Gene-environment interactions in human diseases

Studies of gene-environment interactions aim to describe how genetic and environmental factors jointly influence the risk of developing a human disease. Gene-environment interactions can be described by using several models, which take into account the various ways in which genetic effects can be modified by environmental exposures, the number of levels of these exposures and the model on which the genetic effects are based. Choice of study design, sample size and genotyping technology influence the analysis and interpretation of observed gene-environment interactions. Current systems for reporting epidemiological studies make it difficult to assess whether the observed interactions are reproducible, so suggestions are made for improvements in this area.     

Protein molecular function influences mutation rates in human genetic diseases with allelic heterogeneity

Molecular epidemiology studies have used the counts of different mutational types like transitions, transversions, etc. to identify putative mutagens, with little reference to gene organization and structure–function of the translated product. Moreover, geographical variation in the mutational spectrum is not limited to the mutational types at the nucleotide level but also have a bearing at the functional level. Here, we developed a novel measure to estimate the rate of spontaneous detrimental mutations called “mutation index” for comparing the mutational spectra consisting of all single base, missense, and non-missense changes. We have analyzed 1609 mutations occurring in 38 exons in 24 populations in three diseases viz. hemophilia B (F9 gene – 420 mutations in 9 populations across 8 exons), hemophilia A (F8 gene – 650, 8 and 26, respectively) and ovarian carcinoma (TP53 gene – 539, 7 and 4, respectively). We considered exons as units of evolution instead of the entire gene and observed feeble differences among populations implying lack of a mutagen-specific effect and the possibility of mutation causing endogenous factors. In all the three genes we observed elevated rates of detrimental mutations in exons encoding regions of significance for the molecular function of the protein. We propose that this can be extended to the entire exome with implications in exon-shuffling and complex human diseases.     

Connexin gene mutations in human genetic diseases

Rapid advances in understanding the molecular biology of the gap junctional proteins - connexins (Cx) - have revealed that these proteins are indispensable for various cellular functions. Recent findings that mutational alterations of Cx genes leads to several quite different human diseases provide additional evidence that these proteins possess several not yet fully understood functions. Many different mutations of Cx32 have been found in the hereditary peripheral neuropathy - X-linked Charcot-Marie-Tooth syndrome and several mutations of Cx26 and Cx31 have been detected in deafness. Individual mutations of Cx46, Cx50 and Cx43 have been found in cataract or heart malformations. In this review, we analyzed the functional importance of mutations of different Cx described in different human diseases. Topological comparison of mutations in different Cx species has revealed several hot spots, where mutations are common for two different Cx or diseases. The value of Cx mutations associated with diseases for understanding Cx functions is discussed.     

慢性代谢性疾病的环境与遗传交互作用以及早期预防

随着我国经济的发展和营养与生活方式的迅速变迁,近年来我国居民肥胖、2型糖尿病等慢性代谢性疾病患病率激增,已成为影响国民健康最主要的威胁。有研究显示:与白种人相比,亚洲人具有较高的2型糖尿病遗传易感性,这可能与"代谢性肥胖"表型和遭遇营养转型中的"致肥胖环境"有关。大量的研究结果表明,此类慢性代谢性疾病是遗传和环境因素交互作用的结果。随着全基因组关联研究开展,目前已发现了20多个肥胖和2型糖尿病易感基因,不仅揭示了不同种族人群在基因结构和效应值方面存在着差异,但同时也发现遗传方面的差异仍无法完全解释东西方人在发病风险方面的不同。膳食、生活方式等环境因素仍被认为是2型糖尿病发病中的重要决定因素。在全基因组关联研究后时代,国际上的研究将更加强调基因—基因、基因—环境、基因—表型之间的交互作用对代谢性疾病的影响和相关的机制。事实上,有研究表明,各种基因多态性、炎性因子和脂肪细胞因子等都可能成为早期诊断的生物标记物,而通过改变膳食和生活方式则是目前国际公认的预防和控制慢性代谢性疾病最有效的方法。然而,我国尤为缺乏在大规模前瞻性流行病学研究中对导致慢性代谢性疾病流行的主要遗传和环境因素,以及基因—环境相互作用对健康的影响方面的系统的研究。而这类研究将为建立适用于中国人群遗传和表型特征的早期诊断生物标记物和有效预防干预策略奠定基础。     

Evolution of genetic diversity and human diseases

The problem of development and dispersion of complex diseases in human populations requires new views, approaches, hypotheses, and paradigms. Evolutionary medicine provides one of the promising approaches to this problem, putting the disease into an evolutionary context. Unlike classic approaches oriented to proximate issues on structure and mechanisms of a disease, evolutionary considerations are broader. It provides the basis for understanding the origin, dispersion, and maintenance of the high frequencies of pathological phenotypes in modern human populations. In the current paper, we try to review the modern concepts on the evolution of human genetic diversity, to shape the outlines of evolutionary medicine, and to illustrate evolutionary medical problems using our experimental data. Data on genome-wide search for the signals of decanalization and adaptation in the human genome and on related biological processes and diseases are presented. Some hypotheses and concepts of evolutionary medicine may be productive for revealing the mechanisms of origin and dispersion of complex diseases and for pathogenetics of multifactorial diseases. One of such concepts is the hypothesis of decanalization of genome–phenome relationships under natural selection during modern human dispersion. Probably, the high frequency of alleles associated with complex diseases (and partially the high prevalence of diseases themselves) could be explained in the framework of the hypothesis.     

Silencing human genetic diseases with oligonucleotide-based therapies

RNA interference is an endogenous mechanism present in most eukaryotic cells that enables degradation of specific mRNAs. Pharmacological exploitation of this mechanism for therapeutic purposes attracted a whole amount of attention in its initial years, but was later hampered due to difficulties in delivery of the pharmacological agents to the appropriate organ or tissue. Advances in recent years have to a certain level started to address this specific issue. Genetic diseases are caused by aberrations in gene sequences or structure; these particular abnormalities are in theory easily addressable by RNAi therapeutics. Sequencing of the human genome has largely contributed to the identification of alterations responsible for genetic conditions, thus facilitating the design of compounds that can address these diseases. This review addresses the currently on-going programs with the aim of developing RNAi and other antisense compounds for the treatment of genetic conditions and the pros and cons that these products may encounter along the way. The authors have focused on those programs that have reached clinical trials or are very close to do so.     

RNase MRP RNA and human genetic diseases

RNase MRP RNA is the RNA subunit of the RNase mitochondrial RNA processing （MRP） enzyme complex that is involved in multiple cellular RNA processing events. Mutations on RNase MRP RNA gene （RMRP） cause a recessively inherited developmental disorder, cartilage-hair hypoplasia （CHH）. The relationship of the genotype （RMRP mutation）, RNA processing deficiency of the RNase MRP complex, and the phenotype of CHH and other skeletal dysplasias is yet to be explored.     

Protein function from the perspective of molecular interactions and genetic networks

Protein function is a complex notion, which is now receiving renewed attention from a bioinformatics and genomics perspective. After a general discussion of the principles of experimental methods employed to decipher gene/protein function, the contributions made by new, high-throughput methods in terms of function discovery are discussed. Recent work on functional ontologies and the necessity to describe function within the context of hierarchical levels of complexity are presented. The concepts of molecular interactions and genetic networks are then discussed, leading to a useful new framework with which to describe protein function using new tools such as 2D interaction maps. Finally, it is proposed that interaction data could be used to develop new methods for the functional classification of proteins. An example of functional comparisons on a real data set of yeast chromosomal proteins is presented.     

The genetic heterogeneity of hereditary human diseases]

The paper deals with the probability regularities of mutations arising in the same locus (or nucleotide) in human populations. It is shown that in a population of constant size the number of such recurrent mutations tends to an equilibrium value. It is demonstrated that dynamics of this number of recurrent mutations depends on the population structure essentially. This phenomenon is illustrated by comparing non-subdivided and hierarchy populations of the same size.     

Introducing sense into nonsense in treatments of human genetic diseases

Approximately one-third of alleles causing genetic diseases carry premature termination codons (PTCs), which lead to the production of truncated proteins. The past decade has seen considerable interest in therapeutic approaches aimed at readthrough of in-frame PTCs to enable synthesis of full-length proteins. However, attempts to readthrough PTCs in many diseases resulted in variable effects. Here, we focus on the efforts of such therapeutic approaches in cystic fibrosis and Duchenne muscular dystrophy and discuss the factors contributing to successful readthrough and how the nonsense-mediated mRNA decay (NMD) pathway regulates this response. A deeper understanding of the molecular basis for variable response to readthrough of PTCs is necessary so that appropriate therapies can be developed to treat many human genetic diseases caused by PTCs.     

The mTOR pathway and its role in human genetic diseases

The signalling components upstream and downstream of the protein kinase mammalian target of rapamycin (mTOR) are frequently altered in a wide variety of human diseases. Upstream of mTOR key signalling molecules are the small GTPase Ras, the lipid kinase PI3K, the Akt kinase, and the GTPase Rheb, which are known to be deregulated in many human cancers. Mutations in the mTOR pathway component genes TSC1, TSC2, LKB1, PTEN, VHL, NF1 and PKD1 trigger the development of the syndromes tuberous sclerosis, Peutz-Jeghers syndrome, Cowden syndrome, Bannayan-Riley-Ruvalcaba syndrome, Lhermitte-Duclos disease, Proteus syndrome, von Hippel-Lindau disease, Neurofibromatosis type 1, and Polycystic kidney disease, respectively. In addition, the tuberous sclerosis proteins have been implicated in the development of several sporadic tumors and in the control of the cyclin-dependent kinase inhibitor p27, known to be of relevance for several cancers. Recently, it has been recognized that mTOR is regulated by TNF-alpha and Wnt, both of which have been shown to play critical roles in the development of many human neoplasias. In addition to all these human diseases, the role of mTOR in Alzheimer's disease, cardiac hypertrophy, obesity and type 2 diabetes is discussed.     

The nuclear envelope, human genetic diseases and ageing

Here we present an overview of the experimental evidence and of the conceptual basis for the involvement of lamins and nuclear envelope proteins in a group of genetic diseases collectively referred to as laminopathies. Some of these diseases affect a specific tissue (skeletal and/or cardiac muscles, subcutaneous fat, peripheral nerves), while others affect a variety of tissues; this suggests that the pathogenic mechanism of laminopathies could reside in the alteration of basic mechanisms affecting gene expression. On the other hand, a common feature of cells from laminopathic patients is represented by nuclear shape alterations and heterochromatin rearrangements. The definition of the role of lamins in the fine regulation of heterochromatin organization may help understanding not only the pathogenic mechanism of laminopathies but also the molecular basis of cell differentiation and ageng.     

Protein interactions and disease: computational approaches to uncover the etiology of diseases

The genomic era has been characterised by vast amounts of data from diverse sources, creating a need for new tools to extract biologically meaningful information. Bioinformatics is, for the most part, responding to that need. The sparseness of the genomic data associated with diseases, however, creates a new challenge. Understanding the complex interplay between genes and proteins requires integration of data from a wide variety of sources, i.e. gene expression, genetic linkage, protein interaction, and protein structure among others. Thus, computational tools have become critical for the integration, representation and visualization of heterogeneous biomedical data. Furthermore, several bioinformatics methods have been developed to formulate predictions about the functional role of genes and proteins, including their role in diseases. After an introduction to the complex interplay between proteins and genetic diseases, this review explores recent approaches to the understanding of the mechanisms of disease at the molecular level. Finally, because most known mechanisms leading to disease involve some form of protein interaction, this review focuses on the recent methodologies for understanding diseases through their underlying protein interactions. Recent contributions from genetics, protein structure and protein interaction network analyses to the understanding of diseases are discussed here.