An atlas connecting shared genetic architecture of human diseases and molecular phenotypes provides insight into COVID-19 susceptibility.

BACKGROUND: While genome-wide associations studies (GWAS) have successfully elucidated the genetic architecture of complex human traits and diseases, understanding mechanisms that lead from genetic variation to pathophysiology remains an important challenge. Methods are needed to systematically bridge this crucial gap to facilitate experimental testing of hypotheses and translation to clinical utility. RESULTS: Here, we leveraged cross-phenotype associations to identify traits with shared genetic architecture, using linkage disequilibrium (LD) information to accurately capture shared SNPs by proxy, and calculate significance of enrichment. This shared genetic architecture was examined across differing biological scales through incorporating data from catalogs of clinical, cellular, and molecular GWAS. We have created an interactive web database (interactive Cross-Phenotype Analysis of GWAS database (iCPAGdb)) to facilitate exploration and allow rapid analysis of user-uploaded GWAS summary statistics. This database revealed well-known relationships among phenotypes, as well as the generation of novel hypotheses to explain the pathophysiology of common diseases. Application of iCPAGdb to a recent GWAS of severe COVID-19 demonstrated unexpected overlap of GWAS signals between COVID-19 and human diseases, including with idiopathic pulmonary fibrosis driven by the DPP9 locus. Transcriptomics from peripheral blood of COVID-19 patients demonstrated that DPP9 was induced in SARS-CoV-2 compared to healthy controls or those with bacterial infection. Further investigation of cross-phenotype SNPs associated with both severe COVID-19 and other human traits demonstrated colocalization of the GWAS signal at the ABO locus with plasma protein levels of a reported receptor of SARS-CoV-2, CD209 (DC-SIGN). This finding points to a possible mechanism whereby glycosylation of CD209 by ABO may regulate COVID-19 disease severity. CONCLUSIONS: Thus, connecting genetically related traits across phenotypic scales links human diseases to molecular and cellular measurements that can reveal mechanisms and lead to novel biomarkers and therapeutic approaches. The iCPAGdb web portal is accessible at http://cpag.oit.duke.edu and the software code at https://github.com/tbalmat/iCPAGdb .

An atlas connecting shared genetic architecture of human diseases and molecular phenotypes provides insight into COVID-19 susceptibility.

While genome-wide associations studies (GWAS) have successfully elucidated the genetic architecture of complex human traits and diseases, understanding mechanisms that lead from genetic variation to pathophysiology remains an important challenge. Methods are needed to systematically bridge this crucial gap to facilitate experimental testing of hypotheses and translation to clinical utility. Here, we leveraged cross-phenotype associations to identify traits with shared genetic architecture, using linkage disequilibrium (LD) information to accurately capture shared SNPs by proxy, and calculate significance of enrichment. This shared genetic architecture was examined across differing biological scales through incorporating data from catalogs of clinical, cellular, and molecular GWAS. We have created an interactive web database (interactive Cross-Phenotype Analysis of GWAS database (iCPAGdb); http://cpag.oit.duke.edu) to facilitate exploration and allow rapid analysis of user-uploaded GWAS summary statistics. This database revealed well-known relationships among phenotypes, as well as the generation of novel hypotheses to explain the pathophysiology of common diseases. Application of iCPAGdb to a recent GWAS of severe COVID-19 demonstrated unexpected overlap of GWAS signals between COVID-19 and human diseases, including with idiopathic pulmonary fibrosis driven by the DPP9 locus. Transcriptomics from peripheral blood of COVID-19 patients demonstrated that DPP9 was induced in SARS-CoV-2 compared to healthy controls or those with bacterial infection. Further investigation of cross-phenotype SNPs with severe COVID-19 demonstrated colocalization of the GWAS signal of the ABO locus with plasma protein levels of a reported receptor of SARS-CoV-2, CD209 (DC-SIGN), pointing to a possible mechanism whereby glycosylation of CD209 by ABO may regulate COVID-19 disease severity. Thus, connecting genetically related traits across phenotypic scales links human diseases to molecular and cellular measurements that can reveal mechanisms and lead to novel biomarkers and therapeutic approaches.

An Atlas of Genetic Variation Linking Pathogen-Induced Cellular Traits to Human Disease.

Pathogens have been a strong driving force for natural selection. Therefore, understanding how human genetic differences impact infection-related cellular traits can mechanistically link genetic variation to disease susceptibility. Here we report the Hi-HOST Phenome Project (H2P2): a catalog of cellular genome-wide association studies (GWAS) comprising 79 infection-related phenotypes in response to 8 pathogens in 528 lymphoblastoid cell lines. Seventeen loci surpass genome-wide significance for infection-associated phenotypes ranging from pathogen replication to cytokine production. We combined H2P2 with clinical association data from patients to identify a SNP near CXCL10 as a risk factor for inflammatory bowel disease. A SNP in the transcriptional repressor ZBTB20 demonstrated pleiotropy, likely through suppression of multiple target genes, and was associated with viral hepatitis. These data are available on a web portal to facilitate interpreting human genome variation through the lens of cell biology and should serve as a rich resource for the research community.

Design and application of a data-independent precursor and product ion repository.

The functional design and application of a data-independent LC-MS precursor and product ion repository for protein identification, quantification, and validation is conceptually described. The ion repository was constructed from the sequence search results of a broad range of discovery experiments investigating various tissue types of two closely related mammalian species. The relative high degree of similarity in protein complement, ion detection, and peptide and protein identification allows for the analysis of normalized precursor and product ion intensity values, as well as standardized retention times, creating a multidimensional/orthogonal queryable, qualitative, and quantitative space. Peptide ion map selection for identification and quantification is primarily based on replication and limited variation. The information is stored in a relational database and is used to create peptide- and protein-specific fragment ion maps that can be queried in a targeted fashion against the raw or time aligned ion detections. These queries can be conducted either individually or as groups, where the latter affords pathway and molecular machinery analysis of the protein complement. The presented results also suggest that peptide ionization and fragmentation efficiencies are highly conserved between experiments and practically independent of the analyzed biological sample when using similar instrumentation. Moreover, the data illustrate only minor variation in ionization efficiency with amino acid sequence substitutions occurring between species. Finally, the data and the presented results illustrate how LC-MS performance metrics can be extracted and utilized to ensure optimal performance of the employed analytical workflows.

Imaging diffractometer with holographic encoding enhancements for laser sensing and characterization.

What is believed to be a novel holographic optical encoding scheme has been developed to enhance the performance of laser sensors designed for the measurement of wavelength and angular trajectory. A prototype holographic imaging diffractometer has been created to reconstruct holographic cueing patterns superimposed in the focal plane of wide-angle scene imagery. Based on experimental pattern metric measurements at the focal plane, a theoretical model is used to compute the laser source wavelength and its apparent propagation direction within the sensor's field of view. The benefits of incorporating holographic enhancements within an imager-based sensor architecture are discussed.

Dose delivery characteristics of the AIR pulmonary delivery system over a range of inspiratory flow rates.

The purpose of this study was to evaluate the in vitro and in vivo dose delivery characteristics of the AIR pulmonary delivery system over a range of flow rates. A 5-mg placebo powder of engineered particles with low densities (<0.4 g/cc) and large geometric diameters (>5 microm) was delivered via a simple, capsule based, passive dry powder inhaler. The emitted dose, geometric and aerodynamic particle size distributions (aPSDs) were obtained over a range of flow rates (15-60 LPM). The in vitro results demonstrated improved powder dispersion with increasing flow rate through the inhaler. The in vivo dose delivery characteristics were obtained by gamma scintigraphy. Twelve healthy subjects performed the following three inhalation maneuvers: (i) a targeted peak inspiratory flow rate (PIFR) of 20 +/- 10 LPM, (ii) a deep comfortable inhalation, and (iii) a deep forced inhalation. PIFR and inhaled volume were obtained during the inhalation of the dose using a spirometer. In vivo dose delivery was characterized by high and reproducible emitted doses (mean = 87%; inter and intra-subject CV = 5%) and high lung deposition (mean = 51% of the total dose), with low inter and intra-subject CVs (18% and 13%, respectively) across a range of PIFRs (12-86 LPM). Lung deposition of the total dose was shown not to be dependent on PIFR by analysis of variance across the range of inspiratory flow rates (p = 0.29). This was due to the competing effects of smaller aPSDs, increased extrathoracic deposition and higher emitted doses with increasing PIFR. Fully characterizing the effect of inspiratory flow rate requires analysis of the therapeutic response, as well as in vitro dose delivery and lung deposition.

DIG--a system for gene annotation and functional discovery.

SUMMARY: We describe a database and information discovery system named DIG (Duke Integrated Genomics) designed to facilitate the process of gene annotation and the discovery of functional context. The DIG system collects and organizes gene annotation and functional information, and includes tools that support an understanding of genes in a functional context by providing a framework for integrating and visualizing gene expression, protein interaction and literature-based interaction networks.

In vitro and in vivo dose delivery characteristics of large porous particles for inhalation.

The purpose of this study was to evaluate the in vitro and in vivo dose delivery characteristics of two large porous particle placebo formulations with different mass median aerodynamic diameters (MMAD approximately equal to 3 and 5 microm). In vitro dose delivery characteristics were measured using the multistage liquid impinger (MSLI). In vitro lung deposition was predicted by calculating the extrathoracic deposition using the ICRP model, with the remaining fraction assumed to deposit in the lungs. Healthy subjects were trained to inhale through the AIR delivery system at a target peak inspiratory flow rate (PIFR) of 60 l/min, The in vivo dose delivery of large porous particles were obtained by gamma-scintigraphy and was characterized by high ( approximately 90%), reproducible emitted doses for both the small and large MMAD powders. The mean in vivo lung deposition relative to the total metered dose were 59.0 and 37.3% for 3 and 5 microm MMAD powders, respectively. The AIR delivery system produced high in vivo lung deposition and low intersubject CVs (approximately 14%) across the range of PIFRs obtained in the study (50-80 l/min), This is relative to a variety of dry powder inhalers (DPI) that have been published in the literature, with in vivo lung deposition ranging from 13 to 35% with intersubject CVs ranging from 17 to 50%. The ICRP model provided a good estimate of the mean in vivo lung deposition for both powders. Intersubject variability was not captured by the ICRP model due to intersubject differences in the morphology and physiology of the oropharyngeal region. The ICRP model was used to predict the regional lung deposition, although these predictions were only considered speculative in the absence of experimental validation.