Significant Role of Collagen XVII And Integrin beta 4 in Migration and Invasion of The Less Aggressive Squamous Cell Carcinoma Cells

Collagen XVII and integrin alpha 6 beta 4 have well-established roles as epithelial adhesion molecules. Their binding partner laminin 332 as well as integrin alpha 6 beta 4 are largely recognized to promote invasion and metastasis in various cancers, and collagen XVII is essential for the survival of colon and lung cancer stem cells. We have studied the expression of laminin.2, collagen XVII and integrin beta 4 in tissue microarray samples of squamous cell carcinoma (SCC) and its precursors, actinic keratosis and Bowen's disease. The expression of laminin.2 was highest in SCC samples, whereas the expression of collagen XVII and integrin beta 4 varied greatly in SCC and its precursors. Collagen XVII and integrin beta 4 were also expressed in SCC cell lines. Virus-mediated RNAi knockdown of collagen XVII and integrin beta 4 reduced the migration of less aggressive SCC-25 cells in horizontal scratch wound healing assay. Additionally, in a 3D organotypic myoma invasion assay the loss of collagen XVII or integrin beta 4 suppressed equally the migration and invasion of SCC-25 cells whereas there was no effect on the most aggressive HSC-3 cells. Variable expression patterns and results in migration and invasion assays suggest that collagen XVII and integrin beta 4 contribute to SCC tumorigenesis.Peer reviewe

Evaluation of O2PLS in Omics data integration

Background: Rapid computational and technological developments made large amounts of omics data available in different biological levels. It is becoming clear that simultaneous data analysis methods are needed for better interpretation and understanding of the underlying systems biology. Different methods have been proposed for this task, among them Partial Least Squares (PLS) related methods. To also deal with orthogonal variation, systematic variation in the data unrelated to one another, we consider the Two-way Orthogonal PLS (O2PLS): an integrative data analysis method which is capable of modeling systematic variation, while providing more parsimonious models aiding interpretation. Results: A simulation study to assess the performance of O2PLS showed positive results in both low and higher dimensions. More noise (50 % of the data) only affected the systematic part estimates. A data analysis was conducted using data on metabolomics and transcriptomics from a large Finnish cohort (DILGOM). A previous sequential study, using the same data, showed significant correlations between the Lipo-Leukocyte (LL) module and lipoprotein metabolites. The O2PLS results were in agreement with these findings, identifying almost the same set of co-varying variables. Moreover, our integrative approach identified other associative genes and metabolites, while taking into account systematic variation in the data. Including orthogonal components enhanced overall fit, but the orthogonal variation was difficult to interpret. Conclusions: Simulations showed that the O2PLS estimates were close to the true parameters in both low and higher dimensions. In the presence of more noise (50 %), the orthogonal part estimates could not distinguish well between joint and unique variation. The joint estimates were not systematically affected. Simultaneous analysis with O2PLS on metabolome and transcriptome data showed that the LL module, together with VLDL and HDL metabolites, were important for the metabolomic and transcriptomic relation. This is in agreement with an earlier study. In addition more gene expression and metabolites are identified being important for the joint covariation

Long working hours, socioeconomic status, and the risk of incident type 2 diabetes : a meta-analysis of published and unpublished data from 222 120 individuals

Background Working long hours might have adverse health effects, but whether this is true for all socioeconomic status groups is unclear. In this meta-analysis stratified by socioeconomic status, we investigated the role of long working hours as a risk factor for type 2 diabetes. Methods We identified four published studies through a systematic literature search of PubMed and Embase up to April 30, 2014. Study inclusion criteria were English-language publication; prospective design (cohort study); investigation of the effect of working hours or overtime work; incident diabetes as an outcome; and relative risks, odds ratios, or hazard ratios (HRs) with 95% CIs, or sufficient information to calculate these estimates. Additionally, we used unpublished individual-level data from 19 cohort studies from the Individual-Participant-Data Meta-analysis in Working-Populations Consortium and international open-access data archives. Effect estimates from published and unpublished data from 222 120 men and women from the USA, Europe, Japan, and Australia were pooled with random-effects meta-analysis. Findings During 1.7 million person-years at risk, 4963 individuals developed diabetes (incidence 29 per 10 000 person-years). The minimally adjusted summary risk ratio for long (>= 55 h per week) compared with standard working hours (35-40 h) was 1.07 (95% CI 0.89-1.27, difference in incidence three cases per 10 000 person-years) with significant heterogeneity in study-specific estimates (I-2 = 53%, p = 0.0016). In an analysis stratified by socioeconomic status, the association between long working hours and diabetes was evident in the low socioeconomic status group (risk ratio 1.29, 95% CI 1.06-1.57, difference in incidence 13 per 10 000 person-years, I-2 = 0%, p = 0.4662), but was null in the high socioeconomic status group (1. 00, 95% CI 0.80-1.25, incidence diff erence zero per 10 000 person-years, I-2 = 15%, p = 0.2464). The association in the low socioeconomic status group was robust to adjustment for age, sex, obesity, and physical activity, and remained after exclusion of shift workers. Interpretation In this meta-analysis, the link between longer working hours and type 2 diabetes was apparent only in individuals in the low socioeconomic status groups. Copyright (C) Kivimaki et al. Open Access article distributed under the terms of CC BY.Peer reviewe

systematic review and meta-analysis of published studies and unpublished individual participant data

Objective To quantify the association between long working hours and alcohol use. Design Systematic review and meta-analysis of published studies and unpublished individual participant data. Data sources A systematic search of PubMed and Embase databases in April 2014 for published studies, supplemented with manual searches. Unpublished individual participant data were obtained from 27 additional studies. Review methods The search strategy was designed to retrieve cross sectional and prospective studies of the association between long working hours and alcohol use. Summary estimates were obtained with random effects meta-analysis. Sources of heterogeneity were examined with meta-regression. Results Cross sectional analysis was based on 61 studies representing 333 693 participants from 14 countries. Prospective analysis was based on 20 studies representing 100 602 participants from nine countries. The pooled maximum adjusted odds ratio for the association between long working hours and alcohol use was 1.11 (95% confidence interval 1.05 to 1.18) in the cross sectional analysis of published and unpublished data. Odds ratio of new onset risky alcohol use was 1.12 (1.04 to 1.20) in the analysis of prospective published and unpublished data. In the 18 studies with individual participant data it was possible to assess the European Union Working Time Directive, which recommends an upper limit of 48 hours a week. Odds ratios of new onset risky alcohol use for those working 49-54 hours and ≥55 hours a week were 1.13 (1.02 to 1.26; adjusted difference in incidence 0.8 percentage points) and 1.12 (1.01 to 1.25; adjusted difference in incidence 0.7 percentage points), respectively, compared with working standard 35-40 hours (incidence of new onset risky alcohol use 6.2%). There was no difference in these associations between men and women or by age or socioeconomic groups, geographical regions, sample type (population based v occupational cohort), prevalence of risky alcohol use in the cohort, or sample attrition rate. Conclusions Individuals whose working hours exceed standard recommendations are more likely to increase their alcohol use to levels that pose a health risk

Long working hours and risk of coronary heart disease and stroke : a systematic review and meta-analysis of published and unpublished data for 603 838 individuals

Background Long working hours might increase the risk of cardiovascular disease, but prospective evidence is scarce, imprecise, and mostly limited to coronary heart disease. We aimed to assess long working hours as a risk factor for incident coronary heart disease and stroke. Methods We identified published studies through a systematic review of PubMed and Embase from inception to Aug 20, 2014. We obtained unpublished data for 20 cohort studies from the Individual-Participant-Data Meta-analysis in Working Populations (IPD-Work) Consortium and open-access data archives. We used cumulative random-effects meta-analysis to combine effect estimates from published and unpublished data. Findings We included 25 studies from 24 cohorts in Europe, the USA, and Australia. The meta-analysis of coronary heart disease comprised data for 603 838 men and women who were free from coronary heart disease at baseline; the meta-analysis of stroke comprised data for 528 908 men and women who were free from stroke at baseline. Follow-up for coronary heart disease was 5.1 million person-years (mean 8.5 years), in which 4768 events were recorded, and for stroke was 3.8 million person-years (mean 7.2 years), in which 1722 events were recorded. In cumulative meta-analysis adjusted for age, sex, and socioeconomic status, compared with standard hours (35-40 h per week), working long hours (>= 55 h per week) was associated with an increase in risk of incident coronary heart disease (relative risk [RR] 1.13, 95% CI 1.02-1.26; p=0.02) and incident stroke (1.33, 1.11-1.61; p=0.002). The excess risk of stroke remained unchanged in analyses that addressed reverse causation, multivariable adjustments for other risk factors, and different methods of stroke ascertainment (range of RR estimates 1.30-1.42). We recorded a dose-response association for stroke, with RR estimates of 1.10 (95% CI 0.94-1.28; p=0.24) for 41-48 working hours, 1.27 (1.03-1.56; p=0.03) for 49-54 working hours, and 1.33 (1.11-1.61; p=0.002) for 55 working hours or more per week compared with standard working hours (p(trend) Interpretation Employees who work long hours have a higher risk of stroke than those working standard hours; the association with coronary heart disease is weaker. These findings suggest that more attention should be paid to the management of vascular risk factors in individuals who work long hours. Copyright (C) Kivimaki et al. Open Access article distributed under the terms of CC BY.Peer reviewe

Glycosylation of immunoglobulin G is regulated by a large network of genes pleiotropic with inflammatory diseases

Effector functions of immunoglobulin G (IgG) are regulated by the composition of a glycan moiety, thus affecting activity of the immune system. Aberrant glycosylation of IgG has been observed in many diseases, but little is understood about the underlying mechanisms. We performed a genome-wide association study of IgG N-glycosylation (N = 8090) and, using a data-driven network approach, suggested how associated loci form a functional network. We confirmed in vitro that knockdown of IKZF1 decreases the expression of fucosyltransferase FUT8, resulting in increased levels of fucosylated glycans, and suggest that RUNX1 and RUNX3, together with SMARCB1, regulate expression of glycosyltransferase MGAT3. We also show that variants affecting the expression of genes involved in the regulation of glycoenzymes colocalize with variants affecting risk for inflammatory diseases. This study provides new evidence that variation in key transcription factors coupled with regulatory variation in glycogenes modifies IgG glycosylation and has influence on inflammatory diseases

A systematic analysis of oncogenic gene fusions in primary colon cancer

Genomic rearrangements that give rise to oncogenic gene fusions can offer actionable targets for cancer therapy. Here we present a systematic analysis of oncogenic gene fusions among a clinically well-characterized, prospectively collected set of 278 primary colon cancers spanning diverse tumor stages and clinical outcomes. Gene fusions and somatic genetic variations were identified in fresh frozen clinical specimens by Illumina RNA-sequencing, the STAR fusion gene detection pipeline, and GATK RNA-seq variant calling. We considered gene fusions to be pathogenically relevant when recurrent, producing divergent gene expression (outlier analysis), or as functionally important (e.g., kinase fusions). Overall, 2.5% of all specimens were defined as harboring a relevant gene fusion (kinase fusions 1.8%). Novel configurations of BRAF, NTRK3, and RET gene fusions resulting from chromosomal translocations were identified. An R-spondin fusion was found in only one tumor (0.35%), much less than an earlier reported frequency of 10% in colorectal cancers. We also found a novel fusion involving USP9X-ERAS formed by chromothripsis and leading to high expression of ERAS, a constitutively active RAS protein normally expressed only in embryonic stem cells. This USP9X–ERAS fusion appeared highly oncogenic on the basis of its ability to activate AKT signaling. Oncogenic fusions were identified only in lymph node–negative tumors that lacked BRAF or KRAS mutations. In summary, we identified several novel oncogenic gene fusions in colorectal cancer that may drive malignant development and offer new targets for personalized therapy

Meta-Analysis of 28,141 Individuals Identifies Common Variants within Five New Loci That Influence Uric Acid Concentrations

Elevated serum uric acid levels cause gout and are a risk factor for cardiovascular disease and diabetes. To investigate the polygenetic basis of serum uric acid levels, we conducted a meta-analysis of genome-wide association scans from 14 studies totalling 28,141 participants of European descent, resulting in identification of 954 SNPs distributed across nine loci that exceeded the threshold of genome-wide significance, five of which are novel. Overall, the common variants associated with serum uric acid levels fall in the following nine regions: SLC2A9 (p = 5.2×10−201), ABCG2 (p = 3.1×10−26), SLC17A1 (p = 3.0×10−14), SLC22A11 (p = 6.7×10−14), SLC22A12 (p = 2.0×10−9), SLC16A9 (p = 1.1×10−8), GCKR (p = 1.4×10−9), LRRC16A (p = 8.5×10−9), and near PDZK1 (p = 2.7×10−9). Identified variants were analyzed for gender differences. We found that the minor allele for rs734553 in SLC2A9 has greater influence in lowering uric acid levels in women and the minor allele of rs2231142 in ABCG2 elevates uric acid levels more strongly in men compared to women. To further characterize the identified variants, we analyzed their association with a panel of metabolites. rs12356193 within SLC16A9 was associated with DL-carnitine (p = 4.0×10−26) and propionyl-L-carnitine (p = 5.0×10−8) concentrations, which in turn were associated with serum UA levels (p = 1.4×10−57 and p = 8.1×10−54, respectively), forming a triangle between SNP, metabolites, and UA levels. Taken together, these associations highlight additional pathways that are important in the regulation of serum uric acid levels and point toward novel potential targets for pharmacological intervention to prevent or treat hyperuricemia. In addition, these findings strongly support the hypothesis that transport proteins are key in regulating serum uric acid levels

Genome-wide association and Mendelian randomisation analysis provide insights into the pathogenesis of heart failure

Heart failure (HF) is a leading cause of morbidity and mortality worldwide. A small proportion of HF cases are attributable to monogenic cardiomyopathies and existing genome-wide association studies (GWAS) have yielded only limited insights, leaving the observed heritability of HF largely unexplained. We report results from a GWAS meta-analysis of HF comprising 47,309 cases and 930,014 controls. Twelve independent variants at 11 genomic loci are associated with HF, all of which demonstrate one or more associations with coronary artery disease (CAD), atrial fibrillation, or reduced left ventricular function, suggesting shared genetic aetiology. Functional analysis of non-CAD-associated loci implicate genes involved in cardiac development (MYOZ1, SYNPO2L), protein homoeostasis (BAG3), and cellular senescence (CDKN1A). Mendelian randomisation analysis supports causal roles for several HF risk factors, and demonstrates CAD-independent effects for atrial fibrillation, body mass index, and hypertension. These findings extend our knowledge of the pathways underlying HF and may inform new therapeutic strategies

New genetic loci link adipose and insulin biology to body fat distribution.

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms