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B Devlin

Publications and source records attributed to B Devlin.

At least 19 recordsLinked to original sources
PubMed2004

Yield of human adipose-derived adult stem cells from liposuction aspirates.

BACKGROUND: Primary cultures of isolated human adipose-derived adult stem (ADAS) cells are multipotent and differentiate in vitro along the adipocyte, chondrocyte, neuronal, osteoblast, and skeletal muscle pathways. METHODS: We examined the ADAS cell yield per unit volume of liposuction tissue, and their surface protein phenotype by flow cytometry. Adipogenesis was assessed by Oil Red O staining and ELISA analysis of leptin secretion. RESULTS: The donor population was 87.5% female (n=18) with a mean age (+/-SD) of 44+/-10 years and body mass index (BMI) of 24.9+/-2.7. The mean cell yield was 404 000+/-206 000 cells per milliliter of lipoaspirate (n=18). Linear regression analysis of the cells derived from the female donors demonstrated a significant negative correlation between the number of cells obtained per milliliter of lipoaspirate with the BMI but not the age of the donor. The undifferentiated ADAS cells were homogeneously positive for the cell-surface markers CD10, CD13, CD29, CD44, CD49e, CD59, CD90, and HLA-ABC, and homogeneously negative for the cell surface markers CD11b, CD45, and HLA-DR. The absence of the panhematopoietic marker, CD45, indicates that the ADAS cells do not derive from circulating BM hematopoietic stem cells. Adipocyte differentiation led to a 5.1-fold increase in Oil Red O staining, and a 196-fold increase in leptin secretion levels. Culture of the cells in the presence of antibiotic and fungizone did not alter the undifferentiated ADAS cell immunophenotype based on flow cytometry, or their adipocyte differentiation based on leptin secretion. DISCUSSION: The ability to isolate a consistently homogeneous population of undifferentiated adult stem cells from adipose tissue of multiple donors supports their potential utility in future tissue-engineering applications.

Adipose Tissue↗
PubMed2003

Role of different B-cell subsets in the specific and polyclonal immune response to T-independent antigens type 2.

Role of different B-cell subsets in the immune response to T-independent antigen type 2 (TI-2) was studied. BALB/c and C57BL/6 mice were immunized by polyvinylpyrrolidon (PVP), and the numbers of antibody- and Ig-forming cells (AFC and IFC, respectively) were determined by ELISPOT method. The number of cells producing non-specific Ig (nIFC) was calculated as the difference between the number of IFC and AFC; the number of nIFC induced by PVP was calculated as the difference between the number of nIFC in immune and control splenocytes. Immunization by PVP induced not only the AFC appearance, but also the increase in the number of the antigen-induced nIFC. The treatment of splenocytes by anti-CD5 antibodies and guinea pig complement reduced the increase in the numbers of newly formed AFC and nIFC to approximately 40% of control level. It means that CD5+ cells play an important role not only in the specific, but also in polyclonal immune response to non-self TI-2. To be sure that the decrease of AFC and nIFC numbers is due to depletion for CD5+ B-cells, but not CD5+ T-cells, splenocytes were separated to B-1 and B-2 subsets, and the numbers of AFC, IFC and nIFC were determined in each B-cell subpopulation separately. The overwhelming majority of newly formed AFC and nIFC was detected in B-1 subset. The numbers of AFC and nIFC in B-1 compartment was approximately 10-fold greater than in B-2 cells. A close parallelism between AFC and nIFC formation was observed. It is concluded that specific and polyclonal immune response to non-self TI-2-PVP-depends mainly on CD5+ B-1 subset.

Animals↗
PubMed2003

On the identification of disease mutations by the analysis of haplotype similarity and goodness of fit.

The observation that haplotypes from a particular region of the genome differ between affected and unaffected individuals or between chromosomes transmitted to affected individuals versus those not transmitted is sound evidence for a disease-liability mutation in the region. Tests for differentiation of haplotype distributions often take the form of either Pearson's chi(2) statistic or tests based on the similarity among haplotypes in the different populations. In this article, we show that many measures of haplotype similarity can be expressed in the same quadratic form, and we give the general form of the variance. As we describe, these methods can be applied to either phase-known or phase-unknown data. We investigate the performance of Pearson's chi(2) statistic and haplotype similarity tests through use of evolutionary simulations. We show that both approaches can be powerful, but under quite different conditions. Moreover, we show that the power of both approaches can be enhanced by clustering rare haplotypes from the distributions before performing a test.

Chromosomes, Human↗
PubMed2003

Analysis of multilocus models of association.

It is increasingly recognized that multiple genetic variants, within the same or different genes, combine to affect liability for many common diseases. Indeed, the variants may interact among themselves and with environmental factors. Thus realistic genetic/statistical models can include an extremely large number of parameters, and it is by no means obvious how to find the variants contributing to liability. For models of multiple candidate genes and their interactions, we prove that statistical inference can be based on controlling the false discovery rate (FDR), which is defined as the expected number of false rejections divided by the number of rejections. Controlling the FDR automatically controls the overall error rate in the special case that all the null hypotheses are true. So do more standard methods such as Bonferroni correction. However, when some null hypotheses are false, the goals of Bonferroni and FDR differ, and FDR will have better power. Model selection procedures, such as forward stepwise regression, are often used to choose important predictors for complex models. By analysis of simulations of such models, we compare a computationally efficient form of forward stepwise regression against the FDR methods. We show that model selection includes numerous genetic variants having no impact on the trait, whereas FDR maintains a false-positive rate very close to the nominal rate. With good control over false positives and better power than Bonferroni, the FDR-based methods we introduce present a viable means of evaluating complex, multivariate genetic models. Naturally, as for any method seeking to explore complex genetic models, the power of the methods is limited by sample size and model complexity.

Chromosome Mapping↗
PubMed2003

Evolutionary-based association analysis using haplotype data.

Association studies, both family-based and population-based, can be powerful means of detecting disease-liability alleles. To increase the information of the test, various researchers have proposed targeting haplotypes. The larger number of haplotypes, however, relative to alleles at individual loci, could decrease power because of the additional degrees of freedom required for the test. An optimal strategy would focus the test on particular haplotypes or groups of haplotypes, much as is done with cladistic-based association analysis. First suggested by Templeton et al. ([1987] Genetics 117:343-351), such analyses use the evolutionary relationships among haplotypes to produce a limited set of hypothesis tests and to increase the interpretability of these tests. To more fully utilize the information contained in the evolutionary relationships among haplotypes and in the sample, we propose generalized linear models (GLM) for the analysis of data from family-based and population-based studies. These models fully account for haplotype phase ambiguity and allow for covariates. The models are encoded into a software package (the Evolutionary-Based Haplotype Analysis Package, EHAP), which also provides for various kinds of exploratory data analysis. The exploratory analyses, such as error checking, estimation of haplotype frequencies, and tools for building cladograms, should facilitate the implementation of cladistic-based association analysis with haplotypes.

Genetic Predisposition to Disease↗
PubMed2003

Psychotic symptoms in Alzheimer disease: evidence for a distinct phenotype.

Though efforts to identify the genetic etiology of Alzheimer disease (AD) have made substantial progress, to date only some of the genes contributing to AD risk have been identified. Utilization of more etiologically homogeneous subphenotypes represents one strategy to facilitate the identification of novel risk genes in complex disorders. In this review, we evaluate the hypothesis that psychotic symptoms, such as delusions and hallucinations, define a suitable subphenotype in AD patients for gene-mapping efforts. Psychotic symptoms occur in 40-60% of patients with AD and are associated with more severe cognitive deficits and a more rapidly deteriorating course. The presence of psychotic symptoms in AD confers increased risk of similar symptoms to affected siblings. Candidate gene association analyses and initial linkage analysis have yielded significant results. We discuss possible genetic models of psychotic symptoms in AD, and suggest strategies for further investigation. Identification of such genetic factors may facilitate gene-mapping studies for both AD and idiopathic psychoses.

Alzheimer Disease↗
PubMed2002

Significant linkage on chromosome 10p in families with bulimia nervosa.

Bulimia nervosa (BN) is strongly familial, and additive genetic effects appear to contribute substantially to the observed familiality. In turn, behavioral components of BN, such as self-induced vomiting, are reliably measured and heritable. To identify regions of the genome harboring genetic variants conferring susceptibility to BN, we conducted a linkage analysis of multiplex families with eating disorders that were identified through a proband with BN. Linkage analysis of the entire sample of 308 families yielded a double peak, with the highest nonparametric multipoint maximum LOD score (MLS), of 2.92, on chromosome 10. Given the high heritability of self-induced vomiting and the reliability with which it can be measured, we performed linkage analysis in a subset (n=133) of families in which at least two affected relatives reported a symptom pattern that included self-induced vomiting. The highest MLS (3.39) observed was on chromosome 10, between markers D10S1430 and D10S1423. These results provide evidence of the presence of a susceptibility locus for BN on chromosome 10p. Using simulations, we demonstrate that both of these scores, 2.92 and 3.39, meet the widely accepted criterion for genomewide significance. Another region on 14q meets the criterion for genomewide suggestive linkage, with MLSs of 1.97 (full sample) and 1.75 (subset) at 62 centimorgans from p-ter.

Bulimia↗
PubMed2002

Linkage analysis of Alzheimer disease with psychosis.

Although a portion of risk for late-onset AD (LOAD) is attributable to APOE, the search for other loci is ongoing. The authors hypothesize that psychotic symptoms with LOAD (LOAD+P) identify a potentially more etiologically homogeneous form of AD. Linkage analysis of families with LOAD+P identified one significant and several suggestive novel linkage signals, which bolsters the conjecture of greater etiologic homogeneity.

Alzheimer Disease↗
PubMed2002

Increased familial risk of the psychotic phenotype of Alzheimer disease.

BACKGROUND: Psychotic symptoms in patients with AD (AD with psychosis [AD+P]) define a phenotype characterized by more rapid cognitive and functional decline and a liability to aggressive behaviors. OBJECTIVE: To determine if AD+P aggregates within families. METHODS: Case-control study of AD+P frequency in 461 siblings of 371 probands diagnosed with AD. All siblings were ascertained as part of a genetic investigation and also were diagnosed with AD. Statistical analysis used Generalized Estimating Equations to adjust for clustering within families. RESULTS: AD+P in probands was associated with a significantly increased risk for AD+P in family members (OR, 2.41; 95% CI 1.46-4.0; p = 0.0006). The correlation among siblings for AD+P status was modest: 0.16. CONCLUSION: AD+P demonstrates familial aggregation. Further studies are required to investigate a possible genetic basis of AD+P.

Aged↗
PubMed2002

Genome-wide multipoint linkage analyses of multiplex schizophrenia pedigrees from the oceanic nation of Palau.

The oceanic nation of Palau has been geographically and culturally isolated over most of its 2000 year history. As part of a study of the genetic basis of schizophrenia in Palau, we genotyped five large, multigenerational schizophrenia pedigrees using markers every 10 cM (CHLC/Weber screening set 6). The number of affected/unaffected individuals genotyped per family ranged from 11/21 to 5/5. Thus the pedigrees varied in their information for linkage, but each was capable of producing a substantial LOD score. We fitted a simple dominant and recessive model to these data using multipoint linkage analysis implemented by Simwalk2. Predictably, the most informative pedigrees produced the best linkage results. After genotyping additional markers in the region, one pedigree produced a LOD = 3.4 (5q distal) under the dominant model. Seven of nine schizophrenics in the pedigree, mostly 3rd-4th degree relatives, share a 15-cM, 7-marker haplotype. For a different pedigree, another promising signal occurred on distal 3q, LOD = 2.6, for the recessive model. For two other pedigrees, the best LODs were modest, slightly better than 2.0 on 5q and 9p, while the fifth pedigree produced no noteworthy linkage signal. Similar to the results for other populations, our results suggest there are multiple genes conferring liability to schizophrenia even in the small population of Palau (roughly 21,000 individuals) in remote Oceania.

Genome, Human↗
PubMed2001

Transmission/disequilibrium test meets measured haplotype analysis: family-based association analysis guided by evolution of haplotypes.

Family data teamed with the transmission/disequilibrium test (TDT), which simultaneously evaluates linkage and association, is a powerful means of detecting disease-liability alleles. To increase the information provided by the test, various researchers have proposed TDT-based methods for haplotype transmission. Haplotypes indeed produce more-definitive transmissions than do the alleles comprising them, and this tends to increase power. However, the larger number of haplotypes, relative to alleles at individual loci, tends to decrease power, because of the additional degrees of freedom required for the test. An optimal strategy would focus the test on particular haplotypes or groups of haplotypes. In this report we develop such an approach by combining the theory of TDT with that of measured haplotype analysis (MHA). MHA uses the evolutionary relationships among haplotypes to produce a limited set of hypothesis tests and to increase the interpretability of these tests. The theory of our approach, called the "evolutionary tree" (ET)-TDT, is developed for two cases: when haplotype transmission is certain and when it is not. Simulations show the ET-TDT can be more powerful than other proposed methods under reasonable conditions. More importantly, our results show that, when multiple polymorphisms are found within the gene, the ET-TDT can be useful for determining which polymorphisms affect liability.

Alleles↗
PubMed2001

A Bayesian hierarchical model for allele frequencies.

Genetic epidemiological methodologies, such as linkage analysis, often require accurate estimates of allele frequencies. When studies involve multiple sub-populations with different evolutionary histories, accurate estimates can be difficult to obtain because the number of subjects per sub-population tends to be limited. Given allele counts for a collection of loci and sub-populations, we propose a Bayesian hierarchical model that extends existing empirical Bayesian approaches by allowing for explicit inclusion of prior information about both allele frequencies and inter-population divergence. We describe how such information can be derived from published data and then incorporated into the model via prior distributions for model parameters. By analysis of simulated data, we highlight how the hierarchical model, as implemented in the publicly available program AllDist, combines prior information with the observed data to refine allele frequency estimates.

Alleles↗
PubMed2001

Unbiased methods for population-based association studies.

Large, population-based samples and large-scale genotyping are being used to evaluate disease/gene associations. A substantial drawback to such samples is the fact that population substructure can induce spurious associations between genes and disease. We review two methods, called genomic control (GC) and structured association (SA), that obviate many of the concerns about population substructure by using the features of the genomes present in the sample to correct for stratification. The GC approach exploits the fact that population substructure generates "over dispersion" of statistics used to assess association. By testing multiple polymorphisms throughout the genome, only some of which are pertinent to the disease of interest, the degree of overdispersion generated by population substructure can be estimated and taken into account. The SA approach assumes that the sampled population, although heterogeneous, is composed of subpopulations that are themselves homogeneous. By using multiple polymorphisms throughout the genome, this "latent class method" estimates the probability sampled individuals derive from each of these latent subpopulations. GC has the advantage of robustness, simplicity, and wide applicability, even to experimental designs such as DNA pooling. SA is a bit more complicated but has the advantage of greater power in some realistic settings, such as admixed populations or when association varies widely across subpopulations. It, too, is widely applicable. Both also have weaknesses, as elaborated in our review.

Analysis of Variance↗
PubMed2001

Genomic control, a new approach to genetic-based association studies.

During the past decade, mutations affecting liability to human disease have been discovered at a phenomenal rate, and that rate is increasing. For the most part, however, those diseases have a relatively simple genetic basis. For diseases with a complex genetic and environmental basis, new approaches are needed to pave the way for more rapid discovery of genes affecting liability. One such approach exploits large, population-based samples and large-scale genotyping to evaluate disease/gene associations. A substantial drawback to such samples is the fact that population heterogeneity can induce spurious associations between genes and disease. We describe a method called genomic control (GC), which obviates many of the concerns about population substructure by using the features of the genomes present in the sample to correct for stratification. Two such approaches are now available. The GC approach exploits the fact that population substructure generate "overdispersion" of statistics used to assess association. By testing multiple polymorphisms throughout the genome, only some of which are pertinent to the disease of interest, the degree of overdispersion generated by population substructure can be estimated and taken into account. The other approach, called Structured Association (SA), assumes that the sampled population, while heterogeneous, is composed of subpopulations that are themselves homogeneous. By using multiple polymorphisms throughout the genome, SA probabilistically assigns sampled individuals to these latent subpopulations. We review in detail the overdispersion GC. In addition to outlining the published ideas on this method, we describe several extensions: quantitative trait studies and case-control studies with haplotypes and multiallelic markers. For each study design our goal is to achieve control similar to that obtained for a family-based study, but with the convenience found in a population-based design.

Alleles↗
PubMed2001

Genome-wide distribution of linkage disequilibrium in the population of Palau and its implications for gene flow in Remote Oceania.

Linkage disequilibrium (LD) between alleles on the same human chromosome results from various evolutionary processes and is thus telling about the history of populations. Recently, LD has garnered substantial interest for its value to map and fine-map disease genes. We examine the distribution of LD between short tandem repeat alleles on autosomes and sex chromosomes in the Remote Oceanic population of Palau to evaluate whether the data are consistent with a recent hypothesis about the origins of genetic variation in Palau, specifically that the population experienced extensive male-biased gene flow following initial settlement. Consistent with evolutionary theory based on effective population size, LD between X-linked alleles is stochastically greater than LD between autosomal alleles, however, small but detectable LD occurs for autosomal markers separated by substantial distances. By contrast, while Y-linked alleles experience only one-third the effective population size of X-linked alleles, their mean value for pairwise LD is only slightly larger than X-linked alleles. For a small population known to experience at least two extreme bottlenecks, 56 six-locus Y haplotypes exhibit remarkable diversity (0.96), comparable to Y diversity of Europeans, however, autosomal and X-linked markers display significantly less diversity, as measured by heterozygosity (4.1% less). Palauan Y haplotypes also fall into distinct clusters, again unlike that of Europe. We argue these data are consistent with waves of male-biased gene flow.

Alleles↗
PubMed2001

A high-resolution integrated map spanning the SDHD gene at 11q23: a 1.1-Mb BAC contig, a partial transcript map and 15 new repeat polymorphisms in a tumour-suppressor region.

Chromosomal region 11q22-q23 is a frequent target for deletion during the development of many solid tumour types, including breast, ovary, cervix, stomach, bladder carcinomas and melanoma. One of the most commonly deleted subregions contains the SDHD gene, which encodes the small subunit of cytochrome b (cybS) in mitochondrial complex II (succinate-ubiquinone oxidoreductase). Germline mutations in SDHD cause hereditary paraganglioma type 1 (PGL1), and suggest a tumour suppressor role for cybS. We present a high-resolution physical map spanning SDHD, covered by 19 YACs and 20 BACs. An approximate 1.1-Mb gene-rich region around SDHD is spanned by a complete BAC contig. Twenty-six new STSs are developed from the BAC clone ends. In addition to the discovery and characterisation of 15 new simple tandem repeat polymorphisms, we provide integrated positional information for 33 ESTs and known genes, including KIAA1391, POU2AF1 (OBF1), PPP2R1B, CRYAB, HSPB2, DLAT, IL-18, PTPS, KIAA0781 and KAIA4591, which is mapped by NotI site cloning. We describe full-length transcript sequence for PPP2R1B, encoding the protein phosphatase 2A regulatory subunit A beta isoform. We also discover a processed pseudogene for USA-CYP, a cyclophilin associated with U4/U6 snRPNs, and a novel gene, DDP2, encoding a mitochondrial protein similar to the X-linked deafness-dystonia protein, which is juxtaposed 5'-to-5' to SDHD. This map will help assess this gene-rich region in PGL and in other common tumours.

3' Untranslated Regions↗
PubMed2000

The power of genomic control.

Although association analysis is a useful tool for uncovering the genetic underpinnings of complex traits, its utility is diminished by population substructure, which can produce spurious association between phenotype and genotype within population-based samples. Because family-based designs are robust against substructure, they have risen to the fore of association analysis. Yet, if population substructure could be ignored, this robustness can come at the price of power. Unfortunately it is rarely evident when population substructure can be ignored. Devlin and Roeder recently have proposed a method, termed "genomic control" (GC), which has the robustness of family-based designs even though it uses population-based data. GC uses the genome itself to determine appropriate corrections for population-based association tests. Using the GC method, we contrast the power of two study designs, family trios (i.e., father, mother, and affected progeny) versus case-control. For analysis of trios, we use the TDT test. When population substructure is absent, we find GC is always more powerful than TDT; furthermore, contrary to previous results, we show that as a disease becomes more prevalent the discrepancy in power becomes more extreme. When population substructure is present, however, the results are more complex: TDT is more powerful when population substructure is substantial, and GC is more powerful otherwise. We also explore general issues of power and implementation of GC within the case-control setting and find that, economically, GC is at least comparable to and often less expensive than family-based methods. Therefore, GC methods should prove a useful complement to family-based methods for the genetic analysis of complex traits.

Alleles↗