Paleoclimate of the subtropical Andes during the latest Miocene, Lauca T Basin, Chile

Uplift of the Andean Cordillera during the Miocene and Pliocene produced large-scale changes in regional atmospheric circulation that impacted local ecosystems. The Lauca Basin (northern Chilean Altiplano) contains variably fluvial and lacustrine sedimentary sequences spanning the interval from 8.7 to 2.3 Ma. Field samples were collected from paleo-lacustrine sediments in the basin. Sediments were dated using detrital zircon geochronology on volcanic tuffs, yielding an age range between ~5.57 and 5.44 Ma. These new age constraints provided an opportunity to evaluate changes in the Lauca Basin ecosystem across this dynamic Miocene-Pliocene transition. We employed multiple proxies (lithofacies analysis, diatoms, pollen, and oxygen stable isotopes of authigenic carbonates) to interpret ancient lacustrine and terrestrial paleoenvironments. Alternations among mudstone, carbonate, and evaporitic facies indicate lake-level variability through time. The diatom assemblage is characterized by meso- to hypersaline and alkaline-tolerant taxa typical of shallow lakes. The δ18O values ranged from −8.96 to −2.22‰ indicating fluctuations in water balance. Pollen taxa in the outcrop are typical of a transitional stage between seasonal cloud forest and open grassland. Together, these proxies indicate that the Lauca paleolake sediments were deposited under a wetter-than-modern climate with high temporal variability. Our results refine previous studies in the Lauca Basin and are consistent with other regional studies suggesting that the South American summer monsoon at the Miocene-Pliocene transition was more intense than it is at present

Search for AL amyloidosis risk factors using Mendelian randomization

In amyloid light chain (AL) amyloidosis, amyloid fibrils derived from immunoglobulin light chain are deposited in many organs, interfering with their function. The etiology of AL amyloidosis is poorly understood. Summary data from genome-wide association studies (GWASs) of multiple phenotypes can be exploited by Mendelian randomization (MR) methodology to search for factors influencing AL amyloidosis risk. We performed a 2-sample MR analyzing 72 phenotypes, proxied by 3461 genetic variants, and summary genetic data from a GWAS of 1129 AL amyloidosis cases and 7589 controls. Associations with a Bonferroni-defined significance level were observed for genetically predicted increased monocyte counts (P = 3.8 × 10−4) and the tumor necrosis factor receptor superfamily member 17 (TNFRSF17) gene (P = 3.4 × 10−5). Two other associations with the TNFRSF (members 6 and 19L) reached a nominal significance level. The association between genetically predicted decreased fibrinogen levels may be related to roles of fibrinogen other than blood clotting. be related to its nonhemostatic role. It is plausible that a causal relationship with monocyte concentration could be explained by selection of a light chain–producing clone during progression of monoclonal gammopathy of unknown significance toward AL amyloidosis. Because TNFRSF proteins have key functions in lymphocyte biology, it is entirely plausible that they offer a potential link to AL amyloidosis pathophysiology. Our study provides insight into AL amyloidosis etiology, suggesting high circulating levels of monocytes and TNFRSF proteins as risk factors

Tropospheric jet response to Antarctic ozone depletion: An update with Chemistry-Climate Model Initiative (CCMI) models

The Southern Hemisphere (SH) zonal-mean circulation change in response to Antarctic ozone depletion is re-visited by examining a set of the latest model simulations archived for the Chemistry-Climate Model Initiative (CCMI) project. All models reasonably well reproduce Antarctic ozone depletion in the late 20th century. The related SH-summer circulation changes, such as a poleward intensification of westerly jet and a poleward expansion of the Hadley cell, are also well captured. All experiments exhibit quantitatively the same multi-model mean trend, irrespective of whether the ocean is coupled or prescribed. Results are also quantitatively similar to those derived from the Coupled Model Intercomparison Project phase 5 (CMIP5) high-top model simulations in which the stratospheric ozone is mostly prescribed with monthly- and zonally-averaged values. These results suggest that the ozone-hole-induced SH-summer circulation changes are robust across the models irrespective of the specific chemistry-atmosphere-ocean coupling

New resampling method for evaluating stability of clusters

<p>Abstract</p> <p>Background</p> <p>Hierarchical clustering is a widely applied tool in the analysis of microarray gene expression data. The assessment of cluster stability is a major challenge in clustering procedures. Statistical methods are required to distinguish between real and random clusters. Several methods for assessing cluster stability have been published, including resampling methods such as the bootstrap.</p> <p>We propose a new resampling method based on continuous weights to assess the stability of clusters in hierarchical clustering. While in bootstrapping approximately one third of the original items is lost, continuous weights avoid zero elements and instead allow non integer diagonal elements, which leads to retention of the full dimensionality of space, i.e. each variable of the original data set is represented in the resampling sample.</p> <p>Results</p> <p>Comparison of continuous weights and bootstrapping using real datasets and simulation studies reveals the advantage of continuous weights especially when the dataset has only few observations, few differentially expressed genes and the fold change of differentially expressed genes is low.</p> <p>Conclusion</p> <p>We recommend the use of continuous weights in small as well as in large datasets, because according to our results they produce at least the same results as conventional bootstrapping and in some cases they surpass it.</p

The effector T cell response to influenza infection

Influenza virus infection induces a potent initial innate immune response, which serves to limit the extent of viral replication and virus spread. However, efficient (and eventual) viral clearance within the respiratory tract requires the subsequent activation, rapid proliferation, recruitment, and expression of effector activities by the adaptive immune system, consisting of antibody producing B cells and influenza-specific T lymphocytes with diverse functions. The ensuing effector activities of these T lymphocytes ultimately determine (along with antibodies) the capacity of the host to eliminate the viruses and the extent of tissue damage. In this review, we describe this effector T cell response to influenza virus infection. Based on information largely obtained in experimental settings (i.e., murine models), we will illustrate the factors regulating the induction of adaptive immune T cell responses to influenza, the effector activities displayed by these activated T cells, the mechanisms underlying the expression of these effector mechanisms, and the control of the activation/differentiation of these T cells, in situ, in the infected lungs

Exposure to surrounding greenness and natural-cause and cause-specific mortality in the ELAPSE pooled cohort

Background The majority of studies have shown higher greenness exposure associated with reduced mortality risks, but few controlled for spatially correlated air pollution and traffic noise exposures. We aim to address this research gap in the ELAPSE pooled cohort. Methods Mean Normalized Difference Vegetation Index (NDVI) in a 300-m grid cell and 1-km radius were assigned to participants’ baseline home addresses as a measure of surrounding greenness exposure. We used Cox proportional hazards models to estimate the association of NDVI exposure with natural-cause and cause-specific mortality, adjusting for a number of potential confounders including socioeconomic status and lifestyle factors at individual and area-levels. We further assessed the associations between greenness exposure and mortality after adjusting for fine particulate matter (PM2.5), nitrogen dioxide (NO2) and road traffic noise. Results The pooled study population comprised 327,388 individuals who experienced 47,179 natural-cause deaths during 6,374,370 person-years of follow-up. The mean NDVI in the pooled cohort was 0.33 (SD 0.1) and 0.34 (SD 0.1) in the 300-m grid and 1-km buffer. In the main fully adjusted model, 0.1 unit increment of NDVI inside 300-m grid was associated with 5% lower risk of natural-cause mortality (Hazard Ratio (HR) 0.95 (95% CI: 0.94, 0.96)). The associations attenuated after adjustment for air pollution [HR (95% CI): 0.97 (0.96, 0.98) adjusted for PM2.5; 0.98 (0.96, 0.99) adjusted for NO2]. Additional adjustment for traffic noise hardly affected the associations. Consistent results were observed for NDVI within 1-km buffer. After adjustment for air pollution, NDVI was inversely associated with diabetes, respiratory and lung cancer mortality, yet with wider 95% confidence intervals. No association with cardiovascular mortality was found. Conclusions We found a significant inverse association between surrounding greenness and natural-cause mortality, which remained after adjusting for spatially correlated air pollution and traffic noise

Systematic Evaluation of Pleiotropy Identifies 6 Further Loci Associated With Coronary Artery Disease

Background: Genome-wide association studies have so far identified 56 loci associated with risk of coronary artery disease (CAD). Many CAD loci show pleiotropy; that is, they are also associated with other diseases or traits. Objectives: This study sought to systematically test if genetic variants identified for non-CAD diseases/traits also associate with CAD and to undertake a comprehensive analysis of the extent of pleiotropy of all CAD loci. Methods: In discovery analyses involving 42,335 CAD cases and 78,240 control subjects we tested the association of 29,383 common (minor allele frequency &gt;5%) single nucleotide polymorphisms available on the exome array, which included a substantial proportion of known or suspected single nucleotide polymorphisms associated with common diseases or traits as of 2011. Suggestive association signals were replicated in an additional 30,533 cases and 42,530 control subjects. To evaluate pleiotropy, we tested CAD loci for association with cardiovascular risk factors (lipid traits, blood pressure phenotypes, body mass index, diabetes, and smoking behavior), as well as with other diseases/traits through interrogation of currently available genome-wide association study catalogs. Results: We identified 6 new loci associated with CAD at genome-wide significance: on 2q37 (KCNJ13-GIGYF2), 6p21 (C2), 11p15 (MRVI1-CTR9), 12q13 (LRP1), 12q24 (SCARB1), and 16q13 (CETP). Risk allele frequencies ranged from 0.15 to 0.86, and odds ratio per copy of the risk allele ranged from 1.04 to 1.09. Of 62 new and known CAD loci, 24 (38.7%) showed statistical association with a traditional cardiovascular risk factor, with some showing multiple associations, and 29 (47%) showed associations at p &lt; 1 × 10−4 with a range of other diseases/traits. Conclusions: We identified 6 loci associated with CAD at genome-wide significance. Several CAD loci show substantial pleiotropy, which may help us understand the mechanisms by which these loci affect CAD risk

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

Author Correction: Identification of multiple risk loci and regulatory mechanisms influencing susceptibility to multiple myeloma

Correction to: Nature Communications; https://doi.org/10.1038/s41467-018-04989-w, published online 13 September 2018