Mouse models and the interpretation of human GWAS in type 2 diabetes and obesity

Within the last 3 years, genome-wide association studies (GWAS) have had unprecedented success in identifying loci that are involved in common diseases. For example, more than 35 susceptibility loci have been identified for type 2 diabetes and 32 for obesity thus far. However, the causal gene and variant at a specific linkage disequilibrium block is often unclear. Using a combination of different mouse alleles, we can greatly facilitate the understanding of which candidate gene at a particular disease locus is associated with the disease in humans, and also provide functional analysis of variants through an allelic series, including analysis of hypomorph and hypermorph point mutations, and knockout and overexpression alleles. The phenotyping of these alleles for specific traits of interest, in combination with the functional analysis of the genetic variants, may reveal the molecular and cellular mechanism of action of these disease variants, and ultimately lead to the identification of novel therapeutic strategies for common human diseases. In this Commentary, we discuss the progress of GWAS in identifying common disease loci for metabolic disease, and the use of the mouse as a model to confirm candidate genes and provide mechanistic insights.     

Association of type 2 diabetes susceptibility loci with one-year weight loss in the look AHEAD clinical trial

The importance of lifestyle intervention for the prevention and treatment of type 2 diabetes (T2D) has been underscored by the limited benefit of pharmacologic therapies. We sought to determine whether genetic variants that contribute to T2D risk modify the response of weight and waist circumference to an intensive lifestyle intervention (ILI) in patients with obesity and T2D. Look AHEAD (Action for Health in Diabetes) is a randomized clinical trial comparing an ILI with a control condition on the risk of cardiovascular disease in overweight adults with T2D. We analyzed 28 single-nucleotide polymorphisms (SNPs) at/near 17 T2D-susceptibility genes in 3,903 consented participants. We genetically characterized the cohort by assessing whether T2D-susceptibility loci were overrepresented compared with a nondiabetic community-based cohort (N = 1,016). We evaluated the association of individual variants and a composite genetic risk score (GRS) with anthropometric traits at baseline and after 1-year of intervention. Look AHEAD subjects carried more T2D-susceptibility alleles than the control population. At baseline, TCF7L2 risk alleles and the highest GRS were associated with lower BMI and waist circumference. Nominally significant genotype-by-intervention interactions were detected for 1-year change in waist circumference with JAZF1, MTNR1B, and IRS1, and BMI with JAZF1. Highest GRS was associated with a greater reduction in waist circumference at year 1, although the variance in change attributable to the GRS was small. This study shows that the genetic burden associated with T2D risk does not undermine the effect of lifestyle intervention and suggests the existence of additional genomic regions, distinct from the T2D-susceptibility loci, which may enhance or mitigate weight loss.     

Susceptibility gene search for nephropathy and related traits in Mexican–Americans

The rising global epidemic of diabetic nephropathy (DN) will likely lead to increase in the prevalence of cardiovascular morbidity and mortality posing a serious burden for public health care. Despite greater understanding of the etiology of diabetes and the development of novel treatment strategies to control blood glucose levels, the prevalence and incidence rate of DN is increasing especially in minority populations including Mexican–Americans. Mexican–Americans with type 2 diabetes (T2DM) are three times more likely to develop microalbuminuria, and four times more likely to develop clinical proteinuria compared to non-Hispanic whites. Furthermore, Mexican–Americans have a sixfold increased risk of developing renal failure secondary to T2DM compared to Caucasians. Prevention and better treatment of DN should be a high priority for both health-care organizations and society at large. Pathogenesis of DN is multi-factorial. Familial clustering of DN-related traits in MAs show that DN and related traits are heritable and that genes play a susceptibility role. While, there has been some progress in identifying genes which when mutated influence an individual’s risk, major gene(s) responsible for DN are yet to be identified. Knowledge of the genetic causes of DN is essential for elucidation of its mechanisms, and for adequate classification, prognosis, and treatment. Self-identification and collaboration among researchers with suitable genomic and clinical data for meta-analyses in Mexican–Americans is critical for progress in replicating/identifying DN risk genes in this population. This paper reviews the approaches and recent efforts made to identify genetic variants contributing to risk for DN and related phenotypes in the Mexican–American population.     

Type 2 diabetes: new genes, new understanding

Over the past two years, there has been a spectacular change in the capacity to identify common genetic variants that contribute to predisposition to complex multifactorial phenotypes such as type 2 diabetes (T2D). The principal advance has been the ability to undertake surveys of genome-wide association in large study samples. Through these and related efforts, approximately 20 common variants are now robustly implicated in T2D susceptibility. Current developments, for example in high-throughput resequencing, should help to provide a more comprehensive view of T2D susceptibility in the near future. Although additional investigation is needed to define the causal variants within these novel T2D-susceptibility regions, to understand disease mechanisms and to effect clinical translation, these findings are already highlighting the predominant contribution of defects in pancreatic beta-cell function to the development of T2D.     

Repair of injured articular and growth plate cartilage using mesenchymal stem cells and chondrogenic gene therapy

Injuries to the articular cartilage and growth plate are significant clinical problems due to their limited ability to regenerate themselves. Despite progress in orthopedic surgery and some success in development of chondrocyte transplantation treatment and in early tissue-engineering work, cartilage regeneration using a biological approach still remains a great challenge. In the last 15 years, researchers have made significant advances and tremendous progress in exploring the potentials of mesenchymal stem cells (MSCs) in cartilage repair. These include (a) identifying readily available sources of and devising appropriate techniques for isolation and culture expansion of MSCs that have good chondrogenic differentiation capability, (b) discovering appropriate growth factors (such as TGF-beta, IGF-I, BMPs, and FGF-2) that promote MSC chondrogenic differentiation, (c) identifying or engineering biological or artificial matrix scaffolds as carriers for MSCs and growth factors for their transplantation and defect filling. In addition, representing another new perspective for cartilage repair is the successful demonstration of gene therapy with chondrogenic growth factors or inflammatory inhibitors (either individually or in combination), either directly to the cartilage tissue or mediated through transducing and transplanting cultured chondrocytes, MSCs or other mesenchymal cells. However, despite these rapid pre-clinical advances and some success in engineering cartilage-like tissue and in repairing articular and growth plate cartilage, challenges of their clinical translation remain. To achieve clinical effectiveness, safety, and practicality of using MSCs for cartilage repair, one critical investigation will be to examine the optimal combination of MSC sources, growth factor cocktails, and supporting carrier matrixes. As more insights are acquired into the critical factors regulating MSC migration, proliferation and chondrogenic differentiation both ex vivo and in vivo, it will be possible clinically to orchestrate desirable repair of injured articular and growth plate cartilage, either by transplanting ex vivo expanded MSCs or MSCs with genetic modifications, or by mobilising endogenous MSCs from adjacent source tissues such as synovium, bone marrow, or trabecular bone.     

Progress and promise in understanding the genetic basis of common diseases

Susceptibility to common human diseases is influenced by both genetic and environmental factors. The explosive growth of genetic data, and the knowledge that it is generating, are transforming our biological understanding of these diseases. In this review, we describe the technological and analytical advances that have enabled genome-wide association studies to be successful in identifying a large number of genetic variants robustly associated with common disease. We examine the biological insights that these genetic associations are beginning to produce, from functional mechanisms involving individual genes to biological pathways linking associated genes, and the identification of functional annotations, some of which are cell-type-specific, enriched in disease associations. Although most efforts have focused on identifying and interpreting genetic variants that are irrefutably associated with disease, it is increasingly clear that—even at large sample sizes—these represent only the tip of the iceberg of genetic signal, motivating polygenic analyses that consider the effects of genetic variants throughout the genome, including modest effects that are not individually statistically significant. As data from an increasingly large number of diseases and traits are analysed, pleiotropic effects (defined as genetic loci affecting multiple phenotypes) can help integrate our biological understanding. Looking forward, the next generation of population-scale data resources, linking genomic information with health outcomes, will lead to another step-change in our ability to understand, and treat, common diseases.     

Gender differences in the relationship of ENPP1/PC-1 variants to obesity in a Turkish population

The ectoenzyme ENPP1 (also termed membrane glycoprotein PC-1 or ENPP1/PC-1) is an inhibitor of insulin-induced activation of the insulin receptor. There is evidence from previous studies that coding variants of ENPP1/PC-1 (K121Q) are associated with type 2 diabetes (T2D) and obesity. Studies in the general Turkish population have demonstrated: unique plasma lipid characteristics, a high prevalence of cardiovascular risk factors, and an increased prevalence of obesity and T2D. We investigated, therefore, the association of ENPP1/PC-1 variants with obesity and T2D in Turkish individuals. The TaqMan allelic discrimination assay was used for genotyping the relationship of ENPP1/PC-1 variants to obesity and T2D in a genetic association study of 1,553 genotyped, randomly selected subjects from the Turkish Heart Study. The K121Q (rs1044498) variant and other previously reported variants (rs997509, rs1799774, rs1044548, rs11964389, rs7754561) were analyzed. In this cohort, the minor allele frequency (MAF) of the K121Q variant was associated with obesity in male, but not in female subjects (male, odds ratio 1.64, 95% confidence interval 1.004-2.698, P = 0.048; female, odds ratio 1.003, 95% confidence interval 0.684-1.471, P = ns). In addition, the previously reported ENPP1/PC-1 "risk haplotype" (Q (rs1044498), delT (rs1799774), and G (rs7754561) alleles) was found to be associated with obesity in male, but not in female, subjects (P = 0.035). In contrast, there was no association of either the K121Q variant or the ENPP1/PC-1 haplotype with T2D. We find evidence that variants of ENPP1/PC-1 are associated with obesity in the male Turkish population; thus, these variants may contribute to the development of the obesity in these individuals.     

Progress in the genetics of common obesity: size matters

PURPOSE OF REVIEW: Over the past two decades serious efforts has been invested in the search for genes that predispose to common obesity, but progress has been slow and success limited. Genome-wide association, however, has revived optimism. Here we review recent advances in the field of obesity genetics and discuss the most important findings of candidate gene, genome-wide linkage studies and genome-wide association studies. We conclude by speculating about the way forward in the near future. RECENT FINDINGS: Although large-scale candidate gene studies have placed MC4R more firmly on the human obesity map, the major breakthrough in obesity genetics was the discovery of FTO through genome-wide association. Variants located in the first intron of FTO were unequivocally associated with a 1.67-fold increased risk for obesity and a 0.40-0.66 kg/m2 increase in body mass index. SUMMARY: Genome-wide association promises to enhance greatly our understanding of the genetic basis of common obesity, although candidate gene studies will remain a valuable approach because they allow more detailed analyses of biologically relevant candidates. A key factor contributing to continued success lies in large-scale data integration through international collaboration, which will provide the sample sizes required to identify genetic association with conclusive evidence.     

Viral triggers of multiple sclerosis

Genetic and environmental factors jointly determine the susceptibility to develop Multiple Sclerosis (MS). Collaborative efforts during the past years achieved substantial progress in defining the genetic architecture, underlying susceptibility to MS. Similar to other autoimmune diseases, HLA-DR and HLA-DQ alleles within the HLA class II region on chromosome 6p21 are the highest-risk-conferring genes. Less-robust susceptibility effects have been identified for MHC class I alleles and for non-MHC regions. The role of environmental risk factors and their interaction with genetic susceptibility alleles are much less well defined, despite the fact that infections have long been associated with MS development. Current data suggest that infectious triggers are most likely ubiquitous, i.e., highly prevalent in the general population, and that they require a permissive genetic trait which predisposes for MS development. In this review article, we illustrate mechanisms of infection-induced immunopathologies in experimental animal models of autoimmune CNS inflammation, discuss challenges for the translation of these experimental data into human immunology research, and provide future perspectives on how novel model systems could be utilized to better define the role of viral pathogens in MS.     

Past, present and future strategies to study the genetics of body weight regulation.

Genetic advances have made remarkable progress towards our understanding of body weight regulation. Much of our current knowledge has come from the cloning and characterisation of the genes responsible for obesity syndromes in the mouse, and the identification of homologous mutations causing rare forms of obesity in humans. Gene targeting experiments in mice have been instrumental in confirming the importance of many genes in the aetiology of obesity, and the existence of a fundamental physiological pathway that controls energy balance is becoming clear. The genetic determinants that underlie common forms of human obesity are largely polygenic, with most genes producing small effects. Thus, elucidating the many genetic determinants of obesity is a current challenge for modern geneticists. Despite the inherent difficulties, progress has been made through linkage/association studies and a genetic map of quantitative trait loci for human obesity is beginning to emerge. Obesity research is now very much in a transition period. Not so long ago, access to high throughput screening, as well as microarray and proteomic techniques, was prohibitively expensive and available only to the few. In recent years, these technologies have become more accessible to the larger scientific community and, in this paper, we will discuss how such technological advances are likely to drive the next wave of progress in obesity research. For example, large-scale mutagenesis screens in rodents coupled with high throughput screening are likely to emerge as important technologies for identifying genes previously unexpected to be involved in body weight regulation. Furthermore, applications of microarray and proteomic techniques will further refine our understanding of currently known peptides as well as identify novel pathways and molecules which are involved in energy homeostasis.     

Polycystic ovary syndrome is linked with the fat mass obesity (FTO) gene variants rs17817449 and rs1421085 in western Saudi Arabia

Polycystic ovary syndrome (PCOS) is characterised by infertility, obesity, insulin resistance and clinical and/or biochemical signs of hyperandrogenism. Obesity is known to be correlated with PCOS causing ovulatory dysfunction and hormone imbalances. Moreover, fat mass and the obesity gene (FTO) were linked with obesity and PCOS. Therefore, it is of interest to determine the genotype and allele frequency for three FTO variants - rs17817449 (G/T), rs1421085 (C/T) and rs8050136 (A/C) -in western Saudi population. 95 PCOS patients and 94 controls were recruited for this study. The genetic variants were assayed using real-time polymerase chain reaction using TaqMan genotyping assays. The chi-squared test was applied to investigate the difference between single nucleotide polymorphisms on PCOS and control subjects, and binary logistic regression was used to determine the association of FTO variants with PCOS symptoms. Variants rs17817449 and rs1421085 were significantly linked with PCOS susceptibility in the study population. Rs17817449 and rs8050136 were significantly associated with hair loss in the PCOS group. Furthermore, rs1421085 and rs8050136 were associated with a high body mass index (BMI>30 kg/m2). Risk alleles in our population associated with hair loss and elevated BMI in women with PCOS were homozygous C for rs8050136. This data will help in defining the genetic predisposition of PCOS among women in western Saudi Arabia.     

Admixture and the organization of genetic diversity in a butterfly species complex revealed through common and rare genetic variants

Detailed information about the geographic distribution of genetic and genomic variation is necessary to better understand the organization and structure of biological diversity. In particular, spatial isolation within species and hybridization between them can blur species boundaries and create evolutionary relationships that are inconsistent with a strictly bifurcating tree model. Here, we analyse genome‐wide DNA sequence and genetic ancestry variation in Lycaeides butterflies to quantify the effects of admixture and spatial isolation on how biological diversity is organized in this group. We document geographically widespread and pervasive historical admixture, with more restricted recent hybridization. This includes evidence supporting previously known and unknown instances of admixture. The genome composition of admixed individuals varies much more among than within populations, and tree‐ and genetic ancestry‐based analyses indicate that multiple distinct admixed lineages or populations exist. We find that most genetic variants in Lycaeides are rare (minor allele frequency <0.5%). Because the spatial and taxonomic distributions of alleles reflect demographic and selective processes since mutation, rare alleles, which are presumably younger than common alleles, were spatially and taxonomically restricted compared with common variants. Thus, we show patterns of genetic variation in this group are multifaceted, and we argue that this complexity challenges simplistic notions concerning the organization of biological diversity into discrete, easily delineated and hierarchically structured entities.     

Biomedical Data Commons (BMDC) prioritizes B-lymphocyte non-coding genetic variants in Type 1 Diabetes

The repurposing of biomedical data is inhibited by its fragmented and multi-formatted nature that requires redundant investment of time and resources by data scientists. This is particularly true for Type 1 Diabetes (T1D), one of the most intensely studied common childhood diseases. Intense investigation of the contribution of pancreatic β-islet and T-lymphocytes in T1D has been made. However, genetic contributions from B-lymphocytes, which are known to play a role in a subset of T1D patients, remain relatively understudied. We have addressed this issue through the creation of Biomedical Data Commons (BMDC), a knowledge graph that integrates data from multiple sources into a single queryable format. This increases the speed of analysis by multiple orders of magnitude. We develop a pipeline using B-lymphocyte multi-dimensional epigenome and connectome data and deploy BMDC to assess genetic variants in the context of Type 1 Diabetes (T1D). Pipeline-identified variants are primarily common, non-coding, poorly conserved, and are of unknown clinical significance. While variants and their chromatin connectivity are cell-type specific, they are associated with well-studied disease genes in T-lymphocytes. Candidates include established variants in the HLA-DQB1 and HLA-DRB1 and IL2RA loci that have previously been demonstrated to protect against T1D in humans and mice providing validation for this method. Others are included in the well-established T1D GRS2 genetic risk scoring method. More intriguingly, other prioritized variants are completely novel and form the basis for future mechanistic and clinical validation studies The BMDC community-based platform can be expanded and repurposed to increase the accessibility, reproducibility, and productivity of biomedical information for diverse applications including the prioritization of cell type-specific disease alleles from complex phenotypes.     

Genome-Wide Association Studies in an Isolated Founder Population from the Pacific Island of Kosrae

It has been argued that the limited genetic diversity and reduced allelic heterogeneity observed in isolated founder populations facilitates discovery of loci contributing to both Mendelian and complex disease. A strong founder effect, severe isolation, and substantial inbreeding have dramatically reduced genetic diversity in natives from the island of Kosrae, Federated States of Micronesia, who exhibit a high prevalence of obesity and other metabolic disorders. We hypothesized that genetic drift and possibly natural selection on Kosrae might have increased the frequency of previously rare genetic variants with relatively large effects, making these alleles readily detectable in genome-wide association analysis. However, mapping in large, inbred cohorts introduces analytic challenges, as extensive relatedness between subjects violates the assumptions of independence upon which traditional association test statistics are based. We performed genome-wide association analysis for 15 quantitative traits in 2,906 members of the Kosrae population, using novel approaches to manage the extreme relatedness in the sample. As positive controls, we observe association to known loci for plasma cholesterol, triglycerides, and C-reactive protein and to a compelling candidate loci for thyroid stimulating hormone and fasting plasma glucose. We show that our study is well powered to detect common alleles explaining ≥5% phenotypic variance. However, no such large effects were observed with genome-wide significance, arguing that even in such a severely inbred population, common alleles typically have modest effects. Finally, we show that a majority of common variants discovered in Caucasians have indistinguishable effect sizes on Kosrae, despite the major differences in population genetics and environment.     

Reaching new heights: insights into the genetics of human stature

Human height is a highly heritable, classic polygenic trait. Until recently, there had been limited success in identifying the specific genetic variants that explain normal variation of human height. The advent of large-scale genome-wide association studies, however, has led to dramatic progress. In the past 18 months, the first robust common variant associations were identified and there are now 44 loci known to influence normal variation of height. In this review, we summarize this exciting recent progress, discuss implicated biological pathways, the overlap with monogenic growth and skeletal dysplasia syndromes, links to disease and insights into the genetic architecture of this model polygenic trait. We also discuss the strong probability of finding several hundred more such loci in the near future.     

Genetics of adiponectin

Anti-inflammatory, anti-atherogenic and anti-diabetic properties of adiponectin make this adipokine an attractive target in the metabolism research. Given its biological role, genetic variation in adiponectin affecting its function might consequently play a role in the pathophysiology of various metabolic disorders. In this light, genetic aspects of adiponectin including its gene structure, heritability of serum concentrations and the role of genetic variation have been addressed in multiple genetic studies. Here, we provide a brief summary of adiponectin genetics with focus on gene structure and genetic variation controlling circulating adiponectin levels. We summarize the main findings from genome-wide linkage and association studies that have revealed the major genetic determinants of serum adiponectin. Beside genetic variants in the adiponectin gene, several other genes/loci (ARL15, CDH13, KNG1, FER, ETV5) contributing to the variability in circulating adiponectin have been identified. The majority of these variants are significantly associated with metabolic phenotypes relevant to metabolic diseases (e.g. obesity or type 2 diabetes (T2D)). Considering the protective properties of adiponectin in diseases such as T2D, comprehensive analyses of genetic variants including rare as well as frequent polymorphisms might provide insights on the specific role of adiponectin in the pathophysiology of metabolic diseases.     

Transferability of type 2 diabetes implicated loci in multi-ethnic cohorts from Southeast Asia

Recent large genome-wide association studies (GWAS) have identified multiple loci which harbor genetic variants associated with type 2 diabetes mellitus (T2D), many of which encode proteins not previously suspected to be involved in the pathogenesis of T2D. Most GWAS for T2D have focused on populations of European descent, and GWAS conducted in other populations with different ancestry offer a unique opportunity to study the genetic architecture of T2D. We performed genome-wide association scans for T2D in 3,955 Chinese (2,010 cases, 1,945 controls), 2,034 Malays (794 cases, 1,240 controls), and 2,146 Asian Indians (977 cases, 1,169 controls). In addition to the search for novel variants implicated in T2D, these multi-ethnic cohorts serve to assess the transferability and relevance of the previous findings from European descent populations in the three major ethnic populations of Asia, comprising half of the world's population. Of the SNPs associated with T2D in previous GWAS, only variants at CDKAL1 and HHEX/IDE/KIF11 showed the strongest association with T2D in the meta-analysis including all three ethnic groups. However, consistent direction of effect was observed for many of the other SNPs in our study and in those carried out in European populations. Close examination of the associations at both the CDKAL1 and HHEX/IDE/KIF11 loci provided some evidence of locus and allelic heterogeneity in relation to the associations with T2D. We also detected variation in linkage disequilibrium between populations for most of these loci that have been previously identified. These factors, combined with limited statistical power, may contribute to the failure to detect associations across populations of diverse ethnicity. These findings highlight the value of surveying across diverse racial/ethnic groups towards the fine-mapping efforts for the casual variants and also of the search for variants, which may be population-specific.     

Current status of genome-wide association studies in cancer

Genome-wide association studies in cancer have already identified over 150 regions associated with two dozen specific cancers. Already, a handful of multi-cancer susceptibility regions have been uncovered, providing new insights into perhaps common mechanisms of carcinogenesis. For each new susceptibility allele, investigators now face the arduous task of interrogating each region beginning with fine mapping prior to pursuing the biological basis for the direct association of one or more variants. It appears that there may be a significant number of common alleles that contribute to the heritability of a specific cancer. Since each region confers a small contribution to the risk for cancer, it is daunting to consider any single nucleotide polymorphism (SNP) as a clinical test. Since the complex genomic architecture of each cancer differs, additional genotyping and sequence analysis will be required to comprehensively catalog susceptibility alleles followed by the formidable task of understanding the interactions between genetic regions as well as the environment. It will be critical to assess the applicability of genetic tests in specific clinical settings, such as when to perform screening tests with calculable risks (e.g., biopsies or chemoprevention), before incorporating SNPs into clinical practice. To advance the current genomic observations to the clinical venue, new studies will need to be designed to validate the utility of known genetic variants in assessing risk for cancer as well as its outcomes.     

Genetic determinants of hepatic steatosis in man

Hepatic steatosis is one of the most common liver disorders in the general population. The main cause of hepatic steatosis is nonalcoholic fatty liver disease (NAFLD), representing the hepatic component of the metabolic syndrome, which is characterized by type 2 diabetes, obesity, and dyslipidemia. Insulin resistance and excess adiposity are considered to play key roles in the pathogenesis of NAFLD. Although the risk factors for NAFLD are well established, the genetic basis of hepatic steatosis is largely unknown. Here we review recent progress on genomic variants and their association with hepatic steatosis and discuss the potential impact of these genetic studies on clinical practice. Identifying the genetic determinants of hepatic steatosis will lead to a better understanding of the pathogenesis and progression of NAFLD.