Lipidoid-Coated Iron Oxide Nanoparticles for Efficient DNA and siRNA delivery

The safe, targeted and effective delivery of gene therapeutics remains a significant barrier to their broad clinical application. Here we develop a magnetic nucleic acid delivery system composed of iron oxide nanoparticles and cationic lipid-like materials termed lipidoids. Coated nanoparticles are capable of delivering DNA and siRNA to cells in culture. The mean hydrodynamic size of these nanoparticles was systematically varied and optimized for delivery. While nanoparticles of different sizes showed similar siRNA delivery efficiency, nanoparticles of 50–100 nm displayed optimal DNA delivery activity. The application of an external magnetic field significantly enhanced the efficiency of nucleic acid delivery, with performance exceeding that of the commercially available lipid-based reagent, Lipofectamine 2000. The iron oxide nanoparticle delivery platform developed here offers the potential for magnetically guided targeting, as well as an opportunity to combine gene therapy with MRI imaging and magnetic hyperthermia.National Heart, Lung, and Blood InstituteNational Institutes of Health (U.S.) (Program of Excellence in Nanotechnology (PEN) Award, Contract #HHSN268201000045C

Efficiency of siRNA delivery by lipid nanoparticles is limited by endocytic recycling

Despite substantial efforts to understand the interactions between nanoparticles and cells, the cellular processes that determine the efficiency of intracellular drug delivery remain largely unclear. Here we examined cellular uptake of siRNA delivered in lipid nanoparticles (LNPs) using cellular trafficking probes in combination with automated high-throughput confocal microscopy as well as defined perturbations of cellular pathways paired with systems biology approaches to uncover protein-protein and protein-small molecule interactions. We show that multiple cell signaling effectors are required for initial cellular entry of LNPs through macropinocytosis, including proton pumps, mTOR, and cathepsins. SiRNA delivery is substantially reduced as ≅70% of the internalized siRNA undergoes exocytosis through egress of LNPs from late endosomes/lysosomes. Niemann Pick type C1 (NPC1) is shown to be an important regulator of the major recycling pathways of LNP-delivered siRNAs. NPC1-deficient cells show enhanced cellular retention of LNPs inside late endosomes/lysosomes and increased gene silencing of the target gene. Our data suggests that siRNA delivery efficiency might be improved by designing delivery vehicles that can escape the recycling pathways

SARS-CoV-2 susceptibility and COVID-19 disease severity are associated with genetic variants affecting gene expression in a variety of tissues

Variability in SARS-CoV-2 susceptibility and COVID-19 disease severity between individuals is partly due to genetic factors. Here, we identify 4 genomic loci with suggestive associations for SARS-CoV-2 susceptibility and 19 for COVID-19 disease severity. Four of these 23 loci likely have an ethnicity-specific component. Genome-wide association study (GWAS) signals in 11 loci colocalize with expression quantitative trait loci (eQTLs) associated with the expression of 20 genes in 62 tissues/cell types (range: 1:43 tissues/gene), including lung, brain, heart, muscle, and skin as well as the digestive system and immune system. We perform genetic fine mapping to compute 99% credible SNP sets, which identify 10 GWAS loci that have eight or fewer SNPs in the credible set, including three loci with one single likely causal SNP. Our study suggests that the diverse symptoms and disease severity of COVID-19 observed between individuals is associated with variants across the genome, affecting gene expression levels in a wide variety of tissue types

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 hospitalization2–4 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

SARS-CoV-2 susceptibility and COVID-19 disease severity are associated with genetic variants affecting gene expression in a variety of tissues

Variability in SARS-CoV-2 susceptibility and COVID-19 disease severity between individuals is partly due to genetic factors. Here, we identify 4 genomic loci with suggestive associations for SARS-CoV-2 susceptibility and 19 for COVID-19 disease severity. Four of these 23 loci likely have an ethnicity-specific component. Genome-wide association study (GWAS) signals in 11 loci colocalize with expression quantitative trait loci (eQTLs) associated with the expression of 20 genes in 62 tissues/cell types (range: 1:43 tissues/gene), including lung, brain, heart, muscle, and skin as well as the digestive system and immune system. We perform genetic fine mapping to compute 99% credible SNP sets, which identify 10 GWAS loci that have eight or fewer SNPs in the credible set, including three loci with one single likely causal SNP. Our study suggests that the diverse symptoms and disease severity of COVID-19 observed between individuals is associated with variants across the genome, affecting gene expression levels in a wide variety of tissue types

A second update on mapping the human genetic architecture of COVID-19

Matters Arising From: COVID-19 Host Genetics Initiative. Nature https://doi.org/10.1038/s41586-021-03767-x (2021)Data availability: Summary statistics generated by the COVID-19 HGI are available online, including per-ancestry summary statistics for African, admixed American, East Asian, European and South Asian ancestries (https://www.covid19hg.org/results/r7/). The analyses described here used the data release 7. If available, individual-level data can be requested directly from contributing studies, listed in Supplementary Table 1. We used publicly available data from GTEx (https://gtexportal.org/home/), the Neale laboratory (http://www.nealelab.is/uk-biobank/), the Finucane laboratory (https://www.finucanelab.org), the FinnGen Freeze 4 cohort (https://www.finngen.fi/en/access_results) and the eQTL catalogue release 3 (http://www.ebi.ac.uk/eqtl/).Code availability: The code for summary statistics lift-over, the projection PCA pipeline including precomputed loadings and meta-analyses (https://github.com/covid19-hg/); for heritability estimation (https://github.com/AndrewsLabUCSF/COVID19_heritability); for Mendelian randomization and genetic correlation (https://github.com/marcoralab/MRcovid); and subtype analyses (https://github.com/mjpirinen/covid19-hgi_subtypes) are available at GitHub.Reporting summary: Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article online at: https://www.nature.com/articles/s41586-023-06355-3#MOESM2 .Supplementary information is available online at: https://www.nature.com/articles/s41586-023-06355-3#Sec4 .Copyright © The Author(s) 2023. Investigating the role of host genetic factors in COVID-19 severity and susceptibility can inform our understanding of the underlying biological mechanisms that influence adverse outcomes and drug development1,2. Here we present a second updated genome-wide association study (GWAS) on COVID-19 severity and infection susceptibility to SARS-CoV-2 from the COVID-19 Host Genetic Initiative (data release 7). We performed a meta-analysis of up to 219,692 cases and over 3 million controls, identifying 51 distinct genome-wide significant loci—adding 28 loci from the previous data release2. The increased number of candidate genes at the identified loci helped to map three major biological pathways that are involved in susceptibility and severity: viral entry, airway defence in mucus and type I interferon

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

A first update on mapping the human genetic architecture of COVID-19

peer reviewe

A Novel Method to Determine Optimal Load in Elastic-Based Power Training

Buskard, AN, Oh, J, Eltoukhy, M, Brounstein, SR, and Signorile, JF. A novel method to determine optimal load in elastic-based power training. J Strength Cond Res XX(X): 000-000, 2018-The benefits of muscular power on sport performance and older adults' abilities to live independently and resist falls is well documented. Consequently, a substantial volume of research has focused on establishing the optimal loading patterns for improving muscular power using resistance exercise; however, to date, this research has only targeted optimal loading during training with free weights or selectorized exercise machines. Conversely, no approach has been developed to establish optimal loads for elastic modalities, such as tubes and bands, commonly used for sports rehabilitation, injury prevention, and training older adults. Therefore, the purpose of this study was to evaluate a new method for determining the optimal tubes to use in power training performed with elastic resistance. Thirty-eight recreationally active college students (age, 23.7 ± 4.5 years) were recruited to perform 3 single-arm bicep curls at a maximum intended velocity using 6 elastic tubes of varying resistance. Testing was performed in a 3-dimensional (3D) motion analysis laboratory using a specially constructed platform with an integrated strain gauge to which each tube was anchored. Force data from the strain gauge and velocity data from the 3D motion capture system were then used to compute power for each tube. An analysis based on individual's cable arm curl 1-repetition maximum (1RM) was then used to generate general guidelines for the most appropriate tube to use for arm curl power training based on upper arm 1RM. Our results demonstrate the feasibility of using this methodology for other exercises, thereby establishing optimal tube use for power training based on each exercise's 1RM