Genome-wide association meta-analyses and fine-mapping elucidate pathways influencing albuminuria

Increased levels of the urinary albumin-to-creatinine ratio (UACR) are associated with higher risk of kidney disease progression and cardiovascular events, but underlying mechanisms are incompletely understood. Here, we conduct trans-ethnic (n = 564,257) and European-ancestry specific meta-analyses of genome-wide association studies of UACR, including ancestry- and diabetes-specific analyses, and identify 68 UACR-associated loci. Genetic correlation analyses and risk score associations in an independent electronic medical records database (n = 192,868) reveal connections with proteinuria, hyperlipidemia, gout, and hypertension. Fine-mapping and trans-Omics analyses with gene expression in 47 tissues and plasma protein levels implicate genes potentially operating through differential expression in kidney (including TGFB1, MUC1, PRKCI, and OAF), and allow coupling of UACR associations to altered plasma OAF concentrations. Knockdown of OAF and PRKCI orthologs in Drosophila nephrocytes reduces albumin endocytosis. Silencing fly PRKCI further impairs slit diaphragm formation. These results generate a priority list of genes and pathways for translational research to reduce albuminuria

The trans-ancestral genomic architecture of glycemic traits

Glycemic traits are used to diagnose and monitor type 2 diabetes and cardiometabolic health. To date, most genetic studies of glycemic traits have focused on individuals of European ancestry. Here we aggregated genome-wide association studies comprising up to 281,416 individuals without diabetes (30% non-European ancestry) for whom fasting glucose, 2-h glucose after an oral glucose challenge, glycated hemoglobin and fasting insulin data were available. Trans-ancestry and single-ancestry meta-analyses identified 242 loci (99 novel; P < 5 x 10(-8)), 80% of which had no significant evidence of between-ancestry heterogeneity. Analyses restricted to individuals of European ancestry with equivalent sample size would have led to 24 fewer new loci. Compared with single-ancestry analyses, equivalent-sized trans-ancestry fine-mapping reduced the number of estimated variants in 99% credible sets by a median of 37.5%. Genomic-feature, gene-expression and gene-set analyses revealed distinct biological signatures for each trait, highlighting different underlying biological pathways. Our results increase our understanding of diabetes pathophysiology by using trans-ancestry studies for improved power and resolution.A trans-ancestry meta-analysis of GWAS of glycemic traits in up to 281,416 individuals identifies 99 novel loci, of which one quarter was found due to the multi-ancestry approach, which also improves fine-mapping of credible variant sets.Diabetes mellitus: pathophysiological changes and therap

Using Grant Competition Finalists to Estimate the Effect of Large Research Grants on Early Career Scientists: Evidence from Singapore

The impact of large scale research grant on early-career scientific research is examined by studying Singapore’s NRF Fellowship, launched in 2007. This scheme offers generous grants worth up to S$ 3 million (~ €1.8M) over 5 years and is open annually to international applications without restriction on nationality. We estimate the causal impact of large-scale grants awarded to early career scientists by using the NRF Fellowship’s highly selective award process as a source of quasi-experimental variation. Our empirical strategy relies on using the shortlisted non-awardees to form a counterfactual, allowing us to estimate the impact of the NRF Fellowship grant on the scientific output of early career scientists. Overall, our evidence suggests the NRF Fellowship’s large grant quanta are effective at increasing aggregate publication output. This is an important finding given that the ostensible purpose of such large, internationally competitive grant programs is generally to promote leading edge, high impact research not possible without generous unrestricted funding. The results suggest that the NRF selection process and the generous grant quanta certainly help the awardees with scientific successes by most definitions, having accumulated a substantial number of publications and citations.The results shed light on the public policy initiatives taken by many emerging-countries to jump-start scientific research and development through large-scale scientific funding programs. Results suggest that large-scale funding could effectively stimulate aggregate scientific output of early-career scientists

Applying Machine Learning to Compare Research Grant Programs

Evaluating and comparing the performance of research funding programmes is challenging because programmes differ in how they (a) select grants and (b) select research areas for funding. Do programmes perform well because they are good at selecting research projects, or because they concentrate funding in high-output research areas? These mechanisms can be distinguished if we can identify and control for a set of research projects in common scientific areas. Previous approaches have used costly and arbitrary manual classification of research projects, or relied on coarse research groupings defined by bibliometric services. We propose a new solution: Apply machine learning to map research projects funded by one agency into the funding structure of a different agency. We identify and control for common areas of research, and separately identify the effects of grant selection from research area composition. We apply our method to compare three high-impact high-risk research programmes funding early-career life scientists: The U.S. National Institutes of Health’s New Innovators Award (NIH-NIA), the European Research Council Starting Grant (ERC-StG), and the Singapore National Research Foundation Fellowship (NRFF). We show that the NIH-NIA and NRFF concentrate research funding in selective portions of the life sciences, compared to the ERC-StG which by design evenly distributes research funding. Within common research areas, NIH-NIA and NRFF researchers exhibit faster growth in citations, and to a lesser extent publications, than equivalent ERC-StG researchers. This suggests the NIH-NIA and NRFF are able to select researchers who deliver superior research outcomes

Using Grant Competition Finalists to Estimate the Effect of Large Research Grants on Early Career Scientists: Evidence from Singapore

The impact of large scale research grant on early-career scientific research is examined by studying Singapore’s NRF Fellowship, launched in 2007. This scheme offers generous grants worth up to S$ 3 million (~ €1.8M) over 5 years and is open annually to international applications without restriction on nationality. We estimate the causal impact of large-scale grants awarded to early career scientists by using the NRF Fellowship’s highly selective award process as a source of quasi-experimental variation. Our empirical strategy relies on using the shortlisted non-awardees to form a counterfactual, allowing us to estimate the impact of the NRF Fellowship grant on the scientific output of early career scientists. Overall, our evidence suggests the NRF Fellowship’s large grant quanta are effective at increasing aggregate publication output. This is an important finding given that the ostensible purpose of such large, internationally competitive grant programs is generally to promote leading edge, high impact research not possible without generous unrestricted funding. The results suggest that the NRF selection process and the generous grant quanta certainly help the awardees with scientific successes by most definitions, having accumulated a substantial number of publications and citations.The results shed light on the public policy initiatives taken by many emerging-countries to jump-start scientific research and development through large-scale scientific funding programs. Results suggest that large-scale funding could effectively stimulate aggregate scientific output of early-career scientists

Preparation of Ti(C,N)-WC-TaC solid solution by mechanical alloying technique

Journal of Materials Processing Tech.481-4779-784JMPT

Zirconia-glass ionomer cement - A potential substitute for Miracle Mix

10.1016/j.scriptamat.2004.09.019Scripta Materialia522113-116SCMA