Simpson's Paradox, Lord's Paradox, and Suppression Effects are the same phenomenon – the reversal paradox

This article discusses three statistical paradoxes that pervade epidemiological research: Simpson's paradox, Lord's paradox, and suppression. These paradoxes have important implications for the interpretation of evidence from observational studies. This article uses hypothetical scenarios to illustrate how the three paradoxes are different manifestations of one phenomenon – the reversal paradox – depending on whether the outcome and explanatory variables are categorical, continuous or a combination of both; this renders the issues and remedies for any one to be similar for all three. Although the three statistical paradoxes occur in different types of variables, they share the same characteristic: the association between two variables can be reversed, diminished, or enhanced when another variable is statistically controlled for. Understanding the concepts and theory behind these paradoxes provides insights into some controversial or contradictory research findings. These paradoxes show that prior knowledge and underlying causal theory play an important role in the statistical modelling of epidemiological data, where incorrect use of statistical models might produce consistent, replicable, yet erroneous results

Systematic Bias in Genomic Classification Due to Contaminating Non-neoplastic Tissue in Breast Tumor Samples

Abstract Background Genomic tests are available to predict breast cancer recurrence and to guide clinical decision making. These predictors provide recurrence risk scores along with a measure of uncertainty, usually a confidence interval. The confidence interval conveys random error and not systematic bias. Standard tumor sampling methods make this problematic, as it is common to have a substantial proportion (typically 30-50%) of a tumor sample comprised of histologically benign tissue. This "normal" tissue could represent a source of non-random error or systematic bias in genomic classification. Methods To assess the performance characteristics of genomic classification to systematic error from normal contamination, we collected 55 tumor samples and paired tumor-adjacent normal tissue. Using genomic signatures from the tumor and paired normal, we evaluated how increasing normal contamination altered recurrence risk scores for various genomic predictors. Results Simulations of normal tissue contamination caused misclassification of tumors in all predictors evaluated, but different breast cancer predictors showed different types of vulnerability to normal tissue bias. While two predictors had unpredictable direction of bias (either higher or lower risk of relapse resulted from normal contamination), one signature showed predictable direction of normal tissue effects. Due to this predictable direction of effect, this signature (the PAM50) was adjusted for normal tissue contamination and these corrections improved sensitivity and negative predictive value. For all three assays quality control standards and/or appropriate bias adjustment strategies can be used to improve assay reliability. Conclusions Normal tissue sampled concurrently with tumor is an important source of bias in breast genomic predictors. All genomic predictors show some sensitivity to normal tissue contamination and ideal strategies for mitigating this bias vary depending upon the particular genes and computational methods used in the predictor

The emerging role of MIR-146A in the control of hematopoiesis, immune function and cancer

MicroRNA (miRs) represent a class of small non-coding regulatory RNAs playing a major role in the control of gene expression by repressing protein synthesis at the post-transcriptional level. Studies carried out during the last years have shown that some miRNAs plays a key role in the control of normal and malignant hgematopoiesis. In this review we focus on recent progress in analyzing the functional role of miR-146a in the control of normal and malignant hematopoiesis. On the other hand, this miRNA has shown to impact in the control of innate immune responses. Finally, many recent studies indicate a deregulation of miR-146 in many solid tumors and gene knockout studies indicate a role for this miRNA as a tumor suppressor

Screening in strongly coupled N=2* supersymmetric Yang-Mills plasma

Using gauge-gravity duality, we extend thermodynamic studies and present results for thermal screening masses in strongly coupled N=2* supersymmetric Yang-Mills theory. This non-conformal theory is a mass deformation of maximally supersymmetric N=4 gauge theory. Results are obtained for the entropy density, pressure, specific heat, equation of state, and screening masses, down to previously unexplored low temperatures. The temperature dependence of screening masses in various symmetry channels, which characterize the longest length scales over which thermal fluctuations in the non-Abelian plasma are correlated, is examined and found to be asymptotically linear in the low temperature regime.Comment: 43 pages, 13 figures, typo fixed, published versio

SpxA1 Involved in Hydrogen Peroxide Production, Stress Tolerance and Endocarditis Virulence in Streptococcus sanguinis

Streptococcus sanguinis is one of the most common agents of infective endocarditis. Spx proteins are a group of global regulators that negatively or positively control global transcription initiation. In this study, we characterized the spxA1 gene in S. sanguinis SK36. The spxA1 null mutant displayed opaque colony morphology, reduced hydrogen peroxide (H2O2) production, and reduced antagonistic activity against Streptococcus mutans UA159 relative to the wild type strain. The ΔspxA1 mutant also demonstrated decreased tolerance to high temperature, acidic and oxidative stresses. Further analysis revealed that ΔspxA1 also exhibited a ∼5-fold reduction in competitiveness in an animal model of endocarditis. Microarray studies indicated that expression of several oxidative stress genes was downregulated in the ΔspxA1 mutant. The expression of spxB and nox was significantly decreased in the ΔspxA1 mutant compared with the wild type. These results indicate that spxA1 plays a major role in H2O2 production, stress tolerance and endocarditis virulence in S. sanguinis SK36. The second spx gene, spxA2, was also found in S. sanguinis SK36. The spxA2 null mutant was found to be defective for growth under normal conditions and showed sensitivity to high temperature, acidic and oxidative stresses

Do Two Machine-Learning Based Prognostic Signatures for Breast Cancer Capture the Same Biological Processes?

The fact that there is very little if any overlap between the genes of different prognostic signatures for early-discovery breast cancer is well documented. The reasons for this apparent discrepancy have been explained by the limits of simple machine-learning identification and ranking techniques, and the biological relevance and meaning of the prognostic gene lists was questioned. Subsequently, proponents of the prognostic gene lists claimed that different lists do capture similar underlying biological processes and pathways. The present study places under scrutiny the validity of this claim, for two important gene lists that are at the focus of current large-scale validation efforts. We performed careful enrichment analysis, controlling the effects of multiple testing in a manner which takes into account the nested dependent structure of gene ontologies. In contradiction to several previous publications, we find that the only biological process or pathway for which statistically significant concordance can be claimed is cell proliferation, a process whose relevance and prognostic value was well known long before gene expression profiling. We found that the claims reported by others, of wider concordance between the biological processes captured by the two prognostic signatures studied, were found either to be lacking statistical rigor or were in fact based on addressing some other question

The functional loss of the retinoblastoma tumour suppressor is a common event in basal-like and luminal B breast carcinomas

Introduction Breast cancers can be classified using whole genome expression into distinct subtypes that show differences in prognosis. One of these groups, the basal-like subtype, is poorly differentiated, highly metastatic, genomically unstable, and contains specific genetic alterations such as the loss of tumour protein 53 (TP53). The loss of the retinoblastoma tumour suppressor encoded by the RB1 locus is a well-characterised occurrence in many tumour types; however, its role in breast cancer is less clear with many reports demonstrating a loss of heterozygosity that does not correlate with a loss of RB1 protein expression. Methods We used gene expression analysis for tumour subtyping and polymorphic markers located at the RB1 locus to assess the frequency of loss of heterozygosity in 88 primary human breast carcinomas and their normal tissue genomic DNA samples. Results RB1 loss of heterozygosity was observed at an overall frequency of 39%, with a high frequency in basal-like (72%) and luminal B (62%) tumours. These tumours also concurrently showed low expression of RB1 mRNA. p16INK4a was highly expressed in basal-like tumours, presumably due to a previously reported feedback loop caused by RB1 loss. An RB1 loss of heterozygosity signature was developed and shown to be highly prognostic, and was potentially a predictive marker of response to neoadjuvant chemotherapy. Conclusions These results suggest that the functional loss of RB1 is common in basal-like tumours, which may play a key role in dictating their aggressive biology and unique therapeutic responses