Confidentiality in genome research.
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Genetic Privacy↗
Biomedical subjects
Art B Owen
Publications and source records attributed to Art B Owen.
Transcriptional profiling of aging in human muscle reveals a common aging signature.
We analyzed expression of 81 normal muscle samples from humans of varying ages, and have identified a molecular profile for aging consisting of 250 age-regulated genes. This molecular profile correlates not only with chronological age but also with a measure of physiological age. We compared the transcriptional profile of muscle aging to previous transcriptional profiles of aging in the kidney and the brain, and found a common signature for aging in these diverse human tissues. The common aging signature consists of six genetic pathways; four pathways increase expression with age (genes in the extracellular matrix, genes involved in cell growth, genes encoding factors involved in complement activation, and genes encoding components of the cytosolic ribosome), while two pathways decrease expression with age (genes involved in chloride transport and genes encoding subunits of the mitochondrial electron transport chain). We also compared transcriptional profiles of aging in humans to those of the mouse and fly, and found that the electron transport chain pathway decreases expression with age in all three organisms, suggesting that this may be a public marker for aging across species.
Adolescent↗
A quasi-Monte Carlo Metropolis algorithm.
This work presents a version of the Metropolis-Hastings algorithm using quasi-Monte Carlo inputs. We prove that the method yields consistent estimates in some problems with finite state spaces and completely uniformly distributed inputs. In some numerical examples, the proposed method is much more accurate than ordinary Metropolis-Hastings sampling.
Algorithms↗
A transcriptional profile of aging in the human kidney.
In this study, we found 985 genes that change expression in the cortex and the medulla of the kidney with age. Some of the genes whose transcripts increase in abundance with age are known to be specifically expressed in immune cells, suggesting that immune surveillance or inflammation increases with age. The age-regulated genes show a similar aging profile in the cortex and the medulla, suggesting a common underlying mechanism for aging. Expression profiles of these age-regulated genes mark not only age, but also the relative health and physiology of the kidney in older individuals. Finally, the set of aging-regulated kidney genes suggests specific mechanisms and pathways that may play a role in kidney degeneration with age.
Adult↗
Genetics. Genomic research and human subject privacy.
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Databases, Genetic↗
A Bayesian framework for combining heterogeneous data sources for gene function prediction (in Saccharomyces cerevisiae).
Genomic sequencing is no longer a novelty, but gene function annotation remains a key challenge in modern biology. A variety of functional genomics experimental techniques are available, from classic methods such as affinity precipitation to advanced high-throughput techniques such as gene expression microarrays. In the future, more disparate methods will be developed, further increasing the need for integrated computational analysis of data generated by these studies. We address this problem with MAGIC (Multisource Association of Genes by Integration of Clusters), a general framework that uses formal Bayesian reasoning to integrate heterogeneous types of high-throughput biological data (such as large-scale two-hybrid screens and multiple microarray analyses) for accurate gene function prediction. The system formally incorporates expert knowledge about relative accuracies of data sources to combine them within a normative framework. MAGIC provides a belief level with its output that allows the user to vary the stringency of predictions. We applied MAGIC to Saccharomyces cerevisiae genetic and physical interactions, microarray, and transcription factor binding sites data and assessed the biological relevance of gene groupings using Gene Ontology annotations produced by the Saccharomyces Genome Database. We found that by creating functional groupings based on heterogeneous data types, MAGIC improved accuracy of the groupings compared with microarray analysis alone. We describe several of the biological gene groupings identified.
Algorithms↗
Nomogram for predicting the likelihood of delayed graft function in adult cadaveric renal transplant recipients.
Delayed graft function (DGF) is the need for dialysis in the first week after transplantation. Studied were risk factors for DGF in adult (age >/=16 yr) cadaveric renal transplant recipients by means of a multivariable modeling procedure. Only donor and recipient factors known before transplantation were chosen so that the probabilities of DGF could be calculated before transplantation and appropriate preventative measures taken. Data on 19,706 recipients of cadaveric allografts were obtained from the United States Renal Data System registry (1995 to 1998). Graft losses within the first 24 h after surgery were excluded from the analysis (n = 89). Patients whose DGF information was missing or unknown (n = 2820) and patients missing one or more candidate predictors (n = 2951) were also excluded. By means of a multivariable logistic regression analysis, factors contributing to DGF in the remaining 13,846 patients were identified. After validating the logistic regression model, a nomogram was developed as a tool for identifying patients at risk for DGF. The incidence of DGF was 23.7%. Sixteen independent donor or recipient risk factors were found to predict DGF. A nomogram quantifying the relative contribution of each risk factor was created. This index can be used to calculate the risk of DGF for an individual by adding the points associated with each risk factor. The nomogram provides a useful tool for developing a pretransplantation index of the likelihood of DGF occurrence. With this index in hand, better informed treatment and allocation decisions can be made.
Adolescent↗
A gene recommender algorithm to identify coexpressed genes in C. elegans.
One of the most important uses of whole-genome expression data is for the discovery of new genes with similar function to a given list of genes (the query) already known to have closely related function. We have developed an algorithm, called the gene recommender, that ranks genes according to how strongly they correlate with a set of query genes in those experiments for which the query genes are most strongly coregulated. We used the gene recommender to find other genes coexpressed with several sets of query genes, including genes known to function in the retinoblastoma complex. Genetic experiments confirmed that one gene (JC8.6) identified by the gene recommender acts with lin-35 Rb to regulate vulval cell fates, and that another gene (wrm-1) acts antagonistically. We find that the gene recommender returns lists of genes with better precision, for fixed levels of recall, than lists generated using the C. elegans expression topomap.
Algorithms↗