Meta-analysis of type 2 Diabetes in African Americans Consortium

Type 2 diabetes (T2D) is more prevalent in African Americans than in Europeans. However, little is known about the genetic risk in African Americans despite the recent identification of more than 70 T2D loci primarily by genome-wide association studies (GWAS) in individuals of European ancestry. In order to investigate the genetic architecture of T2D in African Americans, the MEta-analysis of type 2 DIabetes in African Americans (MEDIA) Consortium examined 17 GWAS on T2D comprising 8,284 cases and 15,543 controls in African Americans in stage 1 analysis. Single nucleotide polymorphisms (SNPs) association analysis was conducted in each study under the additive model after adjustment for age, sex, study site, and principal components. Meta-analysis of approximately 2.6 million genotyped and imputed SNPs in all studies was conducted using an inverse variance-weighted fixed effect model. Replications were performed to follow up 21 loci in up to 6,061 cases and 5,483 controls in African Americans, and 8,130 cases and 38,987 controls of European ancestry. We identified three known loci (TCF7L2, HMGA2 and KCNQ1) and two novel loci (HLA-B and INS-IGF2) at genome-wide significance (4.15 × 10(-94)<P<5 × 10(-8), odds ratio (OR)  = 1.09 to 1.36). Fine-mapping revealed that 88 of 158 previously identified T2D or glucose homeostasis loci demonstrated nominal to highly significant association (2.2 × 10(-23) < locus-wide P<0.05). These novel and previously identified loci yielded a sibling relative risk of 1.19, explaining 17.5% of the phenotypic variance of T2D on the liability scale in African Americans. Overall, this study identified two novel susceptibility loci for T2D in African Americans. A substantial number of previously reported loci are transferable to African Americans after accounting for linkage disequilibrium, enabling fine mapping of causal variants in trans-ethnic meta-analysis studies.Peer reviewe

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

Spectroscopic characterization of samples from different environments in a Volcano-Glacial region in Iceland: Implications for in situ planetary exploration

Raman spectroscopy and laser induced breakdown spectroscopy (LIBS) are complementary techniques that together can provide a comprehensive characterization of geologic environments. For landed missions with constrained access to target materials on other planetary bodies, discerning signatures of life and habitability can be daunting, particularly where the preservation of organic compounds that contain the building blocks of life is limited. The main challenge facing any spectroscopy measurements of natural samples is the complicated spectra that often contain signatures for multiple components, particularly in rocks that are composed of several minerals with surfaces colonized by microbes. The goal of this study was to use the combination of Raman spectroscopy and LIBS to discern different environmental regimes based on the identification of minerals and biomolecules in rocks and sediments. Iceland is a terrestrial volcano-glacial location that offers a range of planetary analog environments, including volcanically active regions, extensive lava fields, geothermal springs, and large swaths of ice-covered terrain that are relevant to both rocky and icy planetary bodies. We combined portable VIS (532 nm) and NIR (785 nm) Raman spectroscopy, VIS micro-Raman spectroscopic mapping, and UV/VIS/NIR (200 – 1000 nm) and Mid-IR (5.6 – 10 μm, 1785 – 1000 cm−1) laser induced breakdown spectroscopy (LIBS) to characterize the mineral assemblages, hydrated components, and biomolecules in rock and sediment samples collected from three main sites in the volcanically active Kverkfjöll-Vatnajökull region of Iceland: basalt and basalt-hosted carbonate rind from Hveragil geothermal stream, volcanic sediments from the base of Vatnajökull glacier at Kverkfjöll, and lava from the nearby Holuhraun lava field. With our combination of techniques, we were able to identify major mineral polytypes typical for each sample set, as well as a large diversity of biomolecules typical for lichen communities across all samples. The anatase we observed using micro-Raman spectroscopic mapping of the lava compared with the volcanic sediment suggested different formation pathways: lava anatase formed authigenically, sediment anatase could have formed in association with microbial weathering. Mn-oxide, only detected in the carbonate samples, seems to have two possible formation pathways, either by fluvial or microbial weathering or both. Even with our ability to detect a wide diversity of biomolecules and minerals in all of the samples, there was not enough variation between each set to distinguish different environments based on the limited measurements done for this study