Beta-arrestins regulate atherosclerosis and neointimal hyperplasia by controlling smooth muscle cell proliferation and migration.

Atherosclerosis and arterial injury-induced neointimal hyperplasia involve medial smooth muscle cell (SMC) proliferation and migration into the arterial intima. Because many 7-transmembrane and growth factor receptors promote atherosclerosis, we hypothesized that the multifunctional adaptor proteins beta-arrestin1 and -2 might regulate this pathological process. Deficiency of beta-arrestin2 in ldlr(-/-) mice reduced aortic atherosclerosis by 40% and decreased the prevalence of atheroma SMCs by 35%, suggesting that beta-arrestin2 promotes atherosclerosis through effects on SMCs. To test this potential atherogenic mechanism more specifically, we performed carotid endothelial denudation in congenic wild-type, beta-arrestin1(-/-), and beta-arrestin2(-/-) mice. Neointimal hyperplasia was enhanced in beta-arrestin1(-/-) mice, and diminished in beta-arrestin2(-/-) mice. Neointimal cells expressed SMC markers and did not derive from bone marrow progenitors, as demonstrated by bone marrow transplantation with green fluorescent protein-transgenic cells. Moreover, the reduction in neointimal hyperplasia seen in beta-arrestin2(-/-) mice was not altered by transplantation with either wild-type or beta-arrestin2(-/-) bone marrow cells. After carotid injury, medial SMC extracellular signal-regulated kinase activation and proliferation were increased in beta-arrestin1(-/-) and decreased in beta-arrestin2(-/-) mice. Concordantly, thymidine incorporation and extracellular signal-regulated kinase activation and migration evoked by 7-transmembrane receptors were greater than wild type in beta-arrestin1(-/-) SMCs and less in beta-arrestin2(-/-) SMCs. Proliferation was less than wild type in beta-arrestin2(-/-) SMCs but not in beta-arrestin2(-/-) endothelial cells. We conclude that beta-arrestin2 aggravates atherosclerosis through mechanisms involving SMC proliferation and migration and that these SMC activities are regulated reciprocally by beta-arrestin2 and beta-arrestin1. These findings identify inhibition of beta-arrestin2 as a novel therapeutic strategy for combating atherosclerosis and arterial restenosis after angioplasty.

BAYESIAN MODEL SEARCH AND MULTILEVEL INFERENCE FOR SNP ASSOCIATION STUDIES.

Technological advances in genotyping have given rise to hypothesis-based association studies of increasing scope. As a result, the scientific hypotheses addressed by these studies have become more complex and more difficult to address using existing analytic methodologies. Obstacles to analysis include inference in the face of multiple comparisons, complications arising from correlations among the SNPs (single nucleotide polymorphisms), choice of their genetic parametrization and missing data. In this paper we present an efficient Bayesian model search strategy that searches over the space of genetic markers and their genetic parametrization. The resulting method for Multilevel Inference of SNP Associations, MISA, allows computation of multilevel posterior probabilities and Bayes factors at the global, gene and SNP level, with the prior distribution on SNP inclusion in the model providing an intrinsic multiplicity correction. We use simulated data sets to characterize MISA's statistical power, and show that MISA has higher power to detect association than standard procedures. Using data from the North Carolina Ovarian Cancer Study (NCOCS), MISA identifies variants that were not identified by standard methods and have been externally "validated" in independent studies. We examine sensitivity of the NCOCS results to prior choice and method for imputing missing data. MISA is available in an R package on CRAN.

Polymorphisms at the microRNA binding-site of the stem cell marker gene CD133 modify susceptibility to and survival of gastric cancer.

CD133 is one of the most common stem cell markers, and functional single nucleotide polymorphisms (SNPs) of CD133 may modulate its gene functions and thus cancer risk and patient survival. We hypothesized that potentially functional CD133 SNPs are associated with gastric cancer (GC) risk and survival. To test this hypothesis, we conducted a case-control study of 371 GC patients and 313 cancer-free controls frequency-matched by age, sex, and ethnicity. We genotyped four selected, potentially functional CD133 SNPs (rs2240688A>C, rs7686732C>G, rs10022537T>A, and rs3130C>T) and used logistic regression analysis for associations of these SNPs with GC risk and Cox hazards regression analysis for survival. We found that compared with the miRNA binding site rs2240688 AA genotype, AC + CC genotypes were associated with significantly increased GC risk (adjusted OR = 1.52, 95% CI = 1.09-2.13); for another miRNA binding site rs3130C>T SNP, the TT genotype was associated with significantly reduced GC risk (adjusted OR = 0.68, 95% CI = 0.48-0.97), compared with CC + CT genotypes. In all patients, the risk rs3130 TT variant genotype was significantly associated with overall survival (OS) (adjusted P(trend) = 0.016 and 0.007 under additive and recessive models, respectively). These findings suggest that these two CD133 miRNA binding site variants, rs2240688 and rs3130, may be potential biomarkers for genetic susceptibility to GC and possible predictors for survival in GC patients but require further validation by larger studies.

A novel inflammatory biomarker, GlycA, associates with disease activity in rheumatoid arthritis and cardio-metabolic risk in BMI-matched controls

BACKGROUND: RA and CVD both have inflammation as part of the underlying biology. Our objective was to explore the relationships of GlycA, a measure of glycosylated acute phase proteins, with inflammation and cardiometabolic risk in RA, and explore whether these relationships were similar to those for persons without RA. METHODS: Plasma GlycA was determined for 50 individuals with mild-moderate RA disease activity and 39 controls matched for age, gender, and body mass index (BMI). Regression analyses were performed to assess relationships between GlycA and important markers of traditional inflammation and cardio-metabolic health: inflammatory cytokines, disease activity, measures of adiposity and insulin resistance. RESULTS: On average, RA activity was low (DAS-28 = 3.0 ± 1.4). Traditional inflammatory markers, ESR, hsCRP, IL-1β, IL-6, IL-18 and TNF-α were greater in RA versus controls (P < 0.05 for all). GlycA concentrations were significantly elevated in RA versus controls (P = 0.036). In RA, greater GlycA associated with disease activity (DAS-28; RDAS-28 = 0.5) and inflammation (RESR = 0.7, RhsCRP = 0.7, RIL-6 = 0.3: P < 0.05 for all); in BMI-matched controls, these inflammatory associations were absent or weaker (hsCRP), but GlycA was related to IL-18 (RhsCRP = 0.3, RIL-18 = 0.4: P < 0.05). In RA, greater GlycA associated with more total abdominal adiposity and less muscle density (Rabdominal-adiposity = 0.3, Rmuscle-density = -0.3, P < 0.05 for both). In BMI-matched controls, GlycA associated with more cardio-metabolic markers: BMI, waist circumference, adiposity measures and insulin resistance (R = 0.3-0.6, P < 0.05 for all). CONCLUSIONS: GlycA provides an integrated measure of inflammation with contributions from traditional inflammatory markers and cardio-metabolic sources, dominated by inflammatory markers in persons with RA and cardio-metabolic factors in those without.

Politics by number: Indicators as social pressure in international relations

© 2014, Midwest Political Science Association.The ability to monitor state behavior has become a critical tool of international governance. Systematic monitoring allows for the creation of numerical indicators that can be used to rank, compare, and essentially censure states. This article argues that the ability to disseminate such numerical indicators widely and instantly constitutes an exercise of social power, with the potential to change important policy outputs. It explores this argument in the context of the United States' efforts to combat trafficking in persons and find evidence that monitoring has important effects: Countries are more likely to criminalize human trafficking when they are included in the U.S. annual Trafficking in Persons Report, and countries that are placed on a "watch list" are also more likely to criminalize. These findings have broad implications for international governance and the exercise of soft power in the global information age.

Evaluating marker-guided treatment selection strategies

© 2014, The International Biometric Society.A potential venue to improve healthcare efficiency is to effectively tailor individualized treatment strategies by incorporating patient level predictor information such as environmental exposure, biological, and genetic marker measurements. Many useful statistical methods for deriving individualized treatment rules (ITR) have become available in recent years. Prior to adopting any ITR in clinical practice, it is crucial to evaluate its value in improving patient outcomes. Existing methods for quantifying such values mainly consider either a single marker or semi-parametric methods that are subject to bias under model misspecification. In this article, we consider a general setting with multiple markers and propose a two-step robust method to derive ITRs and evaluate their values. We also propose procedures for comparing different ITRs, which can be used to quantify the incremental value of new markers in improving treatment selection. While working models are used in step I to approximate optimal ITRs, we add a layer of calibration to guard against model misspecification and further assess the value of the ITR non-parametrically, which ensures the validity of the inference. To account for the sampling variability of the estimated rules and their corresponding values, we propose a resampling procedure to provide valid confidence intervals for the value functions as well as for the incremental value of new markers for treatment selection. Our proposals are examined through extensive simulation studies and illustrated with the data from a clinical trial that studies the effects of two drug combinations on HIV-1 infected patients.