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Complex Diseases (complex + disease)
Kinds of Complex Diseases Selected AbstractsAn Analysis Paradigm for Investigating Multi-locus Effects in Complex Disease: Examination of Three GABAA Receptor Subunit Genes on 15q11-q13 as Risk Factors for Autistic Disorder.ANNALS OF HUMAN GENETICS, Issue 3 2006A. E. Ashley-Koch Summary Gene-gene interactions are likely involved in many complex genetic disorders and new statistical approaches for detecting such interactions are needed. We propose a multi-analytic paradigm, relying on convergence of evidence across multiple analysis tools. Our paradigm tests for main and interactive effects, through allele, genotype and haplotype association. We applied our paradigm to genotype data from three GABAA receptor subunit genes (GABRB3, GABRA5, and GABRG3) on chromosome 15 in 470 Caucasian autism families. Previously implicated in autism, we hypothesized these genes interact to contribute to risk. We detected no evidence of main effects by allelic (PDT, FBAT) or genotypic (genotype-PDT) association at individual markers. However, three two-marker haplotypes in GABRG3 were significant (HBAT). We detected no significant multi-locus associations using genotype-PDT analysis or the EMDR data reduction program. However, consistent with the haplotype findings, the best single locus EMDR model selected a GABRG3 marker. Further, the best pairwise genotype-PDT result involved GABRB3 and GABRG3, and all multi-locus EMDR models also selected GABRB3 and GABRG3 markers. GABA receptor subunit genes do not significantly interact to contribute to autism risk in our overall data set. However, the consistency of results across analyses suggests that we have defined a useful framework for evaluating gene-gene interactions. [source] Nonreplication in Genetic Studies of Complex Diseases,Lessons Learned From Studies of Osteoporosis and Tentative Remedies,JOURNAL OF BONE AND MINERAL RESEARCH, Issue 3 2005Hui Shen Abstract Inconsistent results have accumulated in genetic studies of complex diseases/traits over the past decade. Using osteoporosis as an example, we address major potential factors for the nonreplication results and propose some potential remedies. Over the past decade, numerous linkage and association studies have been performed to search for genes predisposing to complex human diseases. However, relatively little success has been achieved, and inconsistent results have accumulated. We argue that those nonreplication results are not unexpected, given the complicated nature of complex diseases and a number of confounding factors. In this article, based on our experience in genetic studies of osteoporosis, we discuss major potential factors for the inconsistent results and propose some potential remedies. We believe that one of the main reasons for this lack of reproducibility is overinterpretation of nominally significant results from studies with insufficient statistical power. We indicate that the power of a study is not only influenced by the sample size, but also by genetic heterogeneity, the extent and degree of linkage disequilibrium (LD) between the markers tested and the causal variants, and the allele frequency differences between them. We also discuss the effects of other confounding factors, including population stratification, phenotype difference, genotype and phenotype quality control, multiple testing, and genuine biological differences. In addition, we note that with low statistical power, even a "replicated" finding is still likely to be a false positive. We believe that with rigorous control of study design and interpretation of different outcomes, inconsistency will be largely reduced, and the chances of successfully revealing genetic components of complex diseases will be greatly improved. [source] Identifying Rarer Genetic Variants for Common Complex Diseases: Diseased Versus Neutral Discovery PanelsANNALS OF HUMAN GENETICS, Issue 1 2009K. Curtin Summary The power of genetic association studies to identify disease susceptibility alleles fundamentally relies on the variants studied. The standard approach is to determine a set of tagging-SNPs (tSNPs) that capture the majority of genomic variation in regions of interest by exploiting local correlation structures. Typically, tSNPs are selected from neutral discovery panels - collections of individuals comprehensively genotyped across a region. We investigated the implications of discovery panel design on tSNP performance in association studies using realistically-simulated sequence data. We found that discovery panels of 24 sequenced ,neutral' individuals (similar to NIEHS or HapMap ENCODE data) were sufficient to select well-powered tSNPs to identify common susceptibility alleles. For less common alleles (0.01,0.05 frequency) we found neutral panels of this size inadequate, particularly if low-frequency variants were removed prior to tSNP selection; superior tSNPs were found using panels of diseased individuals. Only large neutral panels (200 individuals) matched diseased panel performance in selecting well-powered tSNPs to detect both common and rarer alleles. The 1000 Genomes Project initiative may provide larger neutral panels necessary to identify rarer susceptibility alleles in association studies. In the interim, our results suggest investigators can boost power to detect such alleles by sequencing diseased individuals for tSNP selection. [source] Effect of including environmental data in investigations of gene-disease associations in the presence of qualitative interactionsGENETIC EPIDEMIOLOGY, Issue 6 2010Elizabeth Williamson Abstract Complex diseases are likely to be caused by the interplay of genetic and environmental factors. Despite this, gene-disease associations are frequently investigated using models that focus solely on a marginal gene effect, ignoring environmental factors entirely. Failing to take into account a gene-environment interaction can weaken the apparent gene-disease association, leading to loss in statistical power and, potentially, inability to identify genuine risk factors. If a gene-environment interaction exists, therefore, a joint analysis allowing the effect of the gene to differ between groups defined by the environmental exposure can have greater statistical power than a marginal gene-disease model. However, environmental data are subject to measurement error. Substantial losses in statistical power for detecting gene-environment interactions can arise from measurement error in the environmental exposure. It is unclear, however, what effect measurement error may have on the power of the joint analysis. We consider the potential benefits, in terms of statistical power, of collecting concurrent environmental data within large cohorts in order to enhance gene detection. We further consider whether these benefits remain in the presence of misclassification in both the gene and the environmental exposure. We find that when an effect of the gene is apparent only in the presence of the environmental exposure, the joint analysis has greater power than a marginal gene-disease analysis. This comparative increase in power remains in the presence of likely levels of misclassification of either the gene or environmental exposure. Genet. Epidemiol. 34:552,560, 2010. © 2010 Wiley-Liss, Inc. [source] A Combinatorial Searching Method for Detecting a Set of Interacting Loci Associated with Complex TraitsANNALS OF HUMAN GENETICS, Issue 5 2006Qiuying Sha Summary Complex diseases are presumed to be the results of the interaction of several genes and environmental factors, with each gene only having a small effect on the disease. Mapping complex disease genes therefore becomes one of the greatest challenges facing geneticists. Most current approaches of association studies essentially evaluate one marker or one gene (haplotype approach) at a time. These approaches ignore the possibility that effects of multilocus functional genetic units may play a larger role than a single-locus effect in determining trait variability. In this article, we propose a Combinatorial Searching Method (CSM) to detect a set of interacting loci (may be unlinked) that predicts the complex trait. In the application of the CSM, a simple filter is used to filter all the possible locus-sets and retain the candidate locus-sets, then a new objective function based on the cross-validation and partitions of the multi-locus genotypes is proposed to evaluate the retained locus-sets. The locus-set with the largest value of the objective function is the final locus-set and a permutation procedure is performed to evaluate the overall p-value of the test for association between the final locus-set and the trait. The performance of the method is evaluated by simulation studies as well as by being applied to a real data set. The simulation studies show that the CSM has reasonable power to detect high-order interactions. When the CSM is applied to a real data set to detect the locus-set (among the 13 loci in the ACE gene) that predicts systolic blood pressure (SBP) or diastolic blood pressure (DBP), we found that a four-locus gene-gene interaction model best predicts SBP with an overall p-value = 0.033, and similarly a two-locus gene-gene interaction model best predicts DBP with an overall p-value = 0.045. [source] Environmental Risk Factors Predisposing to the Development of Basal Cell CarcinomaDERMATOLOGIC SURGERY, Issue 2004Malgorzata Zak-Prelich MD Background. Basal cell carcinomas (BCCs) are the most common malignancies in white people. The incidence varies depending on the region of the world, with the highest rate of 1% to 2% per year noted in Australia. It is estimated that BCC incidence increases by 5% annually. An increasing incidence of BCC is in line with the changes in the living style and exposure to various environmental factors. Objective. To present the environmental factors that may influence the development of BCCs. The influence of ultraviolet radiation exposure alone and in connection with immunosuppression, smoking, occupational factors, as well as arsenic and ionizing radiation exposure, was described. Conclusion. BCC is a very complex disease, with many factors influencing its development. Environmental factors are very important for the prevalence of BCC, and most of them can be avoided. The exposure to ultraviolet radiation is undoubtedly of great risk; therefore, the national campaigns against aggressive, seasonal sun exposure, especially in children and adolescents, as well as using sunscreens, are of great value in the fight against BCC development. [source] Bioenergetics and the epigenome: Interface between the environment and genes in common diseasesDEVELOPMENTAL DISABILITIES RESEARCH REVIEW, Issue 2 2010Douglas C. Wallace Abstract Extensive efforts have been directed at using genome-wide association studies (GWAS) to identify the genes responsible for common metabolic and degenerative diseases, cancer, and aging, but with limited success. While environmental factors have been evoked to explain this conundrum, the nature of these environmental factors remains unexplained. The availability of and demands for energy constitute one of the most important aspects of the environment. The flow of energy through the cell is primarily mediated by the mitochondrion, which oxidizes reducing equivalents from hydrocarbons via acetyl-CoA, NADH + H+, and FADH2 to generate ATP through oxidative phosphorylation (OXPHOS). The mitochondrial genome encompasses hundreds of nuclear DNA (nDNA)-encoded genes plus 37 mitochondrial DNA (mtDNA)-encoded genes. Although the mtDNA has a high mutation rate, only milder, potentially adaptive mutations are introduced into the population through female oocytes. In contrast, nDNA-encoded bioenergetic genes have a low mutation rate. However, their expression is modulated by histone phosphorylation and acetylation using mitochondrially-generated ATP and acetyl-CoA, which permits increased gene expression, growth, and reproduction when calories are abundant. Phosphorylation, acetylaton, and cellular redox state also regulate most signal transduction pathways and activities of multiple transcription factors. Thus, mtDNA mutations provide heritable and stable adaptation to regional differences while mitochondrially-mediated changes in the epigenome permit reversible modulation of gene expression in response to fluctuations in the energy environment. The most common genomic changes that interface with the environment and cause complex disease must, therefore, be mitochondrial and epigenomic in origin. © 2010 Wiley-Liss, Inc. Dev Disabil Res Rev 2010;16:114,119. [source] Vascular endothelium: the battlefield of dengue virusesFEMS IMMUNOLOGY & MEDICAL MICROBIOLOGY, Issue 3 2008Atanu Basu Abstract Increased vascular permeability without morphological damage to the capillary endothelium is the cardinal feature of dengue haemorrhagic fever (DHF)/dengue shock syndrome (DSS). Extensive plasma leakage in various tissue spaces and serous cavities of the body, including the pleural, pericardial and peritoneal cavities in patients with DHF, may result in profound shock. Among various mechanisms that have been considered include immune complex disease, T-cell-mediated, antibodies cross-reacting with vascular endothelium, enhancing antibodies, complement and its products, various soluble mediators including cytokines, selection of virulent strains and virus virulence, but the most favoured are enhancing antibodies and memory T cells in a secondary infection resulting in cytokine tsunami. Whatever the mechanism, it ultimately targets vascular endothelium (making it a battlefield) leading to severe dengue disease. Extensive recent work has been done in vitro on endothelial cell monolayer models to understand the pathophysiology of vascular endothelium during dengue virus (DV) infection that may be translated to help understand the pathogenesis of DHF/DSS. The present review provides a broad overview of the effects of DV infection and the associated host responses contributing towards alterations in vascular endothelial cell physiology and damage that may be responsible for the DHF/DSS. [source] Estimating haplotype relative risks in complex disease from unphased SNPs data in families using a likelihood adjusted for ascertainmentGENETIC EPIDEMIOLOGY, Issue 8 2006J. Carayol Abstract The understanding of complex diseases and insights to improve their medical management may be achieved through the deduction of how specific haplotypes may play a joint effect to change relative risk information. In this paper we describe an ascertainment adjusted likelihood-based method to estimate haplotype relative risks using pooled family data coming from association and/or linkage studies that were used to identify specific haplotypes. Haplotype-based analysis tends to require a large amount of parameters to capture all the information that leads to efficiency problems. An adaptation of the Stochastic Expectation Maximization algorithm is used for haplotypes inference from genotypic data and to reduce the number of nuisance parameters for risk estimation. Using different simulations, we show that this method provides unbiased relative risk estimates even in case of departure from Hardy-Weinberg equilibrium. Genet. Epidemiol. 2006. © 2006 Wiley-Liss, Inc. [source] Approaches to detecting gene × gene interaction in Genetic Analysis Workshop 14 pedigreesGENETIC EPIDEMIOLOGY, Issue S1 2005Brion S. Maher Abstract Whether driven by the general lack of success in finding single-gene contributions to complex disease, by increased knowledge about the potential involvement of specific biological interactions in complex disease, or by recent dramatic increases in computational power, a large number of approaches to detect locus × locus interactions were recently proposed and implemented. The six Genetic Analysis Workshop 14 (GAW14) papers summarized here each applied either existing or refined approaches with the goal of detecting gene × gene, or locus × locus, interactions in the GAW14 data. Five of six papers analyzed the simulated data; the other analyzed the Collaborative Study on the Genetics of Alcoholism data. The analytic strategies implemented for detecting interactions included multifactor dimensionality reduction, conditional linkage analysis, nonparametric linkage correlation, two-locus parametric linkage analysis, and a joint test of linkage and association. Overall, most of the groups found limited success in consistently detecting all of the simulated interactions due, in large part, to the nature of the generating model. Genet. Epidemiol. 29(Suppl. 1):S116,S119, 2005. © 2005 Wiley-Liss, Inc. [source] Analysis of single-locus tests to detect gene/disease associations,GENETIC EPIDEMIOLOGY, Issue 3 2005Kathryn Roeder Abstract A goal of association analysis is to determine whether variation in a particular candidate region or gene is associated with liability to complex disease. To evaluate such candidates, ubiquitous Single Nucleotide Polymorphisms (SNPs) are useful. It is critical, however, to select a set of SNPs that are in substantial linkage disequilibrium (LD) with all other polymorphisms in the region. Whether there is an ideal statistical framework to test such a set of ,tag SNPs' for association is unknown. Compared to tests for association based on frequencies of haplotypes, recent evidence suggests tests for association based on linear combinations of the tag SNPs (Hotelling T2 test) are more powerful. Following this logical progression, we wondered if single-locus tests would prove generally more powerful than the regression-based tests? We answer this question by investigating four inferential procedures: the maximum of a series of test statistics corrected for multiple testing by the Bonferroni procedure, TB, or by permutation of case-control status, TP; a procedure that tests the maximum of a smoothed curve fitted to the series of of test statistics, TS; and the Hotelling T2 procedure, which we call TR. These procedures are evaluated by simulating data like that from human populations, including realistic levels of LD and realistic effects of alleles conferring liability to disease. We find that power depends on the correlation structure of SNPs within a gene, the density of tag SNPs, and the placement of the liability allele. The clearest pattern emerges between power and the number of SNPs selected. When a large fraction of the SNPs within a gene are tested, and multiple SNPs are highly correlated with the liability allele, TS has better power. Using a SNP selection scheme that optimizes power but also requires a substantial number of SNPs to be genotyped (roughly 10,20 SNPs per gene), power of TP is generally superior to that for the other procedures, including TR. Finally, when a SNP selection procedure that targets a minimal number of SNPs per gene is applied, the average performances of TP and TR are indistinguishable. Genet. Epidemiol. © 2005 Wiley-Liss, Inc. [source] Heterogeneity testing in meta-analysis of genome searchesGENETIC EPIDEMIOLOGY, Issue 2 2005Elias Zintzaras Abstract Genome searches for identifying susceptibility loci for the same complex disease often give inconclusive or inconsistent results. Genome Search Meta-analysis (GSMA) is an established non-parametric method to identify genetic regions that rank high on average in terms of linkage statistics (e.g., lod scores) across studies. Meta-analysis typically aims not only to obtain average estimates, but also to quantify heterogeneity. However, heterogeneity testing between studies included in GSMA has not been developed yet. Heterogeneity may be produced by differences in study designs, study populations, and chance, and the extent of heterogeneity might influence the conclusions of a meta-analysis. Here, we propose and explore metrics that indicate the extent of heterogeneity for specific loci in GSMA based on Monte Carlo permutation tests. We have also developed software that performs both the GSMA and the heterogeneity testing. To illustrate the concept, the proposed methodology was applied to published data from meta-analyses of rheumatoid arthritis (4 scans) and schizophrenia (20 scans). In the first meta-analysis, we identified 11 bins with statistically low heterogeneity and 8 with statistically high heterogeneity. The respective numbers were 9 and 6 for the schizophrenia meta-analysis. For rheumatoid arthritis, bins 6.2 (the HLA region that is a well-documented susceptibility locus for the disease) and 16.3 (16q12.2-q23.1) had both high average ranks and low between-study heterogeneity. For schizophrenia, this was seen for bin 3.2 (3p25.3-p22.1) and heterogeneity was still significantly low after adjusting for its high average rank. Concordance was high between the proposed metrics and between weighted and unweighted analyses. Data from genome searches should be synthesized and interpreted considering both average ranks and heterogeneity between studies. Genet. Epidemiol. 28:123,137, 2005. © 2004 Wiley-Liss, Inc. [source] Issues concerning association studies for fine mapping a susceptibility gene for a complex disease,GENETIC EPIDEMIOLOGY, Issue 4 2001Norman Kaplan Abstract The usefulness of association studies for fine mapping loci with common susceptibility alleles for complex genetic diseases in outbred populations is unclear. We investigate this issue for a battery of tightly linked anonymous genetic markers spanning a candidate region centered around a disease locus, and study the joint behavior of chi-square statistics used to discover and to localize the disease locus. We used simulation methods based on a coalescent process with mutation, recombination, and genetic drift to examine the spatial distribution of markers with large noncentrality parameters in a case-control study design. Simulations with a disease allele at intermediate frequency, presumably representing an old mutation, tend to exhibit the largest noncentrality parameter values at markers near the disease locus. In contrast, simulations with a disease allele at low frequency, presumably representing a young mutation, often exhibit the largest noncentrality parameter values at markers scattered over the candidate region. In the former cases, sample sizes or marker densities sufficient to detect association are likely to lead to useful localization, whereas, in the latter case, localization of the disease locus within the candidate region is much less likely, regardless of the sample size or density of the map. The effects of increasing sample size or marker density are also investigated. Based upon a single marker analysis, we find that a simple strategy of choosing the marker with the smallest associated P value to begin a laboratory search for the disease locus performs adequately for a common disease allele. We also investigated a strategy of pooling nearby sites to form multiple allele markers. Using multiple degree of freedom chi-square tests for two or three nearby sites, we found no clear advantage of this form of pooling over a single marker analysis. Genet. Epidemiol. 20:432,457, 2001. Published by Wiley-Liss, 2001. [source] Molecular mechanisms of hepatocellular carcinoma,HEPATOLOGY, Issue 6 2008Rajagopal N. Aravalli Hepatocellular carcinoma (HCC) typically has poor prognosis, because it is often diagnosed at an advanced stage. Heterogeneous phenotypic and genetic traits of affected individuals and a wide range of risk factors have classified it a complex disease. HCC is not amenable to standard chemotherapy and is resistant to radiotherapy. In most cases, surgical resection and liver transplantation remain the only curative treatment options. Therefore, development of novel, effective therapies is of prime importance. Extensive research over the past decade has identified a number of molecular biomarkers as well as cellular networks and signaling pathways affected in liver cancer. Recent studies using a combination of "omics" technologies, microRNA studies, combinatorial chemistry, and bioinformatics are providing new insights into the gene expression and protein profiles during various stages of the disease. In this review, we discuss the contribution of these newer approaches toward an understanding of molecular mechanisms of HCC and for the development of novel cancer therapeutics. (HEPATOLOGY 2008;48:2047-2063.) [source] The G51S purine nucleoside phosphorylase polymorphism is associated with cognitive decline in Alzheimer's disease patientsHUMAN PSYCHOPHARMACOLOGY: CLINICAL AND EXPERIMENTAL, Issue 2 2007Emanuela Tumini Abstract Alzheimer's disease (AD) is a polygenic and multifactorial complex disease, whose etiopathology is still unclear, however several genetic factors have shown to increase the risk of developing the disease. Purine nucleotides and nucleosides play an important role in the brain. Besides their role in neurotransmission and neuromodulation, they are involved in trophic factor release, apoptosis, and inflammatory responses. These mediators may also have a pivotal role in the control of neurodegenerative processes associated with AD. In this report the distribution of the exonic G/A single nucleotide polymorphism (SNP) in purine nucleoside phosphorylase (PNP) gene, resulting in the amino acid substitution serine to glycine at position 51 (G51S), was investigated in a large population of AD patients (n,=,321) and non-demented control (n,=,208). The PNP polymorphism distribution was not different between patients and controls. The polymorphism distribution was also analyzed in AD patients stratified according to differential progressive rate of cognitive decline during a 2-year follow-up. An increased representation of the PNP AA genotype was observed in AD patients with fast cognitive deterioration in comparison with that from patients with slow deterioration rate. Our findings suggest that the G51S PNP polymorphism is associated with a faster rate of cognitive decline in AD patients, highlighting the important role of purine metabolism in the progression of this neurodegenerative disorder. Copyright © 2007 John Wiley & Sons, Ltd. [source] IBD international genetics consortium: International cooperation making sense of complex diseaseINFLAMMATORY BOWEL DISEASES, Issue 3 2003Juleen A. Cavanaugh Ph.D. Abstract The Inflammatory Bowel Disease International Genetic Consortium was formed in Oxford in 1997. Since then it has grown to include twelve groups from around the world that are each actively involved in identifying the genes that are involved in susceptibility to IBD. The approach of the IBDIGC is to attempt to overcome one of the major issues in complex disease analysis,that of obtaining sufficient power to analyze successfully the inheritance of IBD,by collaboratively studying large numbers of well documented families with multiple affected individuals. This strategy has been marked by considerable success with the publication of a paper authored by the IBDIGC substantiating the localization of IBD1 to chromosome 16. This publication served to encourage researchers and eventually resulted in the identification by several groups simultaneously of risk alleles in the NOD2 gene that cosegregate with disease. The IBDIGC provides a model for studies in complex disease genetics, showing that research groups both large and small can participate equally in complex disease gene identification through the formation of large international consortia. [source] Genetic association analysis: a primer on how it works, its strengths and its weaknessesINTERNATIONAL JOURNAL OF ANDROLOGY, Issue 6 2008Laura Rodriguez-Murillo Summary Currently, the most used approach to mapping disease genes is the genome wide association study, using large samples of cases and controls and hundreds of thousands of markers spread throughout the genome. This review focuses in explaining how an association study works, its strengths and its weaknesses, and the methods available to analyse the data. Issues related to sample size, genetic effect sizes, epistasis, replication and population stratification are specifically addressed, issues that an investigator must take into account when planning an association study of any complex disease. Finally, we include some special features concerning association studies in the Y chromosome, and we contrast the analysis characteristics of linkage and association. [source] High levels of anxiety and depression have a negative effect on quality of life of women with chronic pelvic painINTERNATIONAL JOURNAL OF CLINICAL PRACTICE, Issue 5 2009A. P. M. S. Romão Summary Background:, Chronic pelvic pain (CPP) is a common and complex disease whose cause is often clinically inexplicable, with consequent difficulty in diagnosis and treatment. Patients with CPP have high levels of anxiety and depression, with a consequent impairment of their quality of life. Aims:, The objective of this study was to determine the prevalence of anxiety and depression and their impact on the quality of life of women with CPP. Materials and methods:, A cross-sectional controlled study was conducted on 52 patients with CPP and 54 women without pain. Depression and anxiety were evaluated by the Hospital Anxiety and Depression Scale, and quality of life was evaluated by the World Health Organization Quality of life Whoqol-bref questionnaire. Data were analysed statistically by the Mann-Whitney U -test, the Fisher exact test, chi-square test and Spearman correlation test. Results:, The prevalence of anxiety was 73% and 37% in the CPP and control groups, respectively, and the prevalence of depression was 40% and 30% respectively. Significant differences between groups were observed in the physical, psychological and social domains. Patients with higher anxiety and depression scores present lower quality of life scores. Discussion:, The fact that DPC is a syndromic complex, many patients enter a chronic cycle of search for improvement of medical symptoms. The constant presence of pain may be responsible for affective changes in dynamics, family, social and sexual. Initially the person is facing the loss of a healthy body and active, to a state of dependence and limitations. In this study, patients with higher scores of anxiety and depression scores had lower quality of life and patients with lower scores of anxiety and depression had scores of quality of life. These results show that perhaps the depression and anxiety may be related to the negative impact on quality of life of these patients. Conclusion:, In view of this association, we emphasise the importance of a specific approach to the treatment of anxiety and depression together with clinical treatment to improve the quality of life of these patients. [source] Human MHC architecture and evolution: implications for disease association studiesINTERNATIONAL JOURNAL OF IMMUNOGENETICS, Issue 3 2008J. A. Traherne Summary Major histocompatibility complex (MHC) variation is a key determinant of susceptibility and resistance to a large number of infectious, autoimmune and other diseases. Identification of the MHC variants conferring susceptibility to disease is problematic, due to high levels of variation and linkage disequilibrium. Recent cataloguing and analysis of variation over the complete MHC has facilitated localization of susceptibility loci for autoimmune diseases, and provided insight into the MHC's evolution. This review considers how the unusual genetic characteristics of the MHC impact on strategies to identify variants causing, or contributing to, disease phenotypes. It also considers the MHC in relation to novel mechanisms influencing gene function and regulation, such as epistasis, epigenetics and microRNAs. These developments, along with recent technological advances, shed light on genetic association in complex disease. [source] Approaching risk assessment of complex disease development in horse chestnut trees: a chemical ecologist's perspectiveJOURNAL OF APPLIED ENTOMOLOGY, Issue 5 2008A. B. Johne Abstract The chemo-ecological predispositions were investigated for the development of a complex disease on the basis of an insect,fungus mutualism using the system of horse chestnuts (Aesculus hippocastanum and Aesculus x carnea), the horse chestnut leaf miner (Cameraria ohridella) and the biotrophic powdery mildew (Erysiphe flexuosa). Both C. ohridella and E. flexuosa can appear on the same horse chestnut leaf tissue simultaneously. The olfactory detection of fungal infection by the insect, its ability to discriminate the potentially mutualistic fungus from other fungi and the impact of fungal infection on insect oviposition were examined. Gas chromatography coupled with mass spectroscopic and electroantennographic detection by C. ohridella (GC-MS/EAD) was used to assess the olfactory detection of fungal-infected A. hippocastanum and A. x carnea leaves by C. ohridella. Infection-related compounds, such as benzyl alcohol, dodecane, tridecane and methyl salicylate as well as fungus-related C8 compounds, are perceived by C. ohridella. The discrimination of E. flexuosa from another phytopathogenic fungus, such as Guignardia aesculi, is based primarily on the differing pattern of C8 compounds of these fungi. Oviposition on fungal-infected leaves of A. hippocastanum and leaves treated with fungal-related compounds showed that C. ohridella is able to respond to the modifications in the leaf volatile profiles of horse chestnuts caused by the different fungal infections. Thus, from the perception point of view, the necessary predispositions for the development of a close insect,fungus relation between the biotrophic fungus E. flexuosa and the leaf-mining insect C. ohridella are fulfilled. However, decreased oviposition on infected leaves does not enhance the selective contact between the species. As a consequence, an important predisposition for forming an insect,fungus mutualism is not fulfilled by these two species and, according to this approach, the risk of forming a complex disease can be assessed as low. [source] Molecular staging of gastric cancerJOURNAL OF GASTROENTEROLOGY AND HEPATOLOGY, Issue 6 2008Yan Jie Zhang Abstract Gastric cancer has traditionally been staged using purely histological methods, but these methods provide little information about the biology of gastric cancer and have limited predictive power. Recent studies have shown that clinically relevant gastric cancer subtypes have distinct gene expression profiles. This approach, termed molecular staging, can lead to the discovery of novel diagnostic and prognostic biomarkers of gastric cancers. This update reviews advances in molecular staging of gastric cancer and discusses their implications for the prognosis and diagnosis of this complex disease. Technologies used in molecular staging as well as future directions for the optimization of molecular staging of gastric cancer are also discussed. [source] Genome-Wide Association Study of Alcohol Dependence Implicates a Region on Chromosome 11ALCOHOLISM, Issue 5 2010Howard J. Edenberg Background:, Alcohol dependence is a complex disease, and although linkage and candidate gene studies have identified several genes associated with the risk for alcoholism, these explain only a portion of the risk. Methods:, We carried out a genome-wide association study (GWAS) on a case,control sample drawn from the families in the Collaborative Study on the Genetics of Alcoholism. The cases all met diagnostic criteria for alcohol dependence according to the Diagnostic and Statistical Manual of Mental Disorders,Fourth Edition; controls all consumed alcohol but were not dependent on alcohol or illicit drugs. To prioritize among the strongest candidates, we genotyped most of the top 199 single nucleotide polymorphisms (SNPs) (p , 2.1 × 10,4) in a sample of alcohol-dependent families and performed pedigree-based association analysis. We also examined whether the genes harboring the top SNPs were expressed in human brain or were differentially expressed in the presence of ethanol in lymphoblastoid cells. Results:, Although no single SNP met genome-wide criteria for significance, there were several clusters of SNPs that provided mutual support. Combining evidence from the case,control study, the follow-up in families, and gene expression provided strongest support for the association of a cluster of genes on chromosome 11 (SLC22A18, PHLDA2, NAP1L4, SNORA54, CARS, and OSBPL5) with alcohol dependence. Several SNPs nominated as candidates in earlier GWAS studies replicated in ours, including CPE, DNASE2B, SLC10A2, ARL6IP5, ID4, GATA4, SYNE1, and ADCY3. Conclusions:, We have identified several promising associations that warrant further examination in independent samples. [source] Many asthma patients experience persistent symptoms despite appropriate clinical and guideline-based treatment with inhaled corticosteroidsJOURNAL OF THE AMERICAN ACADEMY OF NURSE PRACTITIONERS, Issue 9 2007Joan Mogil MSN, NP-C (Nurse Practitioner) Abstract Purpose: To review possible reasons for persistence of asthma symptoms despite appropriate use of clinical and guideline-based treatments, including the use of inhaled corticosteroids. Data sources: Review of the worldwide scientific literature on factors related to persistent symptoms in patients with asthma. Conclusions: Patients with asthma may not respond as expected to therapy because of factors that include poor adherence, improper inhaler technique, persistent exposure to symptom triggers, and limitations of current standard therapy, including steroid insensitivity or the steroid plateau effect. Persistent symptoms may also be associated with IgE-mediated airway inflammation, as current standard asthma therapies do not directly address the IgE-mediated component of the inflammatory cascade. Asthma is a complex disease and its treatment requires the full cooperation and participation of the patient. Implications for practice: Healthcare professionals can play a key role by educating patients and their family members about the nature of asthma and rationale for treatment, supporting the importance of strict adherence to prevention measures and the prescribed treatment regimen. [source] A quantitative genetic analysis of intermediate asthma phenotypesALLERGY, Issue 3 2009S. F. Thomsen Aim:, To study the relative contribution of genetic and environmental factors to the correlation between exhaled nitric oxide (FeNO), airway responsiveness, airway obstruction, and serum total immunoglobulin E (IgE). Methods:, Within a sampling frame of 21 162 twin subjects, 20,49 years of age, from the Danish Twin Registry, a total of 575 subjects (256 intact pairs and 63 single twins) who either themselves and/or their co-twins reported a history of asthma at a nationwide questionnaire survey, were clinically examined. Traits were measured using standard techniques. Latent factor models were fitted to the observed data using maximum likelihood methods. Results:, Additive genetic factors explained 67% of the variation in FeNO, 43% in airway responsiveness, 22% in airway obstruction, and 81% in serum total IgE. In general, traits had genetically and environmentally distinct variance structures. The most substantial genetic similarity was observed between FeNO and serum total IgE, genetic correlation (,A) = 0.37, whereas the strongest environmental resemblance was observed between airway responsiveness and airway obstruction, specific environmental correlation (,E) = ,0.46, and between FeNO and airway responsiveness, ,E = 0.34. Conclusions:, Asthma is a complex disease characterized by a set of etiologically heterogeneous biomarkers, which likely constitute diverse targets of intervention. [source] Implementing the severe sepsis care bundles outside the ICU by outreachNURSING IN CRITICAL CARE, Issue 5 2007Chris Carter Abstract Sepsis is not a new challenge facing the health care team, it remains a complex disease, which is difficult to identify and treat. Mortality from sepsis remains high and continues to be a common cause of death among critically ill patients, despite advances in critical care. Sepsis accounts for an estimated 27% of all intensive care admissions in England, Wales and Northern Ireland, and accounted for 46% of all intensive care bed days. Recent research studies and the surviving sepsis campaign have shown that identifying and providing key interventions to patients with severe sepsis and septic shock prior to their admission to the intensive care unit significantly improve outcomes. The aim of this paper was to identify how the Critical Care Outreach Team at one local hospital implemented the severe sepsis resuscitation care bundle for patients in the emergency department (ED) and on the general wards. It will include a presentation on the various ways the team raised the profile of severe sepsis and the care bundle at hospital and at national level. It also includes audit data that have been collected. The results showed that if the resuscitation care bundle was implemented within the first 24 h of hospital admission, mortality was 29%, whereas if the care bundle was instigated after this time mortality was more than at 49%. Audit data showed that the commonest sign of severe sepsis seen in patients in the ED and on wards was tachypnoea. This article discusses the successful implementation of the severe sepsis resuscitation care bundle and the positive impact an Outreach team can have in changing practice in the way patients are managed with severe sepsis. The audit data support the need for regular physiological observations and the use of a Patient At Risk Trigger scoring tool to identify patients at risk of deterioration. This allows referral to the Outreach team, who assess the patient and if appropriate initiate the care bundle. [source] Downregulation of CD36 results in reduced phagocytic ability of peritoneal macrophages of women with endometriosis,THE JOURNAL OF PATHOLOGY, Issue 2 2009Pei-Chin Chuang Abstract Endometriosis, defined as the growth of endometrial tissues outside of the uterine cavity, is a severe and complex disease affecting more than 10% of women. The aetiology of endometriosis is unclear but immune dysfunction might be an important factor for its development. The natural function of the immune system is to detect and destroy aberrant or abnormal cells. Failure of the immune system to eradicate these aberrant cells often results in disease pathogenesis. We report here that the phagocytic ability of macrophages is reduced in peritoneal macrophages isolated from women with endometriosis. In-depth investigation revealed that the level of CD36, a class B scavenger receptor, in peritoneal macrophages derived from women with endometriosis was lower than that in normal macrophages. Blockage of CD36 function by neutralized antibody or knocking down CD36 using siRNA impaired the phagocytic ability of normal macrophages. In contrast, forced expression of CD36 in macrophages isolated from women with endometriosis restored phagocytic ability. Taken together, we identified that the scavenger receptor CD36 is reduced in the peritoneal macrophages of women with endometriosis, which leads to a decrease of the phagocytic ability of macrophages. These findings revealed a potential mechanism of immune dysfunction during endometriosis development. Copyright © 2009 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd. [source] Two-sample Comparison Based on Prediction Error, with Applications to Candidate Gene Association StudiesANNALS OF HUMAN GENETICS, Issue 1 2007K. Yu Summary To take advantage of the increasingly available high-density SNP maps across the genome, various tests that compare multilocus genotypes or estimated haplotypes between cases and controls have been developed for candidate gene association studies. Here we view this two-sample testing problem from the perspective of supervised machine learning and propose a new association test. The approach adopts the flexible and easy-to-understand classification tree model as the learning machine, and uses the estimated prediction error of the resulting prediction rule as the test statistic. This procedure not only provides an association test but also generates a prediction rule that can be useful in understanding the mechanisms underlying complex disease. Under the set-up of a haplotype-based transmission/disequilibrium test (TDT) type of analysis, we find through simulation studies that the proposed procedure has the correct type I error rates and is robust to population stratification. The power of the proposed procedure is sensitive to the chosen prediction error estimator. Among commonly used prediction error estimators, the .632+ estimator results in a test that has the best overall performance. We also find that the test using the .632+ estimator is more powerful than the standard single-point TDT analysis, the Pearson's goodness-of-fit test based on estimated haplotype frequencies, and two haplotype-based global tests implemented in the genetic analysis package FBAT. To illustrate the application of the proposed method in population-based association studies, we use the procedure to study the association between non-Hodgkin lymphoma and the IL10 gene. [source] What role for genetics in the prediction of multiple sclerosis?ANNALS OF NEUROLOGY, Issue 1 2010Stephen Sawcer PhD For most of us, the foundations of our understanding of genetics were laid by considering Mendelian diseases in which familial recurrence risks are high, and mutant alleles are both necessary and sufficient. One consequence of this deterministic teaching is that our conceptualization of genetics tends to be dominated by the notion that the genetic aspects of disease are caused by rare alleles exerting large effects. Unfortunately, the preconceptions that flow from this training are frequently erroneous and misleading in the context of common traits, where familial recurrence risks are modest, and for the most part the relevant alleles are neither rare, necessary, nor sufficient. For these common traits, the genetic architecture is far more complex, with susceptibility rather than causality resulting from the combined effects of many alleles, each exerting only a modest effect on risk. None of these alleles is sufficient to cause disease on its own, and none is essential for the development of disease. Furthermore, most are carried by large sections of the population, the vast majority of which does not develop the disease. One consequence of our innate belief in the Mendelian paradigm is that we have an inherent expectation that knowledge about the genetic basis for a disease should allow genetic testing and thereby accurate risk prediction. There is an inevitable feeling that the same should be true in complex disease, but is it? ANN NEUROL 2010;67:3,10 [source] Lack of effect of a single injection of human C-reactive protein on murine lupus or nephrotoxic nephritisARTHRITIS & RHEUMATISM, Issue 1 2010Francesco Carlucci Objective It has been reported that a single dose of human C-reactive protein (CRP) can prevent and reverse the renal damage in murine models of spontaneous lupus, as well as the rapid-onset immune complex disease induced in the accelerated nephrotoxic nephritis (ANTN) model. This study was undertaken to attempt to replicate these observations using a highly purified and fully characterized human CRP preparation. Methods (NZB × NZW)F1 (NZB/NZW) mice were treated with a single 200-,g subcutaneous injection of CRP or control reagents either before disease onset at 4 months of age or when high-grade proteinuria was present at 7 months of age. Mice were monitored at least monthly for proteinuria and autoantibody levels. ANTN was induced by preimmunizing C57BL/6 mice with sheep IgG, followed 5 days later by injection of sheep anti-mouse glomerular basement membrane antibody and CRP or control reagents. Renal disease was assessed by regular urinalysis and histologic evaluation. Results CRP treatment of NZB/NZW mice, either early or late in the disease, had no effect on proteinuria, autoantibody titers, or survival. CRP administration did not reduce renal injury or alter disease in the ANTN model. Human serum amyloid P component, a pentraxin protein that is very closely related to CRP, similarly had no effect. Conclusion Our completely negative observations do not confirm that human CRP has reproducible antiinflammatory or immunomodulatory effects in these murine models, nor do they support the suggestion that CRP might be useful for therapy of lupus or immune complex,mediated nephritis. [source] Many faces of graft- versus -host diseaseAUSTRALASIAN JOURNAL OF DERMATOLOGY, Issue 1 2010Pablo F Peñas ABSTRACT Allogeneic haematopoietic stem cell transplantation is increasingly used in the treatment of malignant and non-malignant disorders. Despite ongoing advances in the field, morbidity and mortality related to graft- versus -host disease remains a major barrier to its application. Graft- versus -host disease is a difficult-to-diagnose disease. Dermatologists are involved due to its diverse cutaneous expression. In order to appropriately diagnose, classify and treat this complex disease, knowledge of its expanding cutaneous expression is required. This review provides a synopsis of the clinical manifestations of acute, lichenoid and sclerodermatous phases of graft- versus -host disease with a look at the current evidence surrounding its differential diagnosis. [source] | |||||||||||||||||||||||||||||||