Genetic correlation between multiple myeloma and chronic lymphocytic leukaemia provides evidence for shared aetiology

The clustering of different types of B-cell malignancies in families raises the possibility of shared aetiology. To examine this, we performed cross-trait linkage disequilibrium (LD)-score regression of multiple myeloma (MM) and chronic lymphocytic leukaemia (CLL) genome-wide association study (GWAS) data sets, totalling 11,734 cases and 29,468 controls. A significant genetic correlation between these two B-cell malignancies was shown (Rg = 0.4, P = 0.0046). Furthermore, four of the 45 known CLL risk loci were shown to associate with MM risk and five of the 23 known MM risk loci associate with CLL risk. By integrating eQTL, Hi-C and ChIP-seq data, we show that these pleiotropic risk loci are enriched for B-cell regulatory elements and implicate B-cell developmental genes. These data identify shared biological pathways influencing the development of CLL and, MM and further our understanding of the aetiological basis of these B-cell malignancies

Genome-wide association studies of cancer: current insights and future perspectives.

Genome-wide association studies (GWAS) provide an agnostic approach for investigating the genetic basis of complex diseases. In oncology, GWAS of nearly all common malignancies have been performed, and over 450 genetic variants associated with increased risks have been identified. As well as revealing novel pathways important in carcinogenesis, these studies have shown that common genetic variation contributes substantially to the heritable risk of many common cancers. The clinical application of GWAS is starting to provide opportunities for drug discovery and repositioning as well as for cancer prevention. However, deciphering the functional and biological basis of associations is challenging and is in part a barrier to fully unlocking the potential of GWAS

RS2072135, A LOW-PENETRANCE VARIANT FOR CHRONIC LYMPHOCYTIC LEUKAEMIA?

Recent multi-stage genome-wide association studies (GWAS) have identified single nucleotide polymorphisms (SNPs) that are robustly associated with chronic lymphocytic leukaemia (CLL) risk. Given that most of these SNPs map to non-coding regions of the genome, it suggests that the functional basis of many GWAS signals will be through differential gene expression. By referencing publically accessible expression quantitative trait loci (eQTL) data on lymphoblastoid cells lines (LCLs) we have globally demonstrated an association between GWAS P-values and eQTLs, consistent with much of the variation in CLL risk being defined by variants impacting on gene expression. To explore using eQTL data to select GWAS SNPs for replication, we genotyped rs2072135 (GWAS P-value = 0\ub70024, eQTL P-value = 1\ub7510(-19)) in five independent case-control series totalling 1968 cases and 3538 controls. While not attaining statistical significance (combined P-value = 1 7 10(-4)), rs2072135 defines a promising risk locus for CLL. Incorporating eQTL information offers an attractive strategy for selecting SNPs from GWAS for validation

Changes in body composition in triathletes during an Ironman race

PURPOSE: Triathletes lose body mass during an Ironman triathlon. However, the associated body composition changes remain enigmatic. Thus, the purpose of this study was to investigate Ironman-induced changes in segmental body composition, using for the first time dual-energy X-ray absorptiometry (DXA) and peripheral quantitative computed tomography (pQCT). METHODS: Before and after an Ironman triathlon, segmental body composition and lower leg tissue mass, areas and densities were assessed using DXA and pQCT, respectively, in eight non-professional male triathletes. In addition, blood and urine samples were collected for the determination of hydration status. RESULTS: Body mass decreased by 1.9 ± 0.8 kg. This loss was due to 0.4 ± 0.3 and 1.4 ± 0.8 kg decrease in fat and lean mass, respectively (P < 0.01). Calf muscle density was reduced by 1.93 ± 1.04 % (P < 0.01). Hemoglobin, hematocrit, and plasma [K(+)] remained unchanged, while plasma [Na(+)] (P < 0.05), urine specific gravity and plasma and urine osmolality increased (P < 0.01). CONCLUSIONS: The loss in lean mass was explained by a decrease in muscle density, as an indicator of glycogen loss, and increases in several indicators for dehydration. The measurement of body composition with DXA and pQCT before and after an Ironman triathlon provided exact values for the loss in fat and lean mass. Consequently, these results yielded more detailed insights into tissue catabolism during ultra-endurance exercise

Do male 100-km ultra-marathoners overdrink?

Incidences of EAH in 100 km ultra-marathoners were lower compared with reports on marathoners. Body mass decreased, plasma volume increased, and plasma [Na+] was maintained. Since fluid intake was related neither to Δ plasma volume nor to Δ plasma [Na+], we assume that factors other than fluid intake maintained body fluid homeostasis