Genetic and environmental pathways to complex diseases

<p>Abstract</p> <p>Background</p> <p>Pathogenesis of complex diseases involves the integration of genetic and environmental factors over time, making it particularly difficult to tease apart relationships between phenotype, genotype, and environmental factors using traditional experimental approaches.</p> <p>Results</p> <p>Using gene-centered databases, we have developed a network of complex diseases and environmental factors through the identification of key molecular pathways associated with both genetic and environmental contributions. Comparison with known chemical disease relationships and analysis of transcriptional regulation from gene expression datasets for several environmental factors and phenotypes clustered in a metabolic syndrome and neuropsychiatric subnetwork supports our network hypotheses. This analysis identifies natural and synthetic retinoids, antipsychotic medications, Omega 3 fatty acids, and pyrethroid pesticides as potential environmental modulators of metabolic syndrome phenotypes through PPAR and adipocytokine signaling and organophosphate pesticides as potential environmental modulators of neuropsychiatric phenotypes.</p> <p>Conclusion</p> <p>Identification of key regulatory pathways that integrate genetic and environmental modulators define disease associated targets that will allow for efficient screening of large numbers of environmental factors, screening that could set priorities for further research and guide public health decisions.</p

Computational Systems Analysis on Polycystic Ovarian Syndrome (PCOS)

Complex diseases are caused by a combination of genetic and environmental factors. Unraveling the molecular pathways from the genetic factors that affect a phenotype is always difficult, but in the case of complex diseases, this is further complicated since genetic factors in affected individuals might be different. Polycystic ovarian syndrome (PCOS) is an example of a complex disease with limited molecular information. Recently, PCOS molecular omics data have increasingly appeared in many publications. We conduct extensive bioinformatics analyses on the data and perform strong integration of experimental and computational biology to understand its complex biological systems in examining multiple interacting genes and their products. PCOS involves networks of genes, and to understand them, those networks must be mapped. This approach has emerged as powerful tools for studying complex diseases and been coined as network biology. Network biology encompasses wide range of network types including those based on physical interactions between and among cellular components and those baised on similarity among patients or diseases. Each of these offers distinct biological clues that may help scientists transform their cellular parts list into insights about complex diseases. This chapter will discuss some computational analysis aspects on the omics studies that have been conducted in PCOS

Gene-Disease Network Analysis Reveals Functional Modules in Mendelian, Complex and Environmental Diseases

Scientists have been trying to understand the molecular mechanisms of diseases to design preventive and therapeutic strategies for a long time. For some diseases, it has become evident that it is not enough to obtain a catalogue of the disease-related genes but to uncover how disruptions of molecular networks in the cell give rise to disease phenotypes. Moreover, with the unprecedented wealth of information available, even obtaining such catalogue is extremely difficult. We developed a comprehensive gene-disease association database by integrating associations from several sources that cover different biomedical aspects of diseases. In particular, we focus on the current knowledge of human genetic diseases including mendelian, complex and environmental diseases. To assess the concept of modularity of human diseases, we performed a systematic study of the emergent properties of human gene-disease networks by means of network topology and functional annotation analysis. The results indicate a highly shared genetic origin of human diseases and show that for most diseases, including mendelian, complex and environmental diseases, functional modules exist. Moreover, a core set of biological pathways is found to be associated with most human diseases. We obtained similar results when studying clusters of diseases, suggesting that related diseases might arise due to dysfunction of common biological processes in the cell. For the first time, we include mendelian, complex and environmental diseases in an integrated gene-disease association database and show that the concept of modularity applies for all of them. We furthermore provide a functional analysis of disease-related modules providing important new biological insights, which might not be discovered when considering each of the gene-disease association repositories independently. Hence, we present a suitable framework for the study of how genetic and environmental factors, such as drugs, contribute to diseases. The gene-disease networks used in this study and part of the analysis are available at http://ibi.imim.es/DisGeNET/DisGeNETweb.html#Download

Pro-inflammatory genetic markers of atherosclerosis

Atherosclerosis (AS) is a chronic, progressive, multifactorial disease mostly affecting large and medium-sized elastic and muscular arteries. It has formerly been considered a bland lipid storage disease. Currently, multiple independent pathways of evidence suggest this pathological condition is a peculiar form of inflammation, triggered by cholesterol-rich lipoproteins and influenced both by environmental and genetic factors. The Human Genome Project opened up the opportunity to dissect complex human traits and to understand basic pathways of multifactorial diseases such as AS. Population-based association studies have emerged as powerful tools for examining genes with a role in common multifactorial diseases that have a strong environmental component. These association studies often estimate the risk of developing a certain disease in carriers and non-carriers of a particular genetic polymorphism. Dissecting out the influence of pro-inflammatory genes within the complex pathophysiology of AS and its complications will help to provide a more complete risk assessment and complement known classical cardiovascular risk factors. The detection of a risk profile will potentially allow both the early identification of individuals susceptible to disease and the possible discovery of potential targets for drug or lifestyle modification; i.e. it will open the door to personalized medicine

PADB : Published Association Database

<p>Abstract</p> <p>Background</p> <p>Although molecular pathway information and the International HapMap Project data can help biomedical researchers to investigate the aetiology of complex diseases more effectively, such information is missing or insufficient in current genetic association databases. In addition, only a few of the environmental risk factors are included as gene-environment interactions, and the risk measures of associations are not indexed in any association databases.</p> <p>Description</p> <p>We have developed a published association database (PADB; <url>http://www.medclue.com/padb</url>) that includes both the genetic associations and the environmental risk factors available in PubMed database. Each genetic risk factor is linked to a molecular pathway database and the HapMap database through human gene symbols identified in the abstracts. And the risk measures such as odds ratios or hazard ratios are extracted automatically from the abstracts when available. Thus, users can review the association data sorted by the risk measures, and genetic associations can be grouped by human genes or molecular pathways. The search results can also be saved to tab-delimited text files for further sorting or analysis. Currently, PADB indexes more than 1,500,000 PubMed abstracts that include 3442 human genes, 461 molecular pathways and about 190,000 risk measures ranging from 0.00001 to 4878.9.</p> <p>Conclusion</p> <p>PADB is a unique online database of published associations that will serve as a novel and powerful resource for reviewing and interpreting huge association data of complex human diseases.</p

Disparities in allele frequencies and population differentiation for 101 disease-associated single nucleotide polymorphisms between Puerto Ricans and Non-Hispanic Whites

BACKGROUND. Variations in gene allele frequencies can contribute to differences in the prevalence of some common complex diseases among populations. Natural selection modulates the balance in allele frequencies across populations. Population differentiation (FST) can evidence environmental selection pressures. Such genetic information is limited in Puerto Ricans, the second largest Hispanic ethnic group in the US, and a group with high prevalence of chronic disease. We determined allele frequencies and population differentiation for 101 single nucleotide polymorphisms (SNPs) in 30 genes involved in major metabolic and disease-relevant pathways in Puerto Ricans (n = 969, ages 45–75 years) and compared them to similarly aged non-Hispanic whites (NHW) (n = 597). RESULTS. Minor allele frequency (MAF) distributions for 45.5% of the SNPs assessed in Puerto Ricans were significantly different from those of NHW. Puerto Ricans carried risk alleles in higher frequency and protective alleles in lower frequency than NHW. Patterns of population differentiation showed that Puerto Ricans had SNPs with exceptional FST values in intronic, non-synonymous and promoter regions. NHW had exceptional FST values in intronic and promoter region SNPs only. CONCLUSION. These observations may serve to explain and broaden studies on the impact of gene polymorphisms on chronic diseases affecting Puerto Ricans.National Institutes of Health, National Institutes on Aging (P01AG02394, P01AG023394-SI); National Insitutes of Health (53-K06-5-10); US Department of Agriculture Research Service (58-1950-9-001, 58-1950-7-707); National Institutes of Health & Heart, Lung, and Blood Institute (U 01 HL72524, Genetic and Environmental Determinants of Triglycerides, HL54776

Genetic pleiotropy between age-related macular degeneration and 16 complex diseases and traits

Contains fulltext : 175039.pdf (publisher's version ) (Open Access)BACKGROUND: Age-related macular degeneration (AMD) is a common condition of vision loss with disease development strongly influenced by environmental and genetic factors. Recently, 34 loci were associated with AMD at genome-wide significance. So far, little is known about a genetic overlap between AMD and other complex diseases or disease-relevant traits. METHODS: For each of 60 complex diseases/traits with publicly available genome-wide significant association data, the lead genetic variant per independent locus was extracted and a genetic score was calculated for each disease/trait as the weighted sum of risk alleles. The association with AMD was estimated based on 16,144 AMD cases and 17,832 controls using logistic regression. RESULTS: Of the respective disease/trait variance, the 60 genetic scores explained on average 4.8% (0.27-20.69%) and 16 of them were found to be significantly associated with AMD (Q-values < 0.01, p values from < 1.0 x 10-16 to 1.9 x 10-3). Notably, an increased risk for AMD was associated with reduced risk for cardiovascular diseases, increased risk for autoimmune diseases, higher HDL and lower LDL levels in serum, lower bone-mineral density as well as an increased risk for skin cancer. By restricting the analysis to 1824 variants initially used to compute the 60 genetic scores, we identified 28 novel AMD risk variants (Q-values < 0.01, p values from 1.1 x 10-7 to 3.0 x 10-4), known to be involved in cardiovascular disorders, lipid metabolism, autoimmune diseases, anthropomorphic traits, ocular disorders, and neurological diseases. The latter variants represent 20 novel AMD-associated, pleiotropic loci. Genes in the novel loci reinforce previous findings strongly implicating the complement system in AMD pathogenesis. CONCLUSIONS: We demonstrate a substantial overlap of the genetics of several complex diseases/traits with AMD and provide statistically significant evidence for an additional 20 loci associated with AMD. This highlights the possibility that so far unrelated pathologies may have disease pathways in common

Sirtuins and Aging: is there a Role for Resveratrol?

Prolonged human life duration is consequently associated with a higher incidence of chronic diseases. Aging is a very complex process in which genetic, environmental and cellular pathways are involved. Along with aging, longevity has been linked with Sirtuins. Sirtuin enzymes are a family of highly conserved protein deacetylases that have been linked with calorie restriction and aging by modulating energy metabolism, genomic stability and stress resistance. Aim of this brief review is to describe Sirtuins’ influence on the conditions that worsen the physiological aging. We will also report the beneficial effects of the polyphenol resveratrol on these molecules and the possible therapeutical perspectives

Genetic approaches to studying complex human disease

Common, complex diseases such as cardiovascular disease (CVD) represent an intricate interaction between environmental and genetic factors and now account for the leading causes of mortality in western society. By investigating the genetic component of complex disease etiology, we have gained a better understanding of the biological pathways underlying complex disease and the heterogeneity of complex disease risk. However, the development of high throughput genomic technologies and large well-phenotyped multi-ethnic cohorts has opened the door towards more in-depth and trans-disciplinary approaches to studying the genetics of complex disease pathogenesis. Accordingly, we sought to investigate select complex traits and diseases using both established and novel genomic technologies, including candidate gene resequencing, high-throughput targeted microarray genotyping and candidate variant genotyping. We demonstrate that a private and common variant, p.G116S, within the low-density lipoprotein receptor (LDLR) gene among Inuit descendants has a large effect on plasma cholesterol; that variation in cardio-metabolic and Alzheimer disease (AD) loci is not associated with susceptibility to the pre-dementia phenotype known as “cognitive impairment, no dementia”; and that established type 2 diabetes (T2D) variants are not associated with T2D susceptibility among select aboriginal Canadian and Greenland cohorts. Together, these studies represent a selection of established and novel genomic strategies for the investigation of complex disease genetics which are likely to remain fundamental in the continued investigation of complex disease pathogenesis