67 research outputs found
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Optimal Step Length EM Algorithm (OSLEM) for the estimation of haplotype frequency and its application in lipoprotein lipase genotyping
Background: Haplotype based linkage disequilibrium (LD) mapping has become a powerful and cost-effective method for performing genetic association studies, particularly in the search for genetic markers in linkage disequilibrium with complex disease loci. Various methods (e.g. Monte-Carlo (Gibbs sampling); EM (expectation maximization); and Clark's method) have been used to estimate haplotype frequencies from routine genotyping data. Results: These algorithms can be very slow for large number of SNPs. In order to speed them up, we have developed a new algorithm using numerical analysis technology, a so-called optimal step length EM (OSLEM) that accelerates the calculation. By optimizing approximately the step length of the EM algorithm, OSLEM can run at about twice the speed of EM. This algorithm has been used for lipoprotein lipase (LPL) genotyping analysis. Conclusions: This new optimal step length EM (OSLEM) algorithm can accelerate the calculation for haplotype frequency estimation for genotyping data without pedigree information. An OSLEM on-line server is available, as well as a free downloadable version
Association of extreme blood lipid profile phenotypic variation with 11 reverse cholesterol transport genes and 10 non-genetic cardiovascular disease risk factors
This study explored the genetic basis of the combination of extreme blood levels of HDL-C and LDL-C, a well-studied endophenotype for CVD, which has several attractive features as a target for genetic analysis: (1) the trait is moderately heritable; (2) non-genetic risk factors account for a significant but still limited portion of the phenotypic variance; (3) it is known to be moderated by a number of gene products. We exhaustively surveyed 11 candidate genes for allelic variation in a random population-based sample characterized for known CVD risk factors and blood lipid profiles. With the goal of generating specific etiological hypotheses, we compared two groups of subjects with extreme lipid phenotypes, from the same source population, using a case-control design. Cases (n=186) were subjects, within the total sample of 1708 people, who scored in the upper tertile of LDL-C and the lowest tertile of HDL-C, while controls (n=185) scored in the lowest tertile of LDL-C and the upper tertile of HDL-C. We used logistic regression and a four-tiered, systematic model building strategy with internal cross-validation and bootstrapping to investigate the relationships between the trait and 275 genetic variants in the presence of 10 non-genetic risk factors. Our results implicate a subset of nine genetic variants, spanning seven candidate genes, together with five environmental risk factors, in the etiology of extreme lipoprotein phenotypes. We propose a model involving these 14 genetic and non-genetic risk factors for evaluation in future independent studie
Systems Analysis of Human Multigene Disorders
XIII, 122 p. 12 illus. in color.online resource
Genetic-linkage mapping of complex hereditary disorders to a whole-genome molecular-interaction network
Common hereditary neurodevelopmental disorders such as autism, bipolar disorder, and schizophrenia are most likely both genetically multifactorial and heterogeneous. Because of these characteristics traditional methods for genetic analysis fail when applied to such diseases. To address the problem we propose a novel probabilistic framework that combines the standard genetic linkage formalism with whole-genome molecular-interaction data to predict pathways or networks of interacting genes that contribute to common heritable disorders. We apply the model to three large genotype–phenotype data sets, identify a small number of significant candidate genes for autism (24), bipolar disorder (21), and schizophrenia (25), and predict a number of gene targets likely to be shared among the disorders
Evidence for a Language Quantitative Trait Locus on Chromosome 7q in Multiplex Autism Families
Autism is a syndrome characterized by deficits in language and social skills and by repetitive behaviors. We hypothesized that potential quantitative trait loci (QTLs) related to component autism endophenotypes might underlie putative or significant regions of autism linkage. We performed nonparametric multipoint linkage analyses, in 152 families from the Autism Genetic Resource Exchange, focusing on three traits derived from the Autism Diagnostic Interview: “age at first word,” “age at first phrase,” and a composite measure of “repetitive and stereotyped behavior.” Families were genotyped for 335 markers, and multipoint sib pair linkage analyses were conducted. Using nonparametric multipoint linkage analysis, we found the strongest QTL evidence for age at first word on chromosome 7q (nonparametric test statistic [Z] 2.98; P=.001), and subsequent linkage analyses of additional markers and association analyses in the same region supported the initial result (Z=2.85, P=.002; χ(2)=18.84, df 8, P=.016). Moreover, the peak fine-mapping result for repetitive behavior (Z=2.48; P=.007) localized to a region overlapping this language QTL. The putative autism-susceptibility locus on chromosome 7 may be the result of separate QTLs for the language and repetitive or stereotyped behavior deficits that are associated with the disorder
EB Simplex Superficialis Resulting from a Mutation in the Type VII Collagen Gene
8 páginas, 1 figura, 1 tabla.Epidermolysis bullosa simplex (EBS) is an inherited blistering disease characterized by intraepidermal cleavage (Gedde-Dahl and Anton-Lamprecht, 1990;Fine et al, 1991). A very rare subset of EBS, termed "EBS superficialis" (EBSS), has been described in two families byFine et al (1989). Skin biopsy of these patients shows clefts of variable size just beneath the level of the stratum corneum, which can be completely separated from the rest of the epidermis in some cases. In two of the patients reported, there are also some clefts in the lower one-third of the epidermis.
Together with this unusual clinical picture, most of the patients show atrophic scarring, milia, nail dystrophy, and blistering involving the oral cavity. After the first description of EBSS in two unrelated families, no other cases have been reported, emphasizing the rareness of these findings.The authors gratefully acknowledge NIH USPHS grants R01 AR43602, R01 AR44924, and K02 AR02047 (to A.M.C.), K01-HG00055-01 (to D.G.), and HG00008 (to J.O.), the National Epidermolysis Bullosa Registry (to M.S.W. and J.D.F.), the Skin Disease Research Center of Columbia University P30 AR44345 (to J.O. and A.M.C.), and the Dermatology Foundation.Peer reviewe
Altered Hippocampal Transcript Profile Accompanies an Age-Related Spatial Memory Deficit in Mice
We have carried out a global survey of age-related changes in mRNA levels in the C57BL/6NIA mouse hippocampus and found a difference in the hippocampal gene expression profile between 2-month-old young mice and 15-month-old middle-aged mice correlated with an age-related cognitive deficit in hippocampal-based explicit memory formation. Middle-aged mice displayed a mild but specific deficit in spatial memory in the Morris water maze. By using Affymetrix GeneChip microarrays, we found a distinct pattern of age-related change, consisting mostly of gene overexpression in the middle-aged mice, suggesting that the induction of negative regulators in the middle-aged hippocampus could be involved in impairment of learning. Interestingly, we report changes in transcript levels for genes that could affect synaptic plasticity. Those changes could be involved in the memory deficits we observed in the 15-month-old mice. In agreement with previous reports, we also found altered expression in genes related to inflammation, protein processing, and oxidative stress
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Chemokine expression in the early response to injury in human airway epithelial cells
Basal airway epithelial cells (AEC) constitute stem/progenitor cells within the central airways and respond to mucosal injury in an ordered sequence of spreading, migration, proliferation, and differentiation to needed cell types. However, dynamic gene transcription in the early events after mucosal injury has not been studied in AEC. We examined gene expression using microarrays following mechanical injury (MI) in primary human AEC grown in submersion culture to generate basal cells and in the air-liquid interface to generate differentiated AEC (dAEC) that include goblet and ciliated cells. A select group of ~150 genes was in differential expression (DE) within 2–24 hr after MI, and enrichment analysis of these genes showed over-representation of functional categories related to inflammatory cytokines and chemokines. Network-based gene prioritization and network reconstruction using the PINTA heat kernel diffusion algorithm demonstrated highly connected networks that were richer in differentiated AEC compared to basal cells. Similar experiments done in basal AEC collected from asthmatic donor lungs demonstrated substantial changes in DE genes and functional categories related to inflammation compared to basal AEC from normal donors. In dAEC, similar but more modest differences were observed. We demonstrate that the AEC transcription signature after MI identifies genes and pathways that are important to the initiation and perpetuation of airway mucosal inflammation. Gene expression occurs quickly after injury and is more profound in differentiated AEC, and is altered in AEC from asthmatic airways. Our data suggest that the early response to injury is substantially different in asthmatic airways, particularly in basal airway epithelial cells
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