A bivariate genome-wide approach to metabolic syndrome: STAMPEED consortium

Systems genetics of metabolic health in the BXD mouse genetic reference population

Susceptibility to metabolic syndrome (MetS) is dependent on genetics, environment, and gene-by-environment interactions, rendering the study of underlying mechanisms challenging. The majority of experiments in model organisms do not incorporate genetic variation and lack specific evaluation criteria for MetS. Here, we derived a continuous metric, the metabolic health score (MHS), based on standard clinical parameters and defined its molecular signatures in the liver and circulation. In human UK Biobank, the MHS associated with MetS status and was predictive of future disease incidence, even in individuals without MetS. Using quantitative trait locus analyses in mice, we found two MHS-associated genetic loci and replicated them in unrelated mouse populations. Through a prioritization scheme in mice and human genetic data, we identified TNKS and MCPH1 as candidates mediating differences in the MHS. Our findings provide insights into the molecular mechanisms sustaining metabolic health across species and uncover likely regulators. A record of this paper's transparent peer review process is included in the supplemental information.

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.

Consumption of dietary fiber and APOA5 genetic variants in metabolic syndrome: baseline data from the Korean Medicine Daejeon Citizen Cohort Study

BACKGROUND

Consumption of dietary fiber has been suggested as an important aspect of a healthy diet to reduce the risk of metabolic syndrome (MetS), including cardiovascular disease. The role of fiber intake in MetS might differ by individual genetic susceptibility. APOA5 encodes a regulator of plasma triglyceride levels, which impacts the related mechanisms of MetS. This study investigated the association between dietary fiber and the risk of MetS, assessing their associations according to APOA5 genetic variants.

METHODS

A total of 1985 participants aged 30-55 years were included from a cross-sectional study based on the Korean Medicine Daejeon Citizen Cohort study at baseline (2017-2019). Dietary fiber intake was measured using a semiquantitative food frequency questionnaire. The APOA5 polymorphisms (rs2266788 A > G, rs662799 A > G, and rs651821 T > C) were genotyped using the Asia Precision Medicine Research Array. Logistic regression was used to estimate odds ratios (ORs) and 95% confidence intervals (95% CIs).

RESULTS

A higher consumption of dietary fiber was associated with a lower prevalence of MetS (P = 0.025). Among the components of MetS, an inverse association with dietary fiber was observed in increased waist circumference (OR, 95% CI = 0.60, 0.41-0.88, P for trend = 0.009) and elevated triglycerides (OR, 95% CI = 0.69, 0.50-0.96, P for trend = 0.012). Regarding the interaction with APOA5 genetic variants, a stronger association with dietary fiber intake was shown in G allele carriers of rs662799 than in A/A carriers (OR, 95% CI = 2.34, 1.59-3.44, P for interaction = 0.024) and in C allele carriers of rs651821 than in T/T carriers (OR, 95% CI = 2.35, 1.59-3.46, P for interaction = 0.027).

CONCLUSIONS

The findings of this study suggest that the benefits of dietary fiber on the risk of MetS could be modified by genetic variants of the APOA5 gene, providing a more effective strategy for preventing MetS.

Metabolic syndrome risk in adult coffee drinkers with the rs301 variant of the LPL gene

BACKGROUND

Metabolic syndrome (MetS), a cluster of metabolic and cardiovascular risk factors is influenced by environmental, lifestyle, and genetic factors. We explored whether coffee consumption and the rs301 variant of the lipoprotein lipase (LPL) gene are related to MetS.

METHODS

We conducted multiple logistic regression analyses using data gathered from 9523 subjects in Taiwan Biobank (TWB).

RESULTS

Our findings indicated that individuals who consumed coffee had a reduced odds ratio (OR) for MetS (0.750 (95% confidence interval [CI] 0.653-0.861) compared to non-coffee drinkers. Additionally, the risk of MetS was lower for individuals with the 'TC' and 'CC' genotypes of rs301 compared to those with the 'TT' genotype. Specifically, the OR for MetS was 0.827 (95% CI 0.721-0.949) for the 'TC' genotype and 0.848 (95% CI 0.610-1.177) for the 'CC' genotype. We observed an interaction between coffee consumption and the rs301 variant, with a p-value for the interaction of 0.0437. Compared to the reference group ('no coffee drinking/TT'), the ORs for MetS were 0.836 (95% CI 0.706-0.992) for 'coffee drinking/TT', 0.557 (95% CI 0.438-0.707) for 'coffee drinking/TC', and 0.544 (95% CI 0.319-0.927) for 'coffee drinking/CC'. Notably, MetS was not observed in non-coffee drinkers regardless of their rs301 genotype.

CONCLUSION

Our findings suggest that rs301 genotypes may protect against MetS in Taiwanese adults who consume coffee compared to non-coffee drinkers.

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.

Unraveling phenotypic variance in metabolic syndrome through multi-omics

Complex multi-omics effects drive the clustering of cardiometabolic risk factors, underscoring the imperative to comprehend how individual and combined omics shape phenotypic variation. Our study partitions phenotypic variance in metabolic syndrome (MetS), blood glucose (GLU), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), and blood pressure through genome, transcriptome, metabolome, and exposome (i.e., lifestyle exposome) analyses. Our analysis included a cohort of 62,822 unrelated individuals with white British ancestry, sourced from the UK biobank. We employed linear mixed models to partition phenotypic variance using the restricted maximum likelihood (REML) method, implemented in MTG2 (v2.22). We initiated the analysis by individually modeling omics, followed by subsequent integration of pairwise omics in a joint model that also accounted for the covariance and interaction between omics layers. Finally, we estimated the correlations of various omics effects between the phenotypes using bivariate REML. Significant proportions of the MetS variance were attributed to distinct data sources: genome (9.47%), transcriptome (4.24%), metabolome (14.34%), and exposome (3.77%). The phenotypic variances explained by the genome, transcriptome, metabolome, and exposome ranged from 3.28% for GLU to 25.35% for HDL-C, 0% for GLU to 19.34% for HDL-C, 4.29% for systolic blood pressure (SBP) to 35.75% for TG, and 0.89% for GLU to 10.17% for HDL-C, respectively. Significant correlations were found between genomic and transcriptomic effects for TG and HDL-C. Furthermore, significant interaction effects between omics data were detected for both MetS and its components. Interestingly, significant correlation of omics effect between the phenotypes was found. This study underscores omics' roles, interaction effects, and random-effects covariance in unveiling phenotypic variation in multi-omics domains.

Heterogeneity in familial clustering of metabolic syndrome components in the multiethnic GENNID study

OBJECTIVE

Metabolic syndrome (MetS) is defined by clustering of cardiometabolic components, which may be present in different combinations. The authors evaluated clustering in individuals and extended families within and across ancestry groups.

METHODS

The prevalence of different combinations of MetS components (high fasting glucose, low high-density lipoprotein cholesterol, high triglycerides, high blood pressure, and abdominal obesity) was estimated in 1651 individuals (340 families) self-reporting as European American (EA), Hispanic/Mexican American (MA), African American (AA), and Japanese American (JA). Odds ratios were estimated using logistic regression with generalized estimating equations comparing individual MetS components, number, and combinations of components for each ancestry group versus EA.

RESULTS

Clustering of all five components (Combination #16) was more prevalent in EA (29.9%) and MA (25.2%) individuals than in AA (18.7%) and JA (15.5%) individuals. Compared with EA individuals, AA individuals were 64% and 66% less likely to have high triglycerides and low high-density lipoprotein cholesterol, whereas JA individuals were 85% and 56% less likely to have abdominal obesity and high blood pressure, respectively. Compared with EA individuals, the odds of having two, four, or five components were at least 77% lower in JA individuals, whereas the odds of having three, four, or five components were at least 3.79 times greater in MA individuals.

CONCLUSIONS

Understanding heterogeneity in MetS clustering may identify factors important in reducing health disparities.

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.

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.

Risk prediction of the metabolic syndrome using TyG Index and SNPs: a 10-year longitudinal prospective cohort study

TyG (triglyceride and glucose) index using triglyceride and fasting blood glucose is recommended as a useful marker for insulin resistance. To clarify whether the TyG index is a marker for predicting metabolic syndrome (MetS) and to investigate the importance of single-nucleotide polymorphisms (SNPs) in MetS diagnosis. From 2001 to 2014, a longitudinal prospective cohort study of 3580 adults aged 40-70 years was conducted. The area under the receiver operating characteristic curves (AUROC) and Youden index (YI) was calculated to assess the diagnostic value. During the 14-year follow-up, 1270 subjects developed MetS. Five SNPs in four genes (BUD13 rs10790162, ZPR1 rs2075290, APOA5 rs2266788, APOA5 rs2075291, and MKL1 rs4507196) significantly correlated with susceptibility to MetS (p < 0.00005). The areas under the curve of TyG index and HOMA-IR were 0.854 (95% confidence interval [CI], 0.841-0.867) and 0.702 (95% CI, 0.684-0.721), respectively. Despite no statistical significance, AUROC and YI were increased when MetS was diagnosed using TyG index and the five SNPs. TyG index might be useful for identifying individuals at high risk of developing MetS. The combination of TyG index and SNPs showed better diagnostic accuracy than TyG index alone, indicating the potential value of novel SNPs for MetS diagnosis.

Vitamin D Deficiency and COVID-19: A Biological Database Study on Pathways and Gene-Disease Associations

Vitamin D (VD) is a fat-soluble vitamin, and pivotal for maintaining health. Several genetic markers have been related to a deficient VD status; these markers could confer an increased risk to develop osteoporosis and other chronic diseases. A VD deficiency could also be a determinant of a severe COVID-19 disease. This study aimed to interrogate genetic/biological databases on the biological implications of a VD deficiency and its association with diseases, to further explore its link with COVID-19. The genetic variants of both a VD deficiency and COVID-19 were identified in the genome-wide association studies (GWAS) catalog and other sources. We conducted enrichment analyses (considering corrected p-values < 0.05 as statistically significant) of the pathways, and gene-disease associations using tools, such as FUMA, REVIGO, DAVID and DisGeNET, and databases, such as the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO). There were 26 and 46 genes associated with a VD deficiency and COVID-19, respectively. However, there were no genes shared between the two. Genes related to a VD deficiency were involved in the metabolism of carbohydrates, retinol, drugs and xenobiotics, and were associated with the metabolic syndrome and related factors (obesity, hypertension and diabetes mellitus), as well as with neoplasms. There were few enriched pathways and disease connections for the COVID-19-related genes, among which some of the aforementioned comorbidities were also present. In conclusion, genetic factors that influence the VD levels in the body are most prominently associated with nutritional and metabolic diseases. A VD deficiency in high-risk populations could be therefore relevant in a severe COVID-19, underlining the need to examine whether a VD supplementation could reduce the severity of this disease.

Disentangling Genetic Risks for Metabolic Syndrome

A quarter of the world's population is estimated to meet the criteria for metabolic syndrome (MetS), a cluster of cardiometabolic risk factors that promote development of coronary artery disease and type 2 diabetes, leading to increased risk of premature death and significant health costs. In this study we investigate whether the genetics associated with MetS components mirror their phenotypic clustering. A multivariate approach that leverages genetic correlations of fasting glucose, HDL cholesterol, systolic blood pressure, triglycerides, and waist circumference was used, which revealed that these genetic correlations are best captured by a genetic one factor model. The common genetic factor genome-wide association study (GWAS) detects 235 associated loci, 174 more than the largest GWAS on MetS to date. Of these loci, 53 (22.5%) overlap with loci identified for two or more MetS components, indicating that MetS is a complex, heterogeneous disorder. Associated loci harbor genes that show increased expression in the brain, especially in GABAergic and dopaminergic neurons. A polygenic risk score drafted from the MetS factor GWAS predicts 5.9% of the variance in MetS. These results provide mechanistic insights into the genetics of MetS and suggestions for drug targets, especially fenofibrate, which has the promise of tackling multiple MetS components.

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.

A Gene Variation at the ZPR1 Locus (rs964184) Interacts With the Type of Diet to Modulate Postprandial Triglycerides in Patients With Coronary Artery Disease: From the Coronary Diet Intervention With Olive Oil and Cardiovascular Prevention Study

Background and Aims

rs964184 variant in the ZPR1 gene has been associated with blood lipids levels both in fasting and postprandial state and with the risk of myocardial infarction in high-risk cardiovascular patients. However, whether this association is modulated by diet has not been studied.

Objective

To investigate whether the type of diet (low-fat or Mediterranean diets) interacts with genetic variability at this loci to modulate fasting and postprandial lipids in coronary patients.

Materials and Methods

The genotype of the rs964184 polymorphism was determined in the Cordioprev Study population (NCT00924937). Fasting and Postprandial triglycerides were assessed before and after 3 years of dietary intervention with either a Mediterranean or a low-fat diet. Postprandial lipid assessment was done by a 4-h oral fat tolerance test (OFTT). Differences in triglycerides levels were identified using repeated-measures ANCOVA.

Results

From 523 patients (85% males, mean age 59 years) that completed the OFTT at baseline and after 3 years of intervention and had complete genotype information, 125 of them were carriers of the risk allele G. At the start of the study, these patients showed a higher fasting and postprandial triglycerides (TG) plasma levels. After 3 years of dietary intervention, G-carriers following a Mediterranean Diet maintained higher fasting and postprandial triglycerides, while those on the low-fat diet reduced their postprandial triglycerides to similar values to the population without the G-allele.

Conclusion

After 3 years of dietary intervention, the altered postprandial triglyceride response induced by genetic variability in the rs964184 polymorphism of the ZPR1 gene can be modulated by a low-fat diet, better than by a Mediterranean diet, in patients with coronary artery disease.

Towards harnessing the value of organokine crosstalk to predict the risk for cardiovascular disease in non-alcoholic fatty liver disease

Non-alcoholic fatty liver disease (NAFLD) is the most common chronic liver disease. Importantly, NAFLD increases the risk for cardiovascular disease (CVD). A causal relationship has been substantiated. Given the pandemic proportions of NAFLD, a reliable scoring system for predicting the risk of NAFLD-associated CVD is an urgent medical need. We here review cumulative evidence suggesting that systemically released organokines - especially certain adipokines, hepatokines, and cardiokines - may serve this purpose. The underlying rationale is that these signalers directly communicate between white adipose tissue, liver, and heart as key players in the pathogenesis of NAFLD and resultant CVD events. Moreover, evidence suggests that these organ-specific cytokines are secreted in a biologically predetermined, cascade-like pattern. Consequently, upon pinpointing organokines of relevance, we sketch requirements to establish an algorithm predictive of the CVD risk in patients with NAFLD. Such an algorithm, as to be consolidated in the form of an applicable equation, may be improved continuously by machine learning. To the best of our knowledge, such an option has not yet been considered. Establishing and implementing a reliable algorithm for determining the NAFLD-associated CVD risk has the potential to save many NAFLD patients from life-threatening CVD events.

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.

“Big Data” Approaches for Prevention of the Metabolic Syndrome

Metabolic syndrome (MetS) is characterized by the concurrence of multiple metabolic disorders resulting in the increased risk of a variety of diseases related to disrupted metabolism homeostasis. The prevalence of MetS has reached a pandemic level worldwide. In recent years, extensive amount of data have been generated throughout the research targeted or related to the condition with techniques including high-throughput screening and artificial intelligence, and with these “big data”, the prevention of MetS could be pushed to an earlier stage with different data source, data mining tools and analytic tools at different levels. In this review we briefly summarize the recent advances in the study of “big data” applications in the three-level disease prevention for MetS, and illustrate how these technologies could contribute tobetter preventive strategies.

Identification and Characterization of Variants in Intron 6 of the LPL Gene Locus among a Sample of the Kuwaiti Population

Lipoprotein lipase (LPL) is responsible for the hydrolysis of lipoproteins; hence defective LPL is associated with metabolic disorders. Here, we identify certain intronic insertions and deletions (InDels) and single nucleotide polymorphisms (SNPs) in intron 6 of the LPL gene and investigate their associations with different phenotypic characteristics in a cohort of the general Kuwaiti population. Two specific regions of intron 6 of the LPL gene, which contain InDels, were amplified via Sanger sequencing in 729 subjects. Genotypic and allelic frequencies were estimated, and genetic modeling was used to investigate genetic associations of the identified variants with lipid profile, body mass index (BMI), and risk of coronary heart disease (CHD). A total of 16 variants were identified, including 2 InDels, 2 novel SNPs, and 12 known SNPs. The most common variants observed among the population were rs293, rs274, rs295, and rs294. The rs293 “A” insertion showed a significant positive correlation with elevated LDL levels, while rs295 was significantly associated with increased BMI. The rs274 and rs294 variants showed a protective effect of the minor allele with decreased CHD prevalence. These findings shed light on the possible role of LPL intronic variants on metabolic disorders.

The association between rs1260326 with the risk of NAFLD and the mediation effect of triglyceride on NAFLD in the elderly Chinese Han population

Background: Accumulated studies have pointed out the striking association between variants in or near APOC3, GCKR, PNPLA3, and nonalcoholic fatty liver disease (NAFLD) at various ages from multiple ethnic groups. This association remained unclear in the Chinese Han elderly population, and whether this relationship correlated to any clinical parameters was also unclear.

Objectives: This study aims to decipher the complex relevance between gene polymorphisms, clinical parameters, and NAFLD by association study and mediation analysis.

Methods: Eight SNPs (rs2854116, rs2854117, rs780093, rs780094, rs1260362, rs738409, rs2294918, and rs2281135) within APOC3, GCKR, and PNPLA3 were genotyped using the MassARRAY® platform in a large Chinese Han sample comprising of 733 elderly NAFLD patients and 824 age- and ethnic-matched controls. Association and mediation analysis were employed by R.

Results: The genotypic frequencies of rs1260326 and rs780094 were significantly different between NAFLD and control (rs1260326: P=0.004, P_corr=0.020, OR [95%CI]= 0.69 [0.54-0.89]; rs780094: P=0.005, P_corr=0.025, OR [95%CI]= 0.70 [0.55-0.90]). Particularly, an increased triglyceride level was observed in carriers of rs1260326 T allele (1.94±1.19 mmol/L) compared with non-carriers (1.73±1.05 mmol/L).no significant results were observed in rs780094. Notably, triglyceride levels had considerably indirect impacts on association between NAFLD and rs1260326 (β =0.01, 95% CI: 0.01–0.02), indicating that 12.7% of the association of NAFLD with rs1260326 was mediated by triglyceride levels.

Conclusions: Our results identified a prominent relationship between GCKR rs1260326 and NAFLD, and highlighted the mediated effect of triglyceride levels on the that association in the Chinese Han elderly.

Pleiotropic Effects of Common and Rare GCKR Exonic Mutations on Cardiometabolic Traits

Background: The common non-synonymous mutation of the glucokinase regulator (GCKR) gene, namely rs1260326, is widely reported to have pleiotropic effects on cardio-metabolic traits and hematological parameters. Objective: This study aimed to identify whether other GCKR variants may have pleiotropic effects independent of the rs1260326 genotypes. Methods: In total, 81,097 Taiwan Biobank participants were enrolled for the regional plot association studies and candidate variant analysis of the region around the GCKR gene. Results: The initial candidate variant approach showed the significant association of the rs1260326 genotypes with multiple phenotypes. Regional plot association analysis of the GCKR gene region further revealed genome-wide significant associations between GCKR variants and serum total and low-density lipoprotein cholesterol; triglyceride, uric acid, creatinine, aspartate aminotransferase, γ-Glutamyl transferase, albumin, and fasting plasma glucose levels; estimated glomerular filtration rate; leukocyte and platelet counts; microalbuminuria, and metabolic syndrome, with rs1260326 being the most common lead polymorphism. Serial conditional analysis identified genome-wide significant associations of two low-frequency exonic mutations, rs143881585 and rs8179206, with high serum triglyceride and albumin levels. In five rare GCKR exonic non-synonymous or nonsense mutations available for analysis, GCKR rs146175795 showed an independent association with serum triglyceride and albumin levels and rs150673460 showed an independent association with serum triglyceride levels. Weighted genetic risk scores from the combination of GCKR rs143881585 and rs146175795 revealed a significant association with metabolic syndrome. Conclusion: In addition to the rs1260326 variant, low-frequency and rare GCKR exonic mutations exhibit pleiotropic effects on serum triglyceride and albumin levels and the risk of metabolic syndrome. These results provide evidence that both common and rare GCKR variants may play a critical role in predicting the risk of cardiometabolic disorders.

Mediterranean Diet and Genetic Determinants of Obesity and Metabolic Syndrome in European Children and Adolescents

Childhood obesity and metabolic syndrome (MetS) are multifactorial diseases influenced by genetic and environmental factors. The Mediterranean Diet (MD) seems to modulate the genetic predisposition to obesity or MetS in European adults. The FTO gene has also been shown to have an impact on the MD benefits to avoid obesity or MetS. Since these interaction effects have been scarcely analyzed in European youth, the aim was to describe the gene–MD interplay, analyzing the impact of the genetic factors to reduce the obesity and MetS risk through MD adherence, and the MD impact in the obesity and MetS genetic profile. From the limited evidence on gene–MD interaction studies in European youth, a study showed that the influence of high MD adherence on adiposity and MetS was only observed with a limited number of risk alleles; the gene–MD interplay showed sex-specific differences, being higher in females. Most results analyzed in European adults elucidate that, the relationship between MD adherence and both obesity and MetS risk, could be modulated by obesity genetic variants and vice versa. Further research is needed, to better understand the inter-individual differences in the association between MD and body composition, and the integration of omics and personalized nutrition considering MD.

Genetic association of LPL rs326 with BMI among the Kuwaiti population

Supplemental Digital Content is available in the text.

Lipoprotein lipase is a key enzyme in lipid metabolism with reported variants associated with obesity, hypertension, type 2 diabetes, and coronary heart disease. This study was performed to investigate the association between common lipoprotein lipase single nucleotide polymorphisms and metabolic disorders in a sample of Kuwaiti cohort (n = 494). Five lipoprotein lipase variants (rs1801177, rs295, rs326, ss2137497749, and ss2137497750) across the lipoprotein lipase gene were genotyped by real-time PCR employing the TaqMan allele discrimination assay. Genotype, allelic frequencies, and Hardy-Weinberg Equilibrium were determined for each variant in the cohort followed by multivariate and logistic regression analysis. A novel finding was observed for the G allele of single nucleotide polymorphism rs326 which was associated with increased BMI after adjusting for age and sex (β = 1.04; 95% confidence interval = 0.15–1.94; P = 0.02). Moreover, a significant difference in the distribution of the minor C allele of rs295 among coronary heart disease subjects compared with noncoronary heart disease, however, this significance was diminished after controlling for age, sex, and BMI. This study demonstrated that lipoprotein lipase rs326 may be indicative for the increased risk of obesity and possibly rs295 for coronary heart disease. The findings are also in agreement with other reports suggesting that intronic variants are important genetic markers in association studies. The findings warrant further studies in a large cohort to confirm and validate the results presented.

Genome-wide association analysis of metabolic syndrome quantitative traits in the GENNID multiethnic family study

BACKGROUND

To identify genetic associations of quantitative metabolic syndrome (MetS) traits and characterize heterogeneity across ethnic groups.

METHODS

Data was collected from GENetics of Noninsulin dependent Diabetes Mellitus (GENNID), a multiethnic resource of Type 2 diabetic families and included 1520 subjects in 259 African-American, European-American, Japanese-Americans, and Mexican-American families. We focused on eight MetS traits: weight, waist circumference, systolic and diastolic blood pressure, high-density lipoprotein, triglycerides, fasting glucose, and insulin. Using genotyped and imputed data from Illumina's Multiethnic array, we conducted genome-wide association analyses with linear mixed models for all ethnicities, except for the smaller Japanese-American group, where we used additive genetic models with gene-dropping.

RESULTS

Findings included ethnic-specific genetic associations and heterogeneity across ethnicities. Most significant associations were outside our candidate linkage regions and were coincident within a gene or intergenic region, with two exceptions in European-American families: (a) within previously identified linkage region on chromosome 2, two significant GLI2-TFCP2L1 associations with weight, and (b) one chromosome 11 variant near CADM1-LINC00900 with pleiotropic blood pressure effects.

CONCLUSIONS

This multiethnic family study found genetic heterogeneity and coincident associations (with one case of pleiotropy), highlighting the importance of including diverse populations in genetic research and illustrating the complex genetic architecture underlying MetS.

Kernel machine SNP set analysis finds the association of BUD13, ZPR1, and APOA5 variants with metabolic syndrome in Tehran Cardio-metabolic Genetics Study

Metabolic syndrome (MetS) is one of the most important risk factors for cardiovascular disease. The 11p23.3 chromosomal region plays a potential role in the pathogenesis of MetS. The present study aimed to assess the association between 18 single nucleotide polymorphisms (SNPs) located at the BUD13, ZPR1, and APOA5 genes with MetS in the Tehran Cardio-metabolic Genetics Study (TCGS). In 5421 MetS affected and non-affected participants, we analyzed the data using two models. The first model (MetS model) examined SNPs' association with MetS. The second model (HTg-MetS Model) examined the association of SNPs with MetS affection participants who had a high plasma triglyceride (TG). The four-gamete rules were used to make SNP sets from correlated nearby SNPs. The kernel machine regression models and single SNP regression evaluated the association between SNP sets and MetS. The kernel machine results showed two sets over three sets of correlated SNPs have a significant joint effect on both models (p < 0.0001). Also, single SNP regression results showed that the odds ratios (ORs) for both models are almost similar; however, the p-values had slightly higher significance levels in the HTg-MetS model. The strongest ORs in the HTg-MetS model belonged to the G allele in rs2266788 (MetS: OR = 1.3, p = 3.6 × 10^–7; HTg-MetS: OR = 1.4, p = 2.3 × 10^–11) and the T allele in rs651821 (MetS: OR = 1.3, p = 2.8 × 10^–7; HTg-MetS: OR = 1.4, p = 3.6 × 10^–11). In the present study, the kernel machine regression models could help assess the association between the BUD13, ZPR1, and APOA5 gene variants (11p23.3 region) with lipid-related traits in MetS and MetS affected with high TG.

Ancestry specific associations of a genetic risk score, dietary patterns and metabolic syndrome: a longitudinal ARIC study

BACKGROUND

Associations have been observed among genetic variants, dietary patterns, and metabolic syndrome (MetS). A gap in knowledge is whether a genetic risk score (GRS) and dietary patterns interact to increase MetS risk among African Americans. We investigated whether MetS risk was influenced by interaction between a GRS and dietary patterns among Whites and African Americans. A secondary aim examined if molecular genetic clusterings differed by racial ancestry.

METHODS

We used longitudinal data over 4-visits (1987-1998) that included 10,681 participants aged 45-64y at baseline from the Atherosclerosis Risk in Communities study (8451 Whites and 2230 African Americans). We constructed a simple-count GRS as the linear weighted sum of high-risk alleles (0, 1, 2) from cardiovascular disease polymorphisms from the genome-wide association studies catalog associated with MetS risk. Three dietary patterns were determined by factor analysis of food frequency questionnaire data: Western, healthy, and high-fat dairy. MetS was defined according to the 2016 National Cholesterol Education Program Adult Treatment Panel III criteria but used 2017 American Heart Association/American College of Cardiology criteria for elevated blood pressure. Analyses included generalized linear model risk ratios (RR), 95% confidence intervals (CI), and Bonferroni correction for multiple testing.

RESULTS

The Western dietary pattern was associated with higher risk for MetS across increasing GRS tertiles among Whites (p < 0.017). The high-fat dairy pattern was protective against MetS, but its impact was most effective in the lowest GRS tertile in Whites (RR = 0.62; CI: 0.52-0.74) and African Americans (RR = 0.67; CI: 0.49-0.91). Among each racial group within GRS tertiles, the Western dietary pattern was associated with development and cycling of MetS status between visits, and the high-fat dairy pattern with being free from MetS (p < 0.017). The healthy dietary pattern was associated with higher risk of MetS among African Americans which may be explained by higher sucrose intake (p < 0.0001). Fewer genes, but more metabolic pathways for obesity, body fat distribution, and lipid and carbohydrate metabolism were identified in African Americans than Whites. Some polymorphisms were linked to the Western and high-fat dairy patterns.

CONCLUSION

The influence of dietary patterns on MetS risk appears to differ by genetic predisposition and racial ancestry.

Genome-Wide Identification of Rare and Common Variants Driving Triglyceride Levels in a Nevada Population

Clinical conditions correlated with elevated triglyceride levels are well-known: coronary heart disease, hypertension, and diabetes. Underlying genetic and phenotypic mechanisms are not fully understood, partially due to lack of coordinated genotypic-phenotypic data. Here we use a subset of the Healthy Nevada Project, a population of 9,183 sequenced participants with longitudinal electronic health records to examine consequences of altered triglyceride levels. Specifically, Healthy Nevada Project participants sequenced by the Helix Exome+ platform were cross-referenced to their electronic medical records to identify: (1) rare and common single-variant genome-wide associations; (2) gene-based associations using a Sequence Kernel Association Test; (3) phenome-wide associations with triglyceride levels; and (4) pleiotropic variants linked to triglyceride levels. The study identified 549 significant single-variant associations (p < 8.75 × 10-9), many in chromosome 11's triglyceride hotspot: ZPR1, BUD13, APOC3, APOA5. A well-known protective loss-of-function variant in APOC3 (R19X) was associated with a 51% decrease in triglyceride levels in the cohort. Sixteen gene-based triglyceride associations were identified; six of these genes surprisingly did not include a single variant with significant associations. Results at the variant and gene level were validated with the UK Biobank. The combination of a single-variant genome-wide association, a gene-based association method, and phenome wide-association studies identified rare and common variants, genes, and phenotypes associated with elevated triglyceride levels, some of which may have been overlooked with standard approaches.

GCKR common functional polymorphisms are associated with metabolic syndrome and its components: a 10-year retrospective cohort study in Iranian adults

BACKGROUND

Previous studies reported that common functional variants (rs780093, rs780094, and rs1260326) in the glucokinase regulator gene (GCKR) were associated with metabolic syndrome despite the simultaneous association with the favorable and unfavorable metabolic syndrome components. We decided to evaluate these findings in a cohort study with a large sample size of Iranian adult subjects, to our knowledge for the first time. We investigated the association of the GCKR variants with incident MetS in mean follow-up times for nearly 10 years.

METHODS

Analysis of this retrospective cohort study was performed among 5666 participants of the Tehran Cardiometabolic Genetics Study (TCGS) at 19-88 years at baseline. Linear and logistic regression analyses were used to investigate the metabolic syndrome (JIS criteria) association and its components with rs780093, rs780094, and rs1260326 in an additive genetic model. Cox regression was carried out to peruse variants' association with the incidence of metabolic syndrome in the TCGS cohort study.

RESULTS

In the current study, we have consistently replicated the association of the GCKR SNPs with higher triglyceride and lower fasting blood sugar levels (p < 0.05) in Iranian adults. The CT genotype of the variants was associated with lower HDL-C levels. The proportional Cox adjusted model regression resulted that TT carriers of rs780094, rs780093, and rs1260326 were associated with 20%, 23%, and 21% excess risk metabolic syndrome incidence, respectively (p < 0.05).

CONCLUSIONS

Elevated triglyceride levels had the strongest association with GCKR selected variants among the metabolic syndrome components. Despite the association of these variants with decreased fasting blood sugar levels, T alleles of the variants were associated with metabolic syndrome incidence; so whether individuals are T allele carriers of the common functional variants, they have a risk factor for the future incidence of metabolic syndrome.

Fine genetic mapping of the chromosome 11q23.3 region in a Han Chinese population: insights into the apolipoprotein genes underlying the blood lipid-lipoprotein variances

The unusual chromosome 11q23.3 harboring the apolipoprotein (APO) gene cluster has been well documented for its essential roles in plasma lipid-related traits and atherosclerotic cardiovascular diseases. However, its genetic architecture and the potential biological mechanisms underlying complex phenotypes have not been well assessed. We conducted a study for this target region in a Han Chinese population through a stepwise forward framework based on massive parallel sequencing, association analyses, genetic fine mapping, and functional interpretation. The present study identified new meaningful genetic associations that were not simply determined by statistical significance. In addition to the APOA5 gene, we found robust evidence of the genetic commitments of APOC3 and APOA1 to blood lipids. Several variants with high confidence were prioritized along with the potential biological mechanism interpretations in the wake of adaptive fine-mapping analyses. rs2849174 in the APOC3 enhancer was discovered with an unrivaled posterior probability of causality for triglyceride levels and could mediate APOC3 expression through enhancer activity modulated by a combination of histone modifications and transcription factor accessibility. Similarly, multiple lines of evidence converged in favor of rs3741297 as a causal variant influencing high-density lipoprotein cholesterol. Our findings provided novel insights into this genomic locus in the Chinese population.

Hepatic lipase (LIPC) sequencing in individuals with extremely high and low high-density lipoprotein cholesterol levels

Common variants in the hepatic lipase (LIPC) gene have been shown to be associated with plasma lipid levels; however, the distribution and functional features of rare and regulatory LIPC variants contributing to the extreme lipid phenotypes are not well known. This study was aimed to catalogue LIPC variants by resequencing the entire LIPC gene in 95 non-Hispanic Whites (NHWs) and 95 African blacks (ABs) with extreme HDL-C levels followed by in silico functional analyses. A total of 412 variants, including 43 novel variants were identified; 56 were unique to NHWs and 234 were unique to ABs. Seventy-eight variants in NHWs and 89 variants in ABs were present either in high HDL-C group or low HDL-C group. Two non-synonymous variants (p.S289F, p.T405M), found in NHWs with high HDL-C group were predicted to have damaging effect on LIPC protein by SIFT, MT2 and PP2. We also found several non-coding variants that possibly reside in the circRNA and lncRNA binding sites and may have regulatory potential, as identified in rSNPbase and RegulomeDB databases. Our results shed light on the regulatory nature of rare and non-coding LIPC variants as well as suggest their important contributions in affecting the extreme HDL-C phenotypes.

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.

Association of Candidate Gene Polymorphism with Metabolic Syndrome among Mongolian Subjects: A Case-Control Study

Metabolic syndrome (MetS) is complex and determined by the interaction between genetic and environmental factors and their influence on obesity, insulin resistance, and related traits associated with diabetes and cardiovascular disease risk. Some dynamic markers, including adiponectin (ADIPOQ), brain-derived neurotrophic factor (BDNF), and lipoprotein lipase (LPL), are implicated in MetS; however, the influence of their genetic variants on MetS susceptibility varies in racial and ethnic groups. We investigated the association of single nucleotide polymorphism (SNP)-SNP interactions among nine SNPs in six genes with MetS's genetic predisposition in Mongolian subjects. A total of 160 patients with MetS for the case group and 144 healthy individuals for the control group were selected to participate in this study. Regression analysis of individual SNPs showed that the ADIPOQ + 45GG (odds ratio (OR) = 2.09, p = 0.011) and P⁺P⁺ of LPL PvuII (OR = 2.10, p = 0.038) carriers had an increased risk of MetS. Conversely, G allele of LPL S447X (OR = 0.45, p = 0.036) and PGC-1α 482Ser (OR = 0.26, p = 0.001) allele were estimated as protective factors, respectively. Moreover, a haplotype containing the G-P⁺-G combination was related to MetS. Significant loci were also related to body mass index (BMI), systolic blood pressure (SBP), serum high-density lipoprotein cholesterol (HDL-C), triglyceride (TG), and fasting blood glucose (FBG), adipokines, and insulin as well as insulin resistance (p < 0.05). Our results confirm that ADIPOQ + 45T > G, LPL PvII, and PGC-1α Gly482Ser loci are associated with MetS in Mongolian subjects.

Regional distribution of Christensenellaceae and its associations with metabolic syndrome based on a population-level analysis

The link between the gut microbiota and metabolic syndrome (MetS) has attracted widespread attention. Christensenellaceae was recently described as an important player in human health, while its distribution and relationship with MetS in Chinese population is still unknown. This study sought to observe the association between Christensenellaceae and metabolic indexes in a large sample of residents in South China. A total of 4,781 people from the GGMP project were included, and the fecal microbiota composition of these individuals was characterized by 16S rRNA sequencing and analyzed the relation between Christensenellaceae and metabolism using QIIME (Quantitative Insight Into Microbial Ecology, Version 1.9.1). The results demonstrated that microbial richness and diversity were increased in the group with a high abundance of Christensenellaceae, who showed a greater complexity of the co-occurrence network with other bacteria than residents who lacked Christensenellaceae. The enriched bacterial taxa were predominantly represented by Oscillospira, Ruminococcaceae, RF39, Rikenellaceae and Akkermansia as the Christensenellaceae abundance increased, while the abundances of Veillonella, Fusobacterium and Klebsiella were significantly reduced. Furthermore, Christensenellaceae was negatively correlated with the pathological features of MetS, such as obesity, hypertriglyceridemia and body mass index (BMI). We found reduced levels of lipid biosynthesis and energy metabolism pathways in people with a high abundance of Christensenellaceae, which may explain the negative relationship between body weight and Christensenellaceae. In conclusion, we found a negative correlation between Christensenellaceae and MetS in a large Chinese population and reported the geographical distribution of Christensenellaceae in the GGMP study. The association data from this population-level research support the investigation of strains within Christensenellaceae as potentially beneficial gut microbes.

Genetics Insights in the Relationship Between Type 2 Diabetes and Coronary Heart Disease

Diabetes mellitus is a major risk factor for coronary heart disease (CHD). The major form of diabetes mellitus is type 2 diabetes mellitus (T2D), which is thus largely responsible for the CHD association in the general population. Recent years have seen major advances in the genetics of T2D, principally through ever-increasing large-scale genome-wide association studies. This article addresses the question of whether this expanding knowledge of the genomics of T2D provides insight into the etiologic relationship between T2D and CHD. We will investigate this relationship by reviewing the evidence for shared genetic loci between T2D and CHD; by examining the formal testing of this interaction (Mendelian randomization studies assessing whether T2D is causal for CHD); and then turn to the implications of this genetic relationship for therapies for CHD, for therapies for T2D, and for therapies that affect both. In conclusion, the growing knowledge of the genetic relationship between T2D and CHD is beginning to provide the promise for improved prevention and treatment of both disorders.

Mitochondrial dysfunction in metabolic syndrome

Metabolic syndrome is co-occurrence of obesity, insulin resistance, atherogenic dyslipidemia (high triglyceride, low high density lipoprotein cholesterol), and hypertension. It is a global health problem. An estimated 20%-30% of adults of the world have metabolic syndrome. Metabolic syndrome is associated with increased risk of type 2 diabetes mellitus, nonalcoholic fatty liver disease, myocardial infarction, and stroke. Thus, it is a major cause of morbidity and mortality worldwide. However, molecular pathogenesis of metabolic syndrome is not well known. Recently, there has been interest in the role of mitochondria in pathogenesis of metabolic problems such as obesity, metabolic syndrome, and type 2 diabetes mellitus. Mitochondrial dysfunction contributes to the oxidative stress and systemic inflammation seen in metabolic syndrome. Role of mitochondria in the pathogenesis of metabolic syndrome is intriguing but far from completely understood. However, a better understanding will be very rewarding as it may lead to novel approaches to control this major public health problem. This brief review explores pathogenesis of metabolic syndrome from a mitochondrial perspective.

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.

Common genetic variation in obesity, lipid transfer genes and risk of Metabolic Syndrome: Results from IDEFICS/I.Family study and meta-analysis

As the prevalence of metabolic syndrome (MetS) in children and young adults is increasing, a better understanding of genetics that underlie MetS will provide critical insights into the origin of the disease. We examined associations of common genetic variants and repeated MetS score from early childhood to adolescence in a pan-European, prospective IDEFICS/I.Family cohort study with baseline survey and follow-up examinations after two and six years. We tested associations in 3067 children using a linear mixed model and confirmed the results with meta-analysis of identified SNPs. With a stringent Bonferroni adjustment for multiple comparisons we obtained significant associations(p < 1.4 × 10⁻⁴) for 5 SNPs, which were in high LD (r² > 0.85) in the 16q12.2 non-coding intronic chromosomal region of FTO gene with strongest association observed for rs8050136 (effect size(β) = 0.31, p_Wald = 1.52 × 10⁻⁵). We also observed a strong association of rs708272 in CETP with increased HDL (p = 5.63 × 10⁻⁴⁰) and decreased TRG (p = 9.60 × 10⁻⁵) levels. These findings along with meta-analysis advance etiologic understanding of childhood MetS, highlighting that genetic predisposition to MetS is largely driven by genes of obesity and lipid metabolism. Inclusion of the associated genetic variants in polygenic scores for MetS may prove to be fundamental for identifying children and subsequently adults of the high-risk group to allow earlier targeted interventions.

Scaffold-Free Endometrial Organoids Respond to Excess Androgens Associated With Polycystic Ovarian Syndrome

CONTEXT

Polycystic ovary syndrome (PCOS) is a prevalent disorder in reproductive aged women associated with a number of endocrine and metabolic complications, including increased risk of endometrial cancer.

OBJECTIVE

To study the effect of the characteristic increased androgen levels in PCOS on the endometrium, a novel scaffold-free multicellular endometrial organoid was established.

DESIGN

Human endometrial organoids were constructed using primary endometrial epithelial and stromal cells from endometrial tissues. Organoids were treated for 14 days with physiologic levels of estradiol and testosterone to mimic a normal follicular phase or PCOS hormone profiles. Organoids were harvested for immunostaining and ribonucleic acid sequencing.

SETTING

Academic institution.

PATIENTS

Endometrial tissues from 10 premenopausal women undergoing hysterectomy for benign pathologies were obtained following written consent.

MAIN OUTCOME MEASURES

Organoid architecture, cell specific markers, functional markers, proliferation, and gene expression were measured.

RESULTS

A method to generate scaffold-free endometrial organoids containing epithelial and stromal cells was established. These organoids exhibited distinct organization with epithelial cells lining the outer surface and stromal cells in the center of the organoids. Epithelial cells were polarized, organoids expressed cell type specific and functional markers, as well as androgen, estrogen, and progesterone receptors. Treatment with PCOS hormones increased cell proliferation and dysregulated genes in endometrial organoids.

CONCLUSIONS

A new multicellular, scaffold-free endometrial organoid system was established that resembled physiology of the native endometrium. Excess androgens in PCOS promoted cell proliferation in endometrial organoids, revealing new mechanisms of PCOS-associated with risk of endometrial neoplasia.

Legacy Data Confound Genomics Studies

Recent reports have identified differences in the mutational spectra across human populations. Although some of these reports have been replicated in other cohorts, most have been reported only in the 1000 Genomes Project (1kGP) data. While investigating an intriguing putative population stratification within the Japanese population, we identified a previously unreported batch effect leading to spurious mutation calls in the 1kGP data and to the apparent population stratification. Because the 1kGP data are used extensively, we find that the batch effects also lead to incorrect imputation by leading imputation servers and a small number of suspicious GWAS associations. Lower quality data from the early phases of the 1kGP thus continue to contaminate modern studies in hidden ways. It may be time to retire or upgrade such legacy sequencing data.

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 metabolic syndrome in Korean populations

Metabolic syndrome (MetS) which is caused by obesity and insulin resistance, is well known for its predictive capability for the risk of type 2 diabetes mellitus and cardiovascular disease. The development of MetS is associated with multiple genetic factors, environmental factors and lifestyle. We performed a genome-wide association study to identify single-nucleotide polymorphism (SNP) related to MetS in large Korean population based samples of 1,362 subjects with MetS and 6,061 controls using the Axiom^® Korean Biobank Array 1.0. We replicated the data in another sample including 502 subjects with MetS and 1,751 controls. After adjusting for age and sex, rs662799 located in the APOA5 gene were significantly associated with MetS. 15 SNPs in GCKR, C2orf16, APOA5, ZPR1, and BUD13 were associated with high triglyceride (TG). 14 SNPs in APOA5, ALDH1A2, LIPC, HERPUD1, and CETP, and 2 SNPs in MTNR1B were associated with low high density lipoprotein cholesterol (HDL-C) and high fasting blood glucose respectively. Among these SNPs, 6 TG SNPs: rs1260326, rs1260333, rs1919127, rs964184, rs2075295 and rs1558861 and 11 HDL-C SNPs: rs4775041, rs10468017, rs1800588, rs72786786, rs173539, rs247616, rs247617, rs3764261, rs4783961, rs708272, and rs7499892 were first discovered in Koreans. Additional research is needed to confirm these 17 novel SNPs in Korean population.

Longitudinal Phenotypes Improve Genotype Association for Hyperketonemia in Dairy Cattle

Simple Summary

Dairy cows have differing success in supporting their physiological functions while in energy deficit right after calving. Identification of genomic regions associated with different concentrations of non–esterified fatty acids and β–hydroxybutyrate in early postpartum Holstein cows provide insight into an animal’s genetic susceptibility to these conditions. Longitudinal phenotypes may provide a different perspective than cross-sectional phenotype variation and their association with genotypes in the study of complex metabolic diseases in dairy cows. This might allow us to reinforce preventative measures that decrease the incidence of hyperketonemia and improve genetic selection criteria.

Abstract

The objective of our study was to identify genomic regions associated with varying concentrations of non-esterified fatty acid (NEFA), β-hydroxybutyrate (BHB), and the development of hyperketonemia (HYK) in longitudinally sampled Holstein dairy cows. Our study population consisted of 147 multiparous cows intensively characterized by serial NEFA and BHB concentrations. To identify individuals with contrasting combinations in longitudinal BHB and NEFA concentrations, phenotypes were established using incremental area under the curve (AUC) and categorized as follows: Group (1) high NEFA and high BHB, group (2) low NEFA and high BHB), group (3) low NEFA and low BHB, and group (4) high NEFA and low BHB. Cows were genotyped on the Illumina Bovine High-density (777 K) beadchip. Genome-wide association studies using mixed linear models with the least-related animals were performed to establish a genetic association with HYK, BHB-AUC, NEFA-AUC, and the comparisons of the 4 AUC phenotypic groups using Golden Helix software. Nine single-nucleotide polymorphisms were associated with high longitudinal concentrations of BHB and further investigated. Five candidate genes related to energy metabolism and homeostasis were identified. These results provide biological insight and help identify susceptible animals thus improving genetic selection criteria thereby decreasing the incidence of HYK.

Genome-Wide Association Analyses of Equine Metabolic Syndrome Phenotypes in Welsh Ponies and Morgan Horses

Equine metabolic syndrome (EMS) is a complex trait for which few genetic studies have been published. Our study objectives were to perform within breed genome-wide association analyses (GWA) to identify associated loci in two high-risk breeds, coupled with meta-analysis to identify shared and unique loci between breeds. GWA for 12 EMS traits identified 303 and 142 associated genomic regions in 264 Welsh ponies and 286 Morgan horses, respectively. Meta-analysis demonstrated that 65 GWA regions were shared across breeds. Region boundaries were defined based on a fixed-size or the breakdown of linkage disequilibrium, and prioritized if they were: shared between breeds or across traits (high priority), identified in a single GWA cohort (medium priority), or shared across traits with no SNPs reaching genome-wide significance (low priority), resulting in 56 high, 26 medium, and seven low priority regions including 1853 candidate genes in the Welsh ponies; and 39 high, eight medium, and nine low priority regions including 1167 candidate genes in the Morgans. The prioritized regions contained protein-coding genes which were functionally enriched for pathways associated with inflammation, glucose metabolism, or lipid metabolism. These data demonstrate that EMS is a polygenic trait with breed-specific risk alleles as well as those shared across breeds.

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.

Race-ethnic differences in the associations of maternal lipid trait genetic risk scores with longitudinal fetal growth

BACKGROUND

Fetal growth, an important predictor of cardiometabolic diseases in adults, is influenced by maternal and fetal genetic and environmental factors.

OBJECTIVE

We investigated the association between maternal lipid genetic risk score (GRS) and fetal growth among 4 US racial-ethnic populations (Whites, Blacks, Hispanics, and Asians).

METHODS

We extracted genotype data for 2008 pregnant women recruited in the National Institute of Child Health and Human Development Fetal Growth Studies-Singleton cohort with up to 6 standardized ultrasound examinations. GRS was calculated using 240 single-nucleotide polymorphisms previously associated with higher total cholesterol (GRSTChol), low-density lipoprotein cholesterol (GRSLDLc), and triglycerides (GRSTG) and lower high-density lipoprotein cholesterol (GRSHDLc).

RESULTS

At 40 weeks' gestation, a unit increase in GRSTG was associated with 11.4 g higher fetal weight (95% confidence interval [CI] 2.8-20.0 g) among normal-weight Whites, 26.3 g (95% CI 6.0-46.6 g) among obese Blacks, and 30.8 g (95% CI 6.3-55.3 g) among obese Hispanics. Higher GRSHDLc was associated with increased fetal weight across 36 to 40 weeks among normal-weight Whites and across 13 to 20 weeks among normal-weight Asians, but with decreased fetal weight across 26 to 40 weeks among normal-weight Hispanics. Higher GRSTChol was suggestively associated with increased fetal weight in males and decreased in females. Associations remained consistent after adjustment for serum lipids.

CONCLUSION

Associations between fetal weight and maternal lipid GRS appear to vary by maternal race-ethnic group, obesity status, and offspring sex. Genetic susceptibility to unfavorable lipid profiles contributes to fetal growth differences even among normal-weight women suggesting a potential future application in predicting aberrant fetal growth.

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.

Genetic predisposition to increased serum calcium, bone mineral density, and fracture risk in individuals with normal calcium levels: mendelian randomisation study

OBJECTIVE

To determine if genetically increased serum calcium levels are associated with improved bone mineral density and a reduction in osteoporotic fractures.

DESIGN

Mendelian randomisation study.

SETTING

Cohorts used included: the UK Biobank cohort, providing genotypic and estimated bone mineral density data; 25 cohorts from UK, USA, Europe, and China, providing genotypic and fracture data; and 17 cohorts from Europe, providing genotypic and serum calcium data (summary level statistics).

PARTICIPANTS

A genome-wide association meta-analysis of serum calcium levels in up to 61 079 individuals was used to identify genetic determinants of serum calcium levels. The UK Biobank study was used to assess the association of genetic predisposition to increased serum calcium with estimated bone mineral density derived from heel ultrasound in 426 824 individuals who had, on average, calcium levels in the normal range. A fracture genome-wide association meta-analysis comprising 24 cohorts and the UK Biobank including a total of 76 549 cases and 470 164 controls, who, on average, also had calcium levels in the normal range was then performed.

RESULTS

A standard deviation increase in genetically derived serum calcium (0.13 mmol/L or 0.51 mg/dL) was not associated with increased estimated bone mineral density (0.003 g/cm2, 95% confidence interval -0.059 to 0.066; P=0.92) or a reduced risk of fractures (odds ratio 1.01, 95% confidence interval 0.89 to 1.15; P=0.85) in inverse-variance weighted mendelian randomisation analyses. Sensitivity analyses did not provide evidence of pleiotropic effects.

CONCLUSIONS

Genetic predisposition to increased serum calcium levels in individuals with normal calcium levels is not associated with an increase in estimated bone mineral density and does not provide clinically relevant protection against fracture. Whether such predisposition mimics the effect of short term calcium supplementation is not known. Given that the same genetically derived increase in serum calcium is associated with an increased risk of coronary artery disease, widespread calcium supplementation in the general population could provide more risk than benefit.

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.

ZRANB3 is an African-specific type 2 diabetes locus associated with beta-cell mass and insulin response

Genome analysis of diverse human populations has contributed to the identification of novel genomic loci for diseases of major clinical and public health impact. Here, we report a genome-wide analysis of type 2 diabetes (T2D) in sub-Saharan Africans, an understudied ancestral group. We analyze ~18 million autosomal SNPs in 5,231 individuals from Nigeria, Ghana and Kenya. We identify a previously-unreported genome-wide significant locus: ZRANB3 (Zinc Finger RANBP2-Type Containing 3, lead SNP p = 2.831 × 10⁻⁹). Knockdown or genomic knockout of the zebrafish ortholog results in reduction in pancreatic β-cell number which we demonstrate to be due to increased apoptosis in islets. siRNA transfection of murine Zranb3 in MIN6 β-cells results in impaired insulin secretion in response to high glucose, implicating Zranb3 in β-cell functional response to high glucose conditions. We also show transferability in our study of 32 established T2D loci. Our findings advance understanding of the genetics of T2D in non-European ancestry populations.

Type 2 diabetes (T2D) is prevalent in populations worldwide, however, mostly studied in European and mixed-ancestry populations. Here, the authors perform a genome-wide association study for T2D in over 5,000 sub-Saharan Africans and identify a locus, ZRANB3, that is specific for this population.