Increased 90-kDa ribosomal S6 kinase (Rsk) activity is protective against mutant huntingtin toxicity

Uncovering the underlying genetic component of any disease is key to the understanding of its pathophysiology and may open new avenues for development of therapeutic strategies and biomarkers. In the past several years, there has been an explosion of genome-wide association studies (GWAS) resulting in the discovery of novel candidate genes conferring risk for complex diseases, including neurodegenerative diseases. Despite this success, there still remains a substantial genetic component for many complex traits and conditions that is unexplained by the GWAS findings. Additionally, in many cases, the mechanism of action of the newly discovered disease risk variants is not inherently obvious. Furthermore, a genetic region with multiple genes may be identified via GWAS, making it difficult to discern the true disease risk gene. Several alternative approaches are proposed to overcome these potential shortcomings of GWAS, including the use of quantitative, biologically relevant phenotypes. Gene expression levels represent an important class of endophenotypes. Genetic linkage and association studies that utilize gene expression levels as endophenotypes determined that the expression levels of many genes are under genetic influence. This led to the postulate that there may exist many genetic variants that confer disease risk via modifying gene expression levels. Results from the handful of genetic studies which assess gene expression level endophenotypes in conjunction with disease risk suggest that this combined phenotype approach may both increase the power for gene discovery and lead to an enhanced understanding of their mode of action. This review summarizes the evidence in support of gene expression levels as promising endophenotypes in the discovery and characterization of novel candidate genes for complex diseases, which may also represent a novel approach in the genetic studies of Alzheimer's and other neurodegenerative diseases.     

遗传风险评分在复杂疾病遗传学研究中的应用

心血管疾病、2型糖尿病、原发性高血压、哮喘、肥胖、肿瘤等复杂疾病在全球范围内流行,并成为人类死亡的主要原因。越来越多的人开始关注遗传易感性在复杂疾病发病机制中的作用。至今,与复杂疾病相关的易感基因和基因序列变异仍未完全清楚。人们希望通过遗传关联研究来阐明复杂疾病的遗传基础。近年来,全基因组关联研究和候选基因研究发现了大量与复杂疾病有关的基因序列变异。这些与复杂疾病有因果和(或)关联关系的基因序列变异的发现促进了复杂疾病预测和防治方法的产生和发展。遗传风险评分(Genetic risk score,GRS)作为探索单核苷酸多态(Single nucleotide polymorphisms,SNPs)与复杂疾病临床表型之间关系的新兴方法,综合了若干SNPs的微弱效应,使基因多态对疾病的预测性大幅度提升。该方法在许多复杂疾病遗传学研究中得到成功应用。本文重点介绍了GRS的计算方法和评价标准,简要列举了运用GRS取得的系列成果,并对运用过程中所存在的局限性进行了探讨,最后对遗传风险评分的未来发展方向进行了展望。     

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.     

Functional Analysis of Variance for Association Studies

While progress has been made in identifying common genetic variants associated with human diseases, for most of common complex diseases, the identified genetic variants only account for a small proportion of heritability. Challenges remain in finding additional unknown genetic variants predisposing to complex diseases. With the advance in next-generation sequencing technologies, sequencing studies have become commonplace in genetic research. The ongoing exome-sequencing and whole-genome-sequencing studies generate a massive amount of sequencing variants and allow researchers to comprehensively investigate their role in human diseases. The discovery of new disease-associated variants can be enhanced by utilizing powerful and computationally efficient statistical methods. In this paper, we propose a functional analysis of variance (FANOVA) method for testing an association of sequence variants in a genomic region with a qualitative trait. The FANOVA has a number of advantages: (1) it tests for a joint effect of gene variants, including both common and rare; (2) it fully utilizes linkage disequilibrium and genetic position information; and (3) allows for either protective or risk-increasing causal variants. Through simulations, we show that FANOVA outperform two popularly used methods – SKAT and a previously proposed method based on functional linear models (FLM), – especially if a sample size of a study is small and/or sequence variants have low to moderate effects. We conduct an empirical study by applying three methods (FANOVA, SKAT and FLM) to sequencing data from Dallas Heart Study. While SKAT and FLM respectively detected ANGPTL 4 and ANGPTL 3 associated with obesity, FANOVA was able to identify both genes associated with obesity.     

Focus: A Multifaceted Battle Against Cancer: Gene-by-Environment Interactions in Pancreatic Cancer: Implications for Prevention

Pancreatic cancer (PC) has been estimated to have higher incidence and correspondingly higher mortality rates in more developed regions worldwide. Overall, the age-adjusted incidence rate is 4.9/10⁵ and age-adjusted mortality rate is at 4.8/10⁵. We review here our current knowledge of modifiable risk factors (cigarette smoking, obesity, diet, and alcohol) for PC, genetic variants implicated by genome-wide association studies, possible genetic interactions with risk factors, and prevention strategies to provide future research directions that may further our understanding of this complex disease. Cigarette smoking is consistently associated with a two-fold increased PC risk. PC associations with dietary intake have been largely inconsistent, with the potential exception of certain unsaturated fatty acids decreasing risk and well-done red meat or meat mutagens increasing risk. There is strong evidence to support that obesity (and related measures) increase risk of PC. Only the heaviest alcohol drinkers seem to be at an increased risk of PC. Currently, key prevention strategies include avoiding tobacco and excessive alcohol consumption and adopting a healthy lifestyle. Screening technologies and PC chemoprevention are likely to become more sophisticated, but may only apply to those at high risk. Risk stratification may be improved by taking into account gene environment interactions. Research on these modifiable risk factors is key to reducing the incidence of PC and understanding who in the population can be considered high risk.     

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.     

Genetic determinants of platelet function in thromboembolic diseases

Within the past decade our understanding of thromboembolic disorders has become even more sophisticated as recent discoveries have suggested the influence of gene variants on the development of atherosclerotic disease and arterial thrombosis. Candidate genes encode proteins involved in processes relevant to atherosclerosis, ranging from cholesterol metabolism to arterial thrombosis. Platelets are key elements in primary hemostasis, but also in arterial thrombosis. Moreover, a number of genetic polymorphisms of platelet proteins may also induce gain or loss of function, supporting a role predisposing some individuals to thrombotic events. However, after thousands of studies, much controversy remains whether individual platelet polymorphisms contribute to an increased likelihood of thromboembolic disorders. Although platelet polymorphisms are a promising addition to more established cardiovascular risk factors, identifying genetic variants as a single cause of cardiovascular disease would be an oversimplification; instead, the contribution of these polymorphisms should also be considered in the context of a multifactorial disease. Gene-gene and gene-environment studies would identify specific combinations associated with a high risk to suffer from these diseases. The platelet's genetic heterogeneity should also be considered in every aspect of clinical medicine, ranging from susceptibility to diseases, pathogenesis, and clinical outcome to diversity in responses to drug treatment (pharmacogenomics), and bleeding.     

Molecular genetics of human obesity: A comprehensive review

Obesity and its related health complications is a major problem worldwide. Hypothalamus and their signalling molecules play a critical role in the intervening and coordination with energy balance and homeostasis. Genetic factors play a crucial role in determining an individual's predisposition to the weight gain and being obese. In the past few years, several genetic variants were identified as monogenic forms of human obesity having success over common polygenic forms. In the context of molecular genetics, genome-wide association studies (GWAS) approach and their findings signified a number of genetic variants predisposing to obesity. However, the last couple of years, it has also been noticed that alterations in the environmental and epigenetic factors are one of the key causes of obesity. Hence, this review might be helpful in the current scenario of molecular genetics of human obesity, obesity-related health complications (ORHC), and energy homeostasis. Future work based on the clinical discoveries may play a role in the molecular dissection of genetic approaches to find more obesity-susceptible gene loci.     

A targeted genotyping approach enhances identification of variants in taste receptor and appetite/reward genes of potential functional importance for obesity‐related porcine traits

Taste receptors (TASRs) and appetite and reward (AR) mechanisms influence eating behaviour, which in turn affects food intake and risk of obesity. In a previous study, we used next generation sequencing to identify potentially functional mutations in TASR and AR genes and found indications for genetic associations between identified variants and growth and fat deposition in a subgroup of animals (n = 38) from the UNIK resource pig population. This population was created for studying obesity and obesity‐related diseases. In the present study we validated results from our previous study by investigating genetic associations between 24 selected single nucleotide variants in TASR and AR gene variants and 35 phenotypes describing obesity and metabolism in the entire UNIK population (n = 564). Fifteen variants showed significant association with specific obesity‐related phenotypes after Bonferroni correction. Six of the 15 genes, namely SIM1, FOS, TAS2R4, TAS2R9, MCHR2 and LEPR, showed good correlation between known biological function and associated phenotype. We verified a genetic association between potentially functional variants in TASR/AR genes and growth/obesity and conclude that the combination of identification of potentially functional variants by next generation sequencing followed by targeted genotyping and association studies is a powerful and cost‐effective approach for increasing the power of genetic association studies.     

Genetic studies on the ghrelin, growth hormone secretagogue receptor (GHSR) and ghrelin O-acyl transferase (GOAT) genes

Ghrelin is a 28 amino acid peptide hormone that is produced both centrally and peripherally. Regulated by the ghrelin O-acyl transferase enzyme, ghrelin exerts its action through the growth hormone secretagogue receptor, and is implicated in a diverse range of physiological processes. These implications have placed the ghrelin signaling pathway at the center of a large number of candidate gene and genome-wide studies which aim to identify the genetic basis of human heterogeneity. In this review we summarize the available data on the genetic variability of ghrelin, its receptor and its regulatory enzyme, and their association with obesity, stature, type 2 diabetes, cardiovascular disease, eating disorders, and reward seeking behavior.     

Identifying disease related sub-pathways for analysis of genome-wide association studies

Most methods for genome-wide association studies (GWAS) focus on discovering a single genetic variant, but the pathogenesis of complex diseases is thought to arise from the joint effect of multiple genetic variants. Information about pathway structure, such as the interactions and distances between gene products within pathways, can help us learn more about the functions and joint effect of genes associated with disease risk. We developed a novel sub-pathway based approach to study the joint effect of multiple genetic variants that are modestly associated with disease. The approach prioritized sub-pathways based on the significance values of single nucleotide polymorphisms (SNPs) and the interactions and distances between gene products within pathways. We applied the method to seven complex diseases. The result showed that our method can efficiently identify statistically significant sub-pathways associated with the pathogenesis of complex diseases. The approach identified sub-pathways that may inform the interpretation of GWAS data.     

Wie gro? sind die kleinen genetischen Risiken?

While family studies are ideal to pinpoint strong genetic risk effects, genome-wide association studies in unrelated individuals are particularly successful in identifying moderate and small genetic risks for multifactorial diseases and disease-relevant quantitative parameters. Here, we present how the genetic risk for such variants is computed and what models are used to derive cumulative genetic risk. Using the examples of obesity, diabetes, and age-related macular degeneration, we illustrate how these risks are computed and tackle the question of how big the small genetic risks are.     

The octanoylated energy regulating hormone ghrelin: An expanded view of ghrelin’s biological interactions and avenues for controlling ghrelin signaling

Ghrelin is a small peptide hormone that requires a unique post-translational modification, serine octanoylation, to bind and activate the GHS-R1a receptor. Initially demonstrated to stimulate hunger and appetite, ghrelin-dependent signaling is implicated in a variety of neurological and physiological processes influencing diseases such as diabetes, obesity, and Prader-Willi syndrome. In addition to its cognate receptor, recent studies have revealed ghrelin interacts with a range of binding partners within the bloodstream. Defining the scope of ghrelin’s interactions within the body, understanding how these interactions work in concert to modulate ghrelin signaling, and developing molecular tools for controlling ghrelin signaling are essential for exploiting ghrelin for therapeutic effect. In this review, we discuss recent findings regarding the biological effects of ghrelin signaling, outline binding partners that control ghrelin trafficking and stability in circulation, and summarize the current landscape of inhibitors targeting ghrelin octanoylation.     

Indications for Potential Parent-of-Origin Effects within the FTO Gene

Genome-Wide Association Studies (GWAS) were successfully applied to discover associations with obesity. However, the GWAS design is usually based on unrelated individuals and inheritance information on the parental origin of the alleles is missing. Taking into account parent-of-origin may provide further insights into the genetic mechanisms contributing to obesity. We hypothesized that there may be variants within the robustly replicated fat mass and obesity associated (FTO) gene that may confer different risk for obesity depending on transmission from mother or father. Genome-wide genotypes and pedigree information from the Sorbs population were used. Phased genotypes among 525 individuals were generated by AlphaImpute. Subsequently, 22 SNPs within FTO introns 1 to 3 were selected and parent-of-origin specific association analyses were performed using PLINK. Interestingly, we identified several SNPs conferring different genetic effects (P≤0.05) depending on parental origin—among them, rs1861868, rs1121980 and rs9939973 (all in intron 1). To confirm our findings, we investigated the selected variants in 705 German trios comprising an (extremely) obese child or adolescent and both parents. Again, we observed evidence for POE effects in intron 2 and 3 (P≤0.05) as indicated by the parental asymmetry test. Our results suggest that the obesity risk transmitted by several FTO variants may depend on the parental origin of the allele. Larger family-based studies are warranted to replicate our findings.     

Modern probabilistic and statistical approaches to search for nucleotide sequence options associated with integrated diseases

Complex diseases are a major important problem for modern medicine. These diseases arise under the influence of specific environmental and clinical-demographic factors, so-called risk factors, in combination with factors of genetic heredity. The contribution of genetic factors to the development of complex diseases is on average about 50%. The cause of complex diseases can be a lot of variants of the nucleotide sequence. In addition to common variants of single nucleotide polymorphisms (SNPs), rare variants also play a role in the development of complex diseases. This review presents modern probabilistic and statistical approaches to the search for gene variants and their combinations associated with complex diseases with an emphasis on methods for finding rare and unique variants. A comparative analysis of these approaches is performed, and a number of problems requiring resolution are formulated.