Beyond R0 : demographic models for variability of lifetime reproductive output

© The Author(s), 2011. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in PLoS One 6 (2011): e20809, doi:10.1371/journal.pone.0020809.The net reproductive rate measures the expected lifetime reproductive output of an individual, and plays an important role in demography, ecology, evolution, and epidemiology. Well-established methods exist to calculate it from age- or stage-classified demographic data. As an expectation, provides no information on variability; empirical measurements of lifetime reproduction universally show high levels of variability, and often positive skewness among individuals. This is often interpreted as evidence of heterogeneity, and thus of an opportunity for natural selection. However, variability provides evidence of heterogeneity only if it exceeds the level of variability to be expected in a cohort of identical individuals all experiencing the same vital rates. Such comparisons require a way to calculate the statistics of lifetime reproduction from demographic data. Here, a new approach is presented, using the theory of Markov chains with rewards, obtaining all the moments of the distribution of lifetime reproduction. The approach applies to age- or stage-classified models, to constant, periodic, or stochastic environments, and to any kind of reproductive schedule. As examples, I analyze data from six empirical studies, of a variety of animal and plant taxa (nematodes, polychaetes, humans, and several species of perennial plants).Supported by National Science Foundation Grant DEB-0816514 and by a Research Award from the Alexander von Humboldt Foundation

Identifying Host Genetic Risk Factors in the Context of Public Health Surveillance for Invasive Pneumococcal Disease

Host genetic factors that modify risk of pneumococcal disease may help target future public health interventions to individuals at highest risk of disease. We linked data from population-based surveillance for invasive pneumococcal disease (IPD) with state-based newborn dried bloodspot repositories to identify biological samples from individuals who developed invasive pneumococcal disease. Genomic DNA was extracted from 366 case and 732 anonymous control samples. TagSNPs were selected in 34 candidate genes thought to be associated with host response to invasive pneumococcal disease, and a total of 326 variants were successfully genotyped. Among 543 European Americans (EA) (182 cases and 361 controls), and 166 African Americans (AA) (53 cases and 113 controls), common variants in surfactant protein D (SFTPD) are consistently underrepresented in IPD. SFTPD variants with the strongest association for IPD are intronic rs17886286 (allelic OR 0.45, 95% confidence interval (CI) [0.25, 0.82], with p = 0.007) in EA and 5′ flanking rs12219080 (allelic OR 0.32, 95%CI [0.13, 0.78], with p = 0.009) in AA. Variants in CD46 and IL1R1 are also associated with IPD in both EA and AA, but with effects in different directions; FAS, IL1B, IL4, IL10, IL12B, SFTPA1, SFTPB, and PTAFR variants are associated (p≤0.05) with IPD in EA or AA. We conclude that variants in SFTPD may protect against IPD in EA and AA and genetic variation in other host response pathways may also contribute to risk of IPD. While our associations are not corrected for multiple comparisons and therefore must be replicated in additional cohorts, this pilot study underscores the feasibility of integrating public health surveillance with existing, prospectively collected, newborn dried blood spot repositories to identify host genetic factors associated with infectious diseases

Beyond the genetics of HDL:why is HDL cholesterol inversely related to cardiovascular disease?

There is unequivocal evidence that high-density lipoprotein (HDL) cholesterol levels in plasma are inversely associated with the risk of cardiovascular disease (CVD). Studies of families with inherited HDL disorders and genetic association studies in general (and patient) population samples have identified a large number of factors that control HDL cholesterol levels. However, they have not resolved why HDL cholesterol and CVD are inversely related. A growing body of evidence from nongenetic studies shows that HDL in patients at increased risk of CVD has lost its protective properties and that increasing the cholesterol content of HDL does not result in the desired effects. Hopefully, these insights can help improve strategies to successfully intervene in HDL metabolism. It is clear that there is a need to revisit the HDL hypothesis in an unbiased manner. True insights into the molecular mechanisms that regulate plasma HDL cholesterol and triglycerides or control HDL function could provide the handholds that are needed to develop treatment for, e.g., type 2 diabetes and the metabolic syndrome. Especially genome-wide association studies have provided many candidate genes for such studies. In this review we have tried to cover the main molecular studies that have been produced over the past few years. It is clear that we are only at the very start of understanding how the newly identified factors may control HDL metabolism. In addition, the most recent findings underscore the intricate relations between HDL, triglyceride, and glucose metabolism indicating that these parameters need to be studied simultaneously

Carfilzomib and dexamethasone versus bortezomib and dexamethasone for patients with relapsed or refractory multiple myeloma (ENDEAVOR): And randomised, phase 3, open-label, multicentre study

Background: Bortezomib with dexamethasone is a standard treatment option for relapsed or refractory multiple myeloma. Carfilzomib with dexamethasone has shown promising activity in patients in this disease setting. The aim of this study was to compare the combination of carfilzomib and dexamethasone with bortezomib and dexamethasone in patients with relapsed or refractory multiple myeloma. Methods: In this randomised, phase 3, open-label, multicentre study, patients with relapsed or refractory multiple myeloma who had one to three previous treatments were randomly assigned (1:1) using a blocked randomisation scheme (block size of four) to receive carfilzomib with dexamethasone (carfilzomib group) or bortezomib with dexamethasone (bortezomib group). Randomisation was stratified by previous proteasome inhibitor therapy, previous lines of treatment, International Staging System stage, and planned route of bortezomib administration if randomly assigned to bortezomib with dexamethasone. Patients received treatment until progression with carfilzomib (20 mg/m2 on days 1 and 2 of cycle 1; 56 mg/m2 thereafter; 30 min intravenous infusion) and dexamethasone (20 mg oral or intravenous infusion) or bortezomib (1·3 mg/m2; intravenous bolus or subcutaneous injection) and dexamethasone (20 mg oral or intravenous infusion). The primary endpoint was progression-free survival in the intention-to-treat population. All participants who received at least one dose of study drug were included in the safety analyses. The study is ongoing but not enrolling participants; results for the interim analysis of the primary endpoint are presented. The trial is registered at ClinicalTrials.gov, number NCT01568866. Findings: Between June 20, 2012, and June 30, 2014, 929 patients were randomly assigned (464 to the carfilzomib group; 465 to the bortezomib group). Median follow-up was 11·9 months (IQR 9·3-16·1) in the carfilzomib group and 11·1 months (8·2-14·3) in the bortezomib group. Median progression-free survival was 18·7 months (95% CI 15·6-not estimable) in the carfilzomib group versus 9·4 months (8·4-10·4) in the bortezomib group at a preplanned interim analysis (hazard ratio [HR] 0·53 [95% CI 0·44-0·65]; p<0·0001). On-study death due to adverse events occurred in 18 (4%) of 464 patients in the carfilzomib group and in 16 (3%) of 465 patients in the bortezomib group. Serious adverse events were reported in 224 (48%) of 463 patients in the carfilzomib group and in 162 (36%) of 456 patients in the bortezomib group. The most frequent grade 3 or higher adverse events were anaemia (67 [14%] of 463 patients in the carfilzomib group vs 45 [10%] of 456 patients in the bortezomib group), hypertension (41 [9%] vs 12 [3%]), thrombocytopenia (39 [8%] vs 43 [9%]), and pneumonia (32 [7%] vs 36 [8%]). Interpretation: For patients with relapsed or refractory multiple myeloma, carfilzomib with dexamethasone could be considered in cases in which bortezomib with dexamethasone is a potential treatment option. Funding: Onyx Pharmaceuticals, Inc., an Amgen subsidiary

Anthropogenic intensification of short-duration rainfall extremes

Short- duration (1-3 h) rainfall extremes can cause serious damage to societies through rapidly developing (flash) flooding and are determined by complex, multifaceted processes that are altering as Earth's climate warms. In this Review, we examine evidence from observational, theoretical and modelling studies for the intensification of these rainfall extremes, the drivers and the impact on flash flooding. Both short- duration and long- duration (\textgreater1 day) rainfall extremes are intensifying with warming at a rate consistent with the increase in atmospheric moisture (~7% K-1), while in some regions, increases in short- duration extreme rainfall intensities are stronger than expected from moisture increases alone. These stronger local increases are related to feedbacks in convective clouds, but their exact role is uncertain because of the very small scales involved. Future extreme rainfall intensification is also modulated by changes to temperature stratification and large- scale atmospheric circulation. The latter remains a major source of uncertainty. Intensification of short- duration extremes has likely increased the incidence of flash flooding at local scales and this can further compound with an increase in storm spatial footprint to considerably increase total event rainfall. These findings call for urgent climate change adaptation measures to manage increasing flood risks

Differential and shared genetic effects on kidney function between diabetic and non-diabetic individuals

A large-scale GWAS provides insight on diabetes-dependent genetic effects on the glomerular filtration rate, a common metric to monitor kidney health in disease.Reduced glomerular filtration rate (GFR) can progress to kidney failure. Risk factors include genetics and diabetes mellitus (DM), but little is known about their interaction. We conducted genome-wide association meta-analyses for estimated GFR based on serum creatinine (eGFR), separately for individuals with or without DM (nDM = 178,691, nnoDM = 1,296,113). Our genome-wide searches identified (i) seven eGFR loci with significant DM/noDM-difference, (ii) four additional novel loci with suggestive difference and (iii) 28 further novel loci (including CUBN) by allowing for potential difference. GWAS on eGFR among DM individuals identified 2 known and 27 potentially responsible loci for diabetic kidney disease. Gene prioritization highlighted 18 genes that may inform reno-protective drug development. We highlight the existence of DM-only and noDM-only effects, which can inform about the target group, if respective genes are advanced as drug targets. Largely shared effects suggest that most drug interventions to alter eGFR should be effective in DM and noDM.</p

Treating gliomas with glucocorticoids: from bedside to bench

Glucocorticoids are used in the treatment of gliomas to decrease tumour-associated oedema and to reduce the risk of acute encephalopathy associated with radiotherapy. However, the mechanisms by which glucocorticoids work are still largely unknown. In this paper, we survey the experimental and clinical evidence for the effects of glucocorticoids on tumour cell proliferation, apoptosis and sensitivity to chemotherapy, angiogenesis and vascular permeability. We then review current guidelines on the choice of molecule, dose and duration of glucocorticoid treatment for gliomas