Epistasis among genes is a universal phenomenon in obesity:

Gene Interactions in Human Disease Studies-Evidence Is Mounting

Despite monumental advances in molecular technology to generate genome sequence data at scale, there is still a considerable proportion of heritability in most complex diseases that remains unexplained. Because many of the discoveries have been single-nucleotide variants with small to moderate effects on disease, the functional implication of many of the variants is still unknown and, thus, we have limited new drug targets and therapeutics. We, and many others, posit that one primary factor that has limited our ability to identify novel drug targets from genome-wide association studies may be due to gene interactions (epistasis), gene-environment interactions, network/pathway effects, or multiomic relationships. We propose that many of these complex models explain much of the underlying genetic architecture of complex disease. In this review, we discuss the evidence from multiple research avenues, ranging from pairs of alleles to multiomic integration studies and pharmacogenomics, that supports the need for further investigation of gene interactions (or epistasis) in genetic and genomic studies of human disease. Our goal is to catalog the mounting evidence for epistasis in genetic studies and the connections between genetic interactions and human health and disease that could enable precision medicine of the future.

Genomic Insights Into the Multiple Factors Controlling Abdominal Fat Deposition in a Chicken Model

Genetic selection for an increased growth rate in meat-type chickens has been accompanied by excessive fat accumulation particularly in abdominal cavity. These progressed to indirect and often unhealthy effects on meat quality properties and increased feed cost. Advances in genomics technology over recent years have led to the surprising discoveries that the genome is more complex than previously thought. Studies have identified multiple-genetic factors associated with abdominal fat deposition. Meanwhile, the obesity epidemic has focused attention on adipose tissue and the development of adipocytes. The aim of this review is to summarize the current understanding of genetic/epigenetic factors associated with abdominal fat deposition, or as it relates to the proliferation and differentiation of preadipocytes in chicken. The results discussed here have been identified by different genomic approaches, such as QTL-based studies, the candidate gene approach, epistatic interaction, copy number variation, single-nucleotide polymorphism screening, selection signature analysis, genome-wide association studies, RNA sequencing, and bisulfite sequencing. The studies mentioned in this review have described multiple-genetic factors involved in an abdominal fat deposition. Therefore, it is inevitable to further study the multiple-genetic factors in-depth to develop novel molecular markers or potential targets, which will provide promising applications for reducing abdominal fat deposition in meat-type chicken.

Lack of association between genetic polymorphism of FTO, AKT1 and AKTIP in childhood overweight and obesity

OBJECTIVE

Obesity is a chronic disease caused by both environmental and genetic factors. Epidemiological studies have documented that increased energy intake and sedentary lifestyle, as well as a genetic contribution, are forces behind the obesity epidemic. Knowledge about the interaction between genetic and environmental components can facilitate the choice of the most effective and specific measures for the prevention of obesity. The aim of this study was to assess the association between the FTO, AKT1, and AKTIP genes and childhood obesity and insulin resistance.

METHODS

This was a case-control study in which SNPs in the FTO (rs99396096), AKT1, and AKTIP genes were genotyped in groups of controls and obese/overweight children. The study included 195 obese/overweight children and 153 control subjects.

RESULTS

As expected, the obese/overweight group subjects had higher body mass index, higher fasting glucose, HOMA-IR index, total cholesterol, low-density lipoprotein, and triglycerides. However, no significant differences were observed in genes polymorphisms genotype or allele frequencies.

CONCLUSION

The present results suggest that AKT1, FTO, and AKTIP polymorphisms were not associated with obesity/overweight in Brazilians children. Future studies on the genetics of obesity in Brazilian children and their environment interactions are needed.

Obesity and genomics: role of technology in unraveling the complex genetic architecture of obesity

Obesity is a complex and multifactorial disease that occurs as a result of the interaction between "obesogenic" environmental factors and genetic components. Although the genetic component of obesity is clear from the heritability studies, the genetic basis remains largely elusive. Successes have been achieved in identifying the causal genes for monogenic obesity using animal models and linkage studies, but these approaches are not fruitful for polygenic obesity. The developments of genome-wide association approach have brought breakthrough discovery of genetic variants for polygenic obesity where tens of new susceptibility loci were identified. However, the common SNPs only accounted for a proportion of heritability. The arrival of NGS technologies and completion of 1000 Genomes Project have brought other new methods to dissect the genetic architecture of obesity, for example, the use of exome genotyping arrays and deep sequencing of candidate loci identified from GWAS to study rare variants. In this review, we summarize and discuss the developments of these genetic approaches in human obesity.

The Human Obesity Gene Map: The 2004 Update

This paper presents the eleventh update of the human obesity gene map, which incorporates published results up to the end of October 2004. Evidence from single-gene mutation obesity cases, Mendelian disorders exhibiting obesity as a clinical feature, transgenic and knockout murine models relevant to obesity, quantitative trait loci (QTLs) from animal cross-breeding experiments, association studies with candidate genes, and linkages from genome scans is reviewed. As of October 2004, 173 human obesity cases due to single-gene mutations in 10 different genes have been reported, and 49 loci related to Mendelian syndromes relevant to human obesity have been mapped to a genomic region, and causal genes or strong candidates have been identified for most of these syndromes. There are 166 genes which, when mutated or expressed as transgenes in the mouse, result in phenotypes that affect body weight and adiposity. The number of QTLs reported from animal models currently reaches 221. The number of human obesity QTLs derived from genome scans continues to grow, and we have now 204 QTLs for obesity-related phenotypes from 50 genome-wide scans. A total of 38 genomic regions harbor QTLs replicated among two to four studies. The number of studies reporting associations between DNA sequence variation in specific genes and obesity phenotypes has also increased considerably with 358 findings of positive associations with 113 candidate genes. Among them, 18 genes are supported by at least five positive studies. The obesity gene map shows putative loci on all chromosomes except Y. Overall, >600 genes, markers, and chromosomal regions have been associated or linked with human obesity phenotypes. The electronic version of the map with links to useful publications and genomic and other relevant sites can be found at http://obesitygene.pbrc.edu.

Contributions of renin-angiotensin system-related gene interactions to obesity in a Chinese population

BACKGROUND

Gene-gene interactions may be partly responsible for complex traits such as obesity. Increasing evidence suggests that the renin-angiotensin system (RAS) contributes to the etiology of obesity. How the epistasis of genes in the RAS contributes to obesity is still under research. We aim to evaluate the contribution of RAS-related gene interactions to a predisposition of obesity in a Chinese population.

METHODOLOGY AND PRINCIPAL FINDINGS

We selected six single nucleotide polymorphisms (SNPs) located in angiotensin (AGT), angiotensin converting enzyme (ACE), angiotensin type 1 receptor (AGTR1), MAS1, nitric oxide synthase 3 (NOS3) and the bradykinin B2 receptor gene (BDKRB2), and genotyped them in 324 unrelated individuals with obesity (BMI ≥ 28 kg/m(2)) and 373 non-obese controls (BMI 18.5 to <24 kg/m(2)) from a large scale population-based cohort. We analyzed gene-gene interactions among 6 polymorphic loci using the Generalized Multifactor Dimensionality Reduction (GMDR) method, which has been shown to be effective for detecting gene-gene interactions in case-control studies with relatively small samples. Then we used logistic regression models to confirm the best combination of loci identified in the GMDR. It showed a significant gene-gene interaction between the rs220721 polymorphism in the MAS1 gene and the rs1799722 polymorphism in the gene BDKB2R. The best two-locus combination scored 9 for cross-validation consistency and 9 for sign test (p = 0.0107). This interaction showed the maximum consistency and minimum prediction error among all gene-gene interaction models evaluated. Moreover, the combination of the MAS1 rs220721 and the BDKRB2 rs1799722 was associated with a significantly increased risk of obesity (OR 1.82, CI 95%: 1.15-2.88, p = 0.0103).

CONCLUSIONS AND SIGNIFICANCE

These results suggest that the SNPs from the RAS-related genes may contribute to the risk of obesity in an interactive manner in a Chinese population. The gene-gene interaction may serve as a novel area for obesity research.

Epistatic effect between ACACA and FABP2 gene on abdominal fat traits in broilers

Epistasis is generally defined as the interaction between two or more genes or their mRNA or protein products to influence a single trait. Experimental evidence suggested that epistasis could be important in the determination of the genetic architecture of complex traits in domestic animals. Acetyl-coenzyme A carboxylase alpha (ACACA) and fatty acid binding protein 2 (FABP2) are both key factors of lipogenesis and transport. They may play a crucial role in the weight variability of abdominal adipose tissue in the growing chicken. In this study, the polymorphisms of c.2292G>A in ACACA and c.-561A>C in FABP2 were detected among individuals from two broiler lines which were divergently selected for abdominal fat content. Epistasis between the two SNPs on abdominal fat weight (AFW) and abdominal fat percentage (AFP) was analyzed. The additive x additive epistatic components between these two SNPs were found significant or suggestively significant on both AFW and AFP in lean lines of the 9th and 10th generation; whereas, it was not significantly associated with either AFW or AFP in fat lines. At the same time, there were not any other significant epistatic components found in both generations or in both lines. Significant epistatic effects between these two SNPs found only in the lean lines could partly be due to the fact that the abdominal fat traits in these two experimental lines have been greatly modified by strong artificial selection. The results suggested that the epistasis mode may be different between the lean and fat chicken lines. Our results could be helpful in further understanding the genetic interaction between candidate genes contributing to phenotypic variation of abdominal fat content in broilers.

Using biological knowledge to uncover the mystery in the search for epistasis in genome-wide association studies

The search for the missing heritability in genome-wide association studies (GWAS) has become an important focus for the human genetics community. One suspected location of these genetic effects is in gene-gene interactions, or epistasis. The computational burden of exploring gene-gene interactions in the wealth of data generated in GWAS, along with small to moderate sample sizes, have led to epistasis being an afterthought, rather than a primary focus of GWAS analyses. In this review, I discuss some potential approaches to filter a GWAS dataset to a smaller, more manageable dataset where searching for epistasis is considerably more feasible. I describe a number of alternative approaches, but primarily focus on the use of prior biological knowledge from databases in the public domain to guide the search for epistasis. The manner in which prior knowledge is incorporated into a GWA study can be many and these data can be extracted from a variety of database sources. I discuss a number of these approaches and propose that a comprehensive approach will likely be most fruitful for searching for epistasis in large-scale genomic studies of the current state-of-the-art and into the future.

Genetic epistasis analysis of 10 peroxisome proliferator-activated receptor γ-correlated genes in broiler lines divergently selected for abdominal fat content

Chicken peroxisome proliferator-activated receptor γ (PPARγ), which is highly expressed in adipose tissues, is a key factor in fat accumulation in the abdominal fat pad. In this study, association and pairwise epistasis analyses were performed for all the polymorphisms detected in PPARγ and for 9 genes from PPARγ-correlated lipid metabolic pathways for abdominal fat weight (AFW) in 10th-generation populations of Northeast Agricultural University broiler lines divergently selected for abdominal fat content. Epistatic networks were then reconstructed with the identified epistatic effects. Single-marker association analyses showed that 5 of the 20 screened polymorphisms were significantly associated with AFW (P < 0.05), and CCAAT/enhancer-binding protein α (C/EBPα) c.552G>A was 1 of the 5 significant loci. Pairwise interaction analyses showed that 15 pairs of polymorphisms reached a significance level of P < 2.64 × 10(-4) (adjusted by Bonferroni correction) in the lean line, 41 pairs reached significance in the fat line, and 7 pairs reached significance in both lines. Interestingly, many other loci interacted with C/EBPα c.552G>A in both lines. In epistatic network analyses, C/EBPα c.552G>A seemed to behave as a hub for the epistatic network in both lines. All these results revealed that the genetic architecture of C/EBPα c.552G>A for AFW seemed to be an apparent individual main-effect QTL but that it could be dissected into a genetic epistatic network. Our results suggest that C/EBPα c.552G>A might be the most important locus contributing to phenotypic variation in AFW among all the polymorphisms detected in this study.

Epistasis contributes to the genetic buffering of plasma HDL cholesterol in mice

Stressful environmental factors, such as a high-fat diet, can induce responses in the expression of genes that act to maintain physiological homeostasis. We observed variation in plasma concentrations of high-density lipoprotein (HDL) cholesterol across inbred mouse strains in response to high dietary fat intake. Several strains, including C57BL/6J, have stable levels of plasma HDL independent of diet, whereas other strains, including DBA2/J, show marked changes in plasma HDL. To explore this phenomenon further, we used publicly available data from a C57BL/6J × DBA/2J intercross to identify genetic factors that associate with HDL under high-fat diet conditions. Our analysis identified an epistatic interaction that plays a role in the buffering of HDL levels in C57BL/6J mice, and we have identified Arl4d as a candidate gene that mediates this effect. Structural modeling further elucidates the interaction of genetic factors that contribute to the robustness of HDL in response to high-fat diet in the C57BL/6J strain.

The Thrsp null mouse (Thrsp(tm1cnm)) and diet-induced obesity

We created a Thrsp (Spot 14 or S14) null mouse (Thrsp(tm1cnm)) to study the role of Thrsp in de novo lipid synthesis. The Thrsp null mouse exhibits marked deficiencies in de novo lipogenesis in the lactating mammary gland. We now report the Thrsp gene deletion affects body weight and glucose tolerance associated with increased insulin sensitivity. By post-natal day 150 the rate of first generation C57BL/6J backcross Thrsp null mouse weight gain slowed compared to wild type animals. This was due to changes in body fat mass. We studied mice backcrossed for 5 and 11 generations. The weight difference between the null and wild type adult mice diminished with progressive backcross generations. In conclusion the Thrsp gene is involved in the regulation of diet-induced obesity and deletion of Thrsp leads to an improvement in age associated glucose tolerance.

TBC1D1 is a candidate for a severe obesity gene and evidence for a gene/gene interaction in obesity predisposition

The molecular etiology of obesity predisposition is largely unknown. Here, we present evidence that genetic variation in TBC1D1 confers risk for severe obesity in females. We identified a coding variant (R125W) in TBC1D1 that segregated with the disease in 4p15-14-linked obesity pedigrees. In cases derived from pedigrees with the strongest linkage evidence, the variant was significantly associated with obesity (P=0.000007) and chromosomes carrying R125W accounted for the majority of the evidence that originally linked 4p15-14 with the disease. In addition, by selecting families that segregated R125W with obesity, we were able to generate highly significant linkage evidence for an obesity predisposition locus at 4q34-35. This result provides additional and confirming evidence that R125W affects obesity susceptibility, delimits the location of an obesity gene at 4q34-35 and identifies a gene/gene interaction that influences the risk for obesity predisposition. Finally, although the function of TBC1D1 is unknown, the protein is structurally similar to a known regulator of insulin-mediated Glut4 translocation.

Bayesian analyses of multiple epistatic QTL models for body weight and body composition in mice

To comprehensively investigate the genetic architecture of growth and obesity, we performed Bayesian analyses of multiple epistatic quantitative trait locus (QTL) models for body weights at five ages (12 days, 3, 6, 9 and 12 weeks) and body composition traits (weights of two fat pads and five organs) in mice produced from a cross of the F1 between M16i (selected for rapid growth rate) and CAST/Ei (wild-derived strain of small and lean mice) back to M16i. Bayesian model selection revealed a temporally regulated network of multiple QTL for body weight, involving both strong main effects and epistatic effects. No QTL had strong support for both early and late growth, although overlapping combinations of main and epistatic effects were observed at adjacent ages. Most main effects and epistatic interactions had an opposite effect on early and late growth. The contribution of epistasis was more pronounced for body weights at older ages. Body composition traits were also influenced by an interacting network of multiple QTLs. Several main and epistatic effects were shared by the body composition and body weight traits, suggesting that pleiotropy plays an important role in growth and obesity.

Interaction between obesity-susceptibility loci in chromosome regions 2p25-p24 and 13q13-q21

One of the chief complexities of genetic influences on human obesity appears to be gene-gene interactions. Here, we employed model-free approaches to look for gene-gene interaction effects in human obesity using genome scan data from 260 European American families. We found consistent evidence for statistical interaction between 2p25-p24 (18-38 cM) and 13q13-q21 (26-47 cM). For discrete traits, the positive correlations were significant at P<0.0001 (P</=0.0023 after correction for multiple tests) in both IBD-based and NPL-based analyses for BMI>/=40 kg/m(2). Other analytic approaches gave consistent, supportive results. For quantitative traits, interaction effects were significant for BMI (P=0.0012), percent fat (P=0.0265) and waist circumference (P=0.0023) in a Haseman-Elston regression model, and for BMI (P=0.0043) in variance component analysis. Our findings suggest that obesity-susceptibility loci in chromosome regions 2p25-p24 and 13q13-21 may interact to influence extreme human obesity. The identification of gene-gene interactions may prove crucial to understanding the contributions of genes, which, by themselves, have relatively small effects on obesity susceptibility and resistance.

A novel mouse Chromosome 2 congenic strain with obesity phenotypes

Linkage studies have identified many chromosomal regions containing obesity genes in mice. However, only a few of these quantitative trait loci (QTLs) have been used to guide the production of congenic mouse strains that retain obesity phenotypes. We seek to identify chromosomal regions containing obesity genes in the BSB model of spontaneous obesity because the BSB model is a multigenic obesity model. Previous studies identified QTLs on Chromosomes (Chrs) 2, 6, 7,12, and 15. BSB mice are made by backcross of lean C57BL/6J x Mus spretus. F(1)s were backcrossed to C57BL/6J mice to produce BSB progeny. We have constructed a new BSB cross and produced congenic mice with obesity phenotypes by marker-directed selection called B6.S- D2Mit194- D2Mit311. We found a highly significant QTL for percentage body lipid on Chr 2 just proximal to the Agouti locus. Chr 2 congenics were constructed to determine whether the main effects would be detectable. We observed highly significant linkage of the Chr 2 congenic containing Agouti and containing markers distal to D2Mit311 and proximal to D2Mit194. Thus, this congenic contains approximately 14.6 cM or 30 Mb (about 1.1% of the spretus mouse genome) and several hundred genes. The obesity phenotype of the QTL is retained in the congenic. The congenic can now be used to model the genetic and physiological basis for a relatively simple, perhaps monogenic, obesity.

Epistatic interaction between two nonstructural loci on chromosomes 7 and 3 influences hepatic lipase activity in BSB mice

BSB mice exhibit a wide range of obesity despite being produced by a backcross of lean C57BL/6J (B) x lean Mus spretus (SPRET/Pt) F1 animals x B. Previous linkage studies identified a quantitative trait locus (QTL) on mouse chromosome 7 with coincident peaks for hepatic lipase activity, obesity, and plasma cholesterol. However, these mice were not analyzed for gene x gene epistasis. Hepatic lipase activity is correlated with obesity and plasma cholesterol levels. In this study, we identified QTLs for plasma hepatic lipase activity with three statistical mapping methods: maximum likelihood interval mapping, Bayesian nonepistatic mapping, and Bayesian epistatic mapping. Bayesian epistatic mapping detected not only the QTL on chromosome 7 but also an additional QTL on chromosome 3, which has a weak main effect but a strong interaction with chromosome 7. SPRET/Pt alleles of the QTL on each chromosome promote hepatic lipase activity. The proportion of phenotypic variance explained by the epistatic effect is higher than that explained by the main effect of the QTL on chromosome 7.