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Results for “genomics of complex diseases”

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At least 19 recordsLinked to original sources

PubMed1997

Factors influencing the identification of major genes in a complex disease genome scan.

A two-stage linkage strategy was employed to identify major genes for a simulated complex disease via a genome scan. The importance of several approaches for improving the ability to locate major genes has been illustrated. These approaches are: adjusting for covariates, ascertaining through multiple affected family members, increasing the sample size, and using multipoint linkage analysis.

Chromosome Mapping↗

PubMed2003

Genetic and cytogenetic analyses of breast cancer yield different perspectives of a complex disease.

Genomic instability in breast cancer results in low-level changes in DNA copy number, a significant but poorly understood mechanism underlying the genetic heterogeneity of this disorder. Two different approaches, loss of heterozygosity (LOH) and comparative genomic hybridization (CGH), have been used to probe the genetics of breast cancer evolution. LOH is a locus specific method that detects the variation in the parental origin of DNA, but is not quantitative. CGH provides a genome-wide accounting of the magnitude of DNA copy number changes, but not parental origin. Both methods have identified complex and heterogeneous patterns of DNA losses, duplications, and amplifications during breast cancer evolution. LOH and CGH technologies interrogate very distinct mechanisms driving breast tumor evolution, yet are seldom used in parallel to profile specimens. Thus, the relative significance of genetic versus numerical variations of DNA in breast cancer evolution remains undefined. This review will attempt to summarize some of the successes of these investigations, highlight some complex and confounding observations emerging from these studies, and discuss the potential of these studies to improve our understanding of breast cancer biology and treatment.

Breast Neoplasms↗

PubMed2005

Genomic epidemiology of complex disease: the need for an electronic evidence-based approach to research synthesis.

Modern microarray genotyping now permits simultaneous analysis of tens of thousands of polymorphisms, and this technology is being widely used to associate the role of genes with the etiology of complex disease. Genome-wide hypothesis-free mapping will also increasingly generate candidate genes that require further testing in association studies. At the same time, genetic effects are increasingly observed to be buffered by a wide array of biologic mechanisms that evolved to protect the genome from environmental insult and that serve to obscure observation of direct effects of polymorphisms on a disease phenotype. These two forces combine to make replication of genomic epidemiology extraordinarily difficult. Traditional research synthesis of emerging bodies of genomic epidemiology is problematic and often quickly outdated. The author proposes that electronic evidence-based methodology, perhaps modeled after that used by the Cochrane Collaboration in clinical medicine, would facilitate the systematic preparation and frequent updating of systematic reviews, which is essential for identifying valid and replicable gene-disease associations.

Chromosome Mapping↗

PubMed1998

Genetics of complex human diseases: genome screening, association studies and fine mapping.

Positional cloning has been applied successfully to many Mendelian disorders. Because of the public health significance, there is strong interest in mapping susceptibility genes for common disorders, such as asthma and allergy, that have a genetic component. Genome-wide screening has been very useful in detecting regions of the genome likely to contain susceptibility genes. There are multiple chromosomal regions implicated in asthma and now the difficult process of finding the genes and relevant mutations is underway. Two approaches that are being utilized are those of association studies in candidate genes, and haplotype sharing or identical by descent (IBD) mapping. Although these are useful approaches, it is important to realize the strengths and limitations of each. The level of significance needed for an initial study or a replication study should be considered in light of the prior evidence for studying a specific gene polymorphism. Haplotype-sharing approaches, although difficult to use in outbred heterogeneous populations, may provide important insight into fine mapping and gene localization.

Asthma↗

PubMed2003

A need for a 'whole-istic functional genomics' approach in complex human diseases: arthritis.

'Genomic tools', such as gene/protein chips, single nucleotide polymorphism and haplotype analyses, are empowering us to generate staggering amounts of correlative data, from human/animal genetics and from normal and disease-affected tissues obtained from complex diseases such as arthritis. These tools are transforming molecular biology into a 'data rich' science, with subjects with an '-omic' suffix. These disciplines have to converge and integrate at a systemic level to examine the structure and dynamics of cellular and organismal function ('functionomics') simultaneously, using a multidimensional approach for cells, tissues, organs, rodents and Zebra fish models, which intertwines various approaches and readouts to study the development and homeostasis of a system. In summary, the postgenomic era of functionomics will facilitate narrowing the bridge between correlative data and causative data, thus integrating 'intercoms' of interacting and interdependent disciplines and forming a unified whole.

Arthritis↗

PubMed2002

"A system biology" approach to bioinformatics and functional genomics in complex human diseases: arthritis.

Human and other annotated genome sequences have facilitated generation of vast amounts of correlative data, from human/animal genetics, normal and disease-affected tissues from complex diseases such as arthritis using gene/protein chips and SNP analysis. These data sets include genes/proteins whose functions are partially known at the cellular level or may be completely unknown (e.g. ESTs). Thus, genomic research has transformed molecular biology from "data poor" to "data rich" science, allowing further division into subpopulations of subcellular fractions, which are often given an "-omic" suffix. These disciplines have to converge at a systemic level to examine the structure and dynamics of cellular and organismal function. The challenge of characterizing ESTs linked to complex diseases is like interpreting sharp images on a blurred background and therefore requires a multidimensional screen for functional genomics ("functionomics") in tissues, mice and zebra fish model, which intertwines various approaches and readouts to study development and homeostasis of a system. In summary, the post-genomic era of functionomics will facilitate to narrow the bridge between correlative data and causative data by quaint hypothesis-driven research using a system approach integrating "intercoms" of interacting and interdependent disciplines forming a unified whole as described in this review for Arthritis.

Animals↗

PubMedDate not supplied

Canavan disease: a monogenic trait with complex genomic interaction.

Canavan disease (CD) is an inherited leukodystrophy, caused by aspartoacylase (ASPA) deficiency, and accumulation of N-acetylaspartic acid (NAA) in the brain. The gene for ASPA has been cloned and more than 40 mutations have been described, with two founder mutations among Ashkenazi Jewish patients. Screening of Ashkenazi Jews for these two common mutations revealed a high carrier frequency, approximately 1/40, so that programs for carrier testing are currently in practice. The enzyme deficiency in CD interferes with the normal hydrolysis of NAA, which results in disruption of myelin and spongy degeneration of the white matter of the brain. The clinical features of the disease are macrocephaly, head lag, progressive severe mental retardation, and hypotonia in early life, which later changes to spasticity. A knockout mouse for CD has been generated, and used to study the pathophysiological basis for CD. Findings from the knockout mouse indicate that this monogenic trait leads to a series of genomic interaction in the brain. Changes include low levels of glutamate and GABA. Microarray expression analysis showed low level of expression of GABA-A receptor (GABRA6) and glutamate transporter (EAAT4). The gene Spi2, a gene involved in apoptosis and cell death, showed high level of expression. Such complexity of gene interaction results in the phenotype, the proteome, with spongy degeneration of the brain and neurological impairment of the mouse, similar to the human counterpart. Aspartoacylase gene transfer trial in the mouse brain using adenoassociated virus (AAV) as a vector are encouraging showing improved myelination and decrease in spongy degeneration in the area of the injection and also beyond that site.

Amidohydrolases↗

PubMed2005

Characteristics and regulatory elements defining constitutive splicing and different modes of alternative splicing in human and mouse.

Alternative splicing is a major contributor to genomic complexity, disease, and development. Previous studies have captured some of the characteristics that distinguish alternative splicing from constitutive splicing. However, most published work only focuses on skipped exons and/or a single species. Here we take advantage of the highly curated data in the MAASE database (see related paper in this issue) to analyze features that characterize different modes of splicing. Our analysis confirms previous observations about alternative splicing, including weaker splicing signals at alternative splice sites, higher sequence conservation surrounding orthologous alternative exons, shorter exon length, and more frequent reading frame maintenance in skipped exons. In addition, our study reveals potentially novel regulatory principles underlying distinct modes of alternative splicing and a role of a specific class of repeat elements (transposons) in the origin/evolution of alternative exons. These features suggest diverse regulatory mechanisms and evolutionary paths for different modes of alternative splicing.

Alternative Splicing↗

PubMed2001

Evolution of the simulated data problem.

The simulated data problem was designed via an interactive process by the Simulation Problem Organizing Committee and the selected data simulators. Based on discussions at the previous Genetic Analysis Workshop, many of the features of previous simulation problems, such as a complex disease, genome scan, and replication, were retained and in addition, a population genetics model was used to generate the simulated genes. We describe the process that was used to structure the problem and summarize the discussions about many of the scientific issues that were considered.

Chromosome Mapping↗

PubMed2023

The multi-functional Smc5/6 complex in genome protection and disease.

Structural maintenance of chromosomes (SMC) complexes are ubiquitous genome regulators with a wide range of functions. Among the three types of SMC complexes in eukaryotes, cohesin and condensin fold the genome into different domains and structures, while Smc5/6 plays direct roles in promoting chromosomal replication and repair and in restraining pathogenic viral extra-chromosomal DNA. The importance of Smc5/6 for growth, genotoxin resistance and host defense across species is highlighted by its involvement in disease prevention in plants and animals. Accelerated progress in recent years, including structural and single-molecule studies, has begun to provide greater insights into the mechanisms underlying Smc5/6 functions. Here we integrate a broad range of recent studies on Smc5/6 to identify emerging features of this unique SMC complex and to explain its diverse cellular functions and roles in disease pathogenesis. We also highlight many key areas requiring further investigation for achieving coherent views of Smc5/6-driven mechanisms.

Animals↗

PubMed2006

Genomics and complex liver disease: Challenges and opportunities.

The concept of genetic susceptibility in the contribution to human disease is not new. What is new is the emerging ability of the field of genomics to detect, assess, and interpret genetic variation in the study of susceptibility to development of disease. Deciphering the human genome sequence and the publication of the human haplotype map are key elements of this effort. However, we are only beginning to understand the contribution of genetic predisposition to complex liver disease through its interaction with environmental risk factors. In the coming decade, we anticipate the development of human studies to better dissect the genotype/phenotype relationship of complex liver diseases. This endeavor will require large, well-phenotyped patient populations of each disease of interest and proper study designs aimed at answering important questions of hepatic disease prognosis, pathogenesis, and treatment. Teamwork between patients, physicians, and genomics scientists can ensure that this opportunity leads to important biological discoveries and improved treatment of complex disease.

Cholangitis, Sclerosing↗

PubMed1994

LABMAN and LINKMAN: a data management system specifically designed for genome searches of complex diseases.

Two programs have been developed to manage linkage analysis data. The first program, LABMAN, is a comprehensive laboratory data management system organizing pedigrees, blood DNA samples, DNA markers, Southern blot or polyacrylamide gels, autoradiographs, and marker-allele typings generated from these samples. Output includes mendelization checks for genetic incompatibilities in typings and formatted files ready for linkage analysis. LABMAN can also compress highly polymorphic allele systems into smaller allele systems facilitating analysis of large systems. The second program, LINKMAN, provides data management for lod score output from linkage analyses. It reads linkage analysis output files, calculates lod scores by family, associates lod scores with specific marker and family identifiers, and stores these data in a database where they can be combined with lod scores from previous analyses. LINKMAN easily incorporates any of a wide variety of genetic models. It produces formatted output of lod scores by user-specified criteria for reports or as ASCII files for input to other programs. If desired, tests of homogeneity of linkage across families can be run via the HOMOG program [Ott, 1991] and their output included in reports. The programs include features critical for conducting genome searches of complex diseases: They are easy-to-use, well-tested, and reliable. Data from multicenter investigations can be easily combined for analysis. Moreover, they include extensive error-checking capabilities, and they are specifically set up to protect blindness between laboratory workers and data analysts. LABMAN and LINKMAN are currently available free of charge under DOS.

Alleles↗

PubMed1995

Genome scanning for complex disease genes using the transmission/disequilibrium test and haplotype-based haplotype relative risk.

Two tests for allelic association were applied to a simulated complex disease for the Genetic Analysis Workshop 9. The transmission/disequilibrium test [Spielman et al., 1993] and the haplotype-based haplotype relative risk approach [Terwilliger and Ott, 1992] were used to detect disease-associated alleles in a set of 360 computer-simulated markers located on six chromosomes and genotyped in 200 nuclear families. This analysis emulates a genome-based search for linked markers. Computer simulations were also performed to clarify statistical properties of the TDT.

Alleles↗

PubMed2003

Familial neuroblastoma: a complex heritable disease.

Genomic surveys carried out over the years have revealed a great heterogeneity in the pattern of genetic aberrations occurring in neuroblastoma (NB) cells. Studies on familial NB could lead to the discovery of susceptibility genes and their contribution to the development of the disease. The two-hit hypothesis is considered the most consistent model of inherited predisposition to NB, but an oligogenic inheritance governed by a major gene should be also taken into account. The rarity of familial clustering of NB cases and the difficulty to recruit informative families has not allowed the identification of the disease gene until now. In fact, linkage analysis has suggested more than one region candidate to harboring NB predisposing gene(s). These findings indicate that genetic heterogeneity might be the molecular basis of the disorder. Given the complexity of the disease additional studies are required to elucidate the genetic determination of NB.

Chromosomes, Human↗

PubMed2004

Whole-genome scan, in a complex disease, using 11,245 single-nucleotide polymorphisms: comparison with microsatellites.

Despite the theoretical evidence of the utility of single-nucleotide polymorphisms (SNPs) for linkage analysis, no whole-genome scans of a complex disease have yet been published to directly compare SNPs with microsatellites. Here, we describe a whole-genome screen of 157 families with multiple cases of rheumatoid arthritis (RA), performed using 11,245 genomewide SNPs. The results were compared with those from a 10-cM microsatellite scan in the same cohort. The SNP analysis detected HLA*DRB1, the major RA susceptibility locus (P=.00004), with a linkage interval of 31 cM, compared with a 50-cM linkage interval detected by the microsatellite scan. In addition, four loci were detected at a nominal significance level (P<.05) in the SNP linkage analysis; these were not observed in the microsatellite scan. We demonstrate that variation in information content was the main factor contributing to observed differences in the two scans, with the SNPs providing significantly higher information content than the microsatellites. Reducing the number of SNPs in the marker set to 3,300 (1-cM spacing) caused several loci to drop below nominal significance levels, suggesting that decreases in information content can have significant effects on linkage results. In contrast, differences in maps employed in the analysis, the low detectable rate of genotyping error, and the presence of moderate linkage disequilibrium between markers did not significantly affect the results. We have demonstrated the utility of a dense SNP map for performing linkage analysis in a late-age-at-onset disease, where DNA from parents is not always available. The high SNP density allows loci to be defined more precisely and provides a partial scaffold for association studies, substantially reducing the resource requirement for gene-mapping studies.

Arthritis, Rheumatoid↗

PubMed2005

Whole genome association study of rheumatoid arthritis using 27 039 microsatellites.

A major goal of current human genome-wide studies is to identify the genetic basis of complex disorders. However, the availability of an unbiased, reliable, cost efficient and comprehensive methodology to analyze the entire genome for complex disease association is still largely lacking or problematic. Therefore, we have developed a practical and efficient strategy for whole genome association studies of complex diseases by charting the human genome at 100 kb intervals using a collection of 27,039 microsatellites and the DNA pooling method in three successive genomic screens of independent case-control populations. The final step in our methodology consists of fine mapping of the candidate susceptible DNA regions by single nucleotide polymorphisms (SNPs) analysis. This approach was validated upon application to rheumatoid arthritis, a destructive joint disease affecting up to 1% of the population. A total of 47 candidate regions were identified. The top seven loci, withstanding the most stringent statistical tests, were dissected down to individual genes and/or SNPs on four chromosomes, including the previously known 6p21.3-encoded Major Histocompatibility Complex gene, HLA-DRB1. Hence, microsatellite-based genome-wide association analysis complemented by end stage SNP typing provides a new tool for genetic dissection of multifactorial pathologies including common diseases.

Arthritis, Rheumatoid↗

PubMed1999

Genomics of the major histocompatibility complex: haplotypes, duplication, retroviruses and disease.

The genomic region encompassing the Major Histocompatibility Complex (MHC) contains polymorphic frozen blocks which have developed by local imperfect sequential duplication associated with insertion and deletion (indels). In the alpha block surrounding HLA-A, there are ten duplication units or beads on the 62.1 ancestral haplotype. Each bead contains or contained sequences representing Class I, PERB11 (MHC Class I chain related (MIC) and human endogenous retrovirus (HERV) 16. Here we consider explanations for co-occurrence of genomic polymorphism, duplication and HERVs and we ask how these features encode susceptibility to numerous and very diverse diseases. Ancestral haplotypes differ in their copy number and indels in addition to their coding regions. Disease susceptibility could be a function of all of these differences. We propose a model of the evolution of the human MHC. Population-specific integration of retroviral sequences could explain rapid diversification through duplication and differential disease susceptibility. If HERV sequences can be protective, there are exciting prospects for manipulation. In the meanwhile, it will be necessary to understand the function of MHC genes such as PERB11 (MIC) and many others discovered by genomic sequencing.

Animals↗

PubMed2001

The power of genome-wide association studies of complex disease genes: statistical limitations of indirect approaches using SNP markers.

Genome-wide association studies using a dense map of single nucleotide polymorphism (SNP) markers seem to enable us to detect a number of complex disease genes. In such indirect association studies, whether susceptibility genes can be detected is dependent not only on the degree of linkage disequilibrium between the disease variant and the SNP marker but also on the difference in their allele frequencies. These factors, as well as penetrance of the disease variant, influence the statistical power of such approaches. However, the power of indirect association studies is not well understood. We calculated the number of individuals necessary for the detection of the disease variant in both direct and indirect association studies with a case-control design. The result shows that a remarkable reduction in the statistical power of indirect studies, compared with that of direct ones, is unavoidable in the genome-wide screening of complex disease genes. If there is a large difference in allele frequency between the disease variant and the marker, the disease variant cannot be detected. Because the frequency of the disease variant is unknown, SNP markers with various allele frequencies, or a large number of SNP markers, must be used in indirect association studies. However, if the number of SNP markers is increased, the obtained P value may not reach the significance level due to the Bonferroni adjustment. Thus, to test a possible association between functional variants and a complex disease directly, we should identify such SNPs in as many genes as possible for use in genome-wide association studies.

Gene Frequency↗