Gene-gene interaction between APOA5 and USF1: two candidate genes for the metabolic syndrome

Association of Genetically Predicted BCAA Levels with Muscle Fiber Size in Athletes Consuming Protein

Branched-chain amino acid (BCAA) levels are associated with skeletal muscle cross-sectional area (CSA). Serum BCAA levels are enhanced by whey protein supplementation (WPS), and evidence in clinical populations suggests an association of single nucleotide polymorphisms (SNPs) with BCAA metabolite levels. It is not known whether the same SNPs are associated with the ability to catabolise BCAAs from exogenous sources, such as WPS. The present study investigated whether possessing a higher number of alleles associated with increased BCAA metabolites correlates with muscle fiber CSA of m. vastus lateralis in physically active participants, and whether any relationship is enhanced by WPS. Endurance-trained participants (n = 75) were grouped by self-reported habitual WPS consumption and genotyped for five SNPs (PPM1K rs1440580, APOA5 rs2072560, CBLN1 rs1420601, DDX19B rs12325419, and TRMT61A rs58101275). Body mass, BMI, and fat percentage were significantly lower and muscle mass higher in the WPS group compared to Non-WPS. The number of BCAA-increasing alleles was correlated with fiber CSA in the WPS group (r = 0.75, p < 0.0001) and was stronger for fast-twitch fibers (p = 0.001) than slow-twitch fibers (p = 0.048). Similar results remained when corrected for multiple covariates (age, physical activity, and meat and dairy intake). No correlation was found in the Non-WPS group. This study presents novel evidence of a positive relationship between BCAA-increasing alleles and muscle fiber CSA in athletes habitually consuming WPS. We suggest that a high number of BCAA-increasing alleles improves the efficiency of WPS by stimulation of muscle protein synthesis, and contributes to greater fiber CSA.

Novel EDGE encoding method enhances ability to identify genetic interactions

Assumptions are made about the genetic model of single nucleotide polymorphisms (SNPs) when choosing a traditional genetic encoding: additive, dominant, and recessive. Furthermore, SNPs across the genome are unlikely to demonstrate identical genetic models. However, running SNP-SNP interaction analyses with every combination of encodings raises the multiple testing burden. Here, we present a novel and flexible encoding for genetic interactions, the elastic data-driven genetic encoding (EDGE), in which SNPs are assigned a heterozygous value based on the genetic model they demonstrate in a dataset prior to interaction testing. We assessed the power of EDGE to detect genetic interactions using 29 combinations of simulated genetic models and found it outperformed the traditional encoding methods across 10%, 30%, and 50% minor allele frequencies (MAFs). Further, EDGE maintained a low false-positive rate, while additive and dominant encodings demonstrated inflation. We evaluated EDGE and the traditional encodings with genetic data from the Electronic Medical Records and Genomics (eMERGE) Network for five phenotypes: age-related macular degeneration (AMD), age-related cataract, glaucoma, type 2 diabetes (T2D), and resistant hypertension. A multi-encoding genome-wide association study (GWAS) for each phenotype was performed using the traditional encodings, and the top results of the multi-encoding GWAS were considered for SNP-SNP interaction using the traditional encodings and EDGE. EDGE identified a novel SNP-SNP interaction for age-related cataract that no other method identified: rs7787286 (MAF: 0.041; intergenic region of chromosome 7)–rs4695885 (MAF: 0.34; intergenic region of chromosome 4) with a Bonferroni LRT p of 0.018. A SNP-SNP interaction was found in data from the UK Biobank within 25 kb of these SNPs using the recessive encoding: rs60374751 (MAF: 0.030) and rs6843594 (MAF: 0.34) (Bonferroni LRT p: 0.026). We recommend using EDGE to flexibly detect interactions between SNPs exhibiting diverse action.

Although traditional genetic encodings are widely implemented in genetics research, including in genome-wide association studies (GWAS) and epistasis, each method makes assumptions that may not reflect the underlying etiology. Here, we introduce a novel encoding method that estimates and assigns an individualized data-driven encoding for each single nucleotide polymorphism (SNP): the elastic data-driven genetic encoding (EDGE). With simulations, we demonstrate that this novel method is more accurate and robust than traditional encoding methods in estimating heterozygous genotype values, reducing the type I error, and detecting SNP-SNP interactions. We further applied the traditional encodings and EDGE to biomedical data from the Electronic Medical Records and Genomics (eMERGE) Network for five phenotypes, and EDGE identified a novel interaction for age-related cataract not detected by traditional methods, which replicated in data from the UK Biobank. EDGE provides an alternative approach to understanding and modeling diverse SNP models and is recommended for studying complex genetics in common human phenotypes.

New insights into apolipoprotein A5 in controlling lipoprotein metabolism in obesity and the metabolic syndrome patients

Apolipoprotein A5 (apoA5) has been identified to play an important role in lipid metabolism, specifically in triglyceride (TG) and TG-rich lipoproteins (TRLs) metabolism. Numerous evidence has demonstrated for an association between apoA5 and the increased risk of obesity and metabolic syndrome, but the mechanism remains to be fully elucidated. Recently, several studies verified that apoA5 could significantly reduce plasma TG level by stimulating lipoprotein lipase (LPL) activity, and the intracellular role of apoA5 has also been proved since apoA5 is associated with cytoplasmic lipid droplets (LDs) and affects intrahepatic TG accumulation. Furthermore, since adipocytes provide the largest storage depot for TG and play a crucial role in the development of obesity, we could infer that apoA5 also acts as a novel regulator to modulate TG storage in adipocytes. In this review, we focus on the association of gene and protein of apoA5 with obesity and metabolic syndrome, and provide new insights into the physiological role of apoA5 in humans, giving a potential therapeutic target for obesity and associated disorders.

The rs2516839 Polymorphism of the USF1 Gene May Modulate Serum Triglyceride Levels in Response to Cigarette Smoking

Single nucleotide polymorphisms (SNPs) of the USF1 gene (upstream stimulatory factor 1) influence plasma lipid levels. This study aims to determine whether USF1 SNPs interact with traditional risk factors of atherosclerosis to increase coronary artery disease (CAD) risk. In the present study serum lipid levels and USF1 gene polymorphisms (rs2516839 and rs3737787) were determined in 470 subjects: 235 patients with premature CAD and 235 controls. A trend of increasing triglycerides (TG) levels in relation to the C allele dose of rs2516839 SNP was observed. The synergistic effect of cigarette smoking and C allele carrier state on CAD risk was also found (SIM = 2.69, p = 0.015). TG levels differentiated significantly particular genotypes in smokers (1.53 mmol/L for TT, 1.80 mmol/L for CT and 2.27 mmol/L for CC subjects). In contrast, these differences were not observed in the non-smokers subgroup (1.57 mmol/L for TT, 1.46 mmol/L for CT and 1.49 mmol/L for CC subjects). In conclusion, the rs2516839 polymorphism may modulate serum triglyceride levels in response to cigarette smoking. Carriers of the C allele seem to be particularly at risk of CAD, when exposed to cigarette smoking.

Two polymorphisms of USF1 gene (-202G>A and -844C>T) may be associated with hepatocellular carcinoma susceptibility based on a case-control study in Chinese Han population

Hepatocellular carcinoma (HCC) is a prototype of liver cancer, which is closely related to manifested metabolism of lip and glucose. Upstream transcription factor 1 (USF1) is an important transcription factor in human genome, and it regulates the expression of multiple genes associated with lipid and glucose metabolism. This study aims at investigating the correlation between seven common USF1 polymorphisms (i.e., -1994 G>A, -202 G>A, 7998 A>G, -844 C>T, 9042 C>G, 9441 T>C, and -2083 G>A) and the risk of HCC. Elucidation of the interaction might be of vital importance to the diagnosis and prognosis of HCC. One hundred and fifty-five HCC patients and 160 healthy controls from a Chinese Han population were involved in this study. Tag single-nucleotide polymorphisms (SNPs) were identified with reference to CBI-dbSNP and HapMap databases. DNA was extracted from blood samples, and matrix-assisted laser desorption-ionization time-of-flight mass spectrometry (MALDI-TOF-MS) was conducted to determine the polymorphisms of USF1. Odds ratio (OR) and 95% confidence interval were applied to evaluate the difference of genotype distribution. Seven SNPs were selected to be representatives. No significant difference was observed concerning -1994 G>A, 7998 A>G, 9042 C>G, 9441 T>C, and -2083 G>A polymorphisms (all P > 0.05). A significantly elevated genotype frequency regarding -202 G>A polymorphism was observed in HCC patients [AA vs. GG: OR 2.13 (1.13-4.01), P = 0.019; AA vs. GG+GA: OR 2.22 (1.32-3.75), P = 0.003; A allele vs. G allele: OR 1.46 (1.07-2.01), P = 0.018]. Subjects carrying mutant -844 C>T genotypes also had a higher risk of HCC [CT vs. CC: OR 1.88 (1.17-3.04), P = 0.009; CT+TT vs. CC: OR 1.83 (1.17-2.86), P = 0.008; T allele vs. C allele: OR 1.49 (1.06-2.09), P = 0.020]. Further studies are recommended to validate our findings in different ethnicity and to clarify the functional relationship between USF1 polymorphisms and the susceptibility of HCC.

Moderate physical activity level as a protective factor against metabolic syndrome in middle-aged and older women

AIMS AND OBJECTIVES

To investigate whether physical activity is a protective factor against metabolic syndrome in middle-aged and older women.

BACKGROUND

Socio-demographic and lifestyle behaviour factors contribute to metabolic syndrome. To minimise the risk of metabolic syndrome, several global guidelines recommend increasing physical activity level. However, only limited research has investigated the relationship between physical activity levels and metabolic syndrome in middle-aged and older women after adjusting for socio-demographic and lifestyle behaviour factors.

DESIGN

Cross-sectional design.

METHODS

A convenience sample of 326 middle-aged and older women was recruited. Metabolic syndrome was confirmed according to the National Cholesterol Education Program, Adult Treatment Panel III guidelines, and physical activity levels were measured by the International Physical Activity Questionnaire.

RESULTS

The sample had a mean age of 60·9 years, and the prevalence of metabolic syndrome was 43·3%. Postmenopausal women and women with low socioeconomic status (low-education background, without personal income and currently unemployed) had a significantly higher risk of developing metabolic syndrome. After adjusting for significant socio-demographic and lifestyle behaviour factors, the women with moderate or high physical activity levels had a significantly lower (OR = 0·10; OR = 0·11, p < 0·001) risk of metabolic syndrome and a lower risk for each specific component of metabolic syndrome, including elevated fasting plasma glucose (OR = 0·29; OR = 0·26, p = 0·009), elevated blood pressure (OR = 0·18; OR = 0·32, p = 0·029), elevated triglycerides (OR = 0·41; OR = 0·15, p = 0·001), reduced high-density lipoprotein (OR = 0·28; OR = 0·27, p = 0·004) and central obesity (OR = 0·31; OR = 0·22, p = 0·027).

CONCLUSIONS

After adjusting for socio-demographic and lifestyle behaviour factors, physical activity level was a significant protective factor against metabolic syndrome in middle-aged and older women. Higher physical activity levels (moderate or high physical activity level) reduced the risk of metabolic syndrome in middle-aged and older women.

RELEVANCE TO CLINICAL PRACTICE

Appropriate strategies should be developed to encourage middle-aged and older women across different socio-demographic backgrounds to engage in moderate or high levels of physical activity to reduce the risk of metabolic syndrome.

Four pairs of gene-gene interactions associated with increased risk for type 2 diabetes (CDKN2BAS-KCNJ11), obesity (SLC2A9-IGF2BP2, FTO-APOA5), and hypertension (MC4R-IGF2BP2) in Chinese women

Metabolic disorders including type 2 diabetes, obesity and hypertension have growing prevalence globally every year. Genome-wide association studies have successfully identified many genetic markers associated to these diseases, but few studied their interaction effects. In this study, twenty candidate SNPs from sixteen genes are selected, and a lasso-multiple regression approach is implemented to consider the SNP–SNP interactions among them in an Asian population. It is found out that the main effects of the markers are weak but the interactions among the candidates showed a significant association to diseases. SNPs from genes CDKN2BAS and KCNJ11 are significantly associated to risk for developing diabetes, and SNPs from FTO and APOA5 might interact to play an important role for the onset of hypertension.

Association analysis of USF1 gene polymorphisms and total unstable carotid plaque area in atherosclerotic stroke patients

Polymorphisms of the upstream stimulatory factor 1 (USF1) have been associated with carotid artery intima-media thickness and coronary atherosclerotic lesions. Unstable carotid plaque is an atherosclerotic change of vascular morphology that has been correlated with cerebrovascular ischemic symptoms. Associations of three single nucleotide polymorphisms of the USF1 gene with total unstable carotid plaque area (CPA) were investigated in Chinese atherosclerotic stroke patients. We recruited 668 atherosclerotic stroke patients and 602 controls. Total unstable CPA values were measured by ultrasound. Genotypes were analyzed using polymerase chain reaction-based restriction fragment length polymorphism (PCR-RFLP) or mismatched PCR-RFLP. A significant difference in total unstable CPA was found for rs2516838 and rs2516839 genotypes (P = 0.039 and 0.046, respectively) in atherosclerotic stroke patients with unstable carotid plaque. Furthermore, in multiple logistic regression analysis adjusted by age, sex, BMI, hypertension, smoking status, glucose, total cholesterol, triglycerides, high-density lipoprotein-cholesterols, low-density lipoprotein-cholesterols and high-sensitivity C-reactive protein, significant associations were seen between the total unstable CPA values and genotypes of the rs2516838 or the rs2516839 in these patients. The rare allele C of rs2516838 or rare allele A of rs2516839 could predict relative low total unstable CPA values. The rs2516838 and rs2516839 polymorphisms of USF1 influence total unstable CPA in atherosclerotic stroke patients, which might be new markers to predict the risk of recurrence for this disease.

Genetic effects at pleiotropic loci are context-dependent with consequences for the maintenance of genetic variation in populations

Context-dependent genetic effects, including genotype-by-environment and genotype-by-sex interactions, are a potential mechanism by which genetic variation of complex traits is maintained in populations. Pleiotropic genetic effects are also thought to play an important role in evolution, reflecting functional and developmental relationships among traits. We examine context-dependent genetic effects at pleiotropic loci associated with normal variation in multiple metabolic syndrome (MetS) components (obesity, dyslipidemia, and diabetes-related traits). MetS prevalence is increasing in Western societies and, while environmental in origin, presents substantial variation in individual response. We identify 23 pleiotropic MetS quantitative trait loci (QTL) in an F₁₆ advanced intercross between the LG/J and SM/J inbred mouse strains (Wustl:LG,SM-G16; n = 1002). Half of each family was fed a high-fat diet and half fed a low-fat diet; and additive, dominance, and parent-of-origin imprinting genotypic effects were examined in animals partitioned into sex, diet, and sex-by-diet cohorts. We examine the context-dependency of the underlying additive, dominance, and imprinting genetic effects of the traits associated with these pleiotropic QTL. Further, we examine sequence polymorphisms (SNPs) between LG/J and SM/J as well as differential expression of positional candidate genes in these regions. We show that genetic associations are different in different sex, diet, and sex-by-diet settings. We also show that over- or underdominance and ecological cross-over interactions for single phenotypes may not be common, however multidimensional synthetic phenotypes at loci with pleiotropic effects can produce situations that favor the maintenance of genetic variation in populations. Our findings have important implications for evolution and the notion of personalized medicine.

We look at gene-by-diet and gene-by-sex interactions underlying natural variation in multiple metabolic traits mapping to the same regions of the genome in a mouse model. We find that the underlying genetic architecture of these traits is different in different sex and diet contexts. We further use expression data and whole-genome polymorphism data to identify compelling candidates for experimental follow-up. We use these results to examine theoretical evolutionary predictions about how variation in populations can be maintained. There has been much discussion of late on how to use evolutionary theory to inform medical genomics. Mouse models may be especially appropriate for bridging the divide between evolutionary and biomedical research, because they allow the study of the effects of natural alleles on normal variation and because human-mouse homology is well defined. Our study is unique in examining quantitative trait loci from both evolutionary and biomedical perspectives, and we highlight the complex connections of the traits comprising the metabolic syndrome and the evolutionary implications of their underlying genetic architecture. This is important for understanding disease etiology and is relevant to personalized medicine.

Gene-gene and gene-environment interactions defining lipid-related traits

PURPOSE OF REVIEW

Steps towards reducing chronic disease progression are continuously being taken through the form of genomic research. Studies over the last year have highlighted more and more polymorphisms, pathways and interactions responsible for metabolic disorders such as cardiovascular disease, obesity and dyslipidemia.

RECENT FINDINGS

Many of these chronic illnesses can be partially blamed by altered lipid metabolism, combined with individual genetic components. Critical evaluation and comparison of these recent studies is essential in order to comprehend the results, conclusions and future prospects in the field of genomics as a whole. Recent literature elucidates significant gene--diet and gene--environment interactions resulting in altered lipid metabolism, inflammation and other metabolic imbalances leading to cardiovascular disease and obesity.

SUMMARY

Epigenetic and epistatic interactions are now becoming more significantly associated with such disorders, as genomic research digs deeper into the complex nature of genetic individuality and heritability. The vast array of data collected from genome-wide association studies must now be empowered and explored through more complex interaction studies, using standardized methods and larger sample sizes. In doing so the etiology of chronic disease progression will be further understood.