The relation between bone mineral density, bone turnover markers, and vitamin D status in ankylosing spondylitis patients with active disease: a cross-sectional analysis

Osteoporosis is a well recognized complication of ankylosing spondylitis (AS). This study indicates that increased bone turnover, inflammation, and low vitamin D levels are important in the pathophysiology of AS-related osteoporosis, and that bone turnover markers (BTM) are valuable markers to detect bone loss in AS. The aim of this study was to elucidate the pathophysiology of AS-related osteoporosis by investigating the relation between bone mineral density (BMD), BTM, vitamin D, and clinical assessments of disease activity and physical function, as well as to identify parameters that are related to low BMD (osteopenia or osteoporosis) in AS patients with active disease. One hundred twenty-eight consecutive Dutch AS outpatients were included in this cross-sectional study. Bath AS Disease Activity Index (BASDAI), erythrocyte sedimentation rate (ESR), C-reactive protein, ASAS-endorsed disease activity score (ASDAS), Bath AS Functional Index (BASFI), bone formation markers procollagen type 1 N-terminal peptide (PINP) and osteocalcin (OC), bone resorption marker serum C-telopeptides of type I collagen (sCTX), 25-hydroxyvitamin D (25OHvitD), lumbar spine and hip BMD, and vertebral fractures were assessed. Z-scores of BTM were calculated using matched 10-year cohorts of a Dutch reference group to correct for the normal influence that age and gender have on bone turnover. sCTX Z-score, OC Z-score, BASDAI, age, and gender were independently related to low BMD. In addition, PINP Z-score, ESR, 25OHvitD, age, and gender were independently related to sCTX and/or OC Z-score. This study indicates that increased bone turnover, inflammation, and low vitamin D levels are important in the pathophysiology of AS-related osteoporosis. Furthermore, sCTX and OC Z-scores seem to be valuable markers to detect bone loss in AS patients in daily clinical practice where BMD of the lumbar spine, measured by DXA, may be overestimated due to osteoproliferation in patients with advanced AS

Pan-cancer analysis of whole genomes

Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale(1-3). Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter(4); identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation(5,6); analyses timings and patterns of tumour evolution(7); describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity(8,9); and evaluates a range of more-specialized features of cancer genomes(8,10-18).Peer reviewe