A large-scale genome-wide association study of Asian populations uncovers genetic factors influencing eight quantitative traits. Nat Genet. 2009;41:527-534. [PMID: 19396169 DOI: 10.1038/ng.357]

Multipartite network analysis to identify environmental and genetic associations of metabolic syndrome in the Korean population

Network analysis has become a crucial tool in genetic research, enabling the exploration of associations between genes and diseases. Its utility extends beyond genetics to include the assessment of environmental factors. Unipartite network analysis is commonly used in genomics to visualize initial insights and relationships among variables. Syndromic diseases, such as metabolic syndrome, are characterized by the simultaneous occurrence of various signs, symptoms, and clinicopathological features. Metabolic syndrome encompasses hypertension, diabetes, obesity, and dyslipidemia, and both genetic and environmental factors contribute to its development. Given that relevant data often consist of distinct sets of variables, a more intuitive visualization method is needed. This study applied multipartite network analysis as an effective method to understand the associations among genetic, environmental, and disease components in syndromic diseases. We considered three distinct variable sets: genetic factors, environmental factors, and disease components. The process involved projecting a tripartite network onto a two-mode bipartite network and then simplifying it into a one-mode network. This approach facilitated the visualization of relationships among factors across different sets and within individual sets. To transition from multipartite to unipartite networks, we suggest both sequential and concurrent projection methods. Data from the Korean Association Resource (KARE) project were utilized, including 352,228 SNPs from 8840 individuals, alongside information on environmental factors such as lifestyle, dietary, and socioeconomic factors. The single-SNP analysis step filtered SNPs, supplemented by reference SNPs reported in a genome-wide association study catalog. The resulting network patterns differed significantly by sex: demographic factors and fat intake were crucial for women, while alcohol consumption was central for men. Indirect relationships were identified through projected bipartite networks, revealing that SNPs such as rs4244457, rs2156552, and rs10899345 had lifestyle interactions on metabolic components. Our approach offers several advantages: it simplifies the visualization of complex relationships among different datasets, identifies environmental interactions, and provides insights into SNP clusters sharing common environmental factors and metabolic components. This framework provides a comprehensive approach to elucidate the mechanisms underlying complex diseases like metabolic syndrome.

Loss of cped1 does not affect bone and lean tissue in zebrafish

Human genetic studies have nominated Cadherin-like and PC-esterase Domain-containing 1 (CPED1) as a candidate target gene mediating bone mineral density (BMD) and fracture risk heritability. Recent efforts to define the role of CPED1 in bone in mouse and human models have revealed complex alternative splicing and inconsistent results arising from gene targeting, making its function in bone difficult to interpret. To better understand the role of CPED1 in adult bone mass and morphology, we conducted a comprehensive genetic and phenotypic analysis of cped1 in zebrafish, an emerging model for bone and mineral research. We analyzed two different cped1 mutant lines and performed deep phenotyping to characterize more than 200 measures of adult vertebral, craniofacial, and lean tissue morphology. We also examined alternative splicing of zebrafish cped1 and gene expression in various cell/tissue types. Our studies fail to support an essential role of cped1 in adult zebrafish bone. Specifically, homozygous mutants for both cped1 mutant alleles, which are expected to result in loss-of-function and impact all cped1 isoforms, exhibited no significant differences in the measures examined when compared to their respective wildtype controls, suggesting that cped1 does not significantly contribute to these traits. We identified sequence differences in critical residues of the catalytic triad between the zebrafish and mouse orthologs of CPED1, suggesting that differences in key residues, as well as distinct alternative splicing, could underlie different functions of CPED1 orthologs in the two species. Our studies fail to support a requirement of cped1 in zebrafish bone and lean tissue, adding to evidence that variants at 7q31.31 can act independently of CPED1 to influence BMD and fracture risk.

Identification of interactions between genetic risk scores and dietary patterns for personalized prevention of kidney dysfunction in a population-based cohort

BACKGROUND & AIM

Chronic kidney disease (CKD) is a heterogeneous disorder that affects the kidney structure and function. This study investigated the effect of the interaction between genetic factors and dietary pattern on kidney dysfunction in Korean adults.

METHODS

Baseline data were obtained from the Ansan and Ansung Study of the Korean Genome and Epidemiology Study involving 8230 participants aged 40-69 years. Kidney dysfunction was defined as an estimated glomerular filtration rate < 90 mL/minute/1.73 m2. Genomic DNAs genotyped on the Affymetrix® Genome-Wide Human SNP array 5.0 were isolated from peripheral blood. A genome-wide association study using a generalized linear model was performed on 1,590,162 single-nucleotide polymorphisms (SNPs). To select significant SNPs, the threshold criterion was set at P-value < 5 × 10-8. Linkage disequilibrium clumping was performed based on the R2 value, and 94 SNPs had a significant effect. Participants were divided into two groups based on their generic risk score (GRS): the low-GR group had GRS > 0, while the high-GR group had GRS ≤ 0.

RESULTS

Three distinct dietary patterns were extracted, namely, the "prudent pattern," "flour-based and animal food pattern," and "white rice pattern," to analyze the effect of dietary pattern on kidney function. In the "flour-based and animal food pattern," higher pattern scores were associated with a higher prevalence of kidney dysfunction in both the low and high GR groups (P for trend < 0.0001 in the low-, high-GR groups of model 1; 0.0050 and 0.0065 in the low-, high-GR groups of model 2, respectively).

CONCLUSIONS

The results highlight a significant association between the 'flour-based and animal food pattern' and higher kidney dysfunction prevalence in individuals with both low and high GR. These findings suggest that personalized nutritional interventions based on GR profiles may become the basis for presenting GR-based individual dietary patterns for kidney dysfunction.

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.

Association between APOA5 polymorphisms and susceptibility to metabolic syndrome: a systematic review and meta-analysis

BACKGROUND

The association between Apolipoprotein A5 (APOA5) genetic polymorphisms and susceptibility to metabolic syndrome (MetS) has been established by many studies, but there have been conflicting results from the literature. We performed a meta-analysis of observational studies to evaluate the association between APOA5 gene polymorphisms and the prevalence of MetS.

METHODS

PubMed, Web of Science, Embase, and Scopus were searched up to April 2024. The random effects model was used to estimate the odds ratios (ORs) and 95% confidence intervals (CI) of the association between APOA5 gene polymorphisms and the prevalence of MetS development. The potential sources of heterogeneity were evaluated by subgroup analyses and sensitivity analyses.

RESULTS

A total of 30 studies with 54,986 subjects (25,341 MetS cases and 29,645 healthy controls) were included. The presence of rs662799 and rs651821 polymorphisms is associated with an approximately 1.5-fold higher likelihood of MetS prevalence (OR = 1.42, 95% CI: 1.32, 1.53, p < 0.001; I2 = 67.1%; P-heterogeneity < 0.001; and OR = 1.50, 95% CI: 1.36-1.65, p < 0.001), respectively. MetS is also more prevalent in individuals with the genetic variants rs3135506 and rs2075291. There was no evidence of a connection with rs126317.

CONCLUSION

The present findings suggest that polymorphisms located in the promoter and coding regions of the APOA5 gene are associated with an increased prevalence of MetS in the adult population. Identifying individuals with these genetic variations could lead to early disease detection and the implementation of preventive strategies to reduce the risk of MetS and its related health issues. However, because the sample size was small and there was evidence of significant heterogeneity for some APOA5 gene polymorphisms, these results need to be confirmed by more large-scale and well-designed studies.

Genome-wide association study and fine-mapping on Korean biobank to discover renal trait-associated variants

BACKGROUND

Chronic kidney disease is a significant health burden worldwide, with increasing incidence. Although several genome- wide association studies (GWAS) have investigated single nucleotide polymorphisms (SNP) associated with kidney trait, most studies were focused on European ancestry.

METHODS

We utilized clinical and genetic information collected from the Korean Genome and Epidemiology Study (KoGES).

RESULTS

More than five million SNPs from 58,406 participants were analyzed. After meta-GWAS, 1,360 loci associated with estimated glomerular filtration rate (eGFR) at a genome-wide significant level (p = 5 × 10-8) were identified. Among them, 399 loci were validated with at least one other biomarker (blood urea nitrogen [BUN] or eGFRcysC) and 149 loci were validated using both markers. Among them, 18 SNPs (nine known ones and nine novel ones) with 20 putative genes were found. The aggregated effect of genes estimated by MAGMA gene analysis showed that these significant genes were enriched in kidney-associated pathways, with the kidney and liver being the most enriched tissues.

CONCLUSION

In this study, we conducted GWAS for more than 50,000 Korean individuals and identified several variants associated with kidney traits, including eGFR, BUN, and eGFRcysC. We also investigated functions of relevant genes using computational methods to define putative causal variants.

Application of Machine Learning Algorithms to Predict Osteoporotic Fractures in Women

BACKGROUND

Predicting the risk of osteoporotic fractures is vital for prevention. Traditional methods such as the Fracture Risk Assessment Tool (FRAX) model use clinical factors. This study examined the predictive power of the FRAX score and machine-learning algorithms trained on FRAX parameters.

METHODS

We analyzed the data of 2,147 female participants from the Ansan cohort study. The FRAX parameters employed in this study included age, sex (female), height and weight, current smoking status, excessive alcohol consumption (>3 units/d of alcohol), and diagnosis of rheumatoid arthritis. Osteoporotic fracture was defined as one or more fractures of the hip, spine, or wrist during a 10-year observation period. Machine-learning algorithms, such as gradient boosting, random forest, decision tree, and logistic regression, were employed to predict osteoporotic fractures with a 70:30 training-to-test set ratio. We evaluated the area under the receiver operating characteristic curve (AUROC) scores to assess and compare the performance of these algorithms with the FRAX score.

RESULTS

Of the 2,147 participants, 3.5% experienced osteoporotic fractures. Those with fractures were older, shorter in height, and had a higher prevalence of rheumatoid arthritis, as well as higher FRAX scores. The AUROC for the FRAX was 0.617. The machine-learning algorithms showed AUROC values of 0.662, 0.652, 0.648, and 0.637 for gradient boosting, logistic regression, decision tree, and random forest, respectively.

CONCLUSION

This study highlighted the immense potential of machine-learning algorithms to improve osteoporotic fracture risk prediction in women when complete FRAX parameter information is unavailable.

Urinary microbiome-based metagenomic signature for the noninvasive diagnosis of hepatocellular carcinoma

BACKGROUND

Gut microbial dysbiosis is implicated in chronic liver disease and hepatocellular carcinoma (HCC), but the role of microbiomes from various body sites remains unexplored. We assessed disease-specific alterations in the urinary microbiome in HCC patients, investigating their potential as diagnostic biomarkers.

METHODS

We performed cross-sectional analyses of urine samples from 471 HCC patients and 397 healthy controls and validated the results in an independent cohort of 164 HCC patients and 164 healthy controls. Urinary microbiomes were analyzed by 16S rRNA gene sequencing. A microbial marker-based model distinguishing HCC from controls was built based on logistic regression, and its performance was tested.

RESULTS

Microbial diversity was significantly reduced in the HCC patients compared with the controls. There were significant differences in the abundances of various bacteria correlated with HCC, thus defining a urinary microbiome-derived signature of HCC. We developed nine HCC-associated genera-based models with robust diagnostic accuracy (area under the curve [AUC], 0.89; balanced accuracy, 81.2%). In the validation, this model detected HCC with an AUC of 0.94 and an accuracy of 88.4%.

CONCLUSIONS

The urinary microbiome might be a potential biomarker for the detection of HCC. Further clinical testing and validation of these results are needed in prospective studies.

Genome-wide Association Study of Susceptibility Loci for Self-Reported Atopic Dermatitis and Allergic Rhinitis in the Korean Population

BACKGROUND

Allergic diseases include atopic dermatitis (AD) and allergic rhinitis (AR), which are chronic, relapsing inflammatory disorders of the skin or mucosa that usually accompany immunoglobulin E-mediated immune responses. They are complex, multifactorial diseases with an etiology involving interactions between genetic and environmental factors.

OBJECTIVE

We performed a genome-wide association study (GWAS) to identify single nucleotide polymorphisms (SNPs) associated with allergic diseases in the Korean population.

METHODS

A total of 8,840 samples were obtained from the Korean Association Resource Consortium dataset of the Korean Genome and Epidemiology Study Ansan-Anseong cohort. The allergic disease phenotype was determined based on self-reported physician diagnoses. After quality control, 8,823 subjects with 877,242 variants remained for the final analysis. The GWAS was performed using logistic regression analysis in an additive model adjusted for age and sex.

RESULTS

A total of 636 patients with allergic disease and 8,176 controls were analyzed. Three SNPs were associated with allergic disease at a level of genome-wide suggestive significance (p<1.0×10-5) in the Korean population: rs7275360, located in neural cell adhesion molecule 2; rs698195; and rs3750552, located in family with sequence similarity 189, member A2. These polymorphisms were on chromosomes 21q21.1, 7q31.1, and 9q21.12, respectively.

CONCLUSION

We identified 3 novel SNPs significantly associated with allergic diseases in the Korean population. Further research is required to confirm the association between these novel SNPs and allergic disease in the Korean population and in other ethnicities.

ATP2B1 gene polymorphisms associated with resistant hypertension in the Japanese population

Single-nucleotide polymorphisms (SNP) of ATP2B1 gene are associated with essential hypertension but their association with resistant hypertension (RHT) remains unexplored. The authors examined the relationship between ATP2B1 SNPs and RHT by genotyping 12 SNPs in ATP2B1 gene of 1124 Japanese individuals with lifestyle-related diseases. Patients with RHT had inadequate blood pressure (BP) control using three antihypertensive drugs or used ≥4 antihypertensive drugs. Patients with controlled hypertension had BP controlled using ≤3 antihypertensive drugs. The association between each SNP and RHT was analyzed by logistic regression. The final cohort had 888 (79.0%) and 43 (3.8%) patients with controlled hypertension and RHT, respectively. Compared with patients homozygous for the minor allele of each SNP in ATP2B1, a significantly higher number of patients carrying the major allele at 10 SNPs exhibited RHT (most significant at rs1401982: 5.8% vs. 0.8%, p = .014; least significant at rs11105378: 5.7% vs. 0.9%, p = .035; most nonsignificant at rs12817819: 5.1% vs. 10%, p = .413). After multivariate adjustment for age, sex, systolic BP, and other confounders, the association remained significant for rs2681472 and rs1401982 (OR: 7.60, p < .05 and OR: 7.62, p = .049, respectively). Additionally, rs2681472 and rs1401982 were in linkage disequilibrium with rs11105378. This study identified two ATP2B1 SNPs associated with RHT in the Japanese population. rs1401982 was most closely associated with RHT, and major allele carriers of rs1401982 required significantly more antihypertensive medications. Analysis of ATP2B1 SNPs in patients with hypertension can help in early prediction of RHT and identification of high-risk patients who are more likely to require more antihypertensive medications.

Risk prediction and interaction analysis using polygenic risk score of type 2 diabetes in a Korean population

Joint modelling of genetic and environmental risk factors can provide important information to predict the risk of type 2 diabetes (T2D). Therefore, to predict the genetic risk of T2D, we constructed a polygenic risk score (PRS) using genotype data of one Korean cohort, KARE (745 cases and 2549 controls), and the genome-wide association study summary statistics of Biobank Japan. We evaluated the performance of PRS in an independent Korean cohort, HEXA (5684 cases and 35,703 controls). Individuals with T2D had a significantly higher mean PRS than controls (0.492 vs. - 0.078, p ≈ 0 ). PRS predicted the risk of T2D with an AUC of 0.658 (95% CI 0.651-0.666). We also evaluated interaction between PRS and waist circumference (WC) in the HEXA cohort. PRS exhibited a significant sub-multiplicative interaction with WC (ORinteraction 0.991, 95% CI 0.987-0.995, pinteraction = 4.93 × 10-6) in T2D. The effect of WC on T2D decreased as PRS increased. The sex-specific analyses produced similar interaction results, revealing a decreased WC effect on T2D as the PRS increased. In conclusion, the risk of WC for T2D may differ depending on PRS and those with a high PRS might develop T2D with a lower WC threshold. Our findings are expected to improve risk prediction for T2D and facilitate the identification of individuals at an increased risk of T2D.

Genetic imputation of kidney transcriptome, proteome and multi-omics illuminates new blood pressure and hypertension targets

Genetic mechanisms of blood pressure (BP) regulation remain poorly defined. Using kidney-specific epigenomic annotations and 3D genome information we generated and validated gene expression prediction models for the purpose of transcriptome-wide association studies in 700 human kidneys. We identified 889 kidney genes associated with BP of which 399 were prioritised as contributors to BP regulation. Imputation of kidney proteome and microRNAome uncovered 97 renal proteins and 11 miRNAs associated with BP. Integration with plasma proteomics and metabolomics illuminated circulating levels of myo-inositol, 4-guanidinobutanoate and angiotensinogen as downstream effectors of several kidney BP genes (SLC5A11, AGMAT, AGT, respectively). We showed that genetically determined reduction in renal expression may mimic the effects of rare loss-of-function variants on kidney mRNA/protein and lead to an increase in BP (e.g., ENPEP). We demonstrated a strong correlation (r = 0.81) in expression of protein-coding genes between cells harvested from urine and the kidney highlighting a diagnostic potential of urinary cell transcriptomics. We uncovered adenylyl cyclase activators as a repurposing opportunity for hypertension and illustrated examples of BP-elevating effects of anticancer drugs (e.g. tubulin polymerisation inhibitors). Collectively, our studies provide new biological insights into genetic regulation of BP with potential to drive clinical translation in hypertension.

2024 Heart Disease and Stroke Statistics: A Report of US and Global Data From the American Heart Association

BACKGROUND

The American Heart Association (AHA), in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, nutrition, sleep, and obesity) and health factors (cholesterol, blood pressure, glucose control, and metabolic syndrome) that contribute to cardiovascular health. The AHA Heart Disease and Stroke Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, brain health, complications of pregnancy, kidney disease, congenital heart disease, rhythm disorders, sudden cardiac arrest, subclinical atherosclerosis, coronary heart disease, cardiomyopathy, heart failure, valvular disease, venous thromboembolism, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The AHA, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States and globally to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2024 AHA Statistical Update is the product of a full year's worth of effort in 2023 by dedicated volunteer clinicians and scientists, committed government professionals, and AHA staff members. The AHA strives to further understand and help heal health problems inflicted by structural racism, a public health crisis that can significantly damage physical and mental health and perpetuate disparities in access to health care, education, income, housing, and several other factors vital to healthy lives. This year's edition includes additional global data, as well as data on the monitoring and benefits of cardiovascular health in the population, with an enhanced focus on health equity across several key domains.

RESULTS

Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.

CONCLUSIONS

The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

Increased Blood Pressure Variability Over a 16-Year Period Is Associated With Left Ventricular Diastolic Dysfunction in a Population-Based Cohort

BACKGROUND

Left ventricular diastolic dysfunction (LVDD) is often associated with elevated blood pressure (BP). It is prevalent among hypertensive patients. Additionally, increased BP variability has been linked to LVDD. However, the precise connection between LVDD and BP variability within the general population remains unclear. Thus, this study aimed to evaluate this association in a general population.

METHODS

A total of 2,578 participants(1,311 females) with a mean age of 47.8 ± 6.7 years who had echocardiographic data from the Korean Genome and Epidemiology study with 16 years of follow-up were analyzed. LVDD was identified through the last echocardiography during the follow-up period. BP variability was assessed using mean, standard deviation (SD), and coefficient of variance (CV).

RESULTS

LVDD was detected in 249 individuals. The cohort was divided into an LVDD group and a normal LV diastolic function group. The LVDD group had a higher percentage of females, more advanced age, higher body mass index (BMI), higher BP and BUN levels, lower heart rate, lower hemoglobin, and lower serum creatinine than the normal LV diastolic function group. Remarkably, LVDD was associated with higher BP variability. In the multivariate analysis, LVDD was associated with increased age, female sex, increased BMI, hypertension, and increased BUN. Elevated mean systolic and diastolic BPs, SD of systolic BP, mean pulse pressure (PP), SD of PP, and CV of PP were significantly linked to LVDD even after adjusting for other significant variables in the multivariate analysis.

CONCLUSIONS

LVDD was identified in 249 (9.7%) participants. Increased long-term BP variability was significantly associated with LVDD in this population-based cohort.

Interactions Between Depression, Alcohol Intake, and Smoking on the Risk of Acute Coronary Syndrome

OBJECTIVE

Our study hypothesizes that the interaction between depression, alcohol intake, and smoking status can significantly influence the risk of acute coronary syndrome (ACS). We aim to investigate the magnitude of the association between depression and ACS risk and explore how alcohol intake and smoking status affect this association.

METHODS

We used data from the Korean Genome and Epidemiology Study. The primary exposure of interest was the presence of depression, as measured using the Beck Depression Inventory score at baseline. The primary outcome was the occurrence of ACS observed in the biennial follow-up surveys. We used Cox proportional regression analysis to estimate the effect of depression on ACS incidence. We conducted interaction and joint effect analyses to explore the interactions between depression and health-related habits including alcohol intake and smoking with regard to ACS incidence.

RESULTS

During 16 years of follow-up among 3,254 individuals, we documented 88 cases of new-onset ACS (2.2 cases per 1,000 personyears). We found no association between depression and ACS risk; furthermore, the effect of depression on ACS risk by alcohol intake and smoking status did not differ significantly. In the analysis to observe the joint effect of smoking and depression, the multivariate hazard ratios of ACS were 1.26 (95% confidence interval [CI], 0.67-2.36) for non-smoking and depression, 1.52 (95% CI, 0.83-2.82) for smoking and non-depression, and 2.79 (95% CI, 1.21-6.41) for smoking and depression compared with non-smoking and non-depression.

CONCLUSION

Our study reveals the combined effect of depression and smoking on ACS risk, highlighting the potential benefits of concurrent interventions for both depression and smoking for cardiovascular health.

Applications of genomic research in pediatric endocrine diseases

Recent advances in molecular genetics have advanced our understanding of the molecular mechanisms involved in pediatric endocrine disorders and now play a major role in mainstream medical practice. The spectrum of endocrine genetic disorders has 2 extremes: Mendelian and polygenic. Mendelian or monogenic diseases are caused by rare variants of a single gene, each of which exerts a strong effect on disease risk. Polygenic diseases or common traits are caused by the combined effects of multiple genetic variants in conjunction with environmental and lifestyle factors. Testing for a single gene is preferable if the disease is phenotypically and/or geneically homogeneous. Next-generation sequencing (NGS) can be applied to phenotypically and genetically heterogeneous conditions. Genome-wide association studies (GWASs) have examined genetic variants across the entire genome in a large number of individuals who have been matched for population ancestry and assessed for a disease or trait of interest. Common endocrine diseases or traits, such as type 2 diabetes mellitus, obesity, height, and pubertal timing, result from the combined effects of multiple variants in various genes that are frequently found in the general population, each of which contributes a small individual effect. Isolated founder mutations can result from a true founder effect or an extreme reduction in population size. Studies of founder mutations offer powerful advantages for efficiently localizing the genes that underlie Mendelian disorders. The Korean population has settled in the Korean peninsula for thousands of years, and several recurrent mutations have been identified as founder mutations. The application of molecular technology has increased our understanding of endocrine diseases, which have impacted on the practice of pediatric endocrinology related to diagnosis and genetic counseling. This review focuses on the application of genomic research to pediatric endocrine diseases using GWASs and NGS technology for diagnosis and treatment.

Zebrafish as a Model for Osteoporosis: Functional Validations of Genome-Wide Association Studies

PURPOSE OF REVIEW

GWAS, as a largely correlational analysis, requires in vitro or in vivo validation. Zebrafish (Danio rerio) have many advantages for studying the genetics of human diseases. Since gene editing in zebrafish has been highly valuable for studying embryonic skeletal developmental processes that are prenatally or perinatally lethal in mammalian models, we are reviewing pros and cons of this model.

RECENT FINDINGS

The true power for the use of zebrafish is the ease by which the genome can be edited, especially using the CRISPR/Cas9 system. Gene editing, followed by phenotyping, for complex traits such as BMD, is beneficial, but the major physiological differences between the fish and mammals must be considered. Like mammals, zebrafish do have main bone cells; thus, both in vivo stem cell analyses and in vivo imaging are doable. Yet, the "long" bones of fish are peculiar, and their bone cavities do not contain bone marrow. Partial duplication of the zebrafish genome should be taken into account. Overall, small fish toolkit can provide unmatched opportunities for genetic modifications and morphological investigation as a follow-up to human-first discovery.

A genome-wide association scan reveals novel loci for facial traits of Koreans

DNA-based prediction of externally visible characteristics (EVC) with SNPs is one of the research areas of interest in the forensic field. Based on a previous study performing GWAS on facial traits in a Korean population, herein, we present results stemming from GWA analysis with KoreanChip and novel genetic loci satisfying genome-wide significant level. We discovered a total of 20 signals and 12 loci were found to have novel associations with facial traits, including six loci located in intergenic regions and six loci located at UBE2O, HECTD2, CCDC108, TPK1, FCN2, and FRMPD1. Additionally, we performed a polygenic score analysis for 33 distance-related traits in facial phenotyping and determined genetic relationships between facial traits and SNPs using the GCTA program. The results of the current study offer an understanding of how facial morphology is influenced by complex genetic structures and provide insights into forensic investigation and population genetics.

Genetic architecture of adiposity measures among Asians: Findings from GWAS

Adiposity has gradually become a global public threat over the years with drastic increase in the attributable deaths and disability adjusted life years (DALYs). Given an increased metabolic risk among Asians as compared to Europeans for any given body mass index (BMI) and considering the differences in genetic architecture between them, the present review aims to summarize the findings from genome-wide scans for various adiposity indices and related anthropometric measures from Asian populations. The search for related studies, published till February 2022, were made on PubMed and GWAS Catalog using search strategy built with relevant keywords joined by Boolean operators. It was recorded that out of a total of 47 identified studies, maximum studies are from Korean population (n = 14), followed by Chinese (n = 7), and Japanese (n = 6). Nearly 200 loci have been identified for BMI, 660 for height, 16 for weight, 28 for circumferences (waist and hip), 32 for ratios (waist hip ratio [WHR] and thoracic hip ratio [THR]), 5 for body fat, 16 for obesity, and 28 for adiposity-related blood markers among Asians. It was observed that though, most of the loci were unique for each trait, there were 3 loci in common to BMI and WHR. Apart from validation of variants identified in European setting, there were many novel loci discovered in Asian populations. Notably, 125 novel loci form Asian studies have been reported for BMI, 47 for height, 5 for waist circumference, and 2 for adiponectin level to the existing knowledge of the genetic framework of adiposity and related measures. It is necessary to examine more advanced adiposity measures, specifically of relevance to abdominal adiposity, a major risk factor for cardiometabolic disorders among Asians. Moreover, in spite of being one continent, there is diversity among different ethnicities across Asia in terms of lifestyle, climate, geography, genetic structure and consequently the phenotypic manifestations. Hence, it is also important to consider ethnic specific studies for identifying and validating reliable genetic variants of adiposity measures among Asians.

Inducible overexpression of a FAM3C/ILEI transgene has pleiotropic effects with shortened life span, liver fibrosis and anemia in mice

FAM3C/ILEI is an important factor in epithelial-to-mesenchymal transition (EMT) induction, tumor progression and metastasis. Overexpressed in many cancers, elevated ILEI levels and secretion correlate with poor patient survival. Although ILEI's causative role in invasive tumor growth and metastasis has been demonstrated in several cellular tumor models, there are no available transgenic mice to study these effects in the context of a complex organism. Here, we describe the generation and initial characterization of a Tet-ON inducible Fam3c/ILEI transgenic mouse strain. We find that ubiquitous induction of ILEI overexpression (R26-ILEIind) at weaning age leads to a shortened lifespan, reduced body weight and microcytic hypochromic anemia. The anemia was reversible at a young age within a week upon withdrawal of ILEI induction. Vav1-driven overexpression of the ILEIind transgene in all hematopoietic cells (Vav-ILEIind) did not render mice anemic or lower overall fitness, demonstrating that no intrinsic mechanisms of erythroid development were dysregulated by ILEI and that hematopoietic ILEI hyperfunction did not contribute to death. Reduced serum iron levels of R26-ILEIind mice were indicative for a malfunction in iron uptake or homeostasis. Accordingly, the liver, the main organ of iron metabolism, was severely affected in moribund ILEI overexpressing mice: increased alanine transaminase and aspartate aminotransferase levels indicated liver dysfunction, the liver was reduced in size, showed increased apoptosis, reduced cellular iron content, and had a fibrotic phenotype. These data indicate that high ILEI expression in the liver might reduce hepatoprotection and induce liver fibrosis, which leads to liver dysfunction, disturbed iron metabolism and eventually to death. Overall, we show here that the novel Tet-ON inducible Fam3c/ILEI transgenic mouse strain allows tissue specific timely controlled overexpression of ILEI and thus, will serve as a versatile tool to model the effect of elevated ILEI expression in diverse tissue entities and disease conditions, including cancer.

Genome-wide association and replication studies for handedness in a Korean community-based cohort

INTRODUCTION

Handedness is a conspicuous characteristic in human behavior, with a worldwide proportion of approximately 90% of people preferring to use the right hand for many tasks. In the Korean population, the proportion of left-handedness is relatively low at approximately 7%-10%, similar to that in other East-Asian cultures in which the use of the left hand for writing and other public activities has historically been oppressed.

METHODS

In this study, we conducted two genome-wide association studies (GWASs) between right-handedness and left-handedness, and between right-handedness and ambidexterity using logistic regression analyses using a Korean community-based cohort. We also performed association analyses with previously reported variants and our findings.

RESULTS

A total of 8806 participants were included for analysis, and the results identified 28 left-handedness-associated and 15 ambidexterity-associated loci; of these, two left-handedness loci (NEIL3 [rs11726465] and SVOPL [rs117495448]) and one ambidexterity locus (PDE8B/WDR41 [rs118077080]) showed near genome-wide significance. Association analyses with previously reported variants replicated ANKS1B (rs7132513) in left-handedness and ANKIB1 (rs2040498) in ambidexterity.

CONCLUSION

The variants and positional candidate genes identified and replicated in this study were largely associated with brain development, cerebral asymmetry, neurological processes, and neuropsychiatric diseases in line with previous findings. As the first East-Asian GWAS related to handedness, these results may provide an intriguing reference for further human neurologic research in the future.

Increased glutamate in type 2 diabetes in the Korean population is associated with increased plasminogen levels

BACKGROUND

Glutamate is a major neurotransmitter, although it causes cytotoxicity and inflammation in nonneuronal organs. This study aimed to investigate the metabolic disorders in which glutamate, associated with type 2 diabetes onset, is induced in the liver.

METHODS

An analysis of Korean community-based Ansan-Ansung cohort study data as well as functional research using in vitro and mouse models were performed.

RESULTS

Groups with high plasma glutamate levels (T2, T3) had a significantly increased risk of diabetes incidence after 8 years, compared to the group with relatively low glutamate levels (T1). Analysis of the effect of glutamate on diabetes onset in vitro showed that glutamate induces insulin resistance by increasing glucose-related protein 78 (GRP78) and phosphoenolpyruvate carboxykinase (PEPCK) expression in SK-Hep-1 human liver cells. In addition, three different genes, FRMB4B, PLG, and PARD3, were significantly associated with glutamate and were identified via genome-wide association studies. Among glutamate-related genes, plasminogen (PLG) levels were most significantly increased in several environments in which insulin resistance was induced, and was also upregulated by glutamate. Glutamate-induced increase in PLG in liver cells was caused by metabotropic glutamate receptor 5 activation, and PLG levels were also upregulated after extracellular secretion. Moreover, glutamate increased the expression of plasminogen activator inhibitor-1 (PAI-1). Thus, extracellular secreted PLG cannot be converted to plasmin (fibrinolytic enzyme) by increased PAI-1.

CONCLUSIONS

Increased glutamate is closely associated with the development of diabetes, and it may cause metabolic disorders by inhibiting the fibrinolytic system, which plays an important role in determining blood clots, a hallmark of diabetes.

Gene-diet interaction analysis using novel weighted food scores discovers the adipocytokine signaling pathway associated with the development of type 2 diabetes

Introduction

The influence of dietary patterns measured using Recommended Food Score (RFS) with foods with high amounts of antioxidant nutrients for Type 2 diabetes (T2D) was analyzed. Our analysis aims to find associations between dietary patterns and T2D and conduct a gene-diet interaction analysis related to T2D.

Methods

Data analyzed in the current study were obtained from the Korean Genome and Epidemiology Study Cohort. The dietary patterns of 46 food items were assessed using a validated food frequency questionnaire. To maximize the predictive power of the RFS, we propose two weighted food scores, namely HisCoM-RFS calculated using the novel Hierarchical Structural Component model (HisCoM) and PLSDA-RFS calculated using Partial Least Squares-Discriminant Analysis (PLS-DA) method.

Results

Both RFS (OR: 1.11; 95% CI: 1.03- 1.20; P = 0.009) and PLSDA-RFS (OR: 1.10; 95% CI: 1.02-1.19, P = 0.011) were positively associated with T2D. Mapping of SNPs (P < 0.05) from the interaction analysis between SNPs and the food scores to genes and pathways yielded some 12 genes (CACNA2D3, RELN, DOCK2, SLIT3, CTNNA2, etc.) and pathways associated with T2D. The strongest association was observed with the adipocytokine signalling pathway, highlighting 32 genes (STAT3, MAPK10, MAPK8, IRS1, AKT1-3, ADIPOR2, etc.) most likely associated with T2D. Finally, the group of the subjects in low, intermediate and high using both the food scores and a polygenic risk score found an association between diet quality groups with issues at high genetic risk of T2D.

Conclusion

A dietary pattern of poor amounts of antioxidant nutrients is associated with the risk of T2D, and diet affects pathway mechanisms involved in developing T2D.

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.

The KL genetic polymorphisms Associated with type 2 diabetes Mellitus

Growing number of research studies have shown that an anti-ageing gene Klotho (KL) is closely associated with Type 2 Diabetes Mellitus (T2DM). In this study, the association is genetically analyzed with single nucleotide polymorphism (SNP) of KL found in T2DM case of an Asian cohort. KL SNP information was obtained from a big database of the Korean Association Resource (KARE) from which 20 KL SNPs were available. Statistical analyses were conducted based on the 3 genetic models, such as additive, dominant, and recessive. Of the 20 KL SNPs, 12 SNPs were found to be significantly associated with T2DM in both of additive and dominant models. Odds ratios of the KL SNPs indicate increased susceptibility to T2DM in additive and dominant models. Significant association of KL with T2DM was further analyzed using imputed KL SNPs from HapMap reference data of the Eastern population. The statistically significant KL SNPs including the imputed SNPs distributed evenly over the KL gene area. The results in this study suggest klotho is a major player in the development of T2DM and the KL SNPs found in the case could be a risk marker of T2DM in the cohort.

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.

Association of rs9939609 in FTO with BMI among Polynesian peoples living in Aotearoa New Zealand and other Pacific nations

The fat mass and obesity associated (FTO) locus consistently associates with higher body mass index (BMI) across diverse ancestral groups. However, previous small studies of people of Polynesian ancestries have failed to replicate the association. In this study, we used Bayesian meta-analysis to test rs9939609, the most replicated FTO variant, for association with BMI with a large sample (n = 6095) of Aotearoa New Zealanders of Polynesian (Māori and Pacific) ancestry and of Samoan people living in the Independent State of Samoa and in American Samoa. We did not observe statistically significant association within each separate Polynesian subgroup. Bayesian meta-analysis of the Aotearoa New Zealand Polynesian and Samoan samples resulted in a posterior mean effect size estimate of +0.21 kg/m2, with a 95% credible interval [+0.03 kg/m2, +0.39 kg/m2]. While the Bayes Factor (BF) of 0.77 weakly favors the null, the BF = 1.4 Bayesian support interval is [+0.04, +0.20]. These results suggest that rs9939609 in FTO may have a similar effect on mean BMI in people of Polynesian ancestries as previously observed in other ancestral groups.

Genetic dissection of 26 meat cut, meat quality and carcass traits in four pig populations

BACKGROUND

Currently, meat cut traits are integrated in pig breeding objectives to gain extra profit. However, little is known about the heritability of meat cut proportions (MCP) and their correlations with other traits. The aims of this study were to assess the heritability and genetic correlation of MCP with carcass and meat quality traits using single nucleotide polymorphism chips and conduct a genome-wide association study (GWAS) to identify candidate genes for MCP.

RESULTS

Seventeen MCP, 12 carcass, and seven meat quality traits were measured in 2012 pigs from four populations (Landrace; Yorkshire; Landrace and Yorkshire hybrid pigs; Duroc, and Landrace and Yorkshire hybrid pigs). Estimates of the heritability for MCP ranged from 0.10 to 0.55, with most estimates being moderate to high and highly consistent across populations. In the combined population, the heritability estimates for the proportions of scapula bone, loin, back fat, leg bones, and boneless picnic shoulder were 0.44 ± 0.04, 0.36 ± 0.04, 0.44 ± 0.04, 0.38 ± 0.04, and 0.39 ± 0.04, respectively. Proportion of middle cuts was genetically significantly positively correlated with intramuscular fat content and backfat depth. Proportion of ribs was genetically positively correlated with carcass oblique length and straight length (0.35 ± 0.08 to 0.45 ± 0.07) and negatively correlated with backfat depth (- 0.26 ± 0.10 to - 0.45 ± 0.10). However, weak or nonsignificant genetic correlations were observed between most MCP, indicating their independence. Twenty-eight quantitative trait loci (QTL) for MCP were detected by GWAS, and 24 new candidate genes related to MCP were identified, which are involved with growth, height, and skeletal development. Most importantly, we found that the development of the bones in different parts of the body may be regulated by different genes, among which HMGA1 may be the strongest candidate gene affecting forelimb bone development. Moreover, as previously shown, VRTN is a causal gene affecting vertebra number, and BMP2 may be the strongest candidate gene affecting hindlimb bone development.

CONCLUSIONS

Our results indicate that breeding programs for MCP have the potential to enhance carcass composition by increasing the proportion of expensive cuts and decreasing the proportion of inexpensive cuts. Since MCP are post-slaughter traits, the QTL and candidate genes related to these traits can be used for marker-assisted and genomic selection.

UBAP2 plays a role in bone homeostasis through the regulation of osteoblastogenesis and osteoclastogenesis

Osteoporosis is a condition characterized by decreased bone mineral density (BMD) and reduced bone strength, leading to an increased risk of fractures. Here, to identify novel risk variants for susceptibility to osteoporosis-related traits, an exome-wide association study is performed with 6,485 exonic single nucleotide polymorphisms (SNPs) in 2,666 women of two Korean study cohorts. The rs2781 SNP in UBAP2 gene is suggestively associated with osteoporosis and BMD with p-values of 6.1 × 10-7 (odds ratio = 1.72) and 1.1 × 10-7 in the case-control and quantitative analyzes, respectively. Knockdown of Ubap2 in mouse cells decreases osteoblastogenesis and increases osteoclastogenesis, and knockdown of ubap2 in zebrafish reveals abnormal bone formation. Ubap2 expression is associated with E-cadherin (Cdh1) and Fra1 (Fosl1) expression in the osteclastogenesis-induced monocytes. UBAP2 mRNA levels are significantly reduced in bone marrow, but increased in peripheral blood, from women with osteoporosis compared to controls. UBAP2 protein level is correlated with the blood plasma level of the representative osteoporosis biomarker osteocalcin. These results suggest that UBAP2 has a critical role in bone homeostasis through the regulation of bone remodeling.

Association of NAFLD with FGF21 Polygenic Hazard Score, and Its Interaction with Protein Intake Level in Korean Adults

Fibroblast growth factor 21 (FGF21) is a hormone that participates in the regulation of energy homeostasis and is induced by dietary protein restriction. Preclinical studies have suggested that FGF21 induction exerts a protective effect against non-alcoholic fatty liver disease (NAFLD), while human studies have revealed elevated levels of and potential resistance to FGF21 in patients with NAFLD. However, whether the FGF21 pathway also contributes to NAFLD risk at the genetic level remains uncertain. A few attempts to investigate the impact of individual genetic variants at the loci encoding FGF21 and its receptors on NAFLD risk have failed to establish a clear association due to a limited effect size. Therefore, this study aimed to (1) develop a polygenic hazard score (PHS) for FGF21-related loci that are associated with NAFLD risk and (2) investigate the effect of its interaction with protein intake level on NAFLD risk. Data on 3501 participants of the Korean Genome Epidemiology Study (Ansan-Ansung) were analyzed. Eight single-nucleotide polymorphisms of fibroblast growth factor receptors and beta-klotho were selected for PHS determination using forward stepwise analysis. The association between the PHS and NAFLD was validated (p-trend: 0.0171 for men and <0.0001 for women). Moreover, the association was significantly modulated by the protein intake level in all participants as well as women (p-interaction = 0.0189 and 0.0131, respectively) but not in men. In particular, the women with the lowest PHS values and a protein intake lower than the recommended nutrient intake (RNI) exhibited a greater NAFLD risk (HR = 2.021, p-trend = 0.0016) than those with an intake equal to or greater than the RNI; however, those with higher PHS values had a high risk, regardless of protein intake level. These findings demonstrate the contribution of FGF21-related genetic variants and restricted protein intake to NAFLD incidence.

Association between CLOCK Gene Polymorphisms and Insomnia Risk According to Food Groups: A KoGES Longitudinal Study

Food intake could mitigate or exacerbate the risk for insomnia associated with the CLOCK gene. This study investigated the associations between the clock circadian regulator (CLOCK) polymorphisms rs12649507 and rs4580704 and the risk of insomnia, as well as its interactions with food groups. Among 1430 adults, new insomnia cases were identified between 2005 and 2012. Single nucleotide polymorphisms were genotyped, and dietary intake was assessed. Next, Cox proportional hazard models were established. The fruit and meat groups significantly mitigated the risk of insomnia associated with rs12649507 among males (pinteraction = 0.006 in a recessive model; p = 0.010 in a dominant model). In contrast, among females the beverage group significantly increased the risk of insomnia (p = 0.041 in a dominant model). As for rs4580704, among males the fruit and meat groups modified the risk of insomnia (p = 0.006 in a recessive model; p = 0.001 in a dominant model). However, among females, the beverage group exacerbated the risk of insomnia associated with rs4580704 (p = 0.004 in a dominant model). In this longitudinal study, we observed a significantly modified insomnia risk associated with the CLOCK gene depending on food groups. Notably, in a general population the risks were modified according to both the fruit and meat intake among 775 males but exacerbated with beverage intake among 655 females.

Bacterial Extracellular Vesicle Composition in Human Urine and the 10-Year Risk of Abdominal Obesity

Objective: We aimed to evaluate a causal relationship between commensal bacteria and abdominal obesity. Methods: A prospective study, including 2222 adults who provided urine samples at baseline, was performed. These samples were used for assays of genomic DNA from bacterial extracellular vesicles (EVs). During the 10-year period, the incidence rates of obesity (measured as body mass index) and abdominal obesity (measured as waist circumference) were ascertained as outcomes. To evaluate associations of bacterial composition at the phylum and genus levels with the outcomes, the hazard ratio (HR) and its confidence interval (95% CI) were estimated. Results: No significant association was observed for the risk of obesity, whereas the risk of abdominal obesity was inversely associated with the composition of Proteobacteria and positively associated with that of Firmicutes (adjusted P value <0.05). In joint analysis for the combination groups of Proteobacteria and Firmicutes composition tertiles, the group with top tertiles of both Proteobacteria and Firmicutes showed a significant HR of 2.59 (95% CI: 1.33 - 5.01) compared with the reference with lower tertiles (adjusted P value <0.05). Some genera of these phyla were associated with the risk of abdominal obesity. Conclusions: These findings suggest that bacterial composition in urinary EV samples can predict the 10-year risk of abdominal obesity.

Identification of Genetic Markers Linked to The Activity of Indoleamine 2,3-Dioxygenase and Kidney Function

Indoleamine 2,3-dioxygenase (IDO) is a tryptophan-degrading enzyme belonging to the kynurenine pathway. IDO activity has been suggested as a potential biomarker for early diagnosis of chronic kidney disease (CKD). The aim of this study was to perform coincident association analysis to gain genetic insights into the correlation between IDO activity and CKD. This study evaluated the association between IDO activity and CKD using the Korea Association REsource (KARE) cohort. Logistic and linear regression were used to analyze CKD and quantitative phenotypes such as IDO and estimated glomerular filtration rate (eGFR). Our results identified 10 single nucleotide polymorphisms (SNPs) that were coincidently associated with both IDO and CKD (p < 0.001). Among them, rs6550842, rs77624055, and rs35651150 were selected as potential candidates after excluding SNPs with insufficient evidence for having an association with IDO or CKD. Further expression quantitative trait loci (eQTL) analysis for variants at selected loci showed that rs6550842 and rs35651150 significantly affected the expression of NKIRAS1 and SH2D4A genes in human tissues, respectively. Additionally, we highlighted that the NKIRAS1 and BMP6 genes were correlated with IDO activity and CKD through signaling pathways associated with inflammation. Our data suggest that NKIRAS1, SH2D4A, and BMP6 were potential causative genes affecting IDO activity and CKD through integrated analysis. Identifying these genes could aid in early detection and treatment by predicting the risk of CKD associated with IDO activity.

Multiple Mechanisms Explain Genetic Effects at the CPED1-WNT16 Bone Mineral Density Locus

PURPOSE OF REVIEW

Chromosome region 7q31.31, also known as the CPED1-WNT16 locus, is robustly associated with BMD and fracture risk. The aim of the review is to highlight experimental studies examining the function of genes at the CPED1-WNT16 locus.

RECENT FINDINGS

Genes that reside at the CPED1-WNT16 locus include WNT16, FAM3C, ING3, CPED1, and TSPAN12. Experimental studies in mice strongly support the notion that Wnt16 is necessary for bone mass and strength. In addition, roles for Fam3c and Ing3 in regulating bone morphology in vivo and/or osteoblast differentiation in vitro have been identified. Finally, a role for wnt16 in dually influencing bone and muscle morphogenesis in zebrafish has recently been discovered, which has brought forth new questions related to whether the influence of WNT16 in muscle may conspire with its influence in bone to alter BMD and fracture risk.

Evaluation of rs1748195 ANGPTL3 gene polymorphism in patients with angiographic coronary artery disease compared to healthy individuals

SUBJECT

The Angiopoietin-like 3 (ANGPTL3) gene has been reported to be associated with cardiovascular risk. This study is designed to compare the genetic variant (rs1748195) of the ANGPTL3 gene and the presence of a coronary artery occlusion of >50% in Iranian nation.

METHOD

In this study, 184 patients underwent angiography and 317 healthy individuals were evaluated for polymorphism of rs1748195 the ANGPTL3 gene using Tetra-ARMs PCR. Coronary patients who experience angiography were categorized into two groups: 54 patients who had an angiography indication for the first time and coronary occlusion was <50% (Angio-) and 134 patients who formerly underwent coronary stent implanting at least 1 month before with coronary occlusion of ≥50% that again have an angiography indication (Angio+). In addition, individuals with angio+ are categorized in two groups: (1) non-in-stent restenosis (NISR); patient with a patent stent (N = 92). (2) in-stent restenosis (ISR); in-stent stenosis >50% (N = 42).

RESULT

The fundamental of characteristics of our study design population was categorized based on undergoing angiography or not. In the present study, we investigated that the CC genotype, and also the A allele corresponding to rs1748195 at the ANGPTL3 gene loci, was associated with negative angiogram and directly related to the risk of coronary occlusion >50%. In contrast, this result was not significant in genotypes of ANGPTL3 between non-ISR and ISR groups.

CONCLUSION

The outcomes of this study showed that rs1748195 polymorphism at the ANGPTL3 gene loci is associated with an elevated risk for the existence of a coronary occlusion of >50%.

Insights into the Structure and Function of TRIP-1, a Newly Identified Member in Calcified Tissues

Eukaryotic initiation factor subunit I (EIF3i), also called as p36 or TRIP-1, is a component of the translation initiation complex and acts as a modulator of TGF-β signaling. We demonstrated earlier that this intracellular protein is not only exported to the extracellular matrix via exosomes but also binds calcium phosphate and promotes hydroxyapatite nucleation. To assess other functional roles of TRIP-1, we first examined their phylogeny and showed that it is highly conserved in eukaryotes. Comparing human EIF3i sequence with that of 63 other eukaryotic species showed that more than 50% of its sequence is conserved, suggesting the preservation of its important functional role (translation initiation) during evolution. TRIP-1 contains WD40 domains and predicting its function based on this structural motif is difficult as it is present in a vast array of proteins with a wide variety of functions. Therefore, bioinformatics analysis was performed to identify putative regulatory functions for TRIP-1 by examining the structural domains and post-translational modifications and establishing an interactive network using known interacting partners such as type I collagen. Insight into the function of TRIP-1 was also determined by examining structurally similar proteins such as Wdr5 and GPSß, which contain a ß-propeller structure which has been implicated in the calcification process. Further, proteomic analysis of matrix vesicles isolated from TRIP-1-overexpressing preosteoblastic MC3T3-E1 cells demonstrated the expression of several key biomineralization-related proteins, thereby confirming its role in the calcification process. Finally, we demonstrated that the proteomic signature in TRIP1-OE MVs facilitated osteogenic differentiation of stem cells. Overall, we demonstrated by bioinformatics that TRIP-1 has a unique structure and proteomic analysis suggested that the unique osteogenic cargo within the matrix vesicles facilitates matrix mineralization.

Heart Disease and Stroke Statistics-2023 Update: A Report From the American Heart Association

BACKGROUND

The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The American Heart Association, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2023 Statistical Update is the product of a full year's worth of effort in 2022 by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. The American Heart Association strives to further understand and help heal health problems inflicted by structural racism, a public health crisis that can significantly damage physical and mental health and perpetuate disparities in access to health care, education, income, housing, and several other factors vital to healthy lives. This year's edition includes additional COVID-19 (coronavirus disease 2019) publications, as well as data on the monitoring and benefits of cardiovascular health in the population, with an enhanced focus on health equity across several key domains.

RESULTS

Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.

CONCLUSIONS

The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

PLAG1 g.8795C>T Mutation Regulates Early Body Weight in Hu Sheep by Weakening miR-139 Binding

Sheep birth and weaning weights indicate their growth and survival. Thus, identifying molecular genetic markers for early body weight is important in sheep breeding. Pleomorphic adenoma gene 1 (PLAG1) is important for regulating birth weight and body length in mammals; however, its relationship with sheep body weight remains unknown. Here, the 3'-untranslated region (3'-UTR) of the Hu sheep PLAG1 gene was cloned, single nucleotide polymorphisms (SNPs) were screened, genotype-early body weight relationships were analyzed, and the possible molecular mechanism was explored. PLAG1 3'-UTR sequences with five forms of base sequences plus poly(A) tails were detected in Hu sheep and the g.8795C>T mutation was identified. Luciferase reporter assay indicated that the g.8795C>T mutation influenced PLAG1 post-transcriptional activity. miRBase prediction showed that the g.8795C>T mutation was located in the miR-139 seed sequence binding region, and miR-139 overexpression significantly decreased both PLAG1-CC and PLAG1-TT activities. Moreover, the luciferase activity of PLAG1-CC was significantly lower than that of the PLAG1-TT, but miR-139 inhibition substantially increased both PLAG1-CC and PLAG1-TT luciferase activities, suggesting that PLAG1 is the target gene of miR-139. Thus, the g.8795C>T mutation upregulates PLAG1 expression by weakening its binding with miR-139, promoting PLAG1 expression, and increasing Hu sheep birth and weaning weights.

Genome-wide assessment reveals a significant association between ACSS3 and physical activity

Recent genetic studies have identified physical activity (PA)-susceptible loci in European ancestry subjects; however, due to considerable genetic differences, these findings are not likely extendable to East Asian populations. Therefore, the present study aimed to identify significantly associated PA-susceptible loci using genome-wide association studies (GWASs) with East Asian (EAS) subjects and to generalize the findings to European (EUR) ancestries. The mRNA levels of genes located near the genome-wide significantly associated single-nucleotide polymorphisms (SNP) were compared under PA and control conditions. Rs74937256, located in ACSS3 (chromosome 12), which primarily functions in skeletal muscle tissues, was identified as a genome-wide significant variant (P = 6.06 × 10^-9 ) in EAS. Additionally, the rs2525840, also in ACSS3 satisfied the Bonferroni corrected significance (P = 3.77 × 10^-5 ) in EUR. We found that rs74937256 is an expressed trait locus of ACSS3 (P = 10^-4 ), and ACSS3 mRNA expression significantly differs after PA, based on PrediXcan (P = 7 × 10^-8 ) and the gene expression omnibus database (P = 0.043).

Minor alleles in the FTO SNPs contributed to the increased risk of obesity among Korean adults: meta-analysis from nationwide big data-based studies

BACKGROUND/OBJECTIVES

Many studies have revealed an association between fat mass and the obesity-related gene (FTO) and obesity. On the other hand, no meta-analysis was conducted with data from only Koreans. Therefore, this study performed a meta-analysis using Korean data to provide evidence for the association between FTO single nucleotide polymorphisms (SNPs) and the risk of obesity among Korean adults.

SUBJECT/METHODS

Meta-analysis was finally conducted with data extracted from seven datasets of four studies performed on Korean adults after the screening passed. Five kinds of FTO SNPs (rs9939609, rs7193144, rs9940128, rs8050136, and rs9926289) were included, and the relationship between FTO SNPs and body mass index (BMI) was investigated using linear regression with an additive model adjusted for covariants, such as age, sex, and area.

RESULTS

The minor alleles of FTO SNPs were associated with increased BMI (odds ratio [OR], 1.31; 95% confidence interval [CI], 1.21-1.42). In sub-group analysis, FTO rs9939609 T>A was significantly associated with BMI (OR, 1.23; 95% CI, 1.06-1.42). The other FTO SNPs together were significantly associated with BMI (OR, 1.37; 95% CI, 1.25-1.49). The publication bias was not observed based on Egger's test.

CONCLUSIONS

This meta-analysis showed that minor alleles in the FTO SNPs were significantly associated with an increased BMI among Korean adults. This meta-analysis is the first to demonstrate that minor alleles in the FTO SNPs contribute significantly to the increased risk of obesity among Korean adults using data from a Korean population.

Genetic variation rs1121980 in the fat mass and obesity-associated gene (FTO) is associated with dietary intake in Koreans

Background

Fat mass and obesity-associated gene (FTO) is a well-known gene associated with body weight and obesity risk. Recent studies have suggested that genetic variations in FTO may play a role in the regulation of food preference and consumption. However, little is known with respect to Asian populations.

Objective

This study examined whether rs1121980 C > T in FTO is associated with food intake in Koreans.

Design

This study was performed using data from the Korean Genome and Epidemiology Study (Ansan/Ansung cohort). Dietary intake was determined using the semi-food frequency questionnaire, and the FTO rs1121980 genotypes of 6,262 individuals (3,049 males and 3,213 females) were analyzed along with sex and body mass index (BMI).

Result

Genetic variation did not show a significant association with the population's energy-nutrient intake. However, female T allele carriers with BMI ≥ 25 consumed more blue fish and coffee, and their coffee creamer consumption was decisively higher than that of T allele non-carriers (P _adjusted = 0.004). In males, the presence of the T allele showed a putative association with the consumption of sweets, snacks, and coffee creamer by the BMI level.

Conclusion

The FTO rs1121980 variation was associated with a preference for foods particularly high in fat (e.g. coffee creamer, blue fish, sweets, and snacks) in Koreans; these preferences varied by sex and BMI.

Genetics of Obesity in Humans: A Clinical Review

Obesity is a complex multifactorial disorder with genetic and environmental factors. There is an increase in the worldwide prevalence of obesity in both developed and developing countries. The development of genome-wide association studies (GWAS) and next-generation sequencing (NGS) has increased the discovery of genetic associations and awareness of monogenic and polygenic causes of obesity. The genetics of obesity could be classified into syndromic and non-syndromic obesity. Prader-Willi, fragile X, Bardet-Biedl, Cohen, and Albright Hereditary Osteodystrophy (AHO) syndromes are examples of syndromic obesity, which are associated with developmental delay and early onset obesity. Non-syndromic obesity could be monogenic, polygenic, or chromosomal in origin. Monogenic obesity is caused by variants of single genes while polygenic obesity includes several genes with the involvement of members of gene families. New advances in genetic testing have led to the identification of obesity-related genes. Leptin (LEP), the leptin receptor (LEPR), proopiomelanocortin (POMC), prohormone convertase 1 (PCSK1), the melanocortin 4 receptor (MC4R), single-minded homolog 1 (SIM1), brain-derived neurotrophic factor (BDNF), and the neurotrophic tyrosine kinase receptor type 2 gene (NTRK2) have been reported as causative genes for obesity. NGS is now in use and emerging as a useful tool to search for candidate genes for obesity in clinical settings.

Integrated dataset of the Korean Genome and Epidemiology Study cohort with estimated air pollution data

Public concern about the adverse health effects of air pollution has grown rapidly in Korea, and there has been increasing demand for research on ways to minimize the health effects of air pollution. Integrating large epidemiological data and air pollution exposure levels can provide a data infrastructure for studying ambient air pollution and its health effects. The Korean Genome and Epidemiology Study (KoGES), a large population-based study, has been used in many epidemiological studies of chronic diseases. Therefore, KoGES cohort data were linked to air pollution data as a national resource for air pollution studies. Air pollution data were produced using community multiscale air quality modeling with additional adjustment of monitoring data, satellite-derived aerosol optical depth, normalized difference vegetation index, and meteorological data to increase the accuracy and spatial resolution. The modeled air pollution data were linked to the KoGES cohort based on participants' geocoded residential addresses in grids of 1 km (particulate matter) or 9 km (gaseous air pollutants and meteorological variables). As the integrated data become available to all researchers, this resource is expected to serve as a useful infrastructure for research on the health effects of air pollution.

Kidney omics in hypertension: from statistical associations to biological mechanisms and clinical applications

Hypertension is a major cardiovascular disease risk factor and contributor to premature death globally. Family-based investigations confirmed a significant heritable component of blood pressure (BP), whereas genome-wide association studies revealed >1000 common and rare genetic variants associated with BP and/or hypertension. The kidney is not only an organ of key relevance to BP regulation and the development of hypertension, but it also acts as the tissue mediator of genetic predisposition to hypertension. The identity of kidney genes, pathways, and related mechanisms underlying the genetic associations with BP has started to emerge through integration of genomics with kidney transcriptomics, epigenomics, and other omics as well as through applications of causal inference, such as Mendelian randomization. Single-cell methods further enabled mapping of BP-associated kidney genes to cell types, and in conjunction with other omics, started to illuminate the biological mechanisms underpinning associations of BP-associated genetic variants and kidney genes. Polygenic risk scores derived from genome-wide association studies and refined on kidney omics hold the promise of enhanced diagnostic prediction, whereas kidney omics-informed drug discovery is likely to contribute new therapeutic opportunities for hypertension and hypertension-mediated kidney damage.

Interactive effects of the low-carbohydrate diet score and genetic risk score on Hypo-HDL-cholesterolemia among Korean adults: A cross-sectional analysis from the Ansan and Ansung Study of the Korean Genome and Epidemiology Study

This cross-sectional study investigated the interaction between the genetic risk score (GRS) and abnormal high-density lipoprotein (HDL) cholesterol lipid levels, which are modified by low-carbohydrate diets (LCDs) and their effects on the prevalence of hypo-HDL-cholesterolemia (hypo-HDL-C) in Korean adults. Baseline data were obtained from the Ansan and Ansung study of the Korean Genome and Epidemiology Study (KoGES), conducted from 2001 to 2002, that targeted 8,314 Korean adults aged 40-69 years, including old men (47.6%) and women (52.4%), and whole genomic single nucleotide polymorphism (SNP) genotyping was performed. We identified 18 SNPs significantly associated with hypo-HDL-C in the proximity of several genes, including LPL, APOA5, LIPC, and CETP, and calculated the GRS. The low-carbohydrate diet score (LCDS) was calculated on the basis of energy intake information from food frequency questionnaires. Furthermore, we performed multivariable-adjusted logistic modeling to examine the odds ratio (OR) for hypo-HDL-C across tertiles of LCDS and GRS, adjusted for several covariates. Among participants in the highest GRS tertile, those in the highest tertile of the LCDS had a significantly lower risk of hypo-HDL-C (OR: 0.759, 95% CI (confidence interval): 0.625-0.923) than those in the lowest tertile of the LCDS. In the joint effect model, the group with the lowest GRS and highest LCDS was found to have the lowest risk of hypo-HDL-C prevalence. This study suggests that individuals with a high genetic risk for low HDL concentrations may have a beneficial effect on a lower intake of carbohydrates.

A Genome-Wide Association Study of Genetic Variants of Apolipoprotein A1 Levels and Their Association with Vitamin D in Korean Cohorts

Dyslipidemia is an important independent risk factor for cardiovascular disease (CVD). Specifically, apolipoprotein A1 (ApoA1), apolipoprotein B (ApoB), and the ApoB/A1 ratio have been linked to CVD. We conducted a genome-wide association study meta-analysis of two Korean cohorts containing a total of 12,924 patients to identify novel single nucleotide polymorphisms (SNPs) associated with ApoA1 and ApoB levels and the ApoB/A1 ratio. Additionally, an expression quantitative trait locus (eQTL) and differentially expressed genes (DEGs) analysis were performed. The statistically significant eQTL, DEG, and Gene Ontology (GO) results were used to explore the predicted interaction networks and retrieve the interacting genes and proteins. We identified three novel SNPs (rs11066280, p = 3.46 × 10−21; rs1227162, p = 2.98 × 10−15; rs73216931, p = 5.62 × 10−9) associated with ApoA1. SNP rs73216931 was an eQTL for KMT5A in the pancreas and whole blood. The network analysis revealed that HECTD4 and MYL2:LINC1405 are associated with AKT1. Our in silico analysis of ApoA1 genetic variants revealed heart muscle-related signals. ApoA1 also correlated positively with vitamin D, and genes associated with ApoA1 and vitamin D were found. Our data imply that more research into ApoA1 is needed to understand the links between dyslipidemia and CVD and vitamin D and CVD.

Context-dependent CpG methylation directs cell-specific binding of transcription factor ZBTB38

DNA methylation on CpGs regulates transcription in mammals, both by decreasing the binding of methylation-repelled factors and by increasing the binding of methylation-attracted factors. Among the latter, zinc finger proteins have the potential to bind methylated CpGs in a sequence-specific context. The protein ZBTB38 is unique in that it has two independent sets of zinc fingers, which recognize two different methylated consensus sequences in vitro. Here, we identify the binding sites of ZBTB38 in a human cell line, and show that they contain the two methylated consensus sequences identified in vitro. In addition, we show that the distribution of ZBTB38 sites is highly unusual: while 10% of the ZBTB38 sites are also bound by CTCF, the other 90% of sites reside in closed chromatin and are not bound by any of the other factors mapped in our model cell line. Finally, a third of ZBTB38 sites are found upstream of long and active CpG islands. Our work therefore validates ZBTB38 as a methyl-DNA binder in vivo and identifies its unique distribution in the genome.

Identification of genetic variants related to metabolic syndrome by next-generation sequencing

BACKGROUND

Metabolic syndrome (MetS) is a cluster of conditions associated with glucose intolerance, hypertension, abdominal obesity, dyslipidemia, and insulin resistance that increase the risk of cardiovascular diseases (CVD) and type 2 diabetes (T2D). Since MetS is known as a complex symptom with a high incidence of genetic factors, it is important to identify genetic variants for each clinical characteristic of MetS.

METHODS

We performed targeted next-generation sequencing (NGS) to identify genetic variants related to obesity, blood glucose, triacylglycerol (TG), and high-density lipoprotein (HDL)-cholesterol level, and hypertension in 48 subjects with MetS and in 48 healthy subjects.

RESULTS

NGS analysis revealed that 26 of 48 subjects (54.2%) with MetS had putative non-synonymous variants related to the clinical features of MetS. Of the subjects with MetS, 8 (16.7%) had variants in 4 genes (COL6A2, FTO, SPARC, and MTHFR) related to central obesity, 17 (35.4%) had variants in 6 genes (APOB, SLC2A2, LPA, ABCG5, ABCG8, and GCKR) related to hyperglycemia, 3 (6.3%) had variants in 4 genes (APOA1, APOC2, APOA4, and LMF1) related to hypertriglyceridemia, 8 (16.7%) had variants in 4 genes (ABCA1, CETP, SCARB1, and LDLR) related to low HDL-cholesterolemia, and 5 (10.4%) had variants in ADD1 related to hypertension.

CONCLUSIONS

Our findings may contribute to broadening the genetic spectrum of risk variants related to the development of MetS.