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PubMed2002

[How to make the best use of the Internet].

Presently, searching for genetic information successfully requires using the internet. Because the internet world has different common sense than the publication world, those who are going to use the internet should know its characteristics well. First, because there is an overwhelming number of web sites that continue to change, proper techniques for making an efficient search for valuable information are necessary. Second, the contents of web sites need validation. Third, possible harms that can come with the internet should be avoided beforehand, and so on. Recent rapid progress in information technology will soon bring the internet to every field of medical practice and the above-mentioned know-how will become minimum requirements for every clinician.

Databases, Genetic↗

PubMed2003

Functional modules by relating protein interaction networks and gene expression.

Genes and proteins are organized on the basis of their particular mutual relations or according to their interactions in cellular and genetic networks. These include metabolic or signaling pathways and protein interaction, regulatory or co-expression networks. Integrating the information from the different types of networks may lead to the notion of a functional network and functional modules. To find these modules, we propose a new technique which is based on collective, multi-body correlations in a genetic network. We calculated the correlation strength of a group of genes (e.g. in the co-expression network) which were identified as members of a module in a different network (e.g. in the protein interaction network) and estimated the probability that this correlation strength was found by chance. Groups of genes with a significant correlation strength in different networks have a high probability that they perform the same function. Here, we propose evaluating the multi-body correlations by applying the superparamagnetic approach. We compare our method to the presently applied mean Pearson correlations and show that our method is more sensitive in revealing functional relationships.

Algorithms↗

PubMed1992

Data collection strategies in genetic epidemiology: The Epilepsy Family Study of Columbia University.

A large-scale study of genetic influences on seizure disorders is described here as a primer of tested methods for collection of family history data. 1957 adult probands with epilepsy were ascertained from voluntary organizations. Personal and family history data were obtained from probands in semistructured telephone interviews. To increase sensitivity, an independent family history was obtained from a second family informant in a similar interview. To increase specificity and diagnostic detail, family members reported to be affected were interviewed, and medical records of probands and affected relatives were collected. Participation rates for probands were 84-90%. Interviews were completed with second informants in 67% of families, and with 51% of eligible affected relatives. The main reasons for non-interview were lack of permission from probands and difficulties in locating relatives. Although 90% of probands gave verbal permission for medical record review, only 75% of these signed and returned consent forms for this purpose. Physicians returned 87% of the records requested. The resulting proportion of probands with medical records was 59%. These findings illustrate the complexity involved in assembling useful databases in genetic epidemiology.

Adult↗

PubMed2004

Differentially expressed genes in hypertensive rats developing cerebral ischemia.

The molecular events occurring after cerebral ischemia in hypertension may include de novo expression of numerous genes. Receptor genes are predominantly involved in the process of cell death, neuroprotection and reconstruction after ischemic injury. Ischemic stroke was observed in the non-genetic, non-surgical model of hypertension, the cold-induced hypertensive rat. In hypertensive rats suppression subtractive hybridization analysis was used to identify differentially expressed receptor genes in stroke-tissue compared to normal rat brain. We found 76 genes predominantly expressed in hypertensive rat stroke-tissue. These predominantly expressed genes included genes involved in energy metabolism, signal transduction/cell regulation, and replication/transcription/translation. For example, the T3 receptor alpha was predominantly expressed in stroke-tissue, indicating that regeneration of nerves in stroke tissue may be facilitated by increased T3 receptor alpha expression.

Animals↗

PubMed2005

The effect of missing data on linkage disequilibrium mapping and haplotype association analysis in the GAW14 simulated datasets.

We used our newly developed linkage disequilibrium (LD) plotting software, JLIN, to plot linkage disequilibrium between pairs of single-nucleotide polymorphisms (SNPs) for three chromosomes of the Genetic Analysis Workshop 14 Aipotu simulated population to assess the effect of missing data on LD calculations. Our haplotype analysis program, SIMHAP, was used to assess the effect of missing data on haplotype-phenotype association. Genotype data was removed at random, at levels of 1%, 5%, and 10%, and the LD calculations and haplotype association results for these levels of missingness were compared to those for the complete dataset. It was concluded that ignoring individuals with missing data substantially affects the number of regions of LD detected which, in turn, could affect tagging SNPs chosen to generate haplotypes.

Chromosome Mapping↗

PubMed2005

Interval estimation of disease loci: development and applications of new linkage methods.

Three variants of the confidence set inference (CSI) procedure were proposed and applied to both the simulated and the Collaborative Study on the Genetics of Alcoholism (COGA) data. For each of the two applications, we first performed a preliminary genome scan study based on the microsatellite markers using the GENEHUNTER+ software to identify regions that potentially harbor disease loci. For each such region, we estimated the sibling identity-by-descent sharing probability distribution at the putative disease locus. Based on these estimated probabilities, the CSI procedures were employed to further localize the disease loci using the single-nucleotide polymorphism markers, leading to confidence intervals/regions for their locations. For our analysis with the simulated data, we had knowledge of the simulating models at the time we performed the analysis.

Alcoholism↗

PubMed2004

The distribution of transgene insertion sites in barley determined by physical and genetic mapping.

The exact site of transgene insertion into a plant host genome is one feature of the genetic transformation process that cannot, at present, be controlled and is often poorly understood. The site of transgene insertion may have implications for transgene stability and for potential unintended effects of the transgene on plant metabolism. To increase our understanding of transgene insertion sites in barley, a detailed analysis of transgene integration in independently derived transgenic barley lines was carried out. Fluorescence in situ hybridization (FISH) was used to physically map 23 transgene integration sites from 19 independent barley lines. Genetic mapping further confirmed the location of the transgenes in 11 of these lines. Transgene integration sites were present only on five of the seven barley chromosomes. The pattern of transgene integration appeared to be nonrandom and there was evidence of clustering of independent transgene insertion events within the barley genome. In addition, barley genomic regions flanking the transgene insertion site were isolated for seven independent lines. The data from the transgene flanking regions indicated that transgene insertions were preferentially located in gene-rich areas of the genome. These results are discussed in relation to the structure of the barley genome.

Chromosome Mapping↗

PubMed2005

Preparation of samples for comparative studies of arthropod chromosomes: visualization, in situ hybridization, and genome size estimation.

The ability to obtain large amounts of genomic sequence for organisms and high throughput technology has led to a change in the thrust of research at the level of chromosomes in animals. In the past chromosomal analysis of animals was focused on gross changes such as inversions, translocations, and deletions for both genetic and evolutionary studies. The advent of in situ hybridization technology and the ability to measure genome content size changed both the precision and the scale of studies addressing chromosomal change as a tool in evolutionary biology. This chapter addresses two of the major areas of change that have occurred in chromosomal studies in the past decade -- examination of more refined and genome enabled structural changes in chromosomes and genome size measure. This chapter describes some of the chromosome structure approaches such as fluorescent in situ hybridization (FISH), comparative genomic hybridization (CGH) and other techniques. As well, advances in Genome size measurement and theory are described herein.

Animals↗

PubMed2002

Single nucleotide polymorphism mapping using genome-wide unique sequences.

As more and more genomic DNAs are sequenced to characterize human genetic variations, the demand for a very fast and accurate method to genomically position these DNA sequences is high. We have developed a new mapping method that does not require sequence alignment. In this method, we first identified DNA fragments of 15 bp in length that are unique in the human genome and then used them to position single nucleotide polymorphism (SNP) sequences. By use of four desktop personal computers with AMD K7 (1 GHz) processors, our new method mapped more than 1.6 million SNP sequences in 20 hr and achieved a very good agreement with mapping results from alignment-based methods.

Chromosome Mapping↗

PubMed2006

Genes and longevity: a genetic-demographic approach reveals sex- and age-specific gene effects not shown by the case-control approach (APOE and HSP70.1 loci).

Association analyses between gene variability and human longevity carried out by comparing gene frequencies between population samples of different ages (case/control design) may provide information on genes and pathways playing a role in modulating survival at old ages. However, by dealing with cross-sectional data, the gene-frequency (GF) approach ignores cohort effects in population mortality changes. The genetic-demographic (GD) approach adds demographic information to genetic data and allows the estimation of hazard rates and survival functions for candidate alleles and genotypes. Thus mortality changes in the cohort to which the cross-sectional sample belongs are taken into account. In this work, we applied the GD method to a dataset relevant to two genes, APOE and HSP70.1, previously shown to be related to longevity by the GF method. We show that the GD method reveals sex- and age-specific allelic effects not shown by the GF analysis. In addition, we provide an algorithm for the implementation of a non-parametric GD analysis.

Adolescent↗

PubMed2004

Comparisons of predicted genetic modules: identification of co-expressed genes through module gene flow.

A question of fundamental importance is the definition and identification of modules from microarray experiments. A wide variety of techniques have been used to gain insight into the elucidation of such modules. One problem, however, is the inability to directly compare results between the different data sets produced due to the inherent parameterizations of their approaches. We first aim to provide a mechanism by which different approaches to module finding can be directly compared. Moreover, the same approach can be used to internally compare the modules predicted by the same technique, but at different parameterizations. We apply this approach to analyze the flow of genes through modules at different module thresholds of the Barkai Signature method, thereby further resolving the modules into sets of co-expressed genes.

Algorithms↗

PubMed2005

Construction of the model for the Genetic Analysis Workshop 14 simulated data: genotype-phenotype relationships, gene interaction, linkage, association, disequilibrium, and ascertainment effects for a complex phenotype.

The Genetic Analysis Workshop 14 simulated dataset was designed 1) To test the ability to find genes related to a complex disease (such as alcoholism). Such a disease may be given a variety of definitions by different investigators, have associated endophenotypes that are common in the general population, and is likely to be not one disease but a heterogeneous collection of clinically similar, but genetically distinct, entities. 2) To observe the effect on genetic analysis and gene discovery of a complex set of gene x gene interactions. 3) To allow comparison of microsatellite vs. large-scale single-nucleotide polymorphism (SNP) data. 4) To allow testing of association to identify the disease gene and the effect of moderate marker x marker linkage disequilibrium. 5) To observe the effect of different ascertainment/disease definition schemes on the analysis. Data was distributed in two forms. Data distributed to participants contained about 1,000 SNPs and 400 microsatellite markers. Internet-obtainable data consisted of a finer 10,000 SNP map, which also contained data on controls. While disease characteristics and parameters were constant, four "studies" used varying ascertainment schemes based on differing beliefs about disease characteristics. One of the studies contained multiplex two- and three-generation pedigrees with at least four affected members. The simulated disease was a psychiatric condition with many associated behaviors (endophenotypes), almost all of which were genetic in origin. The underlying disease model contained four major genes and two modifier genes. The four major genes interacted with each other to produce three different phenotypes, which were themselves heterogeneous. The population parameters were calibrated so that the major genes could be discovered by linkage analysis in most datasets. The association evidence was more difficult to calibrate but was designed to find statistically significant association in 50% of datasets. We also simulated some marker x marker linkage disequilibrium around some of the genes and also in areas without disease genes. We tried two different methods to simulate the linkage disequilibrium.

Computer Simulation↗

PubMed2006

Development of a human mitochondria-focused cDNA microarray (hMitChip) and validation in skeletal muscle cells: implications for pharmaco- and mitogenomics.

Mitochondrial research has influenced our understanding of human evolution, physiology and pathophysiology. Mitochondria, intracellular organelles widely known as 'energy factories' of the cell, also play fundamental roles in intermediary metabolism, steroid hormone and heme biosyntheses, calcium signaling, generation of radical oxygen species, and apoptosis. Mitochondria possess a distinct DNA (mitochondrial DNA); yet, the vast majority of mitochondrial proteins are encoded by the nuclear DNA. Mitochondria-related genetic defects have been described in a variety of mostly rare, often fatal, primary mitochondrial disorders; furthermore, they are increasingly reported in association with many common morbid conditions, such as cancer, obesity, diabetes and neurodegenerative disorders, although their role remains unclear. This study describes the creation of a human mitochondria-focused cDNA microarray (hMitChip) and its validation in human skeletal muscle cells treated with glucocorticoids. We suggest that hMitChip is a reliable and novel tool that will prove useful for systematically studying the contribution of mitochondrial genomics to human health and disease.

Adolescent↗

PubMed2005

A power study of bivariate LOD score analysis of a complex trait and fear/discomfort with strangers.

Complex diseases are often reported along with disease-related traits (DRT). Sometimes investigators consider both disease and DRT phenotypes separately and sometimes they consider individuals as affected if they have either the disease or the DRT, or both. We propose instead to consider the joint distribution of the disease and the DRT and do a linkage analysis assuming a pleiotropic model. We evaluated our results through analysis of the simulated datasets provided by Genetic Analysis Workshop 14. We first conducted univariate linkage analysis of the simulated disease, Kofendrerd Personality Disorder and one of its simulated associated traits, phenotype b (fear/discomfort with strangers). Subsequently, we considered the bivariate phenotype, which combined the information on Kofendrerd Personality Disorder and fear/discomfort with strangers. We developed a program to perform bivariate linkage analysis using an extension to the Elston-Stewart peeling method of likelihood calculation. Using this program we considered the microsatellites within 30 cM of the gene pleiotropic for this simulated disease and DRT. Based on 100 simulations of 300 families we observed excellent power to detect linkage within 10 cM of the disease locus using the DRT and the bivariate trait.

Databases, Genetic↗

PubMed2006

Fetal pyelectasis: does fetal gender modify the risk of major trisomies?

OBJECTIVE: Several studies have noted an increased prevalence of pyelectasis in male fetuses. It is speculated that pyelectasis represents a normal physiologic variant in males, whereas its presence in females indicates an increased risk of chromosomal abnormalities. Thus, we sought to investigate the association between fetal gender and the risk of major trisomies in fetuses with pyelectasis. METHODS: Retrospective analysis of a Genzyme Genetics amniocentesis database (1995 to 2004) was performed. Specimens obtained after an ultrasonographic finding of pyelectasis were eligible for analysis. The prevalence of major trisomies (trisomy 13, 18, or 21) in male and female fetuses with pyelectasis was compared using binomial distribution. RESULTS: A total of 760,495 amniocentesis specimens were analyzed. Fetal pyelectasis was reported in 671 cases. A male predominance, with a male-to-female ratio of 2.14:1 (457 compared with 214) was statistically significant (P < .001). A major trisomy was detected in 26 male fetuses (5.7%): 18 cases of trisomy 21, 2 cases of trisomy 18, and 6 cases of trisomy 13. Nine female fetuses had a major trisomy (4.2%): 6 cases of trisomy 21 and 3 cases of trisomy 13. There was no significant difference in the overall prevalence of trisomies between male and female fetuses (P = .14). CONCLUSION: We concur with previous studies documenting a higher prevalence of pyelectasis in male fetuses. In addition, our results indicate that the prevalence of major trisomies among fetuses with pyelectasis is unlikely to be dependent on fetal gender. Thus, counseling patients with regard to the genetic implications of fetal pyelectasis should be gender independent. LEVEL OF EVIDENCE: II-2.

Amniocentesis↗

PubMed2002

Parameters for reliable results in genetic association studies in common disease.

It is increasingly apparent that the identification of true genetic associations in common multifactorial disease will require studies comprising thousands rather than the hundreds of individuals employed to date. Using 2,873 families, we were unable to confirm a recently published association of the interleukin 12B gene in 422 type I diabetic families. These results emphasize the need for large datasets, small P values and independent replication if results are to be reliable.

3' Untranslated Regions↗

PubMed2005

Effects of population structure on genetic association studies.

Population-based case-control association is a promising approach for unravelling the genetic basis of complex diseases. One potential problem of this approach is the presence of population structure in the samples. Using the Collaborative Study on the Genetics of Alcoholism (COGA) single-nucleotide polymorphism (SNP) datasets, we addressed three questions: How can the degree of population structure be quantified, and how does the population structure affect association studies? How accurate and efficient is the genomic control method in correcting for population structure? The amount of population structure in the COGA SNP data was found to inflate the p-value in association tests. Genomic control was found to be effective only when the appropriate number of markers was used in the control group in order to correctly calibrate the test. The approach presented in this paper could be used to select the appropriate number of markers for use in the genomic control method of correcting population structure.

Databases, Genetic↗

PubMed2001

Sequence analysis of the human genome: implications for the understanding of nervous system function and disease.

The recent publication of the sequence of the human genome will accelerate the discovery of new genetic susceptibility factors for human disease, leading to the development of novel diagnostics and therapeutics. The exhaustive analysis of the human genome sequence will be the focus of the biomedical research community for many years to come. In particular, comparative analysis of the available eukaryotic genome sequences is an important approach to further our understanding of gene structure, function, and evolution. Our initial analysis of the human genome sequence has revealed many interesting features that are relevant to nervous system function, evolution, and disease. We analyzed the prominent features of predicted human proteins involved in neuronal function and prepared a comparative analysis of 146 human genes that have alleles (or mutations) conferring susceptibility for 168 neurologic diseases.

Animals↗