Preclinical safety and biodistribution of CRISPR targeting SIV in non-human primates.

In this study, we demonstrate the safety and utility of CRISPR-Cas9 gene editing technology for in vivo editing of proviral DNA in ART-treated, virally controlled simian immunodeficiency virus (SIV) infected rhesus macaques, an established model for HIV infection. EBT-001 is an AAV9-based vector delivering SaCas9 and dual guide RNAs designed to target multiple regions of the SIV genome: the viral LTRs, and the Gag gene. The results presented here demonstrate that a single IV inoculation of EBT-001 at each of 3 dose levels (1.4 × 1012, 1.4 × 1013 and 1.4 × 1014 genome copies/kg) resulted in broad and functional biodistribution of AAV9-EBT-001 to known tissue reservoirs of SIV. No off-target effects or abnormal pathology were observed, and animals returned to their normal body weight after receiving EBT-001. Importantly, the macaques that received the 2 highest doses of EBT-001 showed improved absolute lymphocyte counts as compared to antiretroviral-treated controls. Taken together, these results demonstrate safety, biodistribution, and in vivo proviral DNA editing following IV administration of EBT-001, supporting the further development of CRISPR-based gene editing as a potential therapeutic approach for HIV in humans.

Proceedings from the Society of Interventional Radiology Foundation Research Consensus Panel on Artificial Intelligence in Interventional Radiology: From Code to Bedside.

Artificial intelligence (AI)-based technologies are the most rapidly growing field of innovation in healthcare with the promise to achieve substantial improvements in delivery of patient care across all disciplines of medicine. Recent advances in imaging technology along with marked expansion of readily available advanced health information, data offer a unique opportunity for interventional radiology (IR) to reinvent itself as a data-driven specialty. Additionally, the growth of AI-based applications in diagnostic imaging is expected to have downstream effects on all image-guidance modalities. Therefore, the Society of Interventional Radiology Foundation has called upon 13 key opinion leaders in the field of IR to develop research priorities for clinical applications of AI in IR. The objectives of the assembled research consensus panel were to assess the availability and understand the applicability of AI for IR, estimate current needs and clinical use cases, and assemble a list of research priorities for the development of AI in IR. Individual panel members proposed and all participants voted upon consensus statements to rank them according to their overall impact for IR. The results identified the top priorities for the IR research community and provide organizing principles for innovative academic-industrial research collaborations that will leverage both clinical expertise and cutting-edge technology to benefit patient care in IR.

Enabling precision medicine via standard communication of HTS provenance, analysis, and results.

A personalized approach based on a patient's or pathogen's unique genomic sequence is the foundation of precision medicine. Genomic findings must be robust and reproducible, and experimental data capture should adhere to findable, accessible, interoperable, and reusable (FAIR) guiding principles. Moreover, effective precision medicine requires standardized reporting that extends beyond wet-lab procedures to computational methods. The BioCompute framework (https://w3id.org/biocompute/1.3.0) enables standardized reporting of genomic sequence data provenance, including provenance domain, usability domain, execution domain, verification kit, and error domain. This framework facilitates communication and promotes interoperability. Bioinformatics computation instances that employ the BioCompute framework are easily relayed, repeated if needed, and compared by scientists, regulators, test developers, and clinicians. Easing the burden of performing the aforementioned tasks greatly extends the range of practical application. Large clinical trials, precision medicine, and regulatory submissions require a set of agreed upon standards that ensures efficient communication and documentation of genomic analyses. The BioCompute paradigm and the resulting BioCompute Objects (BCOs) offer that standard and are freely accessible as a GitHub organization (https://github.com/biocompute-objects) following the "Open-Stand.org principles for collaborative open standards development." With high-throughput sequencing (HTS) studies communicated using a BCO, regulatory agencies (e.g., Food and Drug Administration [FDA]), diagnostic test developers, researchers, and clinicians can expand collaboration to drive innovation in precision medicine, potentially decreasing the time and cost associated with next-generation sequencing workflow exchange, reporting, and regulatory reviews.

Evolution of echovirus 11 in a chronically infected immunodeficient patient.

Deep sequencing was used to determine complete nucleotide sequences of echovirus 11 (EV11) strains isolated from a chronically infected patient with CVID as well as from cases of acute enterovirus infection. Phylogenetic analysis showed that EV11 strains that circulated in Israel in 1980-90s could be divided into four clades. EV11 strains isolated from a chronically infected individual belonged to one of the four clades and over a period of 4 years accumulated mutations at a relatively constant rate. Extrapolation of mutations accumulation curve into the past suggested that the individual was infected with circulating EV11 in the first half of 1990s. Genomic regions coding for individual viral proteins did not appear to be under strong selective pressure except for protease 3C that was remarkably conserved. This may suggest its important role in maintaining persistent infection.

Novel reference genes in colorectal cancer identify a distinct subset of high stage tumors and their associated histologically normal colonic tissues.

BACKGROUND: Reference genes are often interchangeably called housekeeping genes due to 1) the essential cellular functions their proteins provide and 2) their constitutive expression across a range of normal and pathophysiological conditions. However, given the proliferative drive of malignant cells, many reference genes such as beta-actin (ACTB) and glyceraldehyde-3-phosphate-dehydrogenase (GAPDH) which play critical roles in cell membrane organization and glycolysis, may be dysregulated in tumors versus their corresponding normal controls METHODS: Because Next Generation Sequencing (NGS) technology has several advantages over hybridization-based technologies, such as independent detection and quantitation of transcription levels, greater sensitivity, and increased dynamic range, we evaluated colorectal cancers (CRC) and their histologically normal tissue counterparts by NGS to evaluate the expression of 21 "classical" reference genes used as normalization standards for PCR based methods. Seventy-nine paired tissue samples of CRC and their patient matched healthy colonic tissues were subjected to NGS analysis of their mRNAs. RESULTS: We affirmed that 17 out of 21 classical reference genes had upregulated expression in tumors compared to normal colonic epithelial tissue and dramatically so in some cases. Indeed, tumors were distinguished from normal controls in both unsupervised hierarchical clustering analyses (HCA) and principal component analyses (PCA). We then identified 42 novel potential reference genes with minimal coefficients of variation (CV) across 79 CRC tumor pairs. Though largely consistently expressed across tumors and normal control tissues, a subset of high stage tumors (HSTs) as well as some normal tissue samples (HSNs) located adjacent to these HSTs demonstrated dysregulated expression, thus identifying a subset of tumors with a potentially distinct and aggressive biological profile. CONCLUSION: While classical CRC reference genes were found to be differentially expressed between tumors and normal controls, novel reference genes, identified via NGS, were more consistently expressed across malignant and normal colonic tissues. Nonetheless, a subset of HST had profound dysregulation of such genes as did many of the histologically normal tissues adjacent to such HSTs, indicating that the HSTs so distinguished may have unique biological properties and that their histologically normal tissues likely harbor a small population of microscopically undetected but metabolically active tumors.

Separation and assembly of deep sequencing data into discrete sub-population genomes.

Sequence heterogeneity is a common characteristic of RNA viruses that is often referred to as sub-populations or quasispecies. Traditional techniques used for assembly of short sequence reads produced by deep sequencing, such as de-novo assemblers, ignore the underlying diversity. Here, we introduce a novel algorithm that simultaneously assembles discrete sequences of multiple genomes present in populations. Using in silico data we were able to detect populations at as low as 0.1% frequency with complete global genome reconstruction and in a single sample detected 16 resolved sequences with no mismatches. We also applied the algorithm to high throughput sequencing data obtained for viruses present in sewage samples and successfully detected multiple sub-populations and recombination events in these diverse mixtures. High sensitivity of the algorithm also enables genomic analysis of heterogeneous pathogen genomes from patient samples and accurate detection of intra-host diversity, enabling not just basic research in personalized medicine but also accurate diagnostics and monitoring drug therapies, which are critical in clinical and regulatory decision-making process.

HIVE-heptagon: A sensible variant-calling algorithm with post-alignment quality controls.

Advances in high-throughput sequencing (HTS) technologies have greatly increased the availability of genomic data and potential discovery of clinically significant genomic variants. However, numerous issues still exist with the analysis of these data, including data complexity, the absence of formally agreed upon best practices, and inconsistent reproducibility. Toward a more robust and reproducible variant-calling paradigm, we propose a series of selective noise filtrations and post-alignment quality control (QC) techniques that may reduce the rate of false variant calls. We have implemented both novel and refined post-alignment QC mechanisms to augment existing pre-alignment QC measures. These techniques can be used independently or in combination to identify and correct issues caused during data generation or early analysis stages. The adoption of these procedures by the broader scientific community is expected to improve the identification of clinically significant variants both in terms of computational efficiency and in the confidence of the results. AVAILABILITY: https://hive.biochemistry.gwu.edu/.

A new and updated resource for codon usage tables.

BACKGROUND: Due to the degeneracy of the genetic code, most amino acids can be encoded by multiple synonymous codons. Synonymous codons naturally occur with different frequencies in different organisms. The choice of codons may affect protein expression, structure, and function. Recombinant gene technologies commonly take advantage of the former effect by implementing a technique termed codon optimization, in which codons are replaced with synonymous ones in order to increase protein expression. This technique relies on the accurate knowledge of codon usage frequencies. Accurately quantifying codon usage bias for different organisms is useful not only for codon optimization, but also for evolutionary and translation studies: phylogenetic relations of organisms, and host-pathogen co-evolution relationships, may be explored through their codon usage similarities. Furthermore, codon usage has been shown to affect protein structure and function through interfering with translation kinetics, and cotranslational protein folding. RESULTS: Despite the obvious need for accurate codon usage tables, currently available resources are either limited in scope, encompassing only organisms from specific domains of life, or greatly outdated. Taking advantage of the exponential growth of GenBank and the creation of NCBI's RefSeq database, we have developed a new database, the High-performance Integrated Virtual Environment-Codon Usage Tables (HIVE-CUTs), to present and analyse codon usage tables for every organism with publicly available sequencing data. Compared to existing databases, this new database is more comprehensive, addresses concerns that limited the accuracy of earlier databases, and provides several new functionalities, such as the ability to view and compare codon usage between individual organisms and across taxonomical clades, through graphical representation or through commonly used indices. In addition, it is being routinely updated to keep up with the continuous flow of new data in GenBank and RefSeq. CONCLUSION: Given the impact of codon usage bias on recombinant gene technologies, this database will facilitate effective development and review of recombinant drug products and will be instrumental in a wide area of biological research. The database is available at hive.biochemistry.gwu.edu/review/codon .

Human germline and pan-cancer variomes and their distinct functional profiles.

Identification of non-synonymous single nucleotide variations (nsSNVs) has exponentially increased due to advances in Next-Generation Sequencing technologies. The functional impacts of these variations have been difficult to ascertain because the corresponding knowledge about sequence functional sites is quite fragmented. It is clear that mapping of variations to sequence functional features can help us better understand the pathophysiological role of variations. In this study, we investigated the effect of nsSNVs on more than 17 common types of post-translational modification (PTM) sites, active sites and binding sites. Out of 1 705 285 distinct nsSNVs on 259 216 functional sites we identified 38 549 variations that significantly affect 10 major functional sites. Furthermore, we found distinct patterns of site disruptions due to germline and somatic nsSNVs. Pan-cancer analysis across 12 different cancer types led to the identification of 51 genes with 106 nsSNV affected functional sites found in 3 or more cancer types. 13 of the 51 genes overlap with previously identified Significantly Mutated Genes (Nature. 2013 Oct 17;502(7471)). 62 mutations in these 13 genes affecting functional sites such as DNA, ATP binding and various PTM sites occur across several cancers and can be prioritized for additional validation and investigations.

Generation and propagation of recombinant mumps viruses exhibiting an additional U residue in the homopolymeric U tract of the F gene-end signal.

As a member of the family paramyxoviridae, subfamily paramyxovirinae, the genome of mumps virus (MuV) is postulated to be polyhexameric in length in order to be able to replicate efficiently. While all natural MuV strains sequenced so far obey to this "rule of six," we describe here the isolation of recombinant MuVs that appeared to contain an additional U residue in the homopolymeric tract of the F gene-end signal, resulting in a genome length of 6n + 1. Sequencing of several plaque-purified viruses from these preparations did not reveal the existence of length-correcting mutations, suggesting that they are violators of the rule of six. Employing high-throughput sequencing technology, we provide evidence that the insertion of an additional U residue is mainly the result of the rescue system used that relies on T7 RNA polymerase. Limited in vitro and in vivo testing of the viruses did not reveal any significant impact of the longer genome on virus replication or virulence, suggesting that the rule of six is not a strict requirement for MuV replication.

Whole genome single-nucleotide variation profile-based phylogenetic tree building methods for analysis of viral, bacterial and human genomes.

UNLABELLED: Next-generation sequencing data can be mapped to a reference genome to identify single-nucleotide polymorphisms/variations (SNPs/SNVs; called SNPs hereafter). In theory, SNPs can be compared across several samples and the differences can be used to create phylogenetic trees depicting relatedness among the samples. However, in practice this is difficult because currently there is no stand-alone tool that takes SNP data directly as input and produces phylogenetic trees. In response to this need, PhyloSNP application was created with two analysis methods 1) a quantitative method that creates the presence/absence matrix which can be directly used to generate phylogenetic trees or creates a tree from a shrunk genome alignment (includes additional bases surrounding the SNP position) and 2) a qualitative method that clusters samples based on the frequency of different bases found at a particular position. The algorithms were used to generate trees from Poliovirus, Burkholderia and human cancer genomics NGS datasets. AVAILABILITY: PhyloSNP is freely available for download at http://hive.biochemistry.gwu.edu/dna.cgi?cmd=phylosnp.

Non-synonymous variations in cancer and their effects on the human proteome: workflow for NGS data biocuration and proteome-wide analysis of TCGA data.

BACKGROUND: Next-generation sequencing (NGS) technologies have resulted in petabytes of scattered data, decentralized in archives, databases and sometimes in isolated hard-disks which are inaccessible for browsing and analysis. It is expected that curated secondary databases will help organize some of this Big Data thereby allowing users better navigate, search and compute on it. RESULTS: To address the above challenge, we have implemented a NGS biocuration workflow and are analyzing short read sequences and associated metadata from cancer patients to better understand the human variome. Curation of variation and other related information from control (normal tissue) and case (tumor) samples will provide comprehensive background information that can be used in genomic medicine research and application studies. Our approach includes a CloudBioLinux Virtual Machine which is used upstream of an integrated High-performance Integrated Virtual Environment (HIVE) that encapsulates Curated Short Read archive (CSR) and a proteome-wide variation effect analysis tool (SNVDis). As a proof-of-concept, we have curated and analyzed control and case breast cancer datasets from the NCI cancer genomics program - The Cancer Genome Atlas (TCGA). Our efforts include reviewing and recording in CSR available clinical information on patients, mapping of the reads to the reference followed by identification of non-synonymous Single Nucleotide Variations (nsSNVs) and integrating the data with tools that allow analysis of effect nsSNVs on the human proteome. Furthermore, we have also developed a novel phylogenetic analysis algorithm that uses SNV positions and can be used to classify the patient population. The workflow described here lays the foundation for analysis of short read sequence data to identify rare and novel SNVs that are not present in dbSNP and therefore provides a more comprehensive understanding of the human variome. Variation results for single genes as well as the entire study are available from the CSR website (http://hive.biochemistry.gwu.edu/dna.cgi?cmd=csr). CONCLUSIONS: Availability of thousands of sequenced samples from patients provides a rich repository of sequence information that can be utilized to identify individual level SNVs and their effect on the human proteome beyond what the dbSNP database provides.

Census-based rapid and accurate metagenome taxonomic profiling.

BACKGROUND: Understanding the taxonomic composition of a sample, whether from patient, food or environment, is important to several types of studies including pathogen diagnostics, epidemiological studies, biodiversity analysis and food quality regulation. With the decreasing costs of sequencing, metagenomic data is quickly becoming the preferred typed of data for such analysis. RESULTS: Rapidly defining the taxonomic composition (both taxonomic profile and relative frequency) in a metagenomic sequence dataset is challenging because the task of mapping millions of sequence reads from a metagenomic study to a non-redundant nucleotide database such as the NCBI non-redundant nucleotide database (nt) is a computationally intensive task. We have developed a robust subsampling-based algorithm implemented in a tool called CensuScope meant to take a 'sneak peak' into the population distribution and estimate taxonomic composition as if a census was taken of the metagenomic landscape. CensuScope is a rapid and accurate metagenome taxonomic profiling tool that randomly extracts a small number of reads (based on user input) and maps them to NCBI's nt database. This process is repeated multiple times to ascertain the taxonomic composition that is found in majority of the iterations, thereby providing a robust estimate of the population and measures of the accuracy for the results. CONCLUSION: CensuScope can be run on a laptop or on a high-performance computer. Based on our analysis we are able to provide some recommendations in terms of the number of sequence reads to analyze and the number of iterations to use. For example, to quantify taxonomic groups present in the sample at a level of 1% or higher a subsampling size of 250 random reads with 50 iterations yields a statistical power of >99%. Windows and UNIX versions of CensuScope are available for download at https://hive.biochemistry.gwu.edu/dna.cgi?cmd=censuscope. CensuScope is also available through the High-performance Integrated Virtual Environment (HIVE) and can be used in conjunction with other HIVE analysis and visualization tools.

Building the foundation for a modern patient-partnered infrastructure to study temporomandibular disorders.

Background: Conflicting reports from varying stakeholders related to prognosis and outcomes following placement of temporomandibular joint (TMJ) implants gave rise to the development of the TMJ Patient-Led RoundTable initiative. Following an assessment of the current availability of data, the RoundTable concluded that a strategically Coordinated Registry Network (CRN) is needed to collect and generate accessible data on temporomandibular disorder (TMD) and its care. The aim of this study was therefore to advance the clinical understanding, usage, and adoption of a core minimum dataset for TMD patients as the first foundational step toward building the CRN. Methods: Candidate data elements were extracted from existing data sources and included in a Delphi survey administered to 92 participants. Data elements receiving less than 75% consensus were dropped. A purposive multi-stakeholder sub-group triangulated the items across patient and clinician-based experience to remove redundancies or duplicate items and reduce the response burden for both patients and clinicians. To reliably collect the identified data elements, the identified core minimum data elements were defined in the context of technical implementation within High-performance Integrated Virtual Environment (HIVE) web-application framework. HIVE was integrated with CHIOS™, an innovative permissioned blockchain platform, to strengthen the provenance of data captured in the registry and drive metadata to record all registry transaction and create a robust consent network. Results: A total of 59 multi-stakeholder participants responded to the Delphi survey. The completion of the Delphi surveys followed by the application of the required group consensus threshold resulted in the selection of 397 data elements (254 for patient-generated data elements and 143 for clinician generated data elements). The infrastructure development and integration of HIVE and CHIOS™ was completed showing the maintenance of all data transaction information in blockchain, flexible recording of patient consent, data cataloging, and consent validation through smart contracts. Conclusion: The identified data elements and development of the technological platform establishes a data infrastructure that facilitates the standardization and harmonization of data as well as perform high performance analytics needed to fully leverage the captured patient-generated data, clinical evidence, and other healthcare ecosystem data within the TMJ/TMD-CRN.

RNA polymerase beta subunit (rpoB) gene and the 16S-23S rRNA intergenic transcribed spacer region (ITS) as complementary molecular markers in addition to the 16S rRNA gene for phylogenetic analysis and identification of the species of the family Mycoplasmataceae.

Conventional classification of the species in the family Mycoplasmataceae is mainly based on phenotypic criteria, which are complicated, can be difficult to measure, and have the potential to be hampered by phenotypic deviations among the isolates. The number of biochemical reactions suitable for phenotypic characterization of the Mycoplasmataceae is also very limited and therefore the strategy for the final identification of the Mycoplasmataceae species is based on comparative serological results. However, serological testing of the Mycoplasmataceae species requires a performance panel of hyperimmune sera which contains anti-serum to each known species of the family, a high level of technical expertise, and can only be properly performed by mycoplasma-reference laboratories. In addition, the existence of uncultivated and fastidious Mycoplasmataceae species/isolates in clinical materials significantly complicates, or even makes impossible, the application of conventional bacteriological tests. The analysis of available genetic markers is an additional approach for the primary identification and phylogenetic classification of cultivable species and uncultivable or fastidious organisms in standard microbiological laboratories. The partial nucleotide sequences of the RNA polymerase ß-subunit gene (rpoB) and the 16S-23S rRNA intergenic transcribed spacer (ITS) were determined for all known type strains and the available non-type strains of the Mycoplasmataceae species. In addition to the available 16S rRNA gene data, the ITS and rpoB sequences were used to infer phylogenetic relationships among these species and to enable identification of the Mycoplasmataceae isolates to the species level. The comparison of the ITS and rpoB phylogenetic trees with the 16S rRNA reference phylogenetic tree revealed a similar clustering patterns for the Mycoplasmataceae species, with minor discrepancies for a few species that demonstrated higher divergence of their ITS and rpoB in comparison to their neighbor species. Overall, our results demonstrated that the ITS and rpoB gene could be useful complementary phylogenetic markers to infer phylogenetic relationships among the Mycoplasmataceae species and provide useful background information for the choice of appropriate metabolic and serological tests for the final classification of isolates. In summary, three-target sequence analysis, which includes the ITS, rpoB, and 16S rRNA genes, was demonstrated to be a reliable and useful taxonomic tool for the species differentiation within the family Mycoplasmataceae based on their phylogenetic relatedness and pairwise sequence similarities. We believe that this approach might also become a valuable tool for routine analysis and primary identification of new isolates in medical and veterinary microbiological laboratories.

Where Is Research in the Era of Electronic Health Records?

IntroductionData extraction from electronic health records (EHRs) for use in clinical research continues to be labor-intensive and to offer little benefit over traditional paper chart reviews. This is largely due to poor integration of EHR systems with hospital process flow, which still relies heavily on traditional paperwork as a means of documentation. DiscussionNew methods in data collection through mobile applications have streamlined data entry through better data standardization and improved overall data quality. However, mobile applications address only a portion of the problem. Data entry errors and legacy integration will continue to be an issue when there are changes between practitioners with different EHR systems. The combination of a mobile application with the cloud platform has been applied in multiple specialties to monitor recovery and patient-reported outcomes. ConclusionMobile applications along with a virtual cloud environment to host data provide a reasonable solution for consolidating patient data and can accelerate population research.

Development and Usability Testing of a Mobile Application to Monitor Patient-Reported Outcomes after Stress Urinary Incontinence Surgery.

OBJECTIVE: To develop and perform a usability testing of a mobile application (app) with representative users of surgeons and female patients undergoing stress urinary incontinence (SUI) surgery. METHODS: A mobile app was developed with the Medical Device Epidemiology Network (MDEpiNet) High-Performance Integrated Virtual Environment (HIVE) to streamline the collection of patient-reported outcomes following SUI surgery using validated questionnaires. It was designed as a collaborative effort with the Women's Health Initiative (WHI), including patient and surgeon involvement. The app evaluation questions addressed the user's rating on the clarity and length of the questions and the comfort level in using the interface for patients to report post-operative outcomes and surgeons to review them. RESULTS: A total of twenty patients and 5 surgeons tested the mobile app and reported their experience and level of satisfaction. The average patient experience score was 9 out of ten, with ten being the best. Eleven patients (55%) were interested in replacing in-person follow-up visits with the app. The surgeons reported an average user experience score of 8.6 out of ten. Four surgeons (80%) were interested in replacing in-person visits with the app. The combined experience score between all users was 8.9 out of ten. Fifteen out of twenty-five users (60%) showed interest in replacing in-person visits with the app. CONCLUSION: The mobile app for SUI captured important patient-reported outcomes with a high satisfaction reporting from patients and surgeons.

Can a brief training intervention on schizophrenia and depression improve knowledge, attitudes and practices of primary healthcare workers? The experience in Armenia.

BACKGROUND: Although the World Health Organization has called for mental health services to be integrated into primary care, mental health remains in most countries, and especially in low- and middle-income countries, one of the most neglected topics in the training curriculum of frontline health workers. As a result, primary healthcare professionals leave medical and nursing schools with insufficient knowledge, and often with negative attitudes towards mental disorders. AIM: We investigated the effect of a brief training intervention on schizophrenia and depression conducted among general practitioners and nurses in Armenia. METHODS: Training interventions were one-day, face-to-face, interactive workshops, including didactic presentations and discussions of case studies. We used a quasi-experimental design of the before/after type, to compare data on knowledge, attitudes and practices collected before and after the training sessions. RESULTS: Mean scores for knowledge, attitudes and practices increased significantly (p < 0.001) among both nurses and GPs for both schizophrenia (111 GPs and 167 nurses) and depression (459 GPs and 197 nurses). CONCLUSIONS: Our experience suggests that a brief training intervention can result in significant improvements in knowledge, attitudes and practices among primary healthcare workers and could help improve mental health services.

Development of an Integrated Platform Using Multidisciplinary Real-World Data to Facilitate Biomarker Discovery for Medical Products.

Translational multidisciplinary research is important for the Center for Devices and Radiological Health's efforts for utilizing real-world data (RWD) to enhance predictive evaluation of medical device performance in patient subpopulations. As part of our efforts for developing new RWD-based evidentiary approaches, including in silico discovery of device-related risk predictors and biomarkers, this study aims to characterize the sex/race-related trends in hip replacement outcomes and identify corresponding candidate single nucleotide polymorphisms (SNPs). Adverse outcomes were assessed by deriving RWD from a retrospective analysis of hip replacement hospital discharge data from the National Inpatient Sample (NIS). Candidate SNPs were explored using pre-existing data from the Personalized Medicine Research Project (PMRP). High-Performance Integrated Virtual Environment was used for analyzing and visualizing putative associations between SNPs and adverse outcomes. Ingenuity Pathway Analysis (IPA) was used for exploring plausibility of the sex-related candidate SNPs and characterizing gene networks associated with the variants of interest. The NIS-based epidemiologic evidence showed that periprosthetic osteolysis (PO) was most prevalent among white men. The PMRP-based genetic evidence associated the PO-related male predominance with rs7121 (odds ratio = 4.89; 95% confidence interval = 1.41-17.05) and other candidate SNPs. SNP-based IPA analysis of the expected gene expression alterations and corresponding signaling pathways suggested possible role of sex-related metabolic factors in development of PO, which was substantiated by ad hoc epidemiologic analysis identifying the sex-related differences in metabolic comorbidities in men vs. women with hip replacement-related PO. Thus, our in silico study illustrates RWD-based evidentiary approaches that may facilitate cost/time-efficient discovery of biomarkers for informing use of medical products.