Generalizing Intensive Blood Pressure Treatment to Adults With Diabetes Mellitus

Background: Controversy over blood pressure (BP) treatment targets for individuals with diabetes is in part due to conflicting perspectives about generalizability of available trial data. Objective: The authors sought to estimate how results from the largest clinical trial of intensive BP treatment among adults with diabetes would generalize to the U.S. population. Methods: The authors used transportability methods to reweight individual patient data from the ACCORD (Action to Control Cardiovascular Risk in Diabetes) BP trial (N = 4,507) of intensive (goal systolic BP <120 mm Hg) versus standard (goal systolic BP <140 mm Hg) treatment to better represent the demographic and clinical risk factors of the U.S. population of adults with diabetes (data from NHANES [National Health and Nutrition Examination Survey] 2005 to 2014, n = 1,943). The primary outcome was the first occurrence of nonfatal myocardial infarction, nonfatal stroke, or cardiovascular death. Analysis used weighted Cox proportional hazards regression models with robust standard errors. Results: The ACCORD BP sample had less racial/ethnic diversity and more elevated cardiovascular risk factors than the NHANES participants. Weighted results significantly favored intensive BP treatment, unlike unweighted results (hazard ratio for primary outcome in intensive versus standard treatment in weighted analyses: 0.67, 95% confidence interval: 0.49 to 0.91; in unweighted analyses: hazard ratio: 0.88, 95% confidence interval: 0.73 to 1.07). Over 5 years, the weighted results estimate a number needed to treat of 34, and number needed to harm of 55. Conclusions: After reweighting to better reflect the U.S. adult population with diabetes, intensive BP therapy was associated with significantly lower risk for cardiovascular events. However, data were limited among racial/ethnic minorities and those with lower cardiovascular risk

Supplemental Nutrition Assistance Program (SNAP) participation and health care expenditures among low-income adults

IMPORTANCE: Food insecurity is associated with high health care expenditures, but the effectiveness of food insecurity interventions on health care costs is unknown. OBJECTIVE: To determine whether the Supplemental Nutrition Assistance Program (SNAP), which addresses food insecurity, can reduce health care expenditures. DESIGN, SETTING, AND PARTICIPANTS: This is a retrospective cohort study of 4447 noninstitutionalized adults with income below 200% of the federal poverty threshold who participated in the 2011 National Health Interview Survey (NHIS) and the 2012-2013 Medical Expenditure Panel Survey (MEPS). EXPOSURES: Self-reported SNAP participation in 2011. MAIN OUTCOMES AND MEASURES: Total health care expenditures (all paid claims and out-of-pocket costs) in the 2012-2013 period. To test whether SNAP participation was associated with lower subsequent health care expenditures, we used generalized linear modeling (gamma distribution, log link, with survey design information), adjusting for demographics (age, gender, race/ethnicity), socioeconomic factors (income, education, Social Security Disability Insurance disability, urban/rural), census region, health insurance, and self-reported medical conditions. We also conducted sensitivity analyses as a robustness check for these modeling assumptions. RESULTS: A total of 4447 participants (2567 women and 1880 men) were enrolled in the study, mean (SE) age, 42.7 (0.5) years; 1889 were SNAP participants, and 2558 were not. Compared with other low-income adults, SNAP participants were younger (mean [SE] age, 40.3 [0.6] vs 44.1 [0.7] years), more likely to have public insurance or be uninsured (84.9% vs 67.7%), and more likely to be disabled (24.2% vs 10.6%) (P < .001 for all). In age- and gender-adjusted models, health care expenditures between those who did and did not participate in SNAP were similar (difference, $34; 95$1097 to $1165). In fully adjusted models, SNAP was associated with lower estimated annual health care expenditures (−$1409; 95% CI, −$2694 to −$125). Sensitivity analyses were consistent with these results, also indicating that SNAP participation was associated with significantly lower estimated expenditures. CONCLUSIONS AND RELEVANCE: SNAP enrollment is associated with reduced health care spending among low-income American adults, a finding consistent across several analytic approaches. Encouraging SNAP enrollment among eligible adults may help reduce health care costs in the United States

Dipolar interactions and anisotropic magnetoresistance in metallic granular systems

We revisit the theory of magnetoresistance for a system of nanoscopic magnetic granules in metallic matrix. Using a simple model for the spin dependent perturbation potential of the granules, we solve Boltzmann equation for the spin dependent components of the non equilibrium electronic distribution function. For typical values of the geometric parameters in granular systems, we find a peculiar structure of the distribution function of conduction electrons, which is at variance with the two-current model of conduction in inhomogeneous systems. Our treatment explicitly includes the effects of dipolar correlations yielding a magnetoresistance ratio which contains, in addition to the term proportional to the square of uniform magnetization (), a weak anisotropic contribution depending on the angle between electric and magnetic fields, and arising from the anisotropic character of dipolar interactions.Comment: 9 pages, 2 figures, accepted in PR

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

Review Section : Nature/Nurture Revisited I

Biologically oriented approaches to the study of human conflict have thus far been limited largely to the study of aggression. A sample of the literature on this topic is reviewed, drawing upon four major approaches: comparative psychology, ethology (including some popularized accounts), evolutionary-based theories, and several areas of human physiology. More sophisticated relationships between so-called "innate" and "acquired" determinants of behavior are discussed, along with the proper relevance of animal behavior studies for human behavior. Unless contained in a comprehensive theory which includes social and psychological variables, biolog ically oriented theories (although often valid within their domain) offer at best severely limited and at worst highly misleading explanations of complex social conflicts. The review concludes with a list of several positive contributions of these biological approaches and suggests that social scientists must become more knowledgeable about them.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/68270/2/10.1177_002200277401800206.pd

Driver Fusions and Their Implications in the Development and Treatment of Human Cancers.

Gene fusions represent an important class of somatic alterations in cancer. We systematically investigated fusions in 9,624 tumors across 33 cancer types using multiple fusion calling tools. We identified a total of 25,664 fusions, with a 63% validation rate. Integration of gene expression, copy number, and fusion annotation data revealed that fusions involving oncogenes tend to exhibit increased expression, whereas fusions involving tumor suppressors have the opposite effect. For fusions involving kinases, we found 1,275 with an intact kinase domain, the proportion of which varied significantly across cancer types. Our study suggests that fusions drive the development of 16.5% of cancer cases and function as the sole driver in more than 1% of them. Finally, we identified druggable fusions involving genes such as TMPRSS2, RET, FGFR3, ALK, and ESR1 in 6.0% of cases, and we predicted immunogenic peptides, suggesting that fusions may provide leads for targeted drug and immune therapy

Somatic Mutational Landscape of Splicing Factor Genes and Their Functional Consequences across 33 Cancer Types

Hotspot mutations in splicing factor genes have been recently reported at high frequency in hematological malignancies, suggesting the importance of RNA splicing in cancer. We analyzed whole-exome sequencing data across 33 tumor types in The Cancer Genome Atlas (TCGA), and we identified 119 splicing factor genes with significant non-silent mutation patterns, including mutation over-representation, recurrent loss of function (tumor suppressor-like), or hotspot mutation profile (oncogene-like). Furthermore, RNA sequencing analysis revealed altered splicing events associated with selected splicing factor mutations. In addition, we were able to identify common gene pathway profiles associated with the presence of these mutations. Our analysis suggests that somatic alteration of genes involved in the RNA-splicing process is common in cancer and may represent an underappreciated hallmark of tumorigenesis

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although the MYC oncogene has been implicated in cancer, a systematic assessment of alterations of MYC, related transcription factors, and co-regulatory proteins, forming the proximal MYC network (PMN), across human cancers is lacking. Using computational approaches, we define genomic and proteomic features associated with MYC and the PMN across the 33 cancers of The Cancer Genome Atlas. Pan-cancer, 28% of all samples had at least one of the MYC paralogs amplified. In contrast, the MYC antagonists MGA and MNT were the most frequently mutated or deleted members, proposing a role as tumor suppressors. MYC alterations were mutually exclusive with PIK3CA, PTEN, APC, or BRAF alterations, suggesting that MYC is a distinct oncogenic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such as immune response and growth factor signaling; chromatin, translation, and DNA replication/repair were conserved pan-cancer. This analysis reveals insights into MYC biology and is a reference for biomarkers and therapeutics for cancers with alterations of MYC or the PMN. We present a computational study determining the frequency and extent of alterations of the MYC network across the 33 human cancers of TCGA. These data, together with MYC, positively correlated pathways as well as mutually exclusive cancer genes, will be a resource for understanding MYC-driven cancers and designing of therapeutics

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dysregulated in tumors, but only a handful are known to play pathophysiological roles in cancer. We inferred lncRNAs that dysregulate cancer pathways, oncogenes, and tumor suppressors (cancer genes) by modeling their effects on the activity of transcription factors, RNA-binding proteins, and microRNAs in 5,185 TCGA tumors and 1,019 ENCODE assays. Our predictions included hundreds of candidate onco- and tumor-suppressor lncRNAs (cancer lncRNAs) whose somatic alterations account for the dysregulation of dozens of cancer genes and pathways in each of 14 tumor contexts. To demonstrate proof of concept, we showed that perturbations targeting OIP5-AS1 (an inferred tumor suppressor) and TUG1 and WT1-AS (inferred onco-lncRNAs) dysregulated cancer genes and altered proliferation of breast and gynecologic cancer cells. Our analysis indicates that, although most lncRNAs are dysregulated in a tumor-specific manner, some, including OIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergistically dysregulate cancer pathways in multiple tumor contexts. Chiu et al. present a pan-cancer analysis of lncRNA regulatory interactions. They suggest that the dysregulation of hundreds of lncRNAs target and alter the expression of cancer genes and pathways in each tumor context. This implies that hundreds of lncRNAs can alter tumor phenotypes in each tumor context

The Cancer Genome Atlas Comprehensive Molecular Characterization of Renal Cell Carcinoma

Renal cell carcinoma(RCC) is not a single disease, but several histologically defined cancers with different genetic drivers, clinical courses, and therapeutic responses. The current study evaluated 843 RCC from the three major histologic subtypes, including 488 clear cell RCC, 274 papillary RCC, and 81 chromophobe RCC. Comprehensive genomic and phenotypic analysis of the RCC subtypes reveals distinctive features of each subtype that provide the foundation for the development of subtype-specific therapeutic and management strategies for patients affected with these cancers. Somatic alteration of BAP1, PBRM1, and PTEN and altered metabolic pathways correlated with subtype-specific decreased survival, while CDKN2A alteration, increased DNA hypermethylation, and increases in the immune-related Th2 gene expression signature correlated with decreased survival within all major histologic subtypes. CIMP-RCC demonstrated an increased immune signature, and a uniform and distinct metabolic expression pattern identified a subset of metabolically divergent (MD) ChRCC that associated with extremely poor survival