A genome-wide association study of the metabolic syndrome in Indian Asian men

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.

Comprehensive genetic study of the insulin resistance marker TG:HDL-C in the UK Biobank

Insulin resistance (IR) is a well-established risk factor for metabolic disease. The ratio of triglycerides to high-density lipoprotein cholesterol (TG:HDL-C) is a surrogate marker of IR. We conducted a genome-wide association study of the TG:HDL-C ratio in 402,398 Europeans within the UK Biobank. We identified 369 independent SNPs, of which 114 had a false discovery rate-adjusted P value < 0.05 in other genome-wide studies of IR making them high-confidence IR-associated loci. Seventy-two of these 114 loci have not been previously associated with IR. These 114 loci cluster into five groups upon phenome-wide analysis and are enriched for candidate genes important in insulin signaling, adipocyte physiology and protein metabolism. We created a polygenic-risk score from the high-confidence IR-associated loci using 51,550 European individuals in the Michigan Genomics Initiative. We identified associations with diabetes, hyperglyceridemia, hypertension, nonalcoholic fatty liver disease and ischemic heart disease. Collectively, this study provides insight into the genes, pathways, tissues and subtypes critical in IR.

Metabolic Syndrome: An Overview on Its Genetic Associations and Gene-Diet Interactions

Metabolic syndrome (MetS) is a cluster of cardiometabolic risk factors that includes central obesity, hyperglycemia, hypertension, and dyslipidemias and whose inter-related occurrence may increase the odds of developing type 2 diabetes and cardiovascular diseases. MetS has become one of the most studied conditions, nevertheless, due to its complex etiology, this has not been fully elucidated. Recent evidence describes that both genetic and environmental factors play an important role on its development. With the advent of genomic-wide association studies, single nucleotide polymorphisms (SNPs) have gained special importance. In this review, we present an update of the genetics surrounding MetS as a single entity as well as its corresponding risk factors, considering SNPs and gene-diet interactions related to cardiometabolic markers. In this study, we focus on the conceptual aspects, diagnostic criteria, as well as the role of genetics, particularly on SNPs and polygenic risk scores (PRS) for interindividual analysis. In addition, this review highlights future perspectives of personalized nutrition with regard to the approach of MetS and how individualized multiomics approaches could improve the current outlook.

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.

Current Data and New Insights into the Genetic Factors of Atherogenic Dyslipidemia Associated with Metabolic Syndrome

Atherogenic dyslipidemia plays a critical role in the development of metabolic syndrome (MetS), being one of its major components, along with central obesity, insulin resistance, and hypertension. In recent years, the development of molecular genetics techniques and extended analysis at the genome or exome level has led to important progress in the identification of genetic factors (heritability) involved in lipid metabolism disorders associated with MetS. In this review, we have proposed to present the current knowledge related to the genetic etiology of atherogenic dyslipidemia, but also possible challenges for future studies. Data from the literature provided by candidate gene-based association studies or extended studies, such as genome-wide association studies (GWAS) and whole exome sequencing (WES,) have revealed that atherogenic dyslipidemia presents a marked genetic heterogeneity (monogenic or complex, multifactorial). Despite sustained efforts, many of the genetic factors still remain unidentified (missing heritability). In the future, the identification of new genes and the molecular mechanisms by which they intervene in lipid disorders will allow the development of innovative therapies that act on specific targets. In addition, the use of polygenic risk scores (PRS) or specific biomarkers to identify individuals at increased risk of atherogenic dyslipidemia and/or other components of MetS will allow effective preventive measures and personalized therapy.

GPR19 Coordinates Multiple Molecular Aspects of Stress Responses Associated with the Aging Process

G protein-coupled receptors (GPCRs) play a significant role in controlling biological paradigms such as aging and aging-related disease. We have previously identified receptor signaling systems that are specifically associated with controlling molecular pathologies associated with the aging process. Here, we have identified a pseudo-orphan GPCR, G protein-coupled receptor 19 (GPR19), that is sensitive to many molecular aspects of the aging process. Through an in-depth molecular investigation process that involved proteomic, molecular biological, and advanced informatic experimentation, this study found that the functionality of GPR19 is specifically linked to sensory, protective, and remedial signaling systems associated with aging-related pathology. This study suggests that the activity of this receptor may play a role in mitigating the effects of aging-related pathology by promoting protective and remedial signaling systems. GPR19 expression variation demonstrates variability in the molecular activity in this larger process. At low expression levels in HEK293 cells, GPR19 expression regulates signaling paradigms linked with stress responses and metabolic responses to these. At higher expression levels, GPR19 expression co-regulates systems involved in sensing and repairing DNA damage, while at the highest levels of GPR19 expression, a functional link to processes of cellular senescence is seen. In this manner, GPR19 may function as a coordinator of aging-associated metabolic dysfunction, stress response, DNA integrity management, and eventual senescence.

Metabolic Syndrome and Chronic Disease Risk in South Asian Immigrants: A Review of Prevalence, Factors, and Interventions

South Asians (SAs) are among the fastest-growing ethnic groups in the U.S. Metabolic syndrome (MetS) is a condition that is characterized by multiple health factors that increase the risk for chronic diseases, such as cardiovascular disease (CVD) and diabetes. MetS prevalence among SA immigrants ranges from 27-47% in multiple cross-sectional studies using different diagnostic criteria, which is generally higher compared to other populations in the receiving country. Both genetic and environmental factors are attributed to this increased prevalence. Limited intervention studies have shown effective management of MetS conditions within the SA population. This review reports MetS prevalence in SAs residing in non-native countries, identifies contributing factors, and discusses ways to develop effective community-based strategies for health promotion targeting MetS among SA immigrants. There is a need for more consistently evaluated longitudinal studies to facilitate the development of directed public health policy and education to address chronic diseases in the SA immigrant community.

Precision medicine and metabolic syndrome

Metabolic syndrome (MetS) is one of the most important health issues around the world and a major risk factor for both type 2 diabetes mellitus (T2DM) and cardiovascular diseases. The etiology of MetS is determined by the interaction between genetic and environmental factors. Effective prevention and treatment of MetS notably decreases the risk of its complications such as diabetes, obesity, hypertension, and dyslipidemia. According to recent genome-wide association studies, multiple genes are involved in the incidence and development of MetS. The presence of particular genes which are responsible for obesity and lipid metabolism, affecting insulin sensitivity and blood pressure, as well as genes associated with inflammation, can increase the risk of MetS. These molecular markers, together with clinical data and findings from proteomic, metabolomic, pharmacokinetic, and other methods, would clarify the etiology and pathophysiology of MetS and facilitate the development of personalized approaches to the management of MetS. The application of personalized medicinebased on susceptibility identified genomes would help physicians recommend healthier lifestyles and prescribe medications to improve various aspects of health in patients with MetS. In recent years, personalized medicine by genetic testing has helped physicians determine genetic predisposition to MetS, prevent the disease by behavioral, lifestyle-related, or therapeutic interventions, and detect, diagnose, treat, and manage the disease. Clinically, personalized medicine is providing effective strategies for the prevention and treatment of MetS by reducing the time, cost, and failure rate of pharmaceutical clinical trials. It is also eliminating trial-and-error inefficiencies that inflate health care costs and undermine patient care.

Impact of Lipid Genetic Risk Score and Saturated Fatty Acid Intake on Central Obesity in an Asian Indian Population

Abnormalities in lipid metabolism have been linked to the development of obesity. We used a nutrigenetic approach to establish a link between lipids and obesity in Asian Indians, who are known to have a high prevalence of central obesity and dyslipidaemia. A sample of 497 Asian Indian individuals (260 with type 2 diabetes and 237 with normal glucose tolerance) (mean age: 44 ± 10 years) were randomly chosen from the Chennai Urban Rural Epidemiological Study (CURES). Dietary intake was assessed using a previously validated questionnaire. A genetic risk score (GRS) was constructed based on cholesteryl ester transfer protein (CETP) and lipoprotein lipase (LPL) genetic variants. There was a significant interaction between GRS and saturated fatty acid (SFA) intake on waist circumference (WC) (Pinteraction = 0.006). Individuals with a low SFA intake (≤23.2 g/day), despite carrying ≥2 risk alleles, had a smaller WC compared to individuals carrying <2 risk alleles (Beta = −0.01 cm; p = 0.03). For those individuals carrying ≥2 risk alleles, a high SFA intake (>23.2 g/day) was significantly associated with a larger WC than a low SFA intake (≤23.2 g/day) (Beta = 0.02 cm, p = 0.02). There were no significant interactions between GRS and other dietary factors on any of the measured outcomes. We conclude that a diet low in SFA might help reduce the genetic risk of central obesity confirmed by CETP and LPL genetic variants. Conversely, a high SFA diet increases the genetic risk of central obesity in Asian Indians.

Transethnic meta-analysis of exome-wide variants identifies new loci associated with male-specific metabolic syndrome

BACKGROUND

Metabolic syndrome (MetS) is a group of very common human conditions promoting strong understand the impact of rare variants, beyond exome-wide association studies, to potentially discover causative variants, across different ethnic populations.

OBJECTIVE

We performed transethnic, exome-wide MetS association studies on MetS in men.

METHODS

We analyzed genotype data of 5302 European subjects (2658 cases and 2644 controls), in the discovery stage of the European METabolic Syndrome In Men study, generated from exome chips, and 2481 subjects (714 cases and 1767 controls), in the replication stage, across 6 independent cohorts of 5 ancestries (T2D-GENES consortium), using whole-exome sequencing. We therefore evaluated gene-level and variant-level associations, of rare variants for MetS, using logistic regression (LR) and multivariate analyses (MulA).

RESULTS

Gene-based association found the gene for the cholesteryl ester transfer protein (CETP) (from MulA, p value = 4.67 × 10-9; from LR, p value = 0.009) to well associate with MetS. At two missense variants, from 8 rare variants in CETP, Ala390Pro (rs5880) (from MulA, p value = 1.28 × 10-7; from LR, p value = 1.34 × 10-4) and Arg468Gln (rs1800777) (from MulA, p value = 2.40 × 10-5; from LR, p value = 1.49 × 10-3) significantly associated with MetS across five ancestries.

CONCLUSIONS

Our findings highlight novel rare variants of genes that confer MetS susceptibility, in Europeans, that are shared with diverse populations, emphasizing an opportunity to further understand the biological target or genes that underlie MetS, across populations.

A Nutrigenetic Update on CETP Gene–Diet Interactions on Lipid-Related Outcomes

Purpose of Review

An abnormal lipid profile is considered a main risk factor for cardiovascular diseases and evidence suggests that single nucleotide polymorphisms (SNPs) in the cholesteryl ester transfer protein (CETP) gene contribute to variations in lipid levels in response to dietary intake. The objective of this review was to identify and discuss nutrigenetic studies assessing the interactions between CETP SNPs and dietary factors on blood lipids.

Recent Findings

Relevant articles were obtained through a literature search of PubMed and Google Scholar through to July 2021. An article was included if it examined an interaction between CETP SNPs and dietary factors on blood lipids. From 49 eligible nutrigenetic studies, 27 studies reported significant interactions between 8 CETP SNPs and 17 dietary factors on blood lipids in 18 ethnicities. The discrepancies in the study findings could be attributed to genetic heterogeneity, and differences in sample size, study design, lifestyle and measurement of dietary intake. The most extensively studied ethnicities were those of Caucasian populations and majority of the studies reported an interaction with dietary fat intake. The rs708272 (TaqIB) was the most widely studied CETP SNP, where ‘B1’ allele was associated with higher CETP activity, resulting in lower high-density lipoprotein cholesterol and higher serum triglycerides under the influence of high dietary fat intake.

Summary

Overall, the findings suggest that CETP SNPs might alter blood lipid profiles by modifying responses to diet, but further large studies in multiple ethnic groups are warranted to identify individuals at risk of adverse lipid response to diet.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11883-022-00987-y.

An epigenome-wide association study of metabolic syndrome and its components

The role of metabolic syndrome (MetS) as a preceding metabolic state for type 2 diabetes and cardiovascular disease is widely recognised. To accumulate knowledge of the pathological mechanisms behind the condition at the methylation level, we conducted an epigenome-wide association study (EWAS) of MetS and its components, testing 1187 individuals of European ancestry for approximately 470 000 methylation sites throughout the genome. Methylation site cg19693031 in gene TXNIP —previously associated with type 2 diabetes, glucose and lipid metabolism, associated with fasting glucose level (P = 1.80 × 10⁻⁸). Cg06500161 in gene ABCG1 associated both with serum triglycerides (P = 5.36 × 10⁻⁹) and waist circumference (P = 5.21 × 10⁻⁹). The previously identified type 2 diabetes–associated locus cg08309687 in chromosome 21 associated with waist circumference for the first time (P = 2.24 × 10⁻⁷). Furthermore, a novel HDL association with cg17901584 in chromosome 1 was identified (P = 7.81 × 10⁻⁸). Our study supports previous genetic studies of MetS, finding that lipid metabolism plays a key role in pathology of the syndrome. We provide evidence regarding a close interplay with glucose metabolism. Finally, we suggest that in attempts to identify methylation loci linking separate MetS components, cg19693031 appears to represent a strong candidate.

Four pleiotropic loci associated with fat mass and lean mass

BACKGROUND

Fat mass and lean mass are two biggest components of body mass. Both fat mass and lean mass are under strong genetic determinants and are correlated.

METHODS

We performed a bivariate genome-wide association meta-analysis of (lean adjusted) leg fat mass and (fat adjusted) leg lean mass in 12,517 subjects from 6 samples, and followed by in silico replication in large-scale UK biobank cohort sample (N = 370 097).

RESULTS

We identified four loci that were significant at the genome-wide significance (GWS, α = 5.0 × 10-8) level at the discovery meta-analysis, and successfully replicated in the replication sample: 2q36.3 (rs1024137, pdiscovery = 3.32 × 10-8, preplication = 4.07 × 10-13), 5q13.1 (rs4976033, pdiscovery = 1.93 × 10-9, preplication = 6.35 × 10-7), 12q24.31 (rs4765528, pdiscovery = 7.19 × 10-12, preplication = 1.88 × 10-11) and 18q21.32 (rs371326986, pdiscovery = 9.04 × 10-9, preplication = 2.35 × 10-95). The above four pleiotropic loci may play a pleiotropic role for fat mass and lean mass development.

CONCLUSIONS

Our findings further enhance the understanding of the genetic association between fat mass and lean mass and provide a new theoretical basis for their understanding.

Test Gene-Environment Interactions for Multiple Traits in Sequencing Association Studies

MOTIVATION

The risk of many complex diseases is determined by an interplay of genetic and environmental factors. The examination of gene-environment interactions (G×Es) for multiple traits can yield valuable insights about the etiology of the disease and increase power in detecting disease-associated genes. However, the methods for testing G×Es for multiple traits are very limited.

METHOD

We developed novel approaches to test G×Es for multiple traits in sequencing association studies. We first perform a transformation of multiple traits by using either principal component analysis or standardization analysis. Then, we detect the effects of G×Es using novel proposed tests: testing the effect of an optimally weighted combination of G×Es (TOW-GE) and/or variable weight TOW-GE (VW-TOW-GE). Finally, we employ Fisher's combination test to combine the p values.

RESULTS

Extensive simulation studies show that the type I error rates of the proposed methods are well controlled. Compared to the interaction sequence kernel association test (ISKAT), TOW-GE is more powerful when there are only rare risk and protective variants; VW-TOW-GE is more powerful when there are both rare and common variants. Both TOW-GE and VW-TOW-GE are robust to directions of effects of causal G×Es. Application to the COPDGene Study demonstrates that our proposed methods are very effective.

CONCLUSIONS

Our proposed methods are useful tools in the identification of G×Es for multiple traits. The proposed methods can be used not only to identify G×Es for common variants, but also for rare variants. Therefore, they can be employed in identifying G×Es in both genome-wide association studies and next-generation sequencing data analyses.

Clinical correlations and genetic associations of metabolic syndrome in the United Arab Emirates

BACKGROUND

Metabolic syndrome (MetS) contributes to increased risk of morbidity and mortality. The United Arab Emirates (UAE) has a high prevalence of MetS which may be linked to modifiable and genetic risk factors in the local population. The association between MetS as a phenotype and key genetic variants in the UAE has not been investigated. This study reports on the clinical, biochemical and genetic associations of MetS and its risk factors to improve individualized medicine outcomes.

METHODS

There were 471 subjects included in this cross-sectional study, 367 with MetS and 104 without MetS. Along with clinical and laboratory parameters, multiple risk genetic variants were tested for their association with MetS, which include 49 variants that have previously been shown to be linked with MetS development as a phenotype, 116 variants for association with waist-hip ratio (WHR), 398 variants with body-mass index (BMI), 213 variants with T2DM and insulin resistance, 307 variants with different lipid traits, 308 variants with blood pressure traits, and 64 variants with coronary and cerebrovascular accidents.

RESULTS

Patients with MetS had higher rates of type 2 diabetes mellitus (T2DM), hypertension and dyslipidemia (p < 0.0001). Waist circumference and T2DM were identified as the key risk factors for MetS development. Individuals with MetS were also found to have a higher rate of clinical complications than those without MetS (76% vs. 52%). Several gene variants including those of the FTO gene were found to be associated with a predisposition to developing MetS or some of its components (P_FTO ~0.005-0.009).

CONCLUSIONS

This study showed associations between MetS as well as clinical factors contributing to MetS and specific genetic and metabolic risk factors, providing an insight into the metabolic and genetic links to disease development. Knowledge with respect to population specific risk markers including at risk genotypes will help in early identification of individuals with increased susceptibility to MetS in the UAE and provide the opportunity for timely intervention to prevent or delay the onset of MetS.

Genetic Determinants of Clustering of Cardiometabolic Risk Factors in U.K. Biobank

Objective: The metabolic syndrome (MetS) is a description of a clustering of cardiometabolic risk factors in the same individual. This study searched for genetic loci associated with all five prespecified components of MetS to find a common pathophysiological link for this risk factor clustering. Methods: Using data from 291,107 individuals in the U.K. biobank, a genome-wide association study (GWAS) was performed versus each of the five components of the syndrome as continuous variables (glucose, systolic blood pressure, triglycerides, waist circumference, and high-density lipoprotein-cholesterol). Results: Using false discovery rate <0.05, three loci were related to all five MetS components (rs7575523; nearest gene LINC0112, rs3936511; intron of C5orf67, and rs111970447; intron of GIP). Of those, C5orf67 seems the most interesting candidate for clustering of risk factors, since previous GWASs in other samples have identified this locus as being related to all five risk factors. Also, genetic loci being related to the different combinations of four or three MetS components were presented. Generally, each MetS component combination was related to a unique genetic profile, and the genetic overlap between these combinations was low. Conclusion: A genetic locus was discovered being related to each of the five MetS components, being a candidate for a common pathophysiological link for risk factor clustering. In addition, genetic loci being related to different combinations of four or three MetS components were presented, and the genetic overlap between those combinations of MetS was low.

Genome-Wide Association Study of the Metabolic Syndrome in UK Biobank

Background: The metabolic syndrome (MetS) is a description of a clustering of cardiometabolic risk factors in the same individual. Previous genome-wide association studies (GWASs) have identified 29 independent genetic loci linked to MetS as a binary trait. This study used data from UK biobank to search for additional loci. Methods: Using data from 291,107 individuals in the UK biobank, a GWAS was performed versus the binary trait MetS (harmonized NCEP criteria). Results: In a GWAS of MetS (binary) we found 93 independent loci with P < 5 × 10^-8, of which 80 were not identified in previous GWASs of MetS. However, the majority of those loci have previously been associated with one or more of the five MetS components. Of particular interest are the genes being related to MetS (binary) in this study, but not to any of the MetS components in past studies, such as WDR48, KLF14, NAADL1, GADD45G, and OR5R1, as well as the two loci that have been associated with all five MetS components in past studies, SNX10 and C5orf67. A pathway analysis of the 93 independent loci showed the immune system, transportation of small molecules, and metabolism to be enriched. Conclusion: This GWAS of the MetS in UK biobank identified several new loci being associated with MetS. Most of those have previously been found to be associated with different components of MetS, but several loci were found not previously linked to cardiometabolic disease.

Gut Microbiota Has a Widespread and Modifiable Effect on Host Gene Regulation

The composition of the gut microbiome has been associated with various aspects of human health, but the mechanism of this interaction is still unclear. We utilized a cellular system to characterize the effect of the microbiome on human gene expression. We showed that some of these changes in expression may be mediated by changes in chromatin accessibility. Furthermore, we validate the role of a specific microbe and show that changes in its abundance can modify the host gene expression response. These results show an important role of gut microbiota in regulating host gene expression and suggest that manipulation of microbiome composition could be useful in future therapies.

Variation in gut microbiome is associated with wellness and disease in humans, and yet the molecular mechanisms by which this variation affects the host are not well understood. A likely mechanism is that of changing gene regulation in interfacing host epithelial cells. Here, we treated colonic epithelial cells with live microbiota from five healthy individuals and quantified induced changes in transcriptional regulation and chromatin accessibility in host cells. We identified over 5,000 host genes that change expression, including 588 distinct associations between specific taxa and host genes. The taxa with the strongest influence on gene expression alter the response of genes associated with complex traits. Using ATAC-seq, we showed that a subset of these changes in gene expression are associated with changes in host chromatin accessibility and transcription factor binding induced by exposure to gut microbiota. We then created a manipulated microbial community with titrated doses of Collinsella, demonstrating that manipulation of the composition of the microbiome under both natural and controlled conditions leads to distinct and predictable gene expression profiles in host cells. Taken together, our results suggest that specific microbes play an important role in regulating expression of individual host genes involved in human complex traits. The ability to fine-tune the expression of host genes by manipulating the microbiome suggests future therapeutic routes.

IMPORTANCE The composition of the gut microbiome has been associated with various aspects of human health, but the mechanism of this interaction is still unclear. We utilized a cellular system to characterize the effect of the microbiome on human gene expression. We showed that some of these changes in expression may be mediated by changes in chromatin accessibility. Furthermore, we validate the role of a specific microbe and show that changes in its abundance can modify the host gene expression response. These results show an important role of gut microbiota in regulating host gene expression and suggest that manipulation of microbiome composition could be useful in future therapies.

Evolutionary history of disease-susceptibility loci identified in longitudinal exome-wide association studies

Background

Our longitudinal exome‐wide association studies previously detected various genetic determinants of complex disorders using ~26,000 single‐nucleotide polymorphisms (SNPs) that passed quality control and longitudinal medical examination data (mean follow‐up period, 5 years) in 4884–6022 Japanese subjects. We found that allele frequencies of several identified SNPs were remarkably different among four ethnic groups. Elucidating the evolutionary history of disease‐susceptibility loci may help us uncover the pathogenesis of the related complex disorders.

Methods

In the present study, we conducted evolutionary analyses such as extended haplotype homozygosity, focusing on genomic regions containing disease‐susceptibility loci and based on genotyping data of our previous studies and datasets from the 1000 Genomes Project.

Results

Our evolutionary analyses suggest that derived alleles of rs78338345 of GGA3, rs7656604 at 4q13.3, rs34902660 of SLC17A3, and six SNPs closely located at 12q24.1 associated with type 2 diabetes mellitus, obesity, dyslipidemia, and three complex disorders (hypertension, hyperuricemia, and dyslipidemia), respectively, rapidly expanded after the human dispersion from Africa (Out‐of‐Africa). Allele frequencies of GGA3 and six SNPs at 12q24.1 appeared to have remarkably changed in East Asians, whereas the derived alleles of rs34902660 of SLC17A3 and rs7656604 at 4q13.3 might have spread across Japanese and non‐Africans, respectively, although we cannot completely exclude the possibility that allele frequencies of disease‐associated loci may be affected by demographic events.

Conclusion

Our findings indicate that derived allele frequencies of nine disease‐associated SNPs (rs78338345 of GGA3, rs7656604 at 4q13.3, rs34902660 of SLC17A3, and six SNPs at 12q24.1) identified in the longitudinal exome‐wide association studies largely increased in non‐Africans after Out‐of‐Africa.

A gene based approach to test genetic association based on an optimally weighted combination of multiple traits

There is increasing evidence showing that pleiotropy is a widespread phenomenon in complex diseases for which multiple correlated traits are often measured. Joint analysis of multiple traits could increase statistical power by aggregating multiple weak effects. Existing methods for multiple trait association tests usually study each of the multiple traits separately and then combine the univariate test statistics or combine p-values of the univariate tests for identifying disease associated genetic variants. However, ignoring correlation between phenotypes may cause power loss. Additionally, the genetic variants in one gene (including common and rare variants) are often viewed as a whole that affects the underlying disease since the basic functional unit of inheritance is a gene rather than a genetic variant. Thus, results from gene level association tests can be more readily integrated with downstream functional and pathogenic investigation, whereas many existing methods for multiple trait association tests only focus on testing a single common variant rather than a gene. In this article, we propose a statistical method by Testing an Optimally Weighted Combination of Multiple traits (TOW-CM) to test the association between multiple traits and multiple variants in a genomic region (a gene or pathway). We investigate the performance of the proposed method through extensive simulation studies. Our simulation studies show that the proposed method has correct type I error rates and is either the most powerful test or comparable with the most powerful tests. Additionally, we illustrate the usefulness of TOW-CM based on a COPDGene study.

Genome-Wide Association Study of Metabolic Syndrome Reveals Primary Genetic Variants at CETP Locus in Indians

Indians, a rapidly growing population, constitute vast genetic heterogeneity to that of Western population; however they have become a sedentary population in past decades due to rapid urbanization ensuing in the amplified prevalence of metabolic syndrome (MetS). We performed a genome-wide association study (GWAS) of MetS in 10,093 Indian individuals (6,617 MetS and 3,476 controls) of Indo-European origin, that belong to our previous biorepository of The Indian Diabetes Consortium (INDICO). The study was conducted in two stages-discovery phase (N = 2,158) and replication phase (N = 7,935). We discovered two variants within/near the CETP gene-rs1800775 and rs3816117-associated with MetS at genome-wide significance level during replication phase in Indians. Additional CETP loci rs7205804, rs1532624, rs3764261, rs247617, and rs173539 also cropped up as modest signals in Indians. Haplotype association analysis revealed GCCCAGC as the strongest haplotype within the CETP locus constituting all seven CETP signals. In combined analysis, we perceived a novel and functionally relevant sub-GWAS significant locus-rs16890462 in the vicinity of SFRP1 gene. Overlaying gene regulatory data from ENCODE database revealed that single nucleotide polymorphism (SNP) rs16890462 resides in repressive chromatin in human subcutaneous adipose tissue as characterized by the enrichment of H3K27me3 and CTCF marks (repressive gene marks) and diminished H3K36me3 marks (activation gene marks). The variant displayed active DNA methylation marks in adipose tissue, suggesting its likely regulatory activity. Further, the variant also disrupts a potential binding site of a key transcription factor, NRF2, which is known for involvement in obesity and metabolic syndrome.

Identification of female-specific genetic variants for metabolic syndrome and its component traits to improve the prediction of metabolic syndrome in females

Background

Metabolic syndrome (MetS), defined as a cluster of metabolic risk factors including dyslipidemia, insulin-resistance, and elevated blood pressure, has been known as partly heritable. MetS effects the lives of many people worldwide, yet females have been reported to be more vulnerable to this cluster of risks.

Methods

To elucidate genetic variants underlying MetS specifically in females, we performed a genome-wide association study (GWAS) for MetS as well as its component traits in a total of 9932 Korean female subjects (including 2276 MetS cases and 1692 controls). To facilitate the prediction of MetS in females, we calculated a genetic risk score (GRS) combining 14 SNPs detected in our GWA analyses specific for MetS.

Results

GWA analyses identified 14 moderate signals (P_meta < 5X10^− 5) specific to females for MetS. In addition, two genome-wide significant female-specific associations (P_meta < 5X10^− 8) were detected for rs455489 in DSCAM for fasting plasma glucose (FPG) and for rs7115583 in SIK3 for high-density lipoprotein cholesterol (HDLC). Logistic regression analyses (adjusted for area and age) between the GRS and MetS in females indicated that the GRS was associated with increased prevalence of MetS in females (P = 5.28 × 10^− 14), but not in males (P = 3.27 × 10^− 1). Furthermore, in the MetS prediction models using GRS, the area under the curve (AUC) of the receiver operating characteristics (ROC) curve was higher in females (AUC = 0.85) than in males (AUC = 0.57).

Conclusion

This study highlights new female-specific genetic variants associated with MetS and its component traits and suggests that the GRS of MetS variants is a likely useful predictor of MetS in females.

Electronic supplementary material

The online version of this article (10.1186/s12881-019-0830-y) contains supplementary material, which is available to authorized users.

Metabolic fitness in relation to genetic variation and leukocyte DNA methylation

Metabolic syndrome (MetS) is a highly prevalent condition causing increased risk of several life-threatening diseases. MetS has a pronounced hereditary basis but is also influenced by environmental factors, partly through epigenetic mechanisms. In this study, the five phenotypes underlying MetS were incorporated into a continuous score for metabolic fitness (MF), and associations with both genotypic variation and leukocyte DNA methylation were investigated. Baseline MF phenotypes (waist circumference, blood pressure, blood glucose, serum triglycerides, and high-density lipoproteins) of 710 healthy Flemish adults were measured. After a 10 yr period, follow-up measures were derived from 618 of these subjects. Genotyping was performed for 65 preselected MF-related genetic variants. Next, full genetic predisposition scores (GPSs) were calculated, combining genotype scores of multiple genetic variants. Additionally, stepwise GPSs were constructed, including only the most predictive genetic variants for the different MF phenotypes. For a subset of 68 middle-aged men, global and gene-specific DNA methylation was investigated, and a biological pathway analysis was performed. The full GPSs were predictive for some baseline MF phenotypes, but not for changes over time. Only a limited number of genetic variants were significantly predictive individually. On the contrary, global and gene-specific DNA methylation was associated with changes in the MF phenotypes rather than with the baseline measures, indicating that effects of DNA methylation on MF are somewhat delayed. Furthermore, several biological pathways were associated with the MF phenotypes through gene promoter methylation. For CETP, G6PC2, MC4R, and TFAP2B both a genetic and epigenetic relationship was found with MF.

An in vivo screen for neuronal genes involved in obesity identifies Diacylglycerol kinase as a regulator of insulin secretion

Objective

Obesity is a complex disorder involving many genetic and environmental factors that are required to maintain energy homeostasis. While studies in human populations have led to significant progress in the generation of an obesity gene map and broadened our understanding of the genetic basis of common obesity, there is still a large portion of heritability and etiology that remains unknown. Here, we have used the genetically tractable fruit fly, Drosophila melanogaster, to identify genes/pathways that function in the nervous system to regulate energy balance.

Methods

We performed an in vivo RNAi screen in Drosophila neurons and assayed for obese or lean phenotypes by measuring changes in levels of stored fats (in the form of triacylglycerides or TAG). Three rounds of screening were performed to verify the reproducibility and specificity of the adiposity phenotypes. Genes that produced >25% increase in TAG (206 in total) underwent a second round of screening to verify their effect on TAG levels by retesting the same RNAi line to validate the phenotype. All remaining hits were screened a third time by testing the TAG levels of additional RNAi lines against the genes of interest to rule out any off-target effects.

Results

We identified 24 genes including 20 genes that have not been previously associated with energy homeostasis. One identified hit, Diacylglycerol kinase (Dgk), has mammalian homologues that have been implicated in genome-wide association studies for metabolic defects. Downregulation of neuronal Dgk levels increases TAG and carbohydrate levels and these phenotypes can be recapitulated by reducing Dgk levels specifically within the insulin-producing cells that secrete Drosophila insulin-like peptides (dILPs). Conversely, overexpression of kinase-dead Dgk, but not wild-type, decreased circulating dILP2 and dILP5 levels resulting in lower insulin signalling activity. Despite having higher circulating dILP levels, Dgk RNAi flies have decreased pathway activity suggesting that they are insulin-resistant.

Conclusion

Altogether, we have identified several genes that act within the CNS to regulate energy homeostasis. One of these, Dgk, acts within the insulin-producing cells to regulate the secretion of dILPs and energy homeostasis in Drosophila.

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RNAi screen in neurons identifies 24 regulators of energy homeostasis.

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One of the hits, Dgk, affects lipid and carbohydrate homeostasis.

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Dgk acts within the IPCs to regulate dILP secretion and insulin signalling activity.

Multiple genotype-phenotype association study reveals intronic variant pair on SIDT2 associated with metabolic syndrome in a Korean population

Background

Metabolic syndrome is a risk factor for type 2 diabetes and cardiovascular disease. We identified common genetic variants that alter the risk for metabolic syndrome in the Korean population. To isolate these variants, we conducted a multiple-genotype and multiple-phenotype genome-wide association analysis using the family-based quasi-likelihood score (MFQLS) test. For this analysis, we used 7211 and 2838 genotyped study subjects for discovery and replication, respectively. We also performed a multiple-genotype and multiple-phenotype analysis of a gene-based single-nucleotide polymorphism (SNP) set.

Results

We found an association between metabolic syndrome and an intronic SNP pair, rs7107152 and rs1242229, in SIDT2 gene at 11q23.3. Both SNPs correlate with the expression of SIDT2 and TAGLN, whose products promote insulin secretion and lipid metabolism, respectively. This SNP pair showed statistical significance at the replication stage.

Conclusions

Our findings provide insight into an underlying mechanism that contributes to metabolic syndrome.

Electronic supplementary material

The online version of this article (10.1186/s40246-018-0180-4) contains supplementary material, which is available to authorized users.

A variant in KCNQ1 gene predicts metabolic syndrome among northern urban Han Chinese women

BACKGROUND

Previous studies have reported that the potassium voltage-gated channel subfamily Q member 1 (KCNQ1) gene is associated with diabetes in both European and Asian population. This study aims to find a predictable single nucleotide polymorphism (SNP) to predict the risk of metabolic syndrome (MetS) through investigating the association of SNP in KCNQ1 gene with MetS in Han Chinese women of northern urban area.

METHODS

Six SNPs were selected and genotyped in 1381 unrelated women aged 21 and above, who have had physical check-up in Shandong Provincial Qianfoshan Hospital. Cox proportional model was conducted to access the association between SNPs and MetS.

RESULTS

Sixty one women developed MetS between 2010 and 2015 during the 3055 person-year of follow-up. The cumulative incidence density was 19.964/1000 person-year. The SNP rs163182 was associated with MetS both in the additive genetic model (RR = 1.658, 95% CI: 1.144-2.402) and in the recessive genetic model (RR = 2.461, 95% CI: 1.347-4.496). It remained significant after adjustment. This relationship was also observed in MetS components (BMI and SBP).

CONCLUSION

A novel association between rs163182 and MetS was found in this study, which can predict the occurrence of MetS among northern urban Han Chinese women. More investigations are needed to be done to assess the possible pathway in which KCNQ1 gene affects MetS.

Testing an optimally weighted combination of common and/or rare variants with multiple traits

Recently, joint analysis of multiple traits has become popular because it can increase statistical power to identify genetic variants associated with complex diseases. In addition, there is increasing evidence indicating that pleiotropy is a widespread phenomenon in complex diseases. Currently, most of existing methods test the association between multiple traits and a single genetic variant. However, these methods by analyzing one variant at a time may not be ideal for rare variant association studies because of the allelic heterogeneity as well as the extreme rarity of rare variants. In this article, we developed a statistical method by testing an optimally weighted combination of variants with multiple traits (TOWmuT) to test the association between multiple traits and a weighted combination of variants (rare and/or common) in a genomic region. TOWmuT is robust to the directions of effects of causal variants and is applicable to different types of traits. Using extensive simulation studies, we compared the performance of TOWmuT with the following five existing methods: gene association with multiple traits (GAMuT), multiple sequence kernel association test (MSKAT), adaptive weighting reverse regression (AWRR), single-TOW, and MANOVA. Our results showed that, in all of the simulation scenarios, TOWmuT has correct type I error rates and is consistently more powerful than the other five tests. We also illustrated the usefulness of TOWmuT by analyzing a whole-genome genotyping data from a lung function study.

Identification of six novel susceptibility loci for dyslipidemia using longitudinal exome-wide association studies in a Japanese population

Recent genome-wide association studies have identified various dyslipidemia-related genetic variants. However, most studies were conducted in a cross-sectional manner. We thus performed longitudinal exome-wide association studies of dyslipidemia in a Japanese population. We used ~244,000 genetic variants and clinical data of 6022 Japanese individuals who had undergone annual health checkups for several years. After quality control, the association of dyslipidemia-related phenotypes with 24,691 single nucleotide polymorphisms (SNPs) was tested using the generalized estimating equation model. In total, 82 SNPs were significantly (P < 2.03 × 10^-6) associated with dyslipidemia phenotypes. Of these SNPs, four (rs74416240 of TCHP, rs925368 of GIT2, rs7969300 of ATXN2, and rs12231744 of NAA25) and two (rs34902660 of SLC17A3 and rs1042127 of CDSN) were identified as novel genetic determinants of hypo-HDL- and hyper-LDL-cholesterolemia, respectively. A replication study using the cross-sectional data of 8310 Japanese individuals showed the association of the six identified SNPs with dyslipidemia-related traits.

Identification of rs7350481 at chromosome 11q23.3 as a novel susceptibility locus for metabolic syndrome in Japanese individuals by an exome-wide association study

We have performed exome-wide association studies to identify genetic variants that influence body mass index or confer susceptibility to obesity or metabolic syndrome in Japanese. The exome-wide association study for body mass index included 12,890 subjects, and those for obesity and metabolic syndrome included 12,968 subjects (3954 individuals with obesity, 9014 controls) and 6817 subjects (3998 individuals with MetS, 2819 controls), respectively. Exome-wide association studies were performed with Illumina HumanExome-12 DNA Analysis BeadChip or Infinium Exome-24 BeadChip arrays. The relation of genotypes of single nucleotide polymorphisms to body mass index was examined by linear regression analysis, and that of allele frequencies of single nucleotide polymorphisms to obesity or metabolic syndrome was evaluated with Fisher's exact test. The exome-wide association studies identified six, 11, and 40 single nucleotide polymorphisms as being significantly associated with body mass index, obesity (P <1.21 × 10⁻⁶), or metabolic syndrome (P <1.20 × 10⁻⁶), respectively. Subsequent multivariable logistic regression analysis with adjustment for age and sex revealed that three and five single nucleotide polymorphisms were related (P < 0.05) to obesity or metabolic syndrome, respectively, with one of these latter polymorphisms—rs7350481 (C/T) at chromosome 11q23.3—also being significantly (P < 3.13 × 10⁻⁴) associated with metabolic syndrome. The polymorphism rs7350481 may thus be a novel susceptibility locus for metabolic syndrome in Japanese. In addition, single nucleotide polymorphisms in three genes (CROT, TSC1, RIN3) and at four loci (ANKK1, ZNF804B, CSRNP3, 17p11.2) were implicated as candidate determinants of obesity and metabolic syndrome, respectively.

Identification of four genes as novel susceptibility loci for early-onset type 2 diabetes mellitus, metabolic syndrome, or hyperuricemia

Given that early-onset type 2 diabetes mellitus (T2DM), metabolic syndrome (MetS), and hyperuricemia have been shown to have strong genetic components, the statistical power of a genetic association study may be increased by focusing on early-onset subjects with these conditions. Although genome-wide association studies have identified various genes and loci significantly associated with T2DM, MetS, and hyperuricemia, genetic variants that contribute to predisposition to these conditions in Japanese subjects remain to be identified definitively. We performed exome-wide association studies (EWASs) for early-onset T2DM, MetS, or hyperuricemia to identify genetic variants that confer susceptibility to these conditions. A total of 8,102 individuals aged ≤65 years were enrolled in the present study. The EWAS for T2DM was performed with 7,407 subjects (1,696 cases, 5,711 controls), that for MetS with 4,215 subjects (2,296 cases, 1,919 controls), and that for hyperuricemia with 7,919 subjects (1,365 cases, 6,554 controls). Single nucleotide polymorphisms (SNPs) were genotyped with Illumina Human Exome-12 DNA Analysis BeadChip or Infinium Exome-24 BeadChip arrays. The relationship of allele frequencies for 31,210, 31,521, or 31,142 SNPs that passed quality control for T2DM, MetS, or hyperuricemia, respectively, was examined with Fisher's exact test. To compensate for multiple comparisons of genotypes with T2DM, MetS, or hyperuricemia, we applied Bonferroni's correction for statistical significance of association. The EWAS of allele frequencies revealed that four, six, or nine SNPs were significantly associated with T2DM (P<1.60×10^-6), MetS (P<1.59×10^-6), or hyperuricemia (P<1.61×10^-6), respectively. Multivariable logistic regression analysis with adjustment for age and sex revealed that three, six, or nine SNPs were significantly related to T2DM (P<0.0031), MetS (P<0.0021), or hyperuricemia (P<0.0014). After examination of the association of identified SNPs to T2DM-, MetS-, or hyperuricemia-related traits, linkage disequilibrium of the SNPs, and results of previous genome-wide association studies, newly identified ZNF860 and OR4F6 were the susceptibility loci for T2DM, OR52E4 and OR4F6 for MetS, and HERPUD2 for hyperuricemia. Given that OR4F6 was significantly associated with both T2DM and MetS, we newly identified four genes (ZNF860, OR4F6, OR52E4, HERPUD2) that confer susceptibility to early-onset T2DM, MetS, or hyperuricemia. Determination of genotypes for the SNPs in these genes may prove informative for assessment of the genetic risk for T2DM, MetS, or hyperuricemia.

GIT2-A keystone in ageing and age-related disease

Since its discovery, G protein-coupled receptor kinase-interacting protein 2, GIT2, and its family member, GIT1, have received considerable interest concerning their potential key roles in regulating multiple inter-connected physiological and pathophysiological processes. GIT2 was first identified as a multifunctional protein that is recruited to G protein-coupled receptors (GPCRs) during the process of receptor internalization. Recent findings have demonstrated that perhaps one of the most important effects of GIT2 in physiology concerns its role in controlling multiple aspects of the complex ageing process. Ageing can be considered the most prevalent pathophysiological condition in humans, affecting all tissue systems and acting as a driving force for many common and intractable disorders. The ageing process involves a complex interplay among various deleterious activities that profoundly disrupt the body's ability to cope with damage, thus increasing susceptibility to pathophysiologies such as neurodegeneration, central obesity, osteoporosis, type 2 diabetes mellitus and atherosclerosis. The biological systems that control ageing appear to function as a series of interconnected complex networks. The inter-communication among multiple lower-complexity signaling systems within the global ageing networks is likely coordinated internally by keystones or hubs, which regulate responses to dynamic molecular events through protein-protein interactions with multiple distinct partners. Multiple lines of research have suggested that GIT2 may act as one of these network coordinators in the ageing process. Identifying and targeting keystones, such as GIT2, is thus an important approach in our understanding of, and eventual ability to, medically ameliorate or interdict age-related progressive cellular and tissue damage.

New Common and Rare Variants Influencing Metabolic Syndrome and Its Individual Components in a Korean Population

To identify novel loci for susceptibility to MetS, we conducted genome-wide association and exome wide association studies consisting of a discovery stage cohort (KARE, 1946 cases and 6427 controls), and a replication stage cohort (HEXA, 430 cases and 3,264 controls). For finding genetic variants for MetS, with its components, we performed multivariate analysis for common and rare associations, using a standard logistic regression analysis for MetS. From the discovery and replication GWA studies, we confirmed 21 genome-wide signals significantly associated with MetS. Of these 21, four were previously unreported to associate with any MetS components: rs765547 near LPL; rs3782889 in MYL2; and rs11065756 and rs10849915 in CCDC63. Using exome chip variants, gene-based analysis of rare variants revealed three genes, CETP, SH2B1, and ZFP2, in the discovery stage, among which only CETP was confirmed in the replication stage. Finally, CETP D442G (rs2303790) associated, as a less common variant, with decreased risk of MetS. In conclusion, we discovered a total of five new MetS-associated loci, and their overlap with other disease-related components, suggest roles in the various etiologies of MetS, and its possible preventive strategies.

The Relationship Between Vascular Endothelial Growth Factor Cis- and Trans-Acting Genetic Variants and Metabolic Syndrome

BACKGROUND

We have investigated the association between 4 cis- and trans-genetic variants (rs6921438, rs4416670, rs6993770 and rs10738760) of the vascular endothelial growth factor (VEGF) gene and metabolic syndrome (MetS) and its individual components in an Iranian population.

MATERIAL & METHOD

Three hundred and thirty-six subjects were enrolled and MetS was defined according to the International-Diabetes-Federation (IDF) criteria. Genotyping was carried out in all the individuals for 4 VEGF genetic variants using an assay based on a combination of multiplex polymerase chain reaction and biochip array hybridization.

RESULTS

As may be expected, patients with MetS had significantly higher levels of serum high-sensitivity C-reactive protein, waist circumference, hip circumference, body mass index, fat percentage, systolic blood pressure, diastolic blood pressure and triglyceride, whereas the high-density lipoprotein cholesterol levels were significantly lower, compared to the control group (P < 0.05). We also found that 1 of the VEGF- level associated genetic variants, rs6993770, was associated with the presence of MetS; the less common T allele at this locus was associated with an increased risk for MetS. This association remained significant after adjustment for confounding factors (P = 0.007). Individuals with MetS carrying the AT + TT genotypes had markedly higher levels of fasting blood glucose, triglyceride and systolic blood pressure (P < 0.05).

CONCLUSIONS

We have found an association between the rs6993770 polymorphism and MetS. This gene variant was also associated with serum VEGF concentrations. There was also an association between this variant and the individual components of the MetS, including triglyceride, fasting blood glucose and systolic blood pressure.

Identification of three genetic variants as novel susceptibility loci for body mass index in a Japanese population

Recent genome-wide association studies have identified various obesity or metabolic syndrome (MetS) susceptibility loci. However, most studies were conducted in a cross-sectional manner. To address this gap, we performed a longitudinal exome-wide association study to identify susceptibility loci for obesity and MetS in a Japanese population. We traced clinical data of 6,022 Japanese subjects who had annual health check-ups for several years (mean follow-up period, 5 yr) and genotyped ~244,000 genetic variants. The association of single nucleotide polymorphisms (SNPs) with body mass index (BMI) or the prevalence of obesity and MetS was examined in a generalized estimating equation model. Our longitudinal exome-wide association studies detected 21 BMI- and five MetS-associated SNPs (false discovery rate, FDR <0.01). Among these SNPs, 16 have not been previously implicated as determinants of BMI or MetS. Cross-sectional data for obesity- and MetS-related phenotypes in 7,285 Japanese subjects were examined in a replication study. Among the 16 SNPs, three (rs9491140, rs145848316, and rs7863248) were related to BMI in the replication cohort (P < 0.05). In conclusion, three SNPs [rs9491140 of NKAIN2 (FDR = 0.003, P = 1.9 × 10⁻⁵), rs145848316 of KMT2C (FDR = 0.007, P = 4.5 × 10⁻⁵), and rs7863248 of AGTPBP1 (FDR = 0.006, P = 4.2 × 10⁻⁵)] were newly identified as susceptibility loci for BMI.

Positive Association of Metabolic Syndrome with a Single Nucleotide Polymorphism of Syndecan-3 (rs2282440) in the Taiwanese Population

BACKGROUND/PURPOSE

Metabolic syndrome (MetS) poses a major public health burden on the general population worldwide. Syndecan-3 (SDC3), a heparin sulfate proteoglycan, had been found by previous studies to be linked with energy balance and obesity, but its association with MetS is not known. The objective of this study is to investigate whether SDC3 polymorphism (rs2282440) is associated with MetS in the Taiwanese population.

METHODS

Genotypes of SDC3 polymorphism (rs2282440) were analyzed in 545 Taiwanese adult subjects, of which 154 subjects had MetS.

RESULTS

Subjects with SDC3 rs2282440 TT homozygote had higher frequency of MetS than those with CC or CT genotype (p = 0.0217). SDC3 rs2282440 TT homozygote had a 1.96-fold risk of being obese and 1.8-fold risk of having MetS (with CC genotype as reference). As for the individual components of MetS, subjects with SDC3 rs2282440 TT homozygote were more likely to have large waist circumference and low high-density lipoprotein cholesterol (OR = 1.75 and OR = 1.84, resp.).

CONCLUSION

SDC3 rs2282440 polymorphism is positively associated with MetS in the Taiwanese population. Further investigation is needed to see if this association is mediated by mere adiposity or SDC3 polymorphism is also linked with other components of MetS such as lipid metabolism.

Genetic variations of cholesteryl ester transfer protein and diet interactions in relation to lipid profiles and coronary heart disease: a systematic review

Data on diet–genotype interactions in the prevention or treatment of dyslipidemia have increased remarkably. This systematic review aimed to assess nutrigenetic studies regarding the modulating effect of diet on cholesteryl ester transfer protein (CETP) polymorphisms in relation to metabolic traits.

Data were collected through studies published between 2000 and SEP. 2016 using five electronic databases. The quality of eligible studies was assessed using a 12-item quality checklist, derived from the STrengthening the REporting of Genetic Association Studies (STREGA) statement. CETP variants that had associations with lipid profiles in previous studies were extracted for drawing of the linkage disequilibrium (LD) plot.

Among CETP variants, the rs9989419 best represented this genome wide association signal across all populations, based on LD r² estimates from 1000 genomes references. In the 23 found eligible studies (clinical trials and observational), the TaqIB and I405V polymorphisms were the two most intensively studied. Two studies reported the effect of interaction between rs3764261 and diet on lipid levels. Regarding the rs708272 (Taq1B), individuals with the B1 risk allele showed better responses to dietary interventions than those with B2B2 genotype, whereas with I405V, inconsistent results have been reported. Modest alcohol consumption was associated with decreased risk of coronary heart disease among B2 carriers of rs708272.

It is concluded that variations in the CETP gene may modulate the effects of dietary components on metabolic traits. These results have been controversial, indicating complex polygenic factors in metabolic response to diet and lack of uniformity in the study conditions and designs.

Association study of HNF1A polymorphisms with metabolic syndrome in the Moroccan population

AIMS

Variants in Hepatocyte Nuclear Factor 1 alpha (HNF1A) gene are associated with Metabolic Syndromeand its components independently. In this study, we aimed to assess the statistical association of the rs1169288, rs2464196 and rs735396 variants and haplotypes of HNF1A gene with metabolic syndrome (MS) and its components in a Moroccan population sample.

METHODS

Three variants in the HNF1A gene were genotyped, rs1169288 A>C, rs2464196 G>A and rs735396 T>C in cases and controls from Moroccan population using KASPar^® technology (KBioscience, UK). Anthropometric and biochemical parameters were assessed. MS was defined according to the international Diabetes Federation (IDF). The effects of HNF1A polymorphisms and constructed haplotypes on MS were estimated using logistic regression analyses.

RESULTS

The HNF1A gene, rs1169288 and rs2464196 variants conferred an increased risk to MS (OR=2.08, 95%CI=1.38-3.14, P=0.0005 and OR=1.52, 95%IC=1.05-2.20, P=0.03, respectively) when adjusted for BMI, sex and age. We found that the C allele of the variant rs735396 was associated with an increased triglycerides level (p-value=0.04434) among patients and high weist circumference (P=0.02005) and total cholesterol (P=0.03227) amount among controls. The haplotype AAT (OR=5.656, P<0.00001) was the most significantly associated with susceptibility to metabolic syndrome.

CONCLUSION

The present study demonstrated that SNPs rs1169288 and rs2464196 of HNF1A gene were significantly associated with metabolic syndrome in a Morrocan population. Furthermore, the CAC, AAC, AAT and AGT haplotypes of these SNPs and rs735396 were significantly associated with metabolic syndrome.

Genetics of Insulin Resistance and the Metabolic Syndrome

Insulin resistance and the metabolic syndrome are complex metabolic traits and key risk factors for the development of cardiovascular disease. They result from the interplay of environmental and genetic factors but the full extent of the genetic background to these conditions remains incomplete. Large-scale genome-wide association studies have helped advance the identification of common genetic variation associated with insulin resistance and the metabolic syndrome, and more recently, exome sequencing has allowed the identification of rare variants associated with the pathogenesis of these conditions. Many variants associated with insulin resistance are directly involved in glucose metabolism; however, functional studies are required to assess the contribution of other variants to the development of insulin resistance. Many genetic variants involved in the pathogenesis of the metabolic syndrome are associated with lipid metabolism.

Detection of susceptibility loci on APOA5 and COLEC12 associated with metabolic syndrome using a genome-wide association study in a Taiwanese population

Background

Although the association of single nucleotide polymorphisms (SNPs) with metabolic syndrome (MetS) has been reported in various populations in several genome-wide association studies (GWAS), the data is not conclusive. In this GWAS study, we assessed whether SNPs are associated with MetS and its individual components independently and/or through complex interactions in a Taiwanese population.

Methods

A total of 10,300 Taiwanese subjects were assessed in this study. Metabolic traits such as waist circumference, triglyceride, high-density lipoprotein (HDL) cholesterol, systolic and diastolic blood pressure, and fasting glucose were measured.

Results

Our data showed an association of MetS at the genome-wide significance level (P < 8.6 x 10^-8) with two SNPs, including the rs662799 SNP in the apolipoprotein A5 (APOA5) gene and the rs16944558 SNP in the collectin subfamily member 12 (COLEC12) gene. Moreover, we identified the effect of APOA5 rs662799 on triglyceride and HDL, the effect of rs1106475 in the actin filament associated protein 1 like 2 (AFAP1L2) gene on systolic blood pressure, and the effect of rs17667932 in the mediator complex subunit 30 (MED30) gene on fasting glucose. Additionally, we found that an interaction between the APOA5 rs662799 and COLEC12 rs16944558 SNPs influenced MetS, high triglyceride, and low HDL.

Conclusions

Our study indicates that the APOA5 and COLEC12 genes may contribute to the risk of MetS and its individual components independently as well as through gene-gene interactions.

Genetics and the metabolic syndrome

Originally coined as "syndrome X" in 1988 by Gerald Reaven (1928), the metabolic syndrome (MetS) encompasses a constellation of risk factors, the coincidence of which amounts to an increased cardiovascular and diabetic risk. Rising numbers of dermatoses are being recognized as cutaneous markers of MetS. Dermatologists should look beyond treating the cutaneous condition and quantify the associated increase in cardiovascular risk. The original dermatosis associated with obesity was acanthosis nigricans-described in 1889 by Paul Gerson Unna (1850-1929) and Sigmund Pollitzer (1859-1937). Over the last 20 years, clear associations between psoriasis, hidradenitis suppurativa, and MetS have also emerged. Several studies have shown synergistic improvement in the cutaneous pathology after treatment of components of MetS. This suggests common causalities and is a burgeoning area of research. We review the available evidence about the genetics underlying psoriasis, hidradenitis suppurativa, and acanthosis nigricans. Despite the strong clinical associations, the underlying genetic basis for a link to MetS remains unclear.

Integrating Genome-Wide Association and eQTLs Studies Identifies the Genes and Gene Sets Associated with Diabetes

AIM

To identify novel candidate genes and gene sets for diabetes.

METHODS

We performed an integrative analysis of genome-wide association studies (GWAS) and expression quantitative trait loci (eQTLs) data for diabetes. Summary data was driven from a large-scale GWAS of diabetes, totally involving 58,070 individuals. eQTLs dataset included 923,021 cis-eQTL for 14,329 genes and 4,732 trans-eQTL for 2,612 genes. Integrative analysis of GWAS and eQTLs data was conducted by summary data-based Mendelian randomization (SMR). To identify the gene sets associated with diabetes, the SMR single gene analysis results were further subjected to gene set enrichment analysis (GSEA). A total of 13,311 annotated gene sets were analyzed in this study.

RESULTS

SMR analysis identified 6 genes significantly associated with fasting glucose, such as C11ORF10 (p value = 6.04 × 10^-8), MRPL33 (p value = 1.24 × 10^-7), and FADS1 (p value = 2.39 × 10^-7). Gene set analysis identified HUANG_FOXA2_TARGETS_UP (false discovery rate = 0.047) associated with fasting glucose.

CONCLUSION

Our study provides novel clues for clarifying the genetic mechanism of diabetes. This study also illustrated the good performance of SMR approach and extended it to gene set association analysis for complex diseases.

Genetic determinants of inherited susceptibility to hypercholesterolemia - a comprehensive literature review

Hypercholesterolemia is a strong determinant of mortality and morbidity associated with cardiovascular diseases and a major contributor to the global disease burden. Mutations in four genes (LDLR, APOB, PCSK9 and LDLRAP1) account for the majority of cases with familial hypercholesterolemia. However, a substantial proportion of adults with hypercholesterolemia do not have a mutation in any of these four genes. This indicates the probability of having other genes with a causative or contributory role in the pathogenesis of hypercholesterolemia and suggests a polygenic inheritance of this condition. Here in, we review the recent evidence of association of the genetic variants with hypercholesterolemia and the three lipid traits; total cholesterol (TC), HDL-cholesterol (HDL-C) and LDL-cholesterol (LDL-C), their biological pathways and the associated pathogenetic mechanisms. Nearly 80 genes involved in lipid metabolism (encoding structural components of lipoproteins, lipoprotein receptors and related proteins, enzymes, lipid transporters, lipid transfer proteins, and activators or inhibitors of protein function and gene transcription) with single nucleotide variants (SNVs) that are recognized to be associated with hypercholesterolemia and serum lipid traits in genome-wide association studies and candidate gene studies were identified. In addition, genome-wide association studies in different populations have identified SNVs associated with TC, HDL-C and LDL-C in nearly 120 genes within or in the vicinity of the genes that are not known to be involved in lipid metabolism. Over 90% of the SNVs in both these groups are located outside the coding regions of the genes. These findings indicates that there might be a considerable number of unrecognized processes and mechanisms of lipid homeostasis, which when disrupted, would lead to hypercholesterolemia. Knowledge of these molecular pathways will enable the discovery of novel treatment and preventive methods as well as identify the biochemical and molecular markers for the risk prediction and early detection of this common, yet potentially debilitating condition.

Susceptibility loci for metabolic syndrome and metabolic components identified in Han Chinese: a multi-stage genome-wide association study

Metabolic syndrome (MetS), a cluster of metabolic disturbances that increase the risk for cardiovascular disease and diabetes, was because of genetic susceptibility and environmental risk factors. To identify the genetic variants associated with MetS and metabolic components, we conducted a genome-wide association study followed by replications in totally 12,720 participants from the north, north-eastern and eastern China. In combined analyses, independent of the top known signal at rs651821 on APOA5, we newly identified a secondary triglyceride-associated signal at rs180326 on BUD13 (P_combined = 2.4 × 10^-8 ). Notably, by an integrated analysis of the genotypes and the serum levels of APOA5, BUD13 and triglyceride, we observed that BUD13 was another potential mediator, besides APOA5, of the association between rs651821 and serum triglyceride. rs671 (ALDH2), an east Asian-specific common variant, was found to be associated with MetS (P_combined = 9.7 × 10^-22 ) in Han Chinese. The effects of rs671 on metabolic components were more prominent in drinkers than in non-drinkers. The replicated loci provided information on the genetic basis and mechanisms of MetS and metabolic components in Han Chinese.

Pathway analysis of bladder cancer genome-wide association study identifies novel pathways involved in bladder cancer development

Genome-wide association studies (GWAS) are designed to identify individual regions associated with cancer risk, but only explain a small fraction of the inherited variability. Alternative approach analyzing genetic variants within biological pathways has been proposed to discover networks of susceptibility genes with additional effects. The gene set enrichment analysis (GSEA) may complement and expand traditional GWAS analysis to identify novel genes and pathways associated with bladder cancer risk. We selected three GSEA methods: Gen-Gen, Aligator, and the SNP Ratio Test to evaluate cellular signaling pathways involved in bladder cancer susceptibility in a Texas GWAS population. The candidate genetic polymorphisms from the significant pathway selected by GSEA were validated in an independent NCI GWAS. We identified 18 novel pathways (P < 0.05) significantly associated with bladder cancer risk. Five of the most promising pathways (P ≤ 0.001 in any of the three GSEA methods) among the 18 pathways included two cell cycle pathways and neural cell adhesion molecule (NCAM), platelet-derived growth factor (PDGF), and unfolded protein response pathways. We validated the candidate polymorphisms in the NCI GWAS and found variants of RAPGEF1, SKP1, HERPUD1, CACNB2, CACNA1C, CACNA1S, COL4A2, SRC, and CACNA1C were associated with bladder cancer risk. Two CCNE1 variants, rs8102137 and rs997669, from cell cycle pathways showed the strongest associations; the CCNE1 signal at 19q12 has already been reported in previous GWAS. These findings offer additional etiologic insights highlighting the specific genes and pathways associated with bladder cancer development. GSEA may be a complementary tool to GWAS to identify additional loci of cancer susceptibility.

Investigation of Genetic Variation Underlying Central Obesity amongst South Asians

South Asians are 1/4 of the world's population and have increased susceptibility to central obesity and related cardiometabolic disease. Knowledge of genetic variants affecting risk of central obesity is largely based on genome-wide association studies of common SNPs in Europeans. To evaluate the contribution of DNA sequence variation to the higher levels of central obesity (defined as waist hip ratio adjusted for body mass index, WHR) among South Asians compared to Europeans we carried out: i) a genome-wide association analysis of >6M genetic variants in 10,318 South Asians with focused analysis of population-specific SNPs; ii) an exome-wide association analysis of ~250K SNPs in protein-coding regions in 2,637 South Asians; iii) a comparison of risk allele frequencies and effect sizes of 48 known WHR SNPs in 12,240 South Asians compared to Europeans. In genome-wide analyses, we found no novel associations between common genetic variants and WHR in South Asians at P<5x10-8; variants showing equivocal association with WHR (P<1x10-5) did not replicate at P<0.05 in an independent cohort of South Asians (N = 1,922) or in published, predominantly European meta-analysis data. In the targeted analyses of 122,391 population-specific SNPs we also found no associations with WHR in South Asians at P<0.05 after multiple testing correction. Exome-wide analyses showed no new associations between genetic variants and WHR in South Asians, either individually at P<1.5x10-6 or grouped by gene locus at P<2.5x10-6. At known WHR loci, risk allele frequencies were not higher in South Asians compared to Europeans (P = 0.77), while effect sizes were unexpectedly smaller in South Asians than Europeans (P<5.0x10-8). Our findings argue against an important contribution for population-specific or cosmopolitan genetic variants underlying the increased risk of central obesity in South Asians compared to Europeans.

A Statistical Approach for Testing Cross-Phenotype Effects of Rare Variants

Increasing empirical evidence suggests that many genetic variants influence multiple distinct phenotypes. When cross-phenotype effects exist, multivariate association methods that consider pleiotropy are often more powerful than univariate methods that model each phenotype separately. Although several statistical approaches exist for testing cross-phenotype effects for common variants, there is a lack of similar tests for gene-based analysis of rare variants. In order to fill this important gap, we introduce a statistical method for cross-phenotype analysis of rare variants using a nonparametric distance-covariance approach that compares similarity in multivariate phenotypes to similarity in rare-variant genotypes across a gene. The approach can accommodate both binary and continuous phenotypes and further can adjust for covariates. Our approach yields a closed-form test whose significance can be evaluated analytically, thereby improving computational efficiency and permitting application on a genome-wide scale. We use simulated data to demonstrate that our method, which we refer to as the Gene Association with Multiple Traits (GAMuT) test, provides increased power over competing approaches. We also illustrate our approach using exome-chip data from the Genetic Epidemiology Network of Arteriopathy.

Association of genetic variants in the FTO gene with metabolic syndrome: A case-control study in the Tunisian population

AIMS

Variants in the fat mass and obesity-associated gene (FTO) are associated with obesity and type 2 diabetes. However, the association of FTO variants in the MENA (Middle East and North Africa) region with MetS is largely unknown. In this study, we aimed to investigate the association of FTO gene with MetS and its components in Tunisian population.

METHODS

Two variants in the FTO gene were genotyped: rs1421085 T>C and rs8057044 A>G in cases and controls from Tunisian population. Anthropometric and biochemical parameters were assessed. Metabolic syndrome was defined according to the International Diabetes Federation (IDF).

RESULTS

The FTO rs1421085 variant conferred an increased risk to MetS (OR=1.61, 95% CI=1.14-2.26, P=0.024) that was abolished when adjusted for fasting plasma glucose (FPG), suggesting that the association may be due to variation in FPG levels. Indeed, this variant was associated to FPG (OR = 1.7, 95% CI=1.23-2.44, P=0.002) independently from BMI or age. The second polymorphism rs8057044 was associated with high blood pressure levels (OR=1.45, 95% CI=1.06-1.99, P=0.019).

CONCLUSIONS

This is the first study highlighting the association between FTO gene variants and MetS in Tunisian population. These findings provide evidence that FTO gene may play a critical role in leading to MetS in Tunisian population.