Validity of participant recorded pedometer step logs in free-living adults.

Purposes. The purposes of this study were to (1) examine the validity of participant recorded pedometer step logs, (2) examine the relationship between steps per day and percent bodyfat (% BF), and (3) examine differences in steps per day by BMI category (< 25 m/kg2 vs. ≥ 25 kg/m2). Methods . Participants (N = 89; Male: n = 29, age = 37.97 +/- 9.41 years, BMI = 25.87 +/- 4.42 kg/m2, % BF = 21.66 +/- 6.21%; Female: n = 60, age = 40.07 +/- 10.72, BMI = 24.83 +/- 4.72 kg/m 2, % BF = 33.73 +/- 8.11%) in this cross-sectional, descriptive study simultaneously wore a sealed pedometer, unsealed pedometer, and Actigraph accelerometer for nine consecutive days. Body composition was assessed via air-displacement plethysmography (BOD POD). Descriptive statistics, tests of equivalence, correlation coefficients, and independent t-tests were calculated. Three conditions were examined for validity: raw Actigraph steps per day (RAW) vs. participant recorded steps per day (PSD), Actigraph steps corrected for vehicular travel (CORRECTED) vs. PSD, and total accumulated steps from the sealed pedometer (SEALED) vs. total accumulated steps from the participant recorded pedometer (PTOT). Results. There was a strong correlation between RAW and PSD (r = 0.88, p < 0.0001). However, RAW and PSD were not equivalent. Similarly, CORRECTED and PSD resulted in a strong correlation (r = 0.88, p < 0.0001), but they were not equivalent. Comparing SEALED and PTOT indicated a strong correlation (r = 0.96, p < 0.0001) and equivalence. All correlations for steps per day and % BF were moderate (range: r = 0.40 to 0.45). There was a significant difference in steps per day by BMI category in PSD (p = 0.03), but not in RAW and CORRECTED. Conclusions. These results indicate (1) acceptable validity for participant recorded pedometer step logs, (2) moderate relationships between steps per day and % BF, and (3) a significant difference in steps per day by BMI category in PST, but not in RAW and CORRECTED. Future research should attempt to further explain the relationship between Actigraph and pedometer-derived steps

Visualization of the Genesis and Fate of Isotype-switched B Cells during a Primary Immune Response

The life history of isotype-switched B cells is unclear, in part, because of an inability to detect rare antigen-specific B cells at early times during the immune response. To address this issue, a small population of B cells carrying targeted antibody transgenes capable of class switching was monitored in immunized mice. After contacting helper T cells, the first switched B cells appeared in follicles rather than in the red pulp, as was expected. Later, some of the switched B cells transiently occupied the red pulp and marginal zone, whereas others persisted in germinal centers (GCs). Antigen-experienced IgM B cells were rarely found in GCs, indicating that these cells switched rapidly after entering GCs or did not persist in this environment

Risk Alleles for Systemic Lupus Erythematosus in a Large Case-Control Collection and Associations with Clinical Subphenotypes

Systemic lupus erythematosus (SLE) is a genetically complex disease with heterogeneous clinical manifestations. Recent studies have greatly expanded the number of established SLE risk alleles, but the distribution of multiple risk alleles in cases versus controls and their relationship to subphenotypes have not been studied. We studied 22 SLE susceptibility polymorphisms with previous genome-wide evidence of association (p<5×10−8) in 1919 SLE cases from 9 independent Caucasian SLE case series and 4813 independent controls. The mean number of risk alleles in cases was 15.1 (SD 3.1) while the mean in controls was 13.1 (SD 2.8), with trend p = 4×10−128. We defined a genetic risk score (GRS) for SLE as the number of risk alleles with each weighted by the SLE risk odds ratio (OR). The OR for high-low GRS tertiles, adjusted for intra-European ancestry, sex, and parent study, was 4.4 (95% CI 3.8–5.1). We studied associations of individual SNPs and the GRS with clinical manifestations for the cases: age at diagnosis, the 11 American College of Rheumatology classification criteria, and double-stranded DNA antibody (anti-dsDNA) production. Six subphenotypes were significantly associated with the GRS, most notably anti-dsDNA (ORhigh-low = 2.36, p = 9e−9), the immunologic criterion (ORhigh-low = 2.23, p = 3e−7), and age at diagnosis (ORhigh-low = 1.45, p = 0.0060). Finally, we developed a subphenotype-specific GRS (sub-GRS) for each phenotype with more power to detect cumulative genetic associations. The sub-GRS was more strongly associated than any single SNP effect for 5 subphenotypes (the above plus hematologic disorder and oral ulcers), while single loci are more significantly associated with renal disease (HLA-DRB1, OR = 1.37, 95% CI 1.14–1.64) and arthritis (ITGAM, OR = 0.72, 95% CI 0.59–0.88). We did not observe significant associations for other subphenotypes, for individual loci or the sub-GRS. Thus our analysis categorizes SLE subphenotypes into three groups: those having cumulative, single, and no known genetic association with respect to the currently established SLE risk loci

Elevated Serum Levels of Interferon-Regulated Chemokines Are Biomarkers for Active Human Systemic Lupus Erythematosus

BACKGROUND: Systemic lupus erythematosus (SLE) is a serious systemic autoimmune disorder that affects multiple organ systems and is characterized by unpredictable flares of disease. Recent evidence indicates a role for type I interferon (IFN) in SLE pathogenesis; however, the downstream effects of IFN pathway activation are not well understood. Here we test the hypothesis that type I IFN-regulated proteins are present in the serum of SLE patients and correlate with disease activity. METHODS AND FINDINGS: We performed a comprehensive survey of the serologic proteome in human SLE and identified dysregulated levels of 30 cytokines, chemokines, growth factors, and soluble receptors. Particularly striking was the highly coordinated up-regulation of 12 inflammatory and/or homeostatic chemokines, molecules that direct the movement of leukocytes in the body. Most of the identified chemokines were inducible by type I IFN, and their levels correlated strongly with clinical and laboratory measures of disease activity. CONCLUSIONS: These data suggest that severely disrupted chemokine gradients may contribute to the systemic autoimmunity observed in human SLE. Furthermore, the levels of serum chemokines may serve as convenient biomarkers for disease activity in lupus

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

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment