What Can Causal Networks Tell Us about Metabolic Pathways?

Graphical models describe the linear correlation structure of data and have been used to establish causal relationships among phenotypes in genetic mapping populations. Data are typically collected at a single point in time. Biological processes on the other hand are often non-linear and display time varying dynamics. The extent to which graphical models can recapitulate the architecture of an underlying biological processes is not well understood. We consider metabolic networks with known stoichiometry to address the fundamental question: “What can causal networks tell us about metabolic pathways?”. Using data from an Arabidopsis BaySha population and simulated data from dynamic models of pathway motifs, we assess our ability to reconstruct metabolic pathways using graphical models. Our results highlight the necessity of non-genetic residual biological variation for reliable inference. Recovery of the ordering within a pathway is possible, but should not be expected. Causal inference is sensitive to subtle patterns in the correlation structure that may be driven by a variety of factors, which may not emphasize the substrate-product relationship. We illustrate the effects of metabolic pathway architecture, epistasis and stochastic variation on correlation structure and graphical model-derived networks. We conclude that graphical models should be interpreted cautiously, especially if the implied causal relationships are to be used in the design of intervention strategies

Cervical Cancer Screening with Liquid Cytology in Women with Developmental Disabilities

Abstract Objective: To evaluate the use of liquid cytology in Pap smears in women with developmental disabilities (DD) for endocervical cell yield and abnormalities, via speculum examination or blind technique. Methods: We used retrospective chart review of gynecological visits by women with DD from October 2002 to November 2005. Cervical cytology screening included speculum examination or blind technique. Endocervical cell yield was analyzed via Pearson's chi-square test. Results: Of 240 attempted liquid cytology Pap smears, 199 (82.9%) were completed. Of these, 193 met inclusion criteria for the study, and 120 (62.2%) contained endocervical cells. The endocervical cell yield with liquid cytology/speculum was 80.0% and was 43.6% with liquid cytology/blind (p < 0.001). Two blind smears (1.0%) were abnormal; both revealed atypical squamous cells of undetermined significance (ASCUS) with subsequent negative human papillomavirus (HPV) typing. Conclusions: Cervical screening with liquid cytology in women with DD provides an overall rate of endocervical cells of approximately 44%-80% depending on the technique used. Although this is much lower than in the general population, this compares favorably with slide Pap smear in women with DD. The 44% yield of endocervical cells and the finding of abnormal Pap smears with the blind technique suggest this is a reasonable alternative for obtaining Pap smears in women with difficult pelvic examinations who otherwise would not receive cervical screening.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/78111/1/jwh.2008.0795.pd