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Results for “complex diseases”

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At least 649 records · Page 36Linked to original sources
PubMed2005

Complex diseases in gastroenterology and hepatology: GERD, Barrett's, and esophageal adenocarcinoma.

Gastroesophageal reflux disease, Barrett's esophagus, and esophageal adenocarcinoma are related diseases with environmental and genetic determinants. The genetic changes are relevant in 2 distinct ways. First, there are heritable variations in germline DNA that may influence the individual susceptibility to cancer. Second, there is an accumulation of somatic-cell genetic and epigenetic changes within the epithelium during the metaplasia-dysplasia-carcinoma sequence, which may be an important determinant for the likelihood for cancer progression. Esophageal cancer occurring in the context of a familial syndrome is rare and most cases are sporadic. The sporadic cases still may have heritable germline influences, but these are likely to involve multiple, low-penetrance susceptibility genes. To date, the relative contribution and identity of such genes are unknown. However, in the future the identification of susceptibility genes could have important public health implications for patient management. With regard to the epithelium, a map gradually is being created of the frequently occurring alterations. Some of these changes are critical whereas others are bystanders. As well as the identification of abnormalities in target genes, it also is possible to determine the global gene expression profile of these diseases and to correlate this profile with clinical outcome. It is hoped that these complementary approaches will enable patients to be stratified in terms of their cancer risk so that prevention, surveillance, and treatment strategies can be targeted appropriately. At the current time, genetics does not influence routine clinical management of patients with gastroesophageal reflux disease, Barrett's esophagus, or esophageal adenocarcinoma.

Adenocarcinoma↗
PubMed2002

Accurate power approximations for chi2-tests in case-control association studies of complex disease genes.

A popular method for the analysis of case-control association studies is to compare the frequencies of the alleles between cases and controls by means of Pearson's chi2-statistic. Here, an approach for computing the power of this test is presented, which by computer simulation is shown to be more reliable than a previously published power approximation. Since the test based on Pearson's chi2- statistic can be anti-conservative if there is an excess of homozygotes for the susceptibility allele in the general population, it has been proposed to analyze case-control association studies by means of a trend test based on genotypes instead of alleles. We present an accurate power approximation for the trend test. The power approximations are implemented in an available computer program 'GenOdyPower', which in addition has an option to determine the empirical power of these tests by simulations.

Algorithms↗
PubMed2002

Diabetic flies? Using Drosophila melanogaster to understand the causes of monogenic and genetically complex diseases.

Approximately three-quarters of human disease loci have counterparts in the fruit fly Drosophila melanogaster. This model organism is therefore extremely valuable for using to understand the role of these loci in normal development, and for unravelling genetic pathways in which these loci take part. Important advantages for Drosophila in such studies are its completed genome, the unparalleled collection of mutations already in existence, the relative ease in which new mutations can be generated, the existence of convenient techniques for inactivating or overexpressing genes in dispensable tissues that are easily observed and measured, and the ability to readily carry out second-site modifier genetics. Recent work in Drosophila on the insulin-signaling pathway, a pathway of profound clinical importance, is reviewed as an illustration of how such research can provide fundamental insights into the functions of this pathway in regulating growth and development. Moreover, Drosophila research is now identifying heretofore unknown regulators of insulin signaling, as well as indicating novel functions for this pathway in suppressing benign tumor formation and regulating life span.

Animals↗
PubMed2001

Association study designs for complex diseases.

Assessing the association between DNA variants and disease has been used widely to identify regions of the genome and candidate genes that contribute to disease. However, there are numerous examples of associations that cannot be replicated, which has led to skepticism about the utility of the approach for common conditions. With the discovery of massive numbers of genetic markers and the development of better tools for genotyping, association studies will inevitably proliferate. Now is the time to consider critically the design of such studies, to avoid the mistakes of the past and to maximize their potential to identify new components of disease.

Genetic Diseases, Inborn↗
PubMed2004

Mapping complex disease loci in whole-genome association studies.

Identification of the genetic polymorphisms that contribute to susceptibility for common diseases such as type 2 diabetes and schizophrenia will aid in the development of diagnostics and therapeutics. Previous studies have focused on the technique of genetic linkage, but new technologies and experimental resources make whole-genome association studies more feasible. Association studies of this type have good prospects for dissecting the genetics of common disease, but they currently face a number of challenges, including problems with multiple testing and study design, definition of intermediate phenotypes and interaction between polymorphisms.

Disease↗
PubMed2005

Many little things: one geneticist's view of complex diseases.

Gene targeting is commonly used to knock out genes in order to understand their function. It has also been used successfully to model the relatively rare human genetic diseases that are caused by homozygous loss of gene function. Modelling the much more common multifactorial diseases that have strong genetic and environmental causes is less easy. Here, I describe my personal voyage into this challenging field, using gene targeting to alter the expression of genes that impact on hypertension and diabetes.

Animals↗
PubMed2006

Inborn errors of metabolism: the flux from Mendelian to complex diseases.

Inborn errors of metabolism are characterized by dysregulation of the metabolic networks that underlie development and homeostasis, and constitute an important and expanding group of genetic disorders in humans. Diagnostic methods that are based on molecular genetic tools have a limited ability to correlate phenotypes with subtle changes in metabolic fluxes. We argue that the direct and dynamic measurement of metabolite flux will facilitate the integration of environmental, genetic and biochemical factors with phenotypic information. Ultimately, this integration will lead to new diagnostic and therapeutic approaches that are focused on the manipulation of these pathways.

Forecasting↗