Returning integrated genomic risk and clinical recommendations: The eMERGE study.

PURPOSE: Assessing the risk of common, complex diseases requires consideration of clinical risk factors as well as monogenic and polygenic risks, which in turn may be reflected in family history. Returning risks to individuals and providers may influence preventive care or use of prophylactic therapies for those individuals at high genetic risk. METHODS: To enable integrated genetic risk assessment, the eMERGE (electronic MEdical Records and GEnomics) network is enrolling 25,000 diverse individuals in a prospective cohort study across 10 sites. The network developed methods to return cross-ancestry polygenic risk scores, monogenic risks, family history, and clinical risk assessments via a genome-informed risk assessment (GIRA) report and will assess uptake of care recommendations after return of results. RESULTS: GIRAs include summary care recommendations for 11 conditions, education pages, and clinical laboratory reports. The return of high-risk GIRA to individuals and providers includes guidelines for care and lifestyle recommendations. Assembling the GIRA required infrastructure and workflows for ingesting and presenting content from multiple sources. Recruitment began in February 2022. CONCLUSION: Return of a novel report for communicating monogenic, polygenic, and family history-based risk factors will inform the benefits of integrated genetic risk assessment for routine health care.

Beyond the override: Using evidence of previous drug tolerance to suppress drug allergy alerts; a retrospective study of opioid alerts.

OBJECTIVE: Despite the extensive literature exploring alert fatigue, most studies have focused on describing the phenomenon, but not on fixing it. The authors aimed to identify data useful to avert clinically irrelevant alerts to inform future research on clinical decision support (CDS) design. METHODS: We conducted a retrospective observational study of opioid drug allergy alert (DAA) overrides for the calendar year of 2019 at a large academic medical center, to identify data elements useful to find irrelevant alerts to be averted. RESULTS: Overall, 227,815 DAAs were fired in 2019, with an override rate of 91 % (n = 208196). Opioids represented nearly two-thirds of these overrides (n = 129063; 62 %) and were the drug class with the highest override rate (96 %). On average, 29 opioid DAAs were overridden per patient. While most opioid alerts (97.1 %) are fired for a possible match (the drug class of the allergen matches the drug class of the prescribed drug), they are overridden significantly less frequently for definite match (exact match between allergen and prescribed drug) (88 % vs. 95.9 %, p < 0.001). When comparing the triggering drug with previously administered drugs, override rates were equally high for both definite match (95.9 %), no match (95.5 %), and possible match (95.1 %). Likewise, when comparing to home medications, overrides were excessively high for possible match (96.3 %), no match (96 %), and definite match (94.4 %). CONCLUSION: We estimate that 74.5% of opioid DAAs (46.4% of all DAAs) at our institution could be relatively safely averted, since they either have a definite match for previous inpatient administrations suggesting drug tolerance or are fired as possible match with low risk of cross-sensitivity. Future research should focus on identifying other relevant data elements ideally with automated methods and use of emerging standards to empower CDS systems to suppress false-positive alerts while avoiding safety hazards.

PAGER-CoV: a comprehensive collection of pathways, annotated gene-lists and gene signatures for coronavirus disease studies.

PAGER-CoV (http://discovery.informatics.uab.edu/PAGER-CoV/) is a new web-based database that can help biomedical researchers interpret coronavirus-related functional genomic study results in the context of curated knowledge of host viral infection, inflammatory response, organ damage, and tissue repair. The new database consists of 11 835 PAGs (Pathways, Annotated gene-lists, or Gene signatures) from 33 public data sources. Through the web user interface, users can search by a query gene or a query term and retrieve significantly matched PAGs with all the curated information. Users can navigate from a PAG of interest to other related PAGs through either shared PAG-to-PAG co-membership relationships or PAG-to-PAG regulatory relationships, totaling 19 996 993. Users can also retrieve enriched PAGs from an input list of COVID-19 functional study result genes, customize the search data sources, and export all results for subsequent offline data analysis. In a case study, we performed a gene set enrichment analysis (GSEA) of a COVID-19 RNA-seq data set from the Gene Expression Omnibus database. Compared with the results using the standard PAGER database, PAGER-CoV allows for more sensitive matching of known immune-related gene signatures. We expect PAGER-CoV to be invaluable for biomedical researchers to find molecular biology mechanisms and tailored therapeutics to treat COVID-19 patients.

Mapping 2 Decades of Research in Health Services Research, Health Policy, and Health Economics Journals.

OBJECTIVE: To identify major research topics and exhibit trends in these topics in 15 health services research, health policy, and health economics journals over 2 decades. DATA SOURCES: The study sample of 35,159 abstracts (1999-2020) were collected from PubMed for 15 journals. STUDY DESIGN: The study used a 3-phase approach for text analyses: (1) developing the corpus of 40,618 references from PubMed (excluding 5459 of those without abstract or author information); (2) preprocessing and generating the term list using natural language processing to eliminate irrelevant textual data and identify important terms and phrases; (3) analyzing the preprocessed text data using latent semantic analysis, topic analyses, and multiple correspondence analysis. PRINCIPAL FINDINGS: Application of analyses generated 16 major research topics: (1) implementation/intervention science; (2) HIV and women's health; (3) outcomes research and quality; (4) veterans/military studies; (5) provider/primary-care interventions; (6) geriatrics and formal/informal care; (7) policies and health outcomes; (8) medication treatment/therapy; (9) patient interventions; (10) health insurance legislation and policies; (11) public health policies; (12) literature reviews; (13) cost-effectiveness and economic evaluation; (14) cancer care; (15) workforce issues; and (16) socioeconomic status and disparities. The 2-dimensional map revealed that some journals have stronger associations with specific topics. Findings were not consistent with previous studies based on user perceptions. CONCLUSION: Findings of this study can be used by the stakeholders of health services research, policy, and economics to develop future research agendas, target journal submissions, and generate interdisciplinary solutions by examining overlapping journals for particular topics.

The biomedical informatics short course at Woods Hole/Georgia: Training to support institutional change.

The US National Library of Medicine's Biomedical Informatics Short Course ran from 1992 to 2017, most of that time at the Marine Biological Laboratory in Woods Hole, Massachusetts. Its intention was to provide physicians, medical librarians and others engaged in health care with a basic understanding of the major topics in informatics so that they could return to their home institutions as "change agents". Over the years, the course provided week-long, intense, morning-to-night experiences for some 1,350 students, consisting of lectures and hands-on project development, taught by many luminaries in the field, not the least of which was Donald A.B. Lindberg M.D., who spoke on topics ranging from bioinformatics to national policy.

A state-based approach to genomics for rare disease and population screening.

PURPOSE: The Alabama Genomic Health Initiative (AGHI) is a state-funded effort to provide genomic testing. AGHI engages two distinct cohorts across the state of Alabama. One cohort includes children and adults with undiagnosed rare disease; a second includes an unselected adult population. Here we describe findings from the first 176 rare disease and 5369 population cohort AGHI participants. METHODS: AGHI participants enroll in one of two arms of a research protocol that provides access to genomic testing results and biobank participation. Rare disease cohort participants receive genome sequencing to identify primary and secondary findings. Population cohort participants receive genotyping to identify pathogenic and likely pathogenic variants for actionable conditions. RESULTS: Within the rare disease cohort, genome sequencing identified likely pathogenic or pathogenic variation in 20% of affected individuals. Within the population cohort, 1.5% of individuals received a positive genotyping result. The rate of genotyping results corroborated by reported personal or family history varied by gene. CONCLUSIONS: AGHI demonstrates the ability to provide useful health information in two contexts: rare undiagnosed disease and population screening. This utility should motivate continued exploration of ways in which emerging genomic technologies might benefit broad populations.

What Every Reader Should Know About Studies Using Electronic Health Record Data but May Be Afraid to Ask.

Coincident with the tsunami of COVID-19-related publications, there has been a surge of studies using real-world data, including those obtained from the electronic health record (EHR). Unfortunately, several of these high-profile publications were retracted because of concerns regarding the soundness and quality of the studies and the EHR data they purported to analyze. These retractions highlight that although a small community of EHR informatics experts can readily identify strengths and flaws in EHR-derived studies, many medical editorial teams and otherwise sophisticated medical readers lack the framework to fully critically appraise these studies. In addition, conventional statistical analyses cannot overcome the need for an understanding of the opportunities and limitations of EHR-derived studies. We distill here from the broader informatics literature six key considerations that are crucial for appraising studies utilizing EHR data: data completeness, data collection and handling (eg, transformation), data type (ie, codified, textual), robustness of methods against EHR variability (within and across institutions, countries, and time), transparency of data and analytic code, and the multidisciplinary approach. These considerations will inform researchers, clinicians, and other stakeholders as to the recommended best practices in reviewing manuscripts, grants, and other outputs from EHR-data derived studies, and thereby promote and foster rigor, quality, and reliability of this rapidly growing field.

Recruiting diversity where it exists: The Alabama Genomic Health Initiative.

Lack of diversity among genomic research participants results in disparities in benefits from genetic testing. To address this, the Alabama Genomic Health Initiative employed community engagement strategies to recruit diverse populations where they lived. In this paper, we describe our engagement techniques and recruitment strategies, which resulted in significant improvement in representation of African American participants. While African American participation has not reached the representation of this community as a percentage of Alabama's overall population (26%-27%), we have achieved an overall representation exceeding 20% for African Americans. We believe this demonstrates the value of engagement and recruitment where diverse populations reside.

Phosphoinositide 3-Kinase Gamma Inhibition Protects From Anthracycline Cardiotoxicity and Reduces Tumor Growth.

BACKGROUND: Anthracyclines, such as doxorubicin (DOX), are potent anticancer agents for the treatment of solid tumors and hematologic malignancies. However, their clinical use is hampered by cardiotoxicity. This study sought to investigate the role of phosphoinositide 3-kinase γ (PI3Kγ) in DOX-induced cardiotoxicity and the potential cardioprotective and anticancer effects of PI3Kγ inhibition. METHODS: Mice expressing a kinase-inactive PI3Kγ or receiving PI3Kγ-selective inhibitors were subjected to chronic DOX treatment. Cardiac function was analyzed by echocardiography, and DOX-mediated signaling was assessed in whole hearts or isolated cardiomyocytes. The dual cardioprotective and antitumor action of PI3Kγ inhibition was assessed in mouse mammary tumor models. RESULTS: PI3Kγ kinase-dead mice showed preserved cardiac function after chronic low-dose DOX treatment and were protected against DOX-induced cardiotoxicity. The beneficial effects of PI3Kγ inhibition were causally linked to enhanced autophagic disposal of DOX-damaged mitochondria. Consistently, either pharmacological or genetic blockade of autophagy in vivo abrogated the resistance of PI3Kγ kinase-dead mice to DOX cardiotoxicity. Mechanistically, PI3Kγ was triggered in DOX-treated hearts, downstream of Toll-like receptor 9, by the mitochondrial DNA released by injured organelles and contained in autolysosomes. This autolysosomal PI3Kγ/Akt/mTOR/Ulk1 signaling provided maladaptive feedback inhibition of autophagy. PI3Kγ blockade in models of mammary gland tumors prevented DOX-induced cardiac dysfunction and concomitantly synergized with the antitumor action of DOX by unleashing anticancer immunity. CONCLUSIONS: Blockade of PI3Kγ may provide a dual therapeutic advantage in cancer therapy by simultaneously preventing anthracyclines cardiotoxicity and reducing tumor growth.