The HIF-1alpha C1772T polymorphism may be associated with susceptibility to clinically localised prostate cancer but not with elevated expression of hypoxic biomarkers

We investigated the role of the C1772T polymorphisms in exon 12 of the Hypoxia-inducible factor-1 alpha (HIF-1alpha) gene C1772T genotype in prostate cancer (PCa) and amplification of the hypoxic response. We identified the heterozygous germline CT genotype as an increased risk factor for clinically localised prostate cancer (Odds ratio = 6.2; p < 0.0001). While immunostaining intensity for HIF-1alpha and VEGF was significantly enhanced in 75% of PCa specimens when compared to matched benign specimens (p < 0.0001), the CT genotype did not modulate the kinetics of HIF-1alpha protein expression in hypoxia in vitro, and was not associated with enhanced expression of hypoxic biomarkers. This study provides the first evidence of an increased risk for clinically localised prostate cancer in men carrying the C1772T HIF-1alpha gene polymorphism. Although our results did not suggest an association between expression of hypoxic biomarkers and genotype status, the correlation may merit further investigation.

Multicenter Blinded Analysis of RT-PCR Detection Methods for Paramyxoviruses in Relation to Paget's Disease of Bone

Conflicting results have been reported on the detection of paramyxovirus transcripts in Paget's disease, and a possible explanation is differences in the sensitivity of RT-PCR methods for detecting virus. In a blinded study, we found no evidence to suggest that laboratories that failed to detect viral transcripts had less sensitive RT-PCR assays, and we did not detect measles or distemper transcripts in Paget's samples using the most sensitive assays evaluated.

Introduction: There is conflicting evidence on the possible role of persistent paramyxovirus infection in Paget's disease of bone (PDB). Some workers have detected measles virus (MV) or canine distemper virus (CDV) transcripts in cells and tissues from patients with PDB, but others have failed to confirm this finding. A possible explanation might be differences in the sensitivity of RT-PCR methods for detecting virus. Here we performed a blinded comparison of the sensitivity of different RT-PCR-based techniques for MV and CDV detection in different laboratories and used the most sensitive assays to screen for evidence of viral transcripts in bone and blood samples derived from patients with PDB.

Materials and Methods: Participating laboratories analyzed samples spiked with known amounts of MV and CDV transcripts and control samples that did not contain viral nucleic acids. All analyses were performed on a blinded basis.

Results: The limit of detection for CDV was 1000 viral transcripts in three laboratories (Aberdeen, Belfast, and Liverpool) and 10,000 transcripts in another laboratory (Manchester). The limit of detection for MV was 16 transcripts in one laboratory (NIBSC), 1000 transcripts in two laboratories (Aberdeen and Belfast), and 10,000 transcripts in two laboratories (Liverpool and Manchester). An assay previously used by a U.S.-based group to detect MV transcripts in PDB had a sensitivity of 1000 transcripts. One laboratory (Manchester) detected CDV transcripts in a negative control and in two samples that had been spiked with MV. None of the other laboratories had false-positive results for MV or CDV, and no evidence of viral transcripts was found on analysis of 12 PDB samples using the most sensitive RT-PCR assays for MV and CDV.

Conclusions: We found that RT-PCR assays used by different laboratories differed in their sensitivity to detect CDV and MV transcripts but found no evidence to suggest that laboratories that previously failed to detect viral transcripts had less sensitive RT-PCR assays than those that detected viral transcripts. False-positive results were observed with one laboratory, and we failed to detect paramyxovirus transcripts in PDB samples using the most sensitive assays evaluated. Our results show that failure of some laboratories to detect viral transcripts is unlikely to be caused by problems with assay sensitivity and highlight the fact that contamination can be an issue when searching for pathogens by sensitive RT-PCR-based techniques.

Genome-wide meta-analysis identifies 11 new loci for anthropometric traits and provides insights into genetic architecture

Approaches exploiting trait distribution extremes may be used to identify loci associated with common traits, but it is unknown whether these loci are generalizable to the broader population. In a genome-wide search for loci associated with the upper versus the lower 5th percentiles of body mass index, height and waist-to-hip ratio, as well as clinical classes of obesity, including up to 263,407 individuals of European ancestry, we identified 4 new loci (IGFBP4, H6PD, RSRC1 and PPP2R2A) influencing height detected in the distribution tails and 7 new loci (HNF4G, RPTOR, GNAT2, MRPS33P4, ADCY9, HS6ST3 and ZZZ3) for clinical classes of obesity. Further, we find a large overlap in genetic structure and the distribution of variants between traits based on extremes and the general population and little etiological heterogeneity between obesity subgroups.

The PREDICTS database: a global database of how local terrestrial biodiversity responds to human impacts

Biodiversity continues to decline in the face of increasing anthropogenic pressures such as habitat destruction, exploitation, pollution and introduction of alien species. Existing global databases of species' threat status or population time series are dominated by charismatic species. The collation of datasets with broad taxonomic and biogeographic extents, and that support computation of a range of biodiversity indicators, is necessary to enable better understanding of historical declines and to project - and avert - future declines. We describe and assess a new database of more than 1.6 million samples from 78 countries representing over 28,000 species, collated from existing spatial comparisons of local-scale biodiversity exposed to different intensities and types of anthropogenic pressures, from terrestrial sites around the world. The database contains measurements taken in 208 (of 814) ecoregions, 13 (of 14) biomes, 25 (of 35) biodiversity hotspots and 16 (of 17) megadiverse countries. The database contains more than 1% of the total number of all species described, and more than 1% of the described species within many taxonomic groups - including flowering plants, gymnosperms, birds, mammals, reptiles, amphibians, beetles, lepidopterans and hymenopterans. The dataset, which is still being added to, is therefore already considerably larger and more representative than those used by previous quantitative models of biodiversity trends and responses. The database is being assembled as part of the PREDICTS project (Projecting Responses of Ecological Diversity In Changing Terrestrial Systems - http://www.predicts.org.uk). We make site-level summary data available alongside this article. The full database will be publicly available in 2015.