These data suggest that BMI based on self-reported weight and height is not accurate for BMI prediction at an individual level. However, self-reported BMI may be used as a simple and valid tool for BMI estimates of overweight and obesity in epidemiological studies.

Aberrant expression of cancer genes and non-canonical RNA species is a hallmark of cancer. However, the mechanisms driving such atypical gene expression programs are incompletely understood. Here, our transcriptional profiling of a cohort of 50 primary clear cell renal cell carcinoma (ccRCC) samples from The Cancer Genome Atlas (TCGA) reveals that transcription read-through beyond the termination site is a source of transcriptome diversity in cancer cells. Amongst the genes most frequently mutated in ccRCC, we identified SETD2 inactivation as a potent enhancer of transcription read-through. We further show that invasion of neighbouring genes and generation of RNA chimeras are functional outcomes of transcription read-through. We identified the BCL2 oncogene as one of such invaded genes and detected a novel chimera, the CTSC-RAB38, in 20% of ccRCC samples. Collectively, our data highlight a novel link between transcription read-through and aberrant expression of oncogenes and chimeric transcripts that is prevalent in cancer.DOI: http://dx.doi.org/10.7554/eLife.09214.001

IntroductionA number of genetic-association studies have identified genes contributing to ankylosing spondylitis (AS) susceptibility but such approaches provide little information as to the gene activity changes occurring during the disease process. Transcriptional profiling generates a 'snapshot' of the sampled cells' activity and thus can provide insights into the molecular processes driving the disease process. We undertook a whole-genome microarray approach to identify candidate genes associated with AS and validated these gene-expression changes in a larger sample cohort.MethodsA total of 18 active AS patients, classified according to the New York criteria, and 18 gender- and age-matched controls were profiled using Illumina HT-12 whole-genome expression BeadChips which carry cDNAs for 48,000 genes and transcripts. Class comparison analysis identified a number of differentially expressed candidate genes. These candidate genes were then validated in a larger cohort using qPCR-based TaqMan low density arrays (TLDAs).ResultsA total of 239 probes corresponding to 221 genes were identified as being significantly different between patients and controls with a P-value <0.0005 (80% confidence level of false discovery rate). Forty-seven genes were then selected for validation studies, using the TLDAs. Thirteen of these genes were validated in the second patient cohort with 12 downregulated 1.3- to 2-fold and only 1 upregulated (1.6-fold). Among a number of identified genes with well-documented inflammatory roles we also validated genes that might be of great interest to the understanding of AS progression such as SPOCK2 (osteonectin) and EP300, which modulate cartilage and bone metabolism.ConclusionsWe have validated a gene expression signature for AS from whole blood and identified strong candidate genes that may play roles in both the inflammatory and joint destruction aspects of the disease.

The LS scale appears to be a tool capable of discriminating the level of wellbeing of adolescent population among countries.

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