Papers by Nicola Armstrong
Oncogene, 2013
Deregulation of microRNA (miRNA) expression can have a critical role in carcinogenesis. Here we s... more Deregulation of microRNA (miRNA) expression can have a critical role in carcinogenesis. Here we show in prostate cancer that miRNA-205 (miR-205) transcription is commonly repressed and the MIR-205 locus is hypermethylated. LOC642587, the MIR-205 host gene of unknown function, is also concordantly inactivated. We show that miR-205 targets mediator 1 (MED1, also called TRAP220 and PPARBP) for transcriptional silencing in normal prostate cells, leading to reduction in MED1 mRNA levels, and in total and active phospho-MED1 protein. Overexpression of miR-205 in prostate cancer cells negatively affects cell viability, consistent with a tumor suppressor function. We found that hypermethylation of the MIR-205 locus was strongly related with a decrease in miR-205 expression and an increase in MED1 expression in primary tumor samples (n ¼ 14), when compared with matched normal prostate (n ¼ 7). An expanded patient cohort (tumor n ¼ 149, matched normal n ¼ 30) also showed significant MIR-205 DNA methylation in tumors compared with normal, and MIR-205 hypermethylation is significantly associated with biochemical recurrence (hazard ratio ¼ 2.005, 95% confidence interval (1.109, 3.625), P ¼ 0.02), in patients with low preoperative prostate specific antigen. In summary, these results suggest that miR-205 is an epigenetically regulated tumor suppressor that targets MED1 and may provide a potential biomarker in prostate cancer management.
Brain Imaging and Behavior, 2014
Human Molecular Genetics, 2010
Multiple sclerosis (MS) is an autoimmune disease with a genetic component, caused at least in par... more Multiple sclerosis (MS) is an autoimmune disease with a genetic component, caused at least in part by aberrant lymphocyte activity. The whole blood mRNA transcriptome was measured for 99 untreated MS patients: 43 primary progressive MS, 20 secondary progressive MS, 36 relapsing remitting MS and 45 age-matched healthy controls. The ANZgene Multiple Sclerosis Genetics Consortium genotyped more than 300 000 SNPs for 115 of these samples. Transcription from genes on translational regulation, oxidative phosphorylation, immune synapse and antigen presentation pathways was markedly increased in all forms of MS. Expression of genes tagging T cells was also upregulated (P < 10(-12)) in MS. A T cell gene signature predicts disease state with a concordance index of 0.79 with age and gender as co-variables, but the signature is not associated with clinical course or disability. The ANZgene genome wide association screen identified two novel regions with genome wide significance: one encoding the T cell co-stimulatory molecule, CD40; the other a region on chromosome 12q13-14. The CD40 haplotype associated with increased MS susceptibility has decreased gene expression in MS (P < 0.0007). The second MS susceptibility region includes 17 genes on 12q13-14 in tight linkage disequilibrium. Of these, only 13 are expressed in leukocytes, and of these the expression of one, FAM119B, is much lower in the susceptibility haplotype (P…
Biostatistics, 2005
The phenomenon of interference in genetic recombination is well-known and studied in a wide varie... more The phenomenon of interference in genetic recombination is well-known and studied in a wide variety of organisms. Multilocus linkage analysis, which makes use of recombination patterns among all genetic markers simultaneously, is routinely used with data on humans and experimental organisms to build genetic maps. It is also used to try to determine the genes involved in traits of interest, such as common diseases. Most linkage analyses performed today ignore the occurrence of genetical interference. We present an extension to the Lander-Green algorithm for experimental crosses (backcross and intercross) to incorporate crossover interference according to the χ 2 model. Simulation results show the impact of using this model on the accuracy of estimated genetic maps.
Cell Oncol, 2004
We review several commonly used methods for the design and analysis of microarray data. To begin ... more We review several commonly used methods for the design and analysis of microarray data. To begin with, some experimental design issues are addressed. Several approaches for pre-processing the data (filtering and normalization) before the statistical analysis stage are then discussed. A common first step in this type of analysis is gene selection based on statistical testing. Two approaches, permutation and model-based methods are explained and we emphasize the need to correct for multiple testing. Moreover, powerful approaches based on gene sets are mentioned. Clustering of either genes or samples is frequently performed when analyzing microarray data. We summarize the basics of both supervised and unsupervised clustering (classification). The latter may be of use for creating diagnostic arrays, for example. Construction of biological networks, such as pathways, is a statistically challenging but complex task that is a relatively new development and hence mentioned only briefly. We finish with some remarks on literature and software. The emphasis in this paper is on the philosophy behind several statistical issues and on a critical interpretation of microarray related analysis methods.
Molecular immunology, Jan 21, 2015
Regular plasma donors who produce high titre anti-D immunoglobulin (Ig) are overseen by the Austr... more Regular plasma donors who produce high titre anti-D immunoglobulin (Ig) are overseen by the Australian Red Cross Blood Service RhD Program. New donors to the program are immunised with small amounts of RhD-positive RBCs, whilst donors who have developed anti-D due to previous RhD-incompatible blood transfusion or pregnancy are boosted with RhD-positive RBCs to maintain a high level of serum anti-D Ig. A significant proportion of primarily immunised individuals do not respond to RhD immunisation and are therefore unnecessarily exposed to the risks involved in RBC sensitisation. We genotyped 184 anti-D donors for ∼9000 immunological and inflammatory genetic polymorphisms on an Affymetrix GeneChip, and validated the results with a High-Resolution Melt analysis assay. We built and validated a predictive logistic regression model using High Responder and Non-Responder anti-D donors that incorporated highly-associated polymorphisms and gender. High Responder and Non-Responder profiles in ...
Up to 30% of adult patients with sickle cell disease (SCD) will develop pulmonary hypertension (p... more Up to 30% of adult patients with sickle cell disease (SCD) will develop pulmonary hypertension (pHTN), a complication associated with significant morbidity and mortality. To identify genetic factors that contribute to risk for pHTN in SCD, we performed association analysis with 297 single nucleotide polymorphisms (SNPs) in 49 candidate genes in patients with sickle cell anemia (Hb SS) who had been screened for pHTN by echocardiography (n = 111). Evidence of association was primarily identified for genes in the TGFbeta superfamily, including activin A receptor, type II-like 1 (ACVRL1), bone morphogenetic protein receptor 2 (BMPR2), and bone morphogenetic protein 6 (BMP6). The association of pHTN with ACVRL1 and BMPR2 corroborates the previous association of these genes with primary pHTN. Moreover, genes in the TGFbeta pathway have been independently implicated in risk for several sickle cell complications, suggesting that this gene pathway is important in overall sickle cell pathophysiology. Genetic variation in the beta-1 adrenergic receptor (ADRB1) was also associated with pHTN in our dataset. A multiple regression model, which included age and baseline hemoglobin as covariates, retained SNPs in ACVRL1, BMP6, and ADRB1 as independently contributing to pHTN risk. These findings may offer new promise for identifying patients at risk for pHTN, developing new therapeutic targets, and reducing the occurrence of this life-threatening SCD complication.
Statistica Neerlandica, 2008
In the biological sciences, the advent of microarray technology changed the way experiments were ... more In the biological sciences, the advent of microarray technology changed the way experiments were performed. Microarrays were the first mainstream high-throughput technology, generating enormous amounts of data for both the biologist and the statistician to understand. Here, I follow my own experience in microarray analysis, starting during my time at EURANDOM with experimental design and continuing today in my present position at the Netherlands Cancer Institute where the exploitation of data from many different sources is hoped will give greater insight into different aspects of cancer.
Shock, 2013
There is currently no reliable tool available to measure immune dysfunction in septic patients in... more There is currently no reliable tool available to measure immune dysfunction in septic patients in the clinical setting. This proof-of-concept study assesses the potential of gene expression profiling of whole blood as a tool to monitor immune dysfunction in critically ill septic patients. Whole-blood samples were collected daily for up to 5 days from patients admitted to the intensive care unit with sepsis. RNA isolated from whole-blood samples was assayed on Illumina HT-12 gene expression microarrays consisting of 48,804 probes. Microarray analysis identified 3,677 genes as differentially expressed across 5 days between septic patients and healthy controls. Of the 3,677 genes, biological pathway analysis identified 86 genes significantly downregulated in the sepsis patients were present in pathways relating to immune response. These 86 genes correspond to known immune pathways implicated in sepsis, including lymphocyte depletion, reduced T-lymphocyte activation, and deficient antigen presentation. Furthermore, expression levels of these genes correlated with clinical severity, with a significantly greater degree of downregulation found in nonsurvivors compared with survivors. The results show that whole-blood gene expression analysis can capture systemic immune dysfunctions in septic patients. Our study provides an experimental basis to support further study on the use of a gene expression-based assay, to assess immunosuppression, and to guide immunotherapy in future clinical trials.
Mammalian Genome, 2006
The development of congenic mouse strains is the principal approach for confirming and fine mappi... more The development of congenic mouse strains is the principal approach for confirming and fine mapping quantitative trait loci, as well as for comparing the phenotypic effect of a transgene or gene-targeted disruption between different inbred mouse strains. The traditional breeding scheme calls for at least nine consecutive backcrosses before establishing a congenic mouse strain. Recent availability of genome sequence and high-throughput genotyping now permit the use of polymorphic DNA markers to reduce this number of backcrosses, and empirical data suggest that marker-assisted breeding may require as few as four backcrosses. We used simulation studies to investigate the efficiency of different marker-assisted breeding schemes by examining the trade-off between the number of backcrosses, the number of mice produced per generation, and the number of genotypes per mouse required to achieve a quality congenic mouse strain. An established model of crossover interference was also incorporated into these simulations. The quality of the strain produced was assessed by the probability of an undetected region of heterozygosity (i.e., ''gaps'') in the recipient genetic background, while maintaining the desired donor-derived interval. Somewhat surprisingly, we found that there is a relatively high probability for undetected gaps in potential breeders for establishing a congenic mouse strain. Marker-assisted breeding may decrease the number of backcross generations required to generate a congenic strain, but only additional backcrossing will guarantee a reduction in the number and length of undetected gaps harboring contaminating donor alleles.
Journal of Experimental Medicine, 2010
Genetical Research, 2004
Selective genotyping concerns the genotyping of a portion of individuals chosen on the basis of t... more Selective genotyping concerns the genotyping of a portion of individuals chosen on the basis of their phenotypic values. Often individuals are selected for genotyping from the high and low extremes of the phenotypic distribution. This procedure yields savings in cost and time by decreasing the total number of individuals genotyped. Previous work by Darvasi et al. (1993) has shown that the power to detect a QTL by genotyping 40-50 % of a population is roughly equivalent to genotyping the entire sample. However, these power studies have not accounted for different strategies of analysing the data when phenotypes of individuals in the middle are excluded, nor have they investigated the genome-wide type I error rate under these different strategies or different selection percentages. Further, these simulation studies have not considered markers over the entire genome. In this paper, we present simulation studies of power for the maximum likelihood approach to QTL mapping by Lander & Botstein (1989) in the context of selective genotyping. We calculate the power of selectively genotyping the individuals from the middle of the phenotypic distribution when performing QTL mapping over the whole mouse genome.
European Journal of Neuroscience, 2007
Successful regeneration of injured neurons requires a complex molecular response that involves th... more Successful regeneration of injured neurons requires a complex molecular response that involves the expression, modification and transport of a large number of proteins. The identity of neuronal proteins responsible for the initiation of regenerative neurite outgrowth is largely unknown. Dorsal root ganglion (DRG) neurons display robust and successful regeneration following lesion of their peripheral neurite, whereas outgrowth of central neurites is weak and does not lead to functional recovery. We have utilized this differential response to gain insight in the early transcriptional events associated with successful regeneration. Surprisingly, our study shows that peripheral and central nerve crushes elicit very distinct transcriptional activation, revealing a large set of novel genes that are differentially regulated within the first 24 h after the lesion. Here we show that Ankrd1, a gene known to act as a transcriptional modulator, is involved in neurite outgrowth of a DRG neuron-derived cell line as well as in cultured adult DRG neurons. This gene, and others identified in this study, may be part of the transcriptional regulatory module that orchestrates the onset of successful regeneration.
Biostatistics, 2005
The phenomenon of interference in genetic recombination is well-known and studied in a wide varie... more The phenomenon of interference in genetic recombination is well-known and studied in a wide variety of organisms. Multilocus linkage analysis, which makes use of recombination patterns among all genetic markers simultaneously, is routinely used with data on humans and experimental organisms to build genetic maps. It is also used to try to determine the genes involved in traits of interest, such as common diseases. Most linkage analyses performed today ignore the occurrence of genetical interference. We present an extension to the Lander-Green algorithm for experimental crosses (backcross and intercross) to incorporate crossover interference according to the χ 2 model. Simulation results show the impact of using this model on the accuracy of estimated genetic maps.
Cellular oncology : the official journal of the International Society for Cellular Oncology, 2004
We review several commonly used methods for the design and analysis of microarray data. To begin ... more We review several commonly used methods for the design and analysis of microarray data. To begin with, some experimental design issues are addressed. Several approaches for pre-processing the data (filtering and normalization) before the statistical analysis stage are then discussed. A common first step in this type of analysis is gene selection based on statistical testing. Two approaches, permutation and model-based methods are explained and we emphasize the need to correct for multiple testing. Moreover, powerful approaches based on gene sets are mentioned. Clustering of either genes or samples is frequently performed when analyzing microarray data. We summarize the basics of both supervised and unsupervised clustering (classification). The latter may be of use for creating diagnostic arrays, for example. Construction of biological networks, such as pathways, is a statistically challenging but complex task that is a relatively new development and hence mentioned only briefly. We ...
Translational Bioinformatics, 2012
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Papers by Nicola Armstrong