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.

Genetic studies of body mass index yield new insights for obesity biology

Obesity is heritable and predisposes to many diseases. To understand the genetic basis of obesity better, here we conduct a genome-wide association study and Metabochip meta-analysis of body mass index (BMI), a measure commonly used to define obesity and assess adiposity, in up to 339,224 individuals. This analysis identifies 97 BMI-associated loci (P < 5 × 10(-8)), 56 of which are novel. Five loci demonstrate clear evidence of several independent association signals, and many loci have significant effects on other metabolic phenotypes. The 97 loci account for ∼2.7% of BMI variation, and genome-wide estimates suggest that common variation accounts for >20% of BMI variation. Pathway analyses provide strong support for a role of the central nervous system in obesity susceptibility and implicate new genes and pathways, including those related to synaptic function, glutamate signalling, insulin secretion/action, energy metabolism, lipid biology and adipogenesis.

DEAD-box helicase DP103 defines metastatic potential of human breast cancers

Despite advancement in breast cancer treatment, 30% of patients with early breast cancers experience relapse with distant metastasis. It is a challenge to identify patients at risk for relapse; therefore, the identification of markers and therapeutic targets for metastatic breast cancers is imperative. Here, we identified DP103 as a biomarker and metastasis-driving oncogene in human breast cancers and determined that DP103 elevates matrix metallopeptidase 9 (MMP9) levels, which are associated with metastasis and invasion through activation of NF-κB. In turn, NF-κB signaling positively activated DP103 expression. Furthermore, DP103 enhanced TGF-β-activated kinase-1 (TAK1) phosphorylation of NF-κB-activating IκB kinase 2 (IKK2), leading to increased NF-κB activity. Reduction of DP103 expression in invasive breast cancer cells reduced phosphorylation of IKK2, abrogated NF-κB-mediated MMP9 expression, and impeded metastasis in a murine xenograft model. In breast cancer patient tissues, elevated levels of DP103 correlated with enhanced MMP9, reduced overall survival, and reduced survival after relapse. Together, these data indicate that a positive DP103/NF-κB feedback loop promotes constitutive NF-κB activation in invasive breast cancers and activation of this pathway is linked to cancer progression and the acquisition of chemotherapy resistance. Furthermore, our results suggest that DP103 has potential as a therapeutic target for breast cancer treatment.

CD44v8-10 Is a Cancer-Specific Marker for Gastric Cancer Stem Cells

The surface marker CD44 has been identified as one of several markers associated with cancer stem cells (CSC) in solid tumors, but its ubiquitous expression in many cell types, including hematopoietic cells, has hindered its use in targeting CSCs. In this study, 28 paired primary tumor and adjacent nontumor gastric tissue samples were analyzed for cell surface protein expression. Cells that expressed pan-CD44 were found to occur at significantly higher frequency in gastric tumor tissues. We identified CD44v8-10 as the predominant CD44 variant expressed in gastric cancer cells and verified its role as a gastric CSC marker by limiting dilution and serial transplantation assays. Parallel experiments using CD133 failed to enrich for gastric CSCs. Analyses of another 26 primary samples showed significant CD44v8-10 upregulation in gastric tumor sites. Exogenous expression of CD44v8-10 but not CD44 standard (CD44s) increased the frequency of tumor initiation in immunocompromised mice. Reciprocal silencing of total CD44 resulted in reduced tumor-initiating potential of gastric cancer cells that could be rescued by CD44v8-10 but not CD44s expression. Our findings provide important functional evidence that CD44v8-10 marks human gastric CSCs and contributes to tumor initiation, possibly through enhancing oxidative stress defense. In addition, we showed that CD44v8-10 expression is low in normal tissues. Because CD44 also marks CSCs of numerous human cancers, many of which may also overexpress CD44v8-10, CD44v8-10 may provide an avenue to target CSCs in other human cancers.

Hui and Walter's latent-class model extended to estimate diagnostic test properties from surveillance data: a latent model for latent data

Diagnostic test sensitivity and specificity are probabilistic estimates with far reaching implications for disease control, management and genetic studies. In the absence of 'gold standard' tests, traditional Bayesian latent class models may be used to assess diagnostic test accuracies through the comparison of two or more tests performed on the same groups of individuals. The aim of this study was to extend such models to estimate diagnostic test parameters and true cohort-specific prevalence, using disease surveillance data. The traditional Hui-Walter latent class methodology was extended to allow for features seen in such data, including (i) unrecorded data (i.e. data for a second test available only on a subset of the sampled population) and (ii) cohort-specific sensitivities and specificities. The model was applied with and without the modelling of conditional dependence between tests. The utility of the extended model was demonstrated through application to bovine tuberculosis surveillance data from Northern and the Republic of Ireland. Simulation coupled with re-sampling techniques, demonstrated that the extended model has good predictive power to estimate the diagnostic parameters and true herd-level prevalence from surveillance data. Our methodology can aid in the interpretation of disease surveillance data, and the results can potentially refine disease control strategies.

A Concert of Works by Ross Lee Finney, 1966

Concert Program for A Concert of Works by Ross Lee Finney, 1966

Novel loci for adiponectin levels and their influence on type 2 diabetes and metabolic traits: a multi-ethnic meta-analysis of 45,891 individuals.

Circulating levels of adiponectin, a hormone produced predominantly by adipocytes, are highly heritable and are inversely associated with type 2 diabetes mellitus (T2D) and other metabolic traits. We conducted a meta-analysis of genome-wide association studies in 39,883 individuals of European ancestry to identify genes associated with metabolic disease. We identified 8 novel loci associated with adiponectin levels and confirmed 2 previously reported loci (P = 4.5×10(-8)-1.2×10(-43)). Using a novel method to combine data across ethnicities (N = 4,232 African Americans, N = 1,776 Asians, and N = 29,347 Europeans), we identified two additional novel loci. Expression analyses of 436 human adipocyte samples revealed that mRNA levels of 18 genes at candidate regions were associated with adiponectin concentrations after accounting for multiple testing (p<3×10(-4)). We next developed a multi-SNP genotypic risk score to test the association of adiponectin decreasing risk alleles on metabolic traits and diseases using consortia-level meta-analytic data. This risk score was associated with increased risk of T2D (p = 4.3×10(-3), n = 22,044), increased triglycerides (p = 2.6×10(-14), n = 93,440), increased waist-to-hip ratio (p = 1.8×10(-5), n = 77,167), increased glucose two hours post oral glucose tolerance testing (p = 4.4×10(-3), n = 15,234), increased fasting insulin (p = 0.015, n = 48,238), but with lower in HDL-cholesterol concentrations (p = 4.5×10(-13), n = 96,748) and decreased BMI (p = 1.4×10(-4), n = 121,335). These findings identify novel genetic determinants of adiponectin levels, which, taken together, influence risk of T2D and markers of insulin resistance.

Russie d'aujourd'hui : organe de l'Association française des Amis de l'Union soviétique

1940/11 (N1).