Sequence variants in three loci influence monocyte counts and erythrocyte volume

Blood cells participate in vital physiological processes, and their numbers are tightly regulated so that homeostasis is maintained. Disruption of key regulatory mechanisms underlies many blood-related Mendelian diseases but also contributes to more common disorders, including atherosclerosis. We searched for quantitative trait loci (QTL) for hematology traits through a whole-genome association study, because these could provide new insights into both hemopoeitic and disease mechanisms. We tested 1.8 million variants for association with 13 hematology traits measured in 6015 individuals from the Australian and Dutch populations. These traits included hemoglobin composition, platelet counts, and red blood cell and white blood cell indices. We identified three regions of strong association that, to our knowledge, have not been previously reported in the literature. The first was located in an intergenic region of chromosome 9q31 near LPAR1, explaining 1.5% of the variation in monocyte counts (best SNP rs7023923, p=8.9x10(-14)). The second locus was located on chromosome 6p21 and associated with mean cell erythrocyte volume (rs12661667, p=1.2x10(-9), 0.7% variance explained) in a region that spanned five genes, including CCND3, a member of the D-cyclin gene family that is involved in hematopoietic stem cell expansion. The third region was also associated with erythrocyte volume and was located in an intergenic region on chromosome 6q24 (rs592423, p=5.3x10(-9), 0.6% variance explained). All three loci replicated in an independent panel of 1543 individuals (p values=0.001, 9.9x10(-5), and 7x10(-5), respectively). The identification of these QTL provides new opportunities for furthering our understanding of the mechanisms regulating hemopoietic cell fate.

Common variants in TMPRSS6 are associated with iron status and erythrocyte volume

We report a genome-wide association study to iron status. We identify an association of SNPs in TPMRSS6 to serum iron (rs855791, combined P = 1.5 x 10(-20)), transferrin saturation (combined P = 2.2 x 10(-23)) and erythrocyte mean cell volume (MCV, combined P = 1.1 x 10(-10)). We also find suggestive evidence of association with blood hemoglobin levels (combined P = 5.3 x 10(-7)). These findings demonstrate the involvement of TMPRSS6 in control of iron homeostasis and in normal erythropoiesis.

Structural and thermal properties of inorganic–organic montmorillonite: Implications for their potential environmental applications

Inorganic–organic clays (IOCs), clays intercalated with both organic cations such as cationic surfactants and inorganic cations such as metal hydroxy polycations have the properties of both organic and pillared clays, and thereby the ability to remove both inorganic and organic contaminants from water simultaneously. In this study, IOCs were synthesised using three different methods with different surfactant concentrations. Octadecyltrimethylammonium bromide (ODTMA) and hydroxy aluminium ([Al13O4 (OH)24(H2O)12]7+ or Al13) are used as the organic and inorganic modifiers (intercalation agents). According to the results, the interlayer distance, the surfactant loading amount and the Al/Si ratio of IOCs strictly depend on the intercalation method and the intercalation agent ratio. Interlayers of IOCs synthesised by intercalating ODTMA before Al13 and IOCs synthesised by simultaneous intercalation of ODTMA and Al13 were increased with increasing the ODTMA concentration used in the synthesis procedure and comparatively high loading amounts could be observed in them. In contrast, Al/Si decreased with increasing ODTMA concentration in these two types of IOCs. The results suggest that Al-pillars can be fixed within the interlayers by calcination and any increment in the amount of ODTMA used in the synthesis procedure did not affect the interlayer distance of the IOCs. Overall the study provides valuable insights into the structure and properties of the IOCs and their potential environmental applications.

Bayesian estimation of small effects in exercise and sports science

The aim of this paper is to provide a Bayesian formulation of the so-called magnitude-based inference approach to quantifying and interpreting effects, and in a case study example provide accurate probabilistic statements that correspond to the intended magnitude-based inferences. The model is described in the context of a published small-scale athlete study which employed a magnitude-based inference approach to compare the effect of two altitude training regimens (live high-train low (LHTL), and intermittent hypoxic exposure (IHE)) on running performance and blood measurements of elite triathletes. The posterior distributions, and corresponding point and interval estimates, for the parameters and associated effects and comparisons of interest, were estimated using Markov chain Monte Carlo simulations. The Bayesian analysis was shown to provide more direct probabilistic comparisons of treatments and able to identify small effects of interest. The approach avoided asymptotic assumptions and overcame issues such as multiple testing. Bayesian analysis of unscaled effects showed a probability of 0.96 that LHTL yields a substantially greater increase in hemoglobin mass than IHE, a 0.93 probability of a substantially greater improvement in running economy and a greater than 0.96 probability that both IHE and LHTL yield a substantially greater improvement in maximum blood lactate concentration compared to a Placebo. The conclusions are consistent with those obtained using a ‘magnitude-based inference’ approach that has been promoted in the field. The paper demonstrates that a fully Bayesian analysis is a simple and effective way of analysing small effects, providing a rich set of results that are straightforward to interpret in terms of probabilistic statements.