pathogenesis.

Health burden of unbalanced fatty acids intake from 1990 to 2019: A global analysis

BACKGROUND

Unbalanced fatty acids intake is associated with a range of health outcomes; however, the impact on human health remains unclear globally. We aim to provide a comprehensive assessment of the health effect of unbalanced fatty acids intake on a global scale.

METHODS

We analyzed the trends of summary exposure value (SEV) and the attributable burden of unbalanced fatty acids intake, including diet low in polyunsaturated fatty acids (low PUFAs), diet low in seafood omega-3 fatty acids (low seafood-(ω-3)-PUFAs), and diet high in trans fatty acids (high TFAs) from 1990 to 2019 using data from Global Burden of Disease Study 2019.

FINDINGS

The global fatty acids intake was far from the optimal level. High-income North America had the highest SEV of diet of high TFAs, while less-developed regions located in Saharan Africa had the highest SEVs of low PUFAs and low seafood-(ω-3)-PUFAs. The attributable burden was unequally distributed to less-developed regions. Males had lower SEVs but higher attributable burden than females and this gender gap was particularly pronounced before the age of 59. The young population had a higher SEV of diet of low PUFAs, comparable SEV of low seafood-(ω-3)-PUFAs but lower SEV of high TFAs than the elderly population.

CONCLUSIONS

This study underpinned the high prevalence of unbalanced fatty acids intake worldwide and provided evidence-based guidance for identifying at-risk populations and developing effective strategies to improve fatty acids intake in the future.

FUNDING

The study was funded by Shanxi Province "136" Revitalization Medical Project Construction Funds and the Fundamental Research Funds for the Central Universities.

Genetic polymorphisms of GGT1 gene (rs8135987, rs5751901 and rs2017869) are associated with neoadjuvant chemotherapy efficacy and toxicities in breast cancer patients

BACKGROUND

Our previous study illustrated the predictive value of serum gamma-glutamyl transpeptidase (GGT) for neoadjuvant chemotherapy (NAC) sensitivity in breast cancer patients. In this study we aim to determine whether single nucleotide polymorphisms (SNPs) in the gamma-glutamyltransferase 1 (GGT1) gene are related to the NAC response and adverse events and to find out a genetic marker in predicting NAC sensitivity.

METHODS

Three SNP loci (rs8135987, rs5751901, rs2017869) of GGT1 gene were selected and tested among breast cancer patients reciving NAC. Four genotype models were used in SNP analysis: co-dominant model compared AA vs. Aa vs. aa; dominant model compared AA vs. Aa + aa; recessive model compared AA + Aa vs. aa; over-dominant model compared AA + aa vs. Aa. Chi-squared test and multivariable logistic regression analysis were performed between SNP genotypes, haplotypes and pathological complete response(pCR), adverse events as well as serum GGT level.

RESULTS

A total of 143 patients were included in the study. For SNP rs8135987 (T > C), the TC genotype in over-dominant model was inversely related with pCR (adjusted OR = 0.30, 95% CI 0.10-0.88, p = 0.029) as well as the risk of peripheral neuropathy (adjusted OR = 0.39, 95% CI 0.15-0.96, p = 0.042). The TC genotype in dominant model was significantly associated with elevated serum GGT level (OR = 3.11, 95% CI 1.07-9.02, p = 0.036). For rs2017869 (G > C), the occurrence of grade 2 or greater neutropenia (OR = 0.39, 95% CI 0.08-0.84, p = 0.025) and leukopenia (OR = 0.24, 95% CI 0.08-0.78, p = 0.017) were both significantly reduced in patients with CC genotypes. For rs5751901(T > C), the CC genotype could significantly reduce the risk of grade 2 or greater neutropenia (OR = 0.29, 95% CI 0.09-0.96, p = 0.036) and leukopenia (OR = 0.27, 95% CI 0.09-0.84, p = 0.024) in recessive model.

CONCLUSIONS

The GGT1 gene SNPs might be an independent risk factor for poor response of NAC in breast cancer patients, providng theoretical basis for further precision therapy.

Association of coffee consumption with type 2 diabetes and glycemic traits: a Mendelian randomization study

BACKGROUND/OBJECTIVES

Habitual coffee consumption was inversely associated with type 2 diabetes (T2D) and hyperglycemia in observational studies, but the causality of the association remains uncertain. This study tested a causal association of genetically predicted coffee consumption with T2D using the Mendelian randomization (MR) method.

SUBJECTS/METHODS

We used five single-nucleotide polymorphisms (SNPs) as instrumental variables (IVs) associated with habitual coffee consumption in a previous genome-wide association study among Koreans. We analyzed the associations between IVs and T2D, fasting blood glucose (FBG), 2h-postprandial glucose (2h-PG), and glycated haemoglobin (HbA1C) levels. The MR results were further evaluated by standard sensitivity tests for possible pleiotropism.

RESULTS

MR analysis revealed that increased genetically predicted coffee consumption was associated with a reduced prevalence of T2D; ORs per one-unit increment of log-transformed cup per day of coffee consumption ranged from 0.75 (0.62-0.90) for the weighted mode-based method to 0.79 (0.62-0.99) for Wald ratio estimator. We also used the inverse-variance-weighted method, weighted median-based method, MR-Egger method, and MR-PRESSO method. Similarly, genetically predicted coffee consumption was inversely associated with FBG and 2h-PG levels but not with HbA1c. Sensitivity measures gave similar results without evidence of pleiotropy.

CONCLUSIONS

A genetic predisposition to habitual coffee consumption was inversely associated with T2D prevalence and lower levels of FBG and 2h-PG profiles. Our study warrants further exploration.

Development of a Polygenic Risk Score for BMI to Assess the Genetic Susceptibility to Obesity and Related Diseases in the Korean Population

Hundreds of genetic variants for body mass index (BMI) have been identified from numerous genome-wide association studies (GWAS) in different ethnicities. In this study, we aimed to develop a polygenic risk score (PRS) for BMI for predicting susceptibility to obesity and related traits in the Korean population. For this purpose, we obtained base data resulting from a GWAS on BMI using 57,110 HEXA study subjects from the Korean Genome and Epidemiology Study (KoGES). Subsequently, we calculated PRSs in 13,504 target subjects from the KARE and CAVAS studies of KoGES using the PRSice-2 software. The best-fit PRS for BMI (PRS_BMI) comprising 53,341 SNPs was selected at a p-value threshold of 0.064, at which the model fit had the greatest R² score. The PRS_BMI was tested for its association with obesity-related quantitative traits and diseases in the target dataset. Linear regression analyses demonstrated significant associations of PRS_BMI with BMI, blood pressure, and lipid traits. Logistic regression analyses revealed significant associations of PRS_BMI with obesity, hypertension, and hypo-HDL cholesterolemia. We observed about 2-fold, 1.1-fold, and 1.2-fold risk for obesity, hypertension, and hypo-HDL cholesterolemia, respectively, in the highest-risk group in comparison to the lowest-risk group of PRS_BMI in the test population. We further detected approximately 26.0%, 2.8%, and 3.9% differences in prevalence between the highest and lowest risk groups for obesity, hypertension, and hypo-HDL cholesterolemia, respectively. To predict the incidence of obesity and related diseases, we applied PRS_BMI to the 16-year follow-up data of the KARE study. Kaplan-Meier survival analysis showed that the higher the PRS_BMI, the higher the incidence of dyslipidemia and hypo-HDL cholesterolemia. Taken together, this study demonstrated that a PRS developed for BMI may be a valuable indicator to assess the risk of obesity and related diseases in the Korean population.

Prevalence and clinical correlates of abnormal lipid metabolism in first-episode and drug-naïve patients with major depressive disorder: A large-scale cross-sectional study

OBJECTIVE

Studies have shown an association between abnormal lipid profiles and MDD, but there are few studies on the clinical correlates of lipid abnormalities in patients with major depressive disorder (MDD). The purpose of this study was to investigate the prevalence of abnormal lipid metabolism and its correlates in Chinese first-episode and drug-naïve MDD patients, which has not yet been reported.

METHODS

A total of 1718 outpatients with first-episode and drug-naïve MDD were included. Demographic data were collected by a standardized questionnaire and blood lipid levels were measured, including total cholesterol (TC), triglyceride (TG), low density lipoprotein (LDL-C), high density lipoprotein (HDL-C). The Hamilton Depression Scale (HAMD), Hamilton Anxiety Scale (HAMA), Positive and Negative Syndrome Scale (PANSS) positive subscale, and Clinical Global Impression of Severity Scale (CGI-S) were assessed for each patient.

RESULTS

The prevalence of abnormal lipid metabolism was 72.73% (1301/1718), and the rates of high TC, high TG, high LDL-C and low HDL-C were 51.05% (877/1718), 61.18% (1051/1718), 30.09% (517/1718), 23.40% (402/1718), respectively. Logistic regression showed the risk factors for abnormal lipid metabolism were severe anxiety, HAMD score, CGI-S score, BMI and systolic blood pressure (SBP). Multiple linear regression analysis showed that age at onset, SBP, HAMD score, HAMA score, PANSS positive subscale score, and CGI-S were independently associated with TC levels. BMI, HAMD score, PANSS positive subscale score and CGI-S score were independently associated with TG levels. SBP, HAMD score, PANSS positive subscale score and CGI-S score were independently associated with LDL-C levels. Age of onset, SBP and CGI-S score were independently associated with HDL-C levels.

CONCLUSIONS

The prevalence of abnormal lipid metabolism in first-episode and drug-naïve MDD patients is quite high. The severity of psychiatric symptoms may be closely associated with the presence of abnormal lipid metabolism in patients with MDD.

Impact of polyunsaturated fatty acid supplementation on assisted reproductive technology outcomes: a systematic review

This review explores the impact of polyunsaturated fatty acid (PUFA) supplementation in women undergoing assisted reproductive technology (ART) on reproductive outcomes. A systematic search of English peer-reviewed journals was carried out using MEDLINE, EMBASE, and the Cochrane Library to identify articles published from January 1978 to 2021. The primary outcomes assessed included pregnancy and live birth rates. Secondary outcome measures included: (i) implantation rate; (ii) fertilisation rate; (iii) number of oocytes retrieved; (iv) number of metaphase II (MII) oocytes; (v) blastocyst conversion; and (vi) embryo quality. A total of 4 randomised control trials (RCTs) met the inclusion criteria. There is a lack of high-quality research to support widespread dietary supplementation with PUFAs in women undergoing ART. Prior to its clinical recommendation, there is a need for well-designed RCTs to facilitate an in-depth understanding of PUFA supplementation in women undergoing ART.

Genetic association study identifies genetic variants for non-alcoholic fatty liver without comorbidities in the Korean population

BACKGROUND

Non-alcoholic fatty liver (NAFL) refers to a disease in which fat builds up in the liver, similar to what occurs for those who drink a lot of alcohol, even in cases of not drinking alcohol at all or only in a small amount. Along with non-alcoholic steatohepatitis (NASH), NAFL is a type of non-alcoholic fatty liver disease (NAFLD). Currently, the prevalence of NAFLD is increasing worldwide. A wide range of comorbidities that can increase the risk of NAFLD includes obesity, type 2 diabetes, dyslipidemia, and metabolic syndrome.

OBJECTIVE

This study aimed to discover genetic variants for NAFL in the Korean population.

METHODS

Differing from previous studies, we conducted a genome-wide association study for NAFL in the selected subjects without comorbidities to rule out bias due to the inclusion of confounding effects of comorbidities. We grouped 424 NAFL cases and 5,402 controls from the Korean Genome and Epidemiology Study (KoGES) subjects without comorbidities such as dyslipidemia, type 2 diabetes, and metabolic syndrome. All subjects including cases and controls did not consume alcohol at all, or consumed less than 20 g/day for men and less than 10 g/day for women.

RESULTS

The logistic association analysis adjusting for sex, age, BMI, and waist circumference identified one novel genome-wide significant variant (rs7996045, P = 2.3 × 10-8) for NAFL. This variant was located in the intron of CLDN10 and was not detected using previous conventional approaches in which confounding effects resulting from comorbidities were not considered in the study design stage. In addition, we detected several genetic variants showing suggestive association for NAFL (P < 10-5).

CONCLUSION

The unique strategy in our association analysis of excluding major confounding factors provides, for the first time, an insight into the genuine genetic basis influencing NAFL.

An adaptive test based on principal components for detecting multiple phenotype associations using GWAS summary data

Extensive evidence from genome-wide association studies (GWAS) has shown that jointly analyzing multiple phenotypes can improve the power of the association test compared to the traditional single variant versus single trait approach. Here we propose an adaptive test based on principal components (ATPC) that is powerful and efficient for discovering the association between a single variant and multiple traits. Our method only needs GWAS summary statistics that are often available. We first estimate the trait correlation matrix by LD score regression. Then, based on the correlation matrix, we construct a series of test statistics that contain different numbers of principal components. The ultimate test statistic combines the P values of these principal component-based statistics by using the aggregated Cauchy association test. The analytical P-value of the test statistic can be computed quickly without the permutation process, which is the notable feature of our proposed method. The extensive simulation studies demonstrate that ATPC can control the type I error rates and have powerful and robust performance compared to several existing tests in a wide range of simulation settings. The analysis of the lipids GWAS summary data from the Global Lipids Genetics Consortium shows that ATPC identifies 230 new SNPs that are missed by the original single trait association analysis. By searching the GWAS Catalog, some SNPs and mapped genes identified by ATPC are reported to be associated with lipid traits. Through further analysis for GWAS results, we also find some Gene Ontology terms and biological pathways related to lipids.

Genome-Wide Association Study on Longitudinal Change in Fasting Plasma Glucose in Korean Population

BACKGROUND

Genome-wide association studies (GWAS) on type 2 diabetes mellitus (T2DM) have identified more than 400 distinct genetic loci associated with diabetes and nearly 120 loci for fasting plasma glucose (FPG) and fasting insulin level to date. However, genetic risk factors for the longitudinal deterioration of FPG have not been thoroughly evaluated. We aimed to identify genetic variants associated with longitudinal change of FPG over time.

METHODS

We used two prospective cohorts in Korean population, which included a total of 10,528 individuals without T2DM. GWAS of repeated measure of FPG using linear mixed model was performed to investigate the interaction of genetic variants and time, and meta-analysis was conducted. Genome-wide complex trait analysis was used for heritability calculation. In addition, expression quantitative trait loci (eQTL) analysis was performed using the Genotype-Tissue Expression project.

RESULTS

A small portion (4%) of the genome-wide single nucleotide polymorphism (SNP) interaction with time explained the total phenotypic variance of longitudinal change in FPG. A total of four known genetic variants of FPG were associated with repeated measure of FPG levels. One SNP (rs11187850) showed a genome-wide significant association for genetic interaction with time. The variant is an eQTL for NOC3 like DNA replication regulator (NOC3L) gene in pancreas and adipose tissue. Furthermore, NOC3L is also differentially expressed in pancreatic β-cells between subjects with or without T2DM. However, this variant was not associated with increased risk of T2DM nor elevated FPG level.

CONCLUSION

We identified rs11187850, which is an eQTL of NOC3L, to be associated with longitudinal change of FPG in Korean population.

Interactions between Bitter Taste Receptor Gene Variants and Dietary Intake Are Associated with the Incidence of Type 2 Diabetes Mellitus in Middle-Aged and Older Korean Adults

The relationship between the variants of bitter taste receptor gene TAS2R4, dietary intake, and incidence of type 2 diabetes mellitus (T2DM) remains unclear. Hence, we aimed to examine the association of TAS2R4 rs2233998 variants with T2DM incidence in middle-aged and older Korean adults to understand if their association was modulated by dietary intake. Data of the Ansan-Ansung cohort from the Korean Genome and Epidemiology Study were used in this study. A total of 4552 Korean adults aged 40-69 years with no history of T2DM or cancer at baseline were followed-up for 16 years. Dietary intake was assessed using a 103-item food frequency questionnaire, and new T2DM cases were defined based on the World Health Organization and International Diabetes Federation criteria. Multivariate Cox proportional hazards models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for T2DM incidence. During the mean follow-up period of 11.97 years, 1082 (23.77%) new T2DM cases were identified. Women carrying the TT genotype of TAS2R4 rs2233998 exhibited 1.48 times higher incidence of T2DM (HR: 1.48; 95 CI: 1.13-1.93) than those carrying the CC genotype. TAS2R4 rs2233998 variants were positively associated with the incidence of T2DM among Korean women with high intakes of carbohydrates or sugars and low intakes of fruits or vegetables. TT carrier women in the highest tertile of carbohydrate or sugar intake exhibited an increased incidence of T2DM (HR: 2.08, 95% CI: 1.33-3.27 for carbohydrates; HR: 2.31, 95% CI: 1.53-3.51 for sugars) than CC carrier women. Women carrying the TT genotype in the lowest tertile exhibited an increased incidence of T2DM (HR: 1.55, 95% CI: 1.02-2.37 for vegetables; HR: 1.62, 95% CI: 1.06-2.48 for fruits) than women carrying the CC genotype in the highest tertile of vegetable or fruit consumption. However, no association was observed between TAS2R4 rs2233998 variants and dietary intake with T2DM incidence in Korean men. Our findings suggest that variants of TAS2R4 rs2233998 are associated with T2DM incidence, and their associations are strengthened by excessive intake of carbohydrates or sugars and inadequate intake of fruits or vegetables. Diet encompassing optimal intake of carbohydrates or sugars and high intake of fruits or vegetables may minimize the risk of developing T2DM.

Genetic heterogeneity in cardiovascular disease across ancestries: Insights for mechanisms and therapeutic intervention

Cardiovascular diseases (CVDs) are complex in their aetiology, arising due to a combination of genetics, lifestyle and environmental factors. By nature of this complexity, different CVDs vary in their molecular mechanisms, clinical presentation and progression. Although extensive efforts are being made to develop novel therapeutics for CVDs, genetic heterogeneity is often overlooked in the development process. By considering molecular mechanisms at an individual and ancestral level, a richer understanding of the influence of environmental and lifestyle factors can be gained and more refined therapeutic interventions can be developed. It is therefore expedient to understand the molecular and clinical heterogeneity in CVDs that exists across different populations. In this review, we highlight how the mechanisms underlying CVDs vary across diverse population ancestry groups due to genetic heterogeneity. We then discuss how such genetic heterogeneity is being leveraged to inform therapeutic interventions and personalised medicine, highlighting examples across the CVD spectrum. Finally, we present an overview of how polygenic risk scores and Mendelian randomisation can foster more robust insight into disease mechanisms and therapeutic intervention in diverse populations. Fulfilment of the vision of precision medicine requires more exhaustive leveraging of the genetic variability across diverse ancestry populations to improve our understanding of disease onset, progression and response to therapeutic intervention.

Genomic study of maternal lipid traits in early pregnancy concurs with four known adult lipid loci

BACKGROUND

Blood lipids during pregnancy are associated with cardiovascular diseases and adverse pregnancy outcomes. Genome-wide association studies (GWAS) in predominantly male European ancestry populations have identified genetic loci associated with blood lipid levels. However, the genetic architecture of blood lipids in pregnant women remains poorly understood.

OBJECTIVE

Our goal was to identify genetic loci associated with blood lipid levels among pregnant women from diverse ancestry groups and to evaluate whether previously known lipid loci in predominantly European adults are transferable to pregnant women.

METHODS

The trans-ancestry GWAS were conducted on serum levels of total cholesterol, high-density lipoprotein cholesterol (HDL), low-density lipoprotein cholesterol (LDL) and triglycerides during first trimester among pregnant women from four population groups (608 European-, 623 African-, 552 Hispanic- and 235 East Asian-Americans) recruited in the NICHD Fetal Growth Studies cohort. The four GWAS summary statistics were combined using trans-ancestry meta-analysis approaches that account for genetic heterogeneity among populations.

RESULTS

Loci in CELSR2 and APOE were genome-wide significantly associated (p-value < 5×10-8) with total cholesterol and LDL levels. Loci near CETP and ABCA1 approached genome-wide significant association with HDL (p-value = 2.97×10-7 and 9.71×10-8, respectively). Less than 20% of previously known adult lipid loci were transferable to pregnant women.

CONCLUSION

This trans-ancestry GWAS meta-analysis in pregnant women identified associations that concur with four known adult lipid loci. Limited replication of known lipid-loci from predominantly European study populations to pregnant women underlines the need for genomic studies of lipids in ancestrally diverse pregnant women.

CLINICAL TRIAL REGISTRATION

ClinicalTrials.gov, NCT00912132.

Gamma-glutamyl-leucine levels are causally associated with elevated cardio-metabolic risks

Objective

Gamma-glutamyl dipeptides are bioactive peptides involved in inflammation, oxidative stress, and glucose regulation. Gamma-glutamyl-leucine (Gamma-Glu-Leu) has been extensively reported to be associated with the risk of cardio-metabolic diseases, such as obesity, metabolic syndrome, and type 2 diabetes. However, the causality remains to be uncovered. The aim of this study was to explore the causal-effect relationships between Gamma-Glu-Leu and metabolic risk.

Materials and methods

In this study, 1,289 subjects were included from a cross-sectional survey on metabolic syndrome (MetS) in eastern China. Serum Gamma-Glu-Leu levels were measured by untargeted metabolomics. Using linear regressions, a two-stage genome-wide association study (GWAS) for Gamma-Glu-Leu was conducted to seek its instrumental single nucleotide polymorphisms (SNPs). One-sample Mendelian randomization (MR) analyses were performed to evaluate the causality between Gamma-Glu-Leu and the metabolic risk.

Results

Four SNPs are associated with serum Gamma-Glu-Leu levels, including rs12476238, rs56146133, rs2479714, and rs12229654. Out of them, rs12476238 exhibits the strongest association (Beta = -0.38, S.E. = 0.07 in discovery stage, Beta = -0.29, S.E. = 0.14 in validation stage, combined P-value = 1.04 × 10^-8). Each of the four SNPs has a nominal association with at least one metabolic risk factor. Both rs12229654 and rs56146133 are associated with body mass index, waist circumference (WC), the ratio of WC to hip circumference, blood pressure, and triglyceride (5 × 10^-5 < P < 0.05). rs56146133 also has nominal associations with fasting insulin, glucose, and insulin resistance index (5 × 10^-5 < P < 0.05). Using the four SNPs serving as the instrumental SNPs of Gamma-Glu-Leu, the MR analyses revealed that higher Gamma-Glu-Leu levels are causally associated with elevated risks of multiple cardio-metabolic factors except for high-density lipoprotein cholesterol and low-density lipoprotein cholesterol (P > 0.05).

Conclusion

Four SNPs (rs12476238, rs56146133, rs2479714, and rs12229654) may regulate the levels of serum Gamma-Glu-Leu. Higher Gamma-Glu-Leu levels are causally linked to cardio-metabolic risks. Future prospective studies on Gamma-Glu-Leu are required to explain its role in metabolic disorders.

The contribution of common and rare genetic variants to variation in metabolic traits in 288,137 East Asians

Metabolic traits are heritable phenotypes widely-used in assessing the risk of various diseases. We conduct a genome-wide association analysis (GWAS) of nine metabolic traits (including glycemic, lipid, liver enzyme levels) in 125,872 Korean subjects genotyped with the Korea Biobank Array. Following meta-analysis with GWAS from Biobank Japan identify 144 novel signals (MAF ≥ 1%), of which 57.0% are replicated in UK Biobank. Additionally, we discover 66 rare (MAF < 1%) variants, 94.4% of them co-incident to common loci, adding to allelic series. Although rare variants have limited contribution to overall trait variance, these lead, in carriers, substantial loss of predictive accuracy from polygenic predictions of disease risk from common variant alone. We capture groups with up to 16-fold variation in type 2 diabetes (T2D) prevalence by integration of genetic risk scores of fasting plasma glucose and T2D and the I349F rare protective variant. This study highlights the need to consider the joint contribution of both common and rare variants on inherited risk of metabolic traits and related diseases.

Metabolic diversity in human populations and correlation with genetic and ancestral geographic distances

DNA polymorphic markers and self-defined ethnicity groupings are used to group individuals with shared ancient geographic ancestry. Here we studied whether ancestral relationships between individuals could be identified from metabolic screening data reported by the California newborn screening (NBS) program. NBS data includes 41 blood metabolites measured by tandem mass spectrometry from singleton babies in 17 parent-reported ethnicity groupings. Ethnicity-associated differences identified for 71% of NBS metabolites (29 of 41, Cohen's d &gt; 0.5) showed larger differences in blood levels of acylcarnitines than of amino acids (P &lt; 1e-4). A metabolic distance measure, developed to compare ethnic groupings based on metabolic differences, showed low positive correlation with genetic and ancient geographic distances between the groups' ancestral world populations. Several outlier group pairs were identified with larger genetic and smaller metabolic distances (Black versus White) or with smaller genetic and larger metabolic distances (Chinese versus Japanese) indicating the influence of genetic and of environmental factors on metabolism. Using machine learning, comparison of metabolic profiles between all pairs of ethnic groupings distinguished individuals with larger genetic distance (Black versus Chinese, AUC = 0.96), while genetically more similar individuals could not be separated metabolically (Hispanic versus Native American, AUC = 0.51). Additionally, we identified metabolites informative for inferring metabolic ancestry in individuals from genetically similar populations, which included biomarkers for inborn metabolic disorders (C10:1, C12:1, C3, C5OH, Leucine-Isoleucine). This work sheds new light on metabolic differences in healthy newborns in diverse populations, which could have implications for improving genetic disease screening.

Identification of RNA modification-associated single nucleotide polymorphisms in genomic loci for low-density lipoprotein cholesterol concentrations

Introduction: Genome-wide association studies have identified approximately 1000 lipid-associated loci, but functional variants are less known. Materials & methods: The authors identified RNA modification-related single nucleotide polymorphisms (RNAm-SNPs) in summary data from a genome-wide association study. By applying Mendelian randomization analysis, the authors identified gene expression levels involved in the regulation of RNAm-SNPs on low-density lipoprotein cholesterol (LDL-C) levels. Results: The authors identified 391 RNAm-SNPs that were significantly associated with LDL-C levels. RNAm-SNPs in NPC1L1, LDLR, APOB, MYLIP, LDLRAP1 and ABCA6 were identified. The RNAm-SNPs were associated with gene expression. The expression levels of 112 genes were associated with LDL-C levels, and some of them (e.g., APOB, SMARCA4 and SH2B3) were associated with coronary artery disease. Conclusion: This study identified many RNAm-SNPs in LDL-C loci and elucidated the relationship among the SNPs, gene expression and LDL-C.

The potential effects of HECTD4 variants on fasting glucose and triglyceride levels in relation to prevalence of type 2 diabetes based on alcohol intake

Excessive alcohol intake is an important cause of major public health problem in East Asian countries. Growing evidence suggests that genetic factors are associated with alcohol consumption and the risk for alcohol-associated disease, and these factors contribute to the risk of developing chronic diseases, including diabetes. This study aims to investigate the association of type 2 diabetes with genetic polymorphisms within HECTD4 based on alcohol exposure. We performed a genome-wide association study involving the cohorts of the KoGES-HEXA study (n = 50,028) and Ansan and Ansung study (n = 7,980), both of which are prospective cohort studies in Korea. The top three single-nucleotide polymorphisms (SNPs) of the HECTD4 gene, specifically rs77768175, rs2074356 and rs11066280, were found to be significantly associated with alcohol consumption. We found that individuals carrying the variant allele in these SNPs had lower fasting blood glucose, triglyceride, and GGT levels than those with the wild-type allele. Multiple logistic regression showed that statistically significant associations of HECTD4 gene polymorphisms with an increased risk of type 2 diabetes were found in drinkers. Namely, these SNPs were associated with decreased odds of diabetes in the presence of alcohol consumption. As a result of examining the effect of alcohol on the expression of the HECTD4 gene, ethanol increased the expression of HECTD4 in cells, but the level was decreased by NAC treatment. Similar results were obtained from liver samples of mice treated with alcohol. Moreover, a loss of HECTD4 resulted in reduced levels of CYP2E1 and lipogenic gene expression in ethanol-treated cells, while the level of ALDH2 expression increased, indicating a reduction in ethanol-induced hepatotoxicity.

Simultaneous test and estimation of total genetic effect in eQTL integrative analysis through mixed models

Integration of expression quantitative trait loci (eQTL) into genome-wide association studies (GWASs) is a promising manner to reveal functional roles of associated single-nucleotide polymorphisms (SNPs) in complex phenotypes and has become an active research field in post-GWAS era. However, how to efficiently incorporate eQTL mapping study into GWAS for prioritization of causal genes remains elusive. We herein proposed a novel method termed as Mixed transcriptome-wide association studies (TWAS) and mediated Variance estimation (MTV) by modeling the effects of cis-SNPs of a gene as a function of eQTL. MTV formulates the integrative method and TWAS within a unified framework via mixed models and therefore includes many prior methods/tests as special cases. We further justified MTV from another two statistical perspectives of mediation analysis and two-stage Mendelian randomization. Relative to existing methods, MTV is superior for pronounced features including the processing of direct effects of cis-SNPs on phenotypes, the powerful likelihood ratio test for assessment of joint effects of cis-SNPs and genetically regulated gene expression (GReX), two useful quantities to measure relative genetic contributions of GReX and cis-SNPs to phenotypic variance, and the computationally efferent parameter expansion expectation maximum algorithm. With extensive simulations, we identified that MTV correctly controlled the type I error in joint evaluation of the total genetic effect and proved more powerful to discover true association signals across various scenarios compared to existing methods. We finally applied MTV to 41 complex traits/diseases available from three GWASs and discovered many new associated genes that had otherwise been missed by existing methods. We also revealed that a small but substantial fraction of phenotypic variation was mediated by GReX. Overall, MTV constructs a robust and realistic modeling foundation for integrative omics analysis and has the advantage of offering more attractive biological interpretations of GWAS results.

Analyzing the Korean reference genome with meta-imputation increased the imputation accuracy and spectrum of rare variants in the Korean population

Genotype imputation is essential for enhancing the power of association-mapping and discovering rare and indels that are missed by most genotyping arrays. Imputation analysis can be more accurate with a population-specific reference panel or a multi-ethnic reference panel with numerous samples. The National Institute of Health, Republic of Korea, initiated the Korean Reference Genome (KRG) project to identify variants in whole-genome sequences of ∼20,000 Korean participants. In the pilot phase, we analyzed the data from 1,490 participants. The genetic characteristics and imputation performance of the KRG were compared with those of the 1,000 Genomes Project Phase 3, GenomeAsia 100K Project, ChinaMAP, NARD, and TOPMed reference panels. For comparison analysis, genotype panels were artificially generated using whole-genome sequencing data from combinations of four different ancestries (Korean, Japanese, Chinese, and European) and two population-specific optimized microarrays (Korea Biobank Array and UK Biobank Array). The KRG reference panel performed best for the Korean population (R ² = 0.78-0.84, percentage of well-imputed is 91.9% for allele frequency >5%), although the other reference panels comprised a larger number of samples with genetically different background. By comparing multiple reference panels and multi-ethnic genotype panels, optimal imputation was obtained using reference panels from genetically related populations and a population-optimized microarray. Indeed, the reference panels of KRG and TOPMed showed the best performance when applied to the genotype panels of KBA (R ² = 0.84) and UKB (R ² = 0.87), respectively. Using a meta-imputation approach to merge imputation results from different reference panels increased the imputation accuracy for rare variants (∼7%) and provided additional well-imputed variants (∼20%) with comparable imputation accuracy to that of the KRG. Our results demonstrate the importance of using a population-specific reference panel and meta-imputation to assess a substantial number of accurately imputed rare variants.

Genome-wide association study and genomic heritabilities for blood protein levels in Lori-Bakhtiari sheep

Serum protein levels are related to physiological and pathological status of animals and could be affected by both genetic and environmental factors. This study aimed to evaluate genetic variation of serum protein profile in sheep. Blood samples were randomly collected from 96 Lori-Bakhtiari ewes, a heavy meat-type breed. Total protein, albumin, globulin, α1, α2, β and γ globulins and IgG levels were measured in blood serum. The samples were genotyped using the Illumina OvineSNP50 BeadChip. The studied traits adjusted for age, birth type, birth season and estimate of breeding value for body weight were considered as pseudo-phenotypes in genome-wide association analysis. In the GWAS model, the first five principal components were fitted as covariates to correct the biases due to possible population stratification. The Plink, R and GCTA software were used for genome-wide association analysis, construction of Q-Q and Manhattan plots and estimation of genetic variances, respectively. Noticeable genomic heritabilities ± SE were estimated for total and γ globulins (0.868 ± 0.262 and 0.831 ± 0.364, respectively), but other protein fractions had zero or close to zero estimates. Based on the Bonferroni adjusted p values, four QTLs located on 181.7 Mbp of OAR3, 107.7 Mbp of OAR4, 86.3 Mbp of OAR7 and 83.0 Mbp of OAR8 were significantly associated with α1, β, β and γ globulins, respectively. The results showed that the PKP2, IGF2R, SLC22A1 and SLC22A2 genes could be considered as candidate genes for blood serum proteins. The present study showed significant genetic variations of some blood protein fractions.

Genetic Variation in the Mitochondrial Glycerol-3-Phosphate Acyltransferase Is Associated With Liver Injury

BACKGROUND AND AIMS

Most of the genetic basis of chronic liver disease remains undiscovered.

APPROACH AND RESULTS

To identify genetic loci that modulate the risk of liver injury, we performed genome-wide association studies on circulating levels of alanine aminotransferase (ALT), aspartate aminotransferase (AST), alkaline phosphatase (ALP), and total bilirubin across 312,671 White British participants in the UK Biobank. We focused on variants associated with elevations in all four liver biochemistries at genome-wide significance (P < 5 × 10-8 ) and that replicated using Mass General Brigham Biobank in 19,323 European ancestry individuals. We identified a genetic locus in mitochondrial glycerol-3-phosphate acyltransferase (GPAM rs10787429) associated with increased levels of ALT (P = 1.4 × 10-30 ), AST (P = 3.6 × 10-10 ), ALP (P = 9.5 × 10-30 ), and total bilirubin (P = 2.9 × 10-12 ). This common genetic variant was also associated with an allele dose-dependent risk of alcohol-associated liver disease (odd ratio [OR] = 1.34, P = 2.6 × 10-5 ) and fatty liver disease (OR = 1.18, P = 5.8 × 10-4 ) by International Classification of Diseases, 10th Revision codes. We identified significant interactions between GPAM rs10787429 and elevated body mass index in association with ALT and AST (P = 7.1 × 10-9 and 3.95 × 10-8 , respectively), as well as between GPAM rs10787429 and weekly alcohol consumption in association with ALT, AST, and alcohol-associated liver disease (P = 4.0 × 10-2 , 1.6 × 10-2 , and 1.3 × 10-2 , respectively). Unlike previously described genetic variants that are associated with an increased risk of liver injury but confer a protective effect on circulating lipids, GPAM rs10787429 was associated with an increase in total cholesterol (P = 2.0 × 10-17 ), LDL cholesterol (P = 2.0 × 10-10 ), and HDL cholesterol (P = 6.6 × 10-37 ). Single-cell RNA-sequencing data demonstrated hepatocyte-predominant expression of GPAM in cells that co-express genes related to VLDL production (P = 9.4 × 10-103 ).

CONCLUSIONS

Genetic variation in GPAM is associated with susceptibility to liver injury. GPAM may represent a therapeutic target in chronic liver disease.

Replication of European hypertension associations in a case-control study of 9,534 African Americans

Objective

Hypertension is more prevalent in African Americans (AA) than other ethnic groups. Genome-wide association studies (GWAS) have identified loci associated with hypertension and other cardio-metabolic traits like type 2 diabetes, coronary artery disease, and body mass index (BMI), however the AA population is underrepresented in these studies. In this study, we examined a large AA cohort for the generalizability of 14 Metabochip array SNPs with previously reported European hypertension associations.

Methods

To evaluate associations, we analyzed genotype data of 14 SNPs for their associations with a diagnosis of hypertension, systolic blood pressure (SBP), and diastolic blood pressure (DBP) in a case-control study of an AA population (N = 9,534). We also performed an age-stratified analysis (>30, 30≥59 and ≥60 years) following the hypertension definition described by the 8th Joint National Committee (JNC). Associations were adjusted for BMI, age, age², sex, clinical confounders, and genetic ancestry using multivariable regression models to estimate odds ratios (ORs) and beta-coefficients. Analyses stratified by sex were also conducted. Meta-analyses (including both BioVU and COGENT-BP cohorts) were performed using a random-effects model.

Results

We found rs880315 to be associated with systolic hypertension (SBP≥140 mmHg) in the entire cohort (OR = 1.14, p = 0.003) and within women only (OR = 1.16, p = 0.012). Variant rs17080093 associated with lower SBP and DBP (β = -2.99, p = 0.0352 and - β = 1.69, p = 0.0184) among younger individuals, particularly in younger women (β = -3.92, p = 0.0025 and β = -1.87, p = 0.0241 for SBP and DBP respectively). SNP rs1530440 associated with higher SBP and DBP measurements (younger individuals β = 4.1, p = 0.039 and β = 2.5, p = 0.043 for SBP and DBP; (younger women β = 4.5, p = 0.025 and β = 2.9, p = 0.028 for SBP and DBP), and hypertension risk in older women (OR = 1.4, p = 0.050). rs16948048 increases hypertension risk in younger individuals (OR = 1.31, p = 0.011). Among mid-age women rs880315 associated with higher risk of hypertension (OR = 1.20, p = 0.027). rs1361831 associated with DBP (β = -1.96, p = 0.02) among individuals older than 60 years. rs3096277 increases hypertension risk among older individuals (OR = 1.26 p = 0.0015), however, this variant also reduces SBP among younger women (β = -2.63, p = 0.0102).

Conclusion

These findings suggest that European-descent and AA populations share genetic loci that contribute to blood pressure traits and hypertension. However, the OR and beta-coefficient estimates differ, and some are age-dependent. Additional genetic studies of hypertension in AA are warranted to identify new loci associated with hypertension and blood pressure traits in this population.

A Genome-Wide Association Study of a Korean Population Identifies Genetic Susceptibility to Hypertension Based on Sex-Specific Differences

Genome-wide association studies have expanded our understanding of the genetic variation of hypertension. Hypertension and blood pressure are influenced by sex-specific differences; therefore, genetic variants may have sex-specific effects on phenotype. To identify the genetic factors influencing the sex-specific differences concerning hypertension, we conducted a heterogeneity analysis of a genome-wide association study (GWAS) on 13,926 samples from a Korean population. Using the Illumina exome chip data of the population, we performed GWASs of the male and female population independently and applied a statistical test that identified heterogeneous effects of the variants between the two groups. To gain information about the biological implication of the genetic heterogeneity, we used gene set enrichment analysis with GWAS catalog and pathway gene sets. The heterogeneity analysis revealed that the rs11066015 of ACAD10 was a significant locus that had sex-specific genetic effects on the development of hypertension. The rs2074356 of HECTD4 also showed significant genetic heterogeneity in systolic blood pressure. The enrichment analysis showed significant results that are consistent with the pathophysiology of hypertension. These results indicate a sex-specific genetic susceptibility to hypertension that should be considered in future genetic studies of hypertension.

Global Burden of Disease Study 2019 suggests that metabolic risk factors are the leading drivers of the burden of ischemic heart disease

Metabolic dysfunction is becoming a predominant risk for the development of many comorbidities. Ischemic heart disease (IHD) still imposes the highest disease burden among all cardiovascular diseases worldwide. However, the contributions of metabolic risk factors to IHD over time have not been fully characterized. Here, we analyzed the global disease burden of IHD and 15 associated general risk factors from 1990 to 2019 by applying the methodology framework of the Global Burden of Disease Study. We found that the global death cases due to IHD increased steadily during that time frame, while the mortality rate gradually declined. Notably, metabolic risk factors have become the leading driver of IHD, which also largely contributed to the majority of IHD-related deaths shifting from developed countries to developing countries. These findings suggest an urgent need to implement effective measures to control metabolic risk factors to prevent further increases in IHD-related deaths.

Genetic variants associated with serum alanine aminotransferase levels among patients with hepatitis C virus infection: A genome-wide association study

Information on genetic variants associated with elevated serum alanine aminotransferase (ALT) levels remains limited. A genome-wide association study was performed to identify single-nucleotide polymorphisms (SNPs) associated with ALT levels. The ALT-associated SNP was further evaluated for hepatocellular carcinoma (HCC) risk. A cohort of 892 anti-HCV seropositive patients was used for genome-wide SNP array to examine the associations with baseline ALT levels. SNPs <10^-5 were further tested for associations with serial ALT levels then validated in 486 anti-HCV seropositives. Multinomial logistic regressions were used to estimate odds ratios (ORs) and 95% confidence intervals of SNPs associated with ALT. The SNP was evaluated for HCC risk by using Cox's proportional hazards models. After quality control, 803 participants with 564,464 SNPs were included in the analysis. Of these, 12 SNPs were associated with ALT (p < 10^-5 ). Among the participants, 158 (19.7%) had ALT persistently ≤15 U/L, 327 (40.7%) ever >15 U/L but never >45 U/L, and 318 (39.6%) ever >45 U/L during follow-up. The rs568800 was associated with serial ALT levels, and this was replicated in the external population significantly (p < .05). The A allele (vs C) of rs568800 was associated with ALT >15 U/L but ≤45 U/L and ALT >45 U/L, with the adjusted ORs of 1.41 (1.11-1.78) and 1.86 (1.34-2.60), respectively. The adjusted HRs for HCC were 2.09 (0.90-4.89) for AC and 2.64 (1.13-6.17) for AA (CC as a reference). In conclusion, the rs568800 was associated with serum ALT levels and HCC risk. Clinical utility should be evaluated among patients who have received antivirals.

GWAS of serum ALT and AST reveals an association of SLC30A10 Thr95Ile with hypermanganesemia symptoms

Understanding mechanisms of hepatocellular damage may lead to new treatments for liver disease, and genome-wide association studies (GWAS) of alanine aminotransferase (ALT) and aspartate aminotransferase (AST) serum activities have proven useful for investigating liver biology. Here we report 100 loci associating with both enzymes, using GWAS across 411,048 subjects in the UK Biobank. The rare missense variant SLC30A10 Thr95Ile (rs188273166) associates with the largest elevation of both enzymes, and this association replicates in the DiscovEHR study. SLC30A10 excretes manganese from the liver to the bile duct, and rare homozygous loss of function causes the syndrome hypermanganesemia with dystonia-1 (HMNDYT1) which involves cirrhosis. Consistent with hematological symptoms of hypermanganesemia, SLC30A10 Thr95Ile carriers have increased hematocrit and risk of iron deficiency anemia. Carriers also have increased risk of extrahepatic bile duct cancer. These results suggest that genetic variation in SLC30A10 adversely affects more individuals than patients with diagnosed HMNDYT1.

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

AIMS/HYPOTHESIS

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

METHODS

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

RESULTS

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

CONCLUSIONS/INTERPRETATION

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

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

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

SIX2 Regulates Human β Cell Differentiation from Stem Cells and Functional Maturation In Vitro

Generation of insulin-secreting β cells in vitro is a promising approach for diabetes cell therapy. Human embryonic stem cells (hESCs) and human induced pluripotent stem cells (hiPSCs) are differentiated to β cells (SC-β cells) and mature to undergo glucose-stimulated insulin secretion, but molecular regulation of this defining β cell phenotype is unknown. Here, we show that maturation of SC-β cells is regulated by the transcription factor SIX2. Knockdown (KD) or knockout (KO) of SIX2 in SC-β cells drastically limits glucose-stimulated insulin secretion in both static and dynamic assays, along with the upstream processes of cytoplasmic calcium flux and mitochondrial respiration. Furthermore, SIX2 regulates the expression of genes associated with these key β cell processes, and its expression is restricted to endocrine cells. Our results demonstrate that expression of SIX2 influences the generation of human SC-β cells in vitro.

Velazco-Cruz et al. characterize the role of SIX2 in stem cell differentiation to β cells. SIX2 expression is restricted to late-stage endocrine cells. Generation of β cells does not require SIX2, but lack of SIX2 impairs maturation, as assessed by glucose-stimulated insulin secretion, calcium flux, mitochondrial respiration, and gene expression.

A Genome-Wide Association Study of Novel Genetic Variants Associated With Anthropometric Traits in Koreans

Most previous genome-wide association studies (GWAS) have identified genetic variants associated with anthropometric traits. However, most of the evidence were reported in European populations. Anthropometric traits such as height and body fat distribution are significantly affected by gender and genetic factors. Here we performed GWAS involving 64,193 Koreans to identify the genetic factors associated with anthropometric phenotypes including height, weight, body mass index, waist circumference, hip circumference, and waist-to-hip ratio. We found nine novel single-nucleotide polymorphisms (SNPs) and 59 independent genetic signals in genomic regions that were reported previously. Of the 19 SNPs reported previously, eight genetic variants at RP11-513I15.6 and one genetic variant at the RP11-977G19.10 region and six Asian-specific genetic variants were newly found. We compared our findings with those of previous studies in other populations. Five overlapping genetic regions (PAN2, ANKRD52, RNF41, HGMA1, and C6orf106) had been reported previously but none of the SNPs were independently identified in the current study. Seven of the nine newly found novel loci associated with height in women revealed a statistically significant skeletal expression of quantitative trait loci. Our study provides additional insight into the genetic effects of anthropometric phenotypes in East Asians.

Pancreatic Pseudoislets: An Organoid Archetype for Metabolism Research

Pancreatic islets are vital endocrine regulators of systemic metabolism, and recent investigations have increasingly focused on understanding human islet biology. Studies of isolated human islets have advanced understanding of the development, function, and regulation of cells comprising islets, especially pancreatic α- and β-cells. However, the multicellularity of the intact islet has stymied specific experimental approaches-particularly in genetics and cell signaling interrogation. This barrier has been circumvented by the observation that islet cells can survive dispersion and reaggregate to form "pseudoislets," organoids that retain crucial physiological functions, including regulated insulin and glucagon secretion. Recently, exciting advances in the use of pseudoislets for genetics, genomics, islet cell transplantation, and studies of intraislet signaling and islet cell interactions have been reported by investigators worldwide. Here we review molecular and cellular mechanisms thought to promote islet cell reaggregation, summarize methods that optimize pseudoislet development, and detail recent insights about human islet biology from genetic and transplantation-based pseudoislet experiments. Owing to robust, international programs for procuring primary human pancreata, pseudoislets should serve as both a durable paradigm for primary organoid studies and as an engine of discovery for islet biology, diabetes, and metabolism research.

CRISPR-based genome editing in primary human pancreatic islet cells

Gene targeting studies in primary human islets could advance our understanding of mechanisms driving diabetes pathogenesis. Here, we demonstrate successful genome editing in primary human islets using clustered regularly interspaced short palindromic repeats (CRISPR) and CRISPR-associated protein 9 (Cas9). CRISPR-based targeting efficiently mutated protein-coding exons, resulting in acute loss of islet β-cell regulators, like the transcription factor PDX1 and the KATP channel subunit KIR6.2, accompanied by impaired β-cell regulation and function. CRISPR targeting of non-coding DNA harboring type 2 diabetes (T2D) risk variants revealed changes in ABCC8, SIX2 and SIX3 expression, and impaired β-cell function, thereby linking regulatory elements in these target genes to T2D genetic susceptibility. Advances here establish a paradigm for genetic studies in human islet cells, and reveal regulatory and genetic mechanisms linking non-coding variants to human diabetes risk.

Converging vulnerability factors for compulsive food and drug use

Highly palatable foods and substance of abuse have intersecting neurobiological, metabolic and behavioral effects relevant for understanding vulnerability to conditions related to food (e.g., obesity, binge eating disorder) and drug (e.g., substance use disorder) misuse. Here, we review data from animal models, clinical populations and epidemiological evidence in behavioral, genetic, pathophysiologic and therapeutic domains. Results suggest that consumption of highly palatable food and drugs of abuse both impact and conversely are regulated by metabolic hormones and metabolic status. Palatable foods high in fat and/or sugar can elicit adaptation in brain reward and withdrawal circuitry akin to substances of abuse. Intake of or withdrawal from palatable food can impact behavioral sensitivity to drugs of abuse and vice versa. A robust literature suggests common substrates and roles for negative reinforcement, negative affect, negative urgency, and impulse control deficits, with both highly palatable foods and substances of abuse. Candidate genetic risk loci shared by obesity and alcohol use disorders have been identified in molecules classically associated with both metabolic and motivational functions. Finally, certain drugs may have overlapping therapeutic potential to treat obesity, diabetes, binge-related eating disorders and substance use disorders. Taken together, data are consistent with the hypotheses that compulsive food and substance use share overlapping, interacting substrates at neurobiological and metabolic levels and that motivated behavior associated with feeding or substance use might constitute vulnerability factors for one another. This article is part of the special issue on 'Vulnerabilities to Substance Abuse'.

Progress in Defining the Genetic Contribution to Type 2 Diabetes in Individuals of East Asian Ancestry

PURPOSE OF REVIEW

Prevalence of type 2 diabetes (T2D) and progression of complications differ between worldwide populations. While obesity is a major contributing risk factor, variations in physiological manifestations, e.g., developing T2D at lower body mass index in some populations, suggest other contributing factors. Early T2D genetic associations were mostly discovered in European ancestry populations. This review describes the progression of genetic discoveries associated with T2D in individuals of East Asian ancestry in the last 10 years and highlights the shared genetic susceptibility between the population groups and additional insights into genetic contributions to T2D.

RECENT FINDINGS

Through increased sample size and power, new genetic associations with T2D were discovered in East Asian ancestry populations, often with higher allele frequencies than European ancestry populations. As we continue to generate maps of T2D-associated variants across diverse populations, there will be a critical need to expand and diversify other omics resources to enable integration for clinical translation.

Modeling different types of diabetes using human pluripotent stem cells

Diabetes mellitus (DM) is a metabolic disease characterized by chronic hyperglycemia as a result of progressive loss of pancreatic β cells, which could lead to several debilitating complications. Different paths, triggered by several genetic and environmental factors, lead to the loss of pancreatic β cells and/or function. Understanding these many paths to β cell damage or dysfunction could help in identifying therapeutic approaches specific for each path. Most of our knowledge about diabetes pathophysiology has been obtained from studies on animal models, which do not fully recapitulate human diabetes phenotypes. Currently, human pluripotent stem cell (hPSC) technology is a powerful tool for generating in vitro human models, which could provide key information about the disease pathogenesis and provide cells for personalized therapies. The recent progress in generating functional hPSC-derived β cells in combination with the rapid development in genomic and genome-editing technologies offer multiple options to understand the cellular and molecular mechanisms underlying the development of different types of diabetes. Recently, several in vitro hPSC-based strategies have been used for studying monogenic and polygenic forms of diabetes. This review summarizes the current knowledge about different hPSC-based diabetes models and how these models improved our current understanding of the pathophysiology of distinct forms of diabetes. Also, it highlights the progress in generating functional β cells in vitro, and discusses the current challenges and future perspectives related to the use of the in vitro hPSC-based strategies.

Genome-wide association study of serum liver enzymes implicates diverse metabolic and liver pathology

Serum liver enzyme concentrations are the most frequently-used laboratory markers of liver disease, a major cause of mortality. We conduct a meta-analysis of genome-wide association studies of liver enzymes from UK BioBank and BioBank Japan. We identified 160 previously-unreported independent alanine aminotransferase, 190 aspartate aminotransferase, and 199 alkaline phosphatase genome-wide significant associations, with some affecting multiple different enzymes. Associated variants implicate genes that demonstrate diverse liver cell type expression and promote a range of metabolic and liver diseases. These findings provide insight into the pathophysiology of liver and other metabolic diseases that are associated with serum liver enzyme concentrations.

Serum liver enzymes are used as markers of liver disease, their concentration influenced in part by genetic factors. Here the authors meta-analyse genome-wide association studies on the UK Biobank and BioBank Japan to evaluate the association of three liver enzymes with liver and other metabolic diseases.

SIX2 and SIX3 coordinately regulate functional maturity and fate of human pancreatic β cells

The physiological functions of many vital tissues and organs continue to mature after birth, but the genetic mechanisms governing this postnatal maturation remain an unsolved mystery. Human pancreatic β cells produce and secrete insulin in response to physiological cues like glucose, and these hallmark functions improve in the years after birth. This coincides with expression of the transcription factors SIX2 and SIX3, whose functions in native human β cells remain unknown. Here, we show that shRNA-mediated SIX2 or SIX3 suppression in human pancreatic adult islets impairs insulin secretion. However, transcriptome studies revealed that SIX2 and SIX3 regulate distinct targets. Loss of SIX2 markedly impaired expression of genes governing β-cell insulin processing and output, glucose sensing, and electrophysiology, while SIX3 loss led to inappropriate expression of genes normally expressed in fetal β cells, adult α cells, and other non-β cells. Chromatin accessibility studies identified genes directly regulated by SIX2. Moreover, β cells from diabetic humans with impaired insulin secretion also had reduced SIX2 transcript levels. Revealing how SIX2 and SIX3 govern functional maturation and maintain developmental fate in native human β cells should advance β-cell replacement and other therapeutic strategies for diabetes.

KRGDB: the large-scale variant database of 1722 Koreans based on whole genome sequencing

Since 2012, the Center for Genome Science of the Korea National Institute of Health (KNIH) has been sequencing complete genomes of 1722 Korean individuals. As a result, more than 32 million variant sites have been identified, and a large proportion of the variant sites have been detected for the first time. In this article, we describe the Korean Reference Genome Database (KRGDB) and its genome browser. The current version of our database contains both single nucleotide and short insertion/deletion variants. The DNA samples were obtained from four different origins and sequenced in different sequencing depths (10× coverage of 63 individuals, 20× coverage of 194 individuals, combined 10× and 20× coverage of 135 individuals, 30× coverage of 230 individuals and 30× coverage of 1100 individuals). The major features of the KRGDB are that it contains information on the Korean genomic variant frequency, frequency difference between the Korean and other populations and the variant functional annotation (such as regulatory elements in ENCODE regions and coding variant functions) of the variant sites. Additionally, we performed the genome-wide association study (GWAS) between Korean genome variant sites for the 30×230 individuals and three major common diseases (diabetes, hypertension and metabolic syndrome). The association results are displayed on our browser. The KRGDB uses the MySQL database and Apache-Tomcat web server adopted with Java Server Page (JSP) and is freely available at http://coda.nih.go.kr/coda/KRGDB/index.jsp.

Availability: http://coda.nih.go.kr/coda/KRGDB/index.jsp

The Liability Threshold Model for Predicting the Risk of Cardiovascular Disease in Patients with Type 2 Diabetes: A Multi-Cohort Study of Korean Adults

Personalized risk prediction for diabetic cardiovascular disease (DCVD) is at the core of precision medicine in type 2 diabetes (T2D). We first identified three marker sets consisting of 15, 47, and 231 tagging single nucleotide polymorphisms (tSNPs) associated with DCVD using a linear mixed model in 2378 T2D patients obtained from four population-based Korean cohorts. Using the genetic variants with even modest effects on phenotypic variance, we observed improved risk stratification accuracy beyond traditional risk factors (AUC, 0.63 to 0.97). With a cutoff point of 0.21, the discrete genetic liability threshold model consisting of 231 SNPs (GLT₂₃₁) correctly classified 87.7% of 2378 T2D patients as high or low risk of DCVD. For the same set of SNP markers, the GLT and polygenic risk score (PRS) models showed similar predictive performance, and we observed consistency between the GLT and PRS models in that the model based on a larger number of SNP markers showed much-improved predictability. In silico gene expression analysis, additional information was provided on the functional role of the genes identified in this study. In particular, HDAC4, CDKN2B, CELSR2, and MRAS appear to be major hubs in the functional gene network for DCVD. The proposed risk prediction approach based on the liability threshold model may help identify T2D patients at high CVD risk in East Asian populations with further external validations.

Relationship between serum triglyceride to high-density lipoprotein cholesterol ratio and sarcopenia occurrence rate in community-dwelling Chinese adults

Background

A study conducted on elderly Korean men showed that a high serum triglyceride to high-density lipoprotein cholesterol (TG/HDL-C) ratio was associated with a high risk of developing sarcopenia. We aimed to determine such an association in community-dwelling Chinese adults.

Methods

From May 2016 to August 2017, we conducted a cross-sectional study on Chinese adults at the First Affiliated Hospital of Wenzhou Medical University. Univariate and multivariate logistic regression analyses were applied to evaluate a possible relationship between TG/HDL-C ratio and sarcopenia occurrence.

Results

We included 2613 adults in this study, with 13.85% presenting with sarcopenia. The odds ratios (ORs) for TG and HDL-C were 0.67 (95% confidence interval [CI]: 0.51–0.87), and 1.97 (95% CI: 1.49–2.61), respectively. Moreover, TG/HDL-C ratio was independently associated with sarcopenia status (OR: 0.63; 95% CI: 0.49–0.81).

Conclusions

We found that TG and HDL-C were, respectively, negatively and positively associated with sarcopenia occurrence rate in community-dwelling Chinese adults. However, a negative association was found between sarcopenia occurrence rate and TG/HDL-C ratio.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12944-020-01422-4.

Association of low urine pH as a metabolic feature with abdominal obesity

Objective

Low urine pH (LUP) is not only affected by environmental factors, but is also a feature of metabolic syndrome (MS), which is characterized by insulin resistance, abdominal obesity, dyslipidaemia and hypertension. However, it is unclear which factors contribute most to urine acidity. This study investigated factors influencing LUP and the link between LUP and metabolic traits in South Korea.

Methods

Participants were middle-aged subjects (age, 52.2 ± 8.9 years; average body mass index, 24.6 ± 3.2 kg/m²), of whom 4,626 had urine pH of 5.0 and were assigned to the LUP group and 4,185 had urine pH > 5.0 and were assigned to the control group. The association between LUP and various phenotypes, including environmental and metabolic traits, was analysed.

Results

LUP was significantly associated with MS diagnostic components and with environmental exposures such as smoking, alcohol intake and low-fibre diet. Multivariate analysis showed that the waist-to-hip ratio was the best predictor for LUP compared with other MS components (OR: 2.439).

Conclusions

LUP is an indicator of MS and is mainly related to the MS diagnostic criterion of abdominal obesity, even after adjusting for environmental influences on urine acidity.

GENetic characteristics and REsponse to lipid-lowering therapy in familial hypercholesterolemia: GENRE-FH study

Among the 146 patients enrolled in the Korean FH registry, 83 patients who had undergone appropriate LLT escalation and were followed-up for ≥ 6 months were analyzed for pathogenic variants (PVs). The achieved percentage of expected low-density lipoprotein-cholesterol (LDL-C) reduction (primary variable) and achievement rates of LDL-C < 70 mg/dL were assessed. The correlations between the treatment response and the characteristics of PVs, and the weighted 4 SNP-based score were evaluated. The primary variables were significantly lower in the PV-positive patients than in the PV-negative patients (p = 0.007). However, the type of PV did not significantly correlate with the primary variable. The achievement rates of LDL-C < 70 mg/dL was very low, regardless of the PV characteristics. Patients with a higher 4-SNP score showed a lower primary variable (R² = 0.045, p = 0.048). Among evolocumab users, PV-negative patients or those with only defective PVs revealed higher primary variable, whereas patients with at least one null PV showed lower primary variables. The adjusted response of patients with FH to LLT showed significant associations with PV positivity and 4-SNP score. These results may be helpful in managing FH patients with diverse genetic backgrounds.

A Genome-Wide Association Study Identifies the Association between the 12q24 Locus and Black Tea Consumption in Japanese Populations

Several genome-wide association studies (GWASs) have reported the association between genetic variants and the habitual consumption of foods and drinks; however, no association data are available regarding the consumption of black tea. The present study aimed to identify genetic variants associated with black tea consumption in 12,258 Japanese participants. Data on black tea consumption were collected by a self-administered questionnaire, and genotype data were obtained from a single nucleotide polymorphism array. In the discovery GWAS, two loci met suggestive significance (p < 1.0 × 10^-6). Three genetic variants (rs2074356, rs144504271, and rs12231737) at 12q24 locus were also significantly associated with black tea consumption in the replication stage (p < 0.05) and during the meta-analysis (p < 5.0 × 10^-8). The association of rs2074356 with black tea consumption was slightly attenuated by the additional adjustment for alcohol drinking frequency. In conclusion, genetic variants at the 12q24 locus were associated with black tea consumption in Japanese populations, and the association is at least partly mediated by alcohol drinking frequency.

Interaction between the genetic risk score and dietary protein intake on cardiometabolic traits in Southeast Asian

Background

Cardiometabolic diseases are complex traits which are influenced by several single nucleotide polymorphisms (SNPs). Thus, analysing the combined effects of multiple gene variants might provide a better understanding of disease risk than using a single gene variant approach. Furthermore, studies have found that the effect of SNPs on cardiometabolic traits can be influenced by lifestyle factors, highlighting the importance of analysing gene-lifestyle interactions.

Aims

In the present study, we investigated the association of 15 gene variants with cardiometabolic traits and examined whether these associations were modified by lifestyle factors such as dietary intake and physical activity.

Methods

The study included 110 Minangkabau women [aged 25–60 years and body mass index (BMI) 25.13 ± 4.2 kg/m²] from Padang, Indonesia. All participants underwent a physical examination followed by anthropometric, biochemical and dietary assessments and genetic tests. A genetic risk score (GRS) was developed based on 15 cardiometabolic disease-related SNPs. The effect of GRS on cardiometabolic traits was analysed using general linear models. GRS-lifestyle interactions on continuous outcomes were tested by including the interaction term (e.g. lifestyle factor*GRS) in the regression model. Models were adjusted for age, BMI and location (rural or urban), wherever appropriate.

Results

There was a significant association between GRS and BMI, where individuals carrying 6 or more risk alleles had higher BMI compared to those carrying 5 or less risk alleles (P = 0.018). Furthermore, there were significant interactions of GRS with protein intake on waist circumference (WC) and triglyceride concentrations (P_interaction = 0.002 and 0.003, respectively). Among women who had a lower protein intake (13.51 ± 1.18% of the total daily energy intake), carriers of six or more risk alleles had significantly lower WC and triglyceride concentrations compared with carriers of five or less risk alleles (P = 0.0118 and 0.002, respectively).

Conclusions

Our study confirmed the association of GRS with higher BMI and further showed a significant effect of the GRS on WC and triglyceride levels through the influence of a low-protein diet. These findings suggest that following a lower protein diet, particularly in genetically predisposed individuals, might be an effective approach for addressing cardiometabolic diseases among Southeast Asian women.