Evaluation of large language models for discovery of gene set function

Gene set analysis is a mainstay of functional genomics, but it relies on manually curated databases of gene functions that are incomplete and unaware of biological context. Here we evaluate the ability of OpenAI's GPT-4, a Large Language Model (LLM), to develop hypotheses about common gene functions from its embedded biomedical knowledge. We created a GPT-4 pipeline to label gene sets with names that summarize their consensus functions, substantiated by analysis text and citations. Benchmarking against named gene sets in the Gene Ontology, GPT-4 generated very similar names in 50% of cases, while in most remaining cases it recovered the name of a more general concept. In gene sets discovered in 'omics data, GPT-4 names were more informative than gene set enrichment, with supporting statements and citations that largely verified in human review. The ability to rapidly synthesize common gene functions positions LLMs as valuable functional genomics assistants

Drug–gene and drug–drug interactions associated with tramadol and codeine therapy in the INGENIOUS trial

Background: Tramadol and codeine are metabolized by CYP2D6 and are subject to drug-gene and drug-drug interactions. Methods: This interim analysis examined prescribing behavior and efficacy in 102 individuals prescribed tramadol or codeine while receiving pharmaco-genotyping as part of the INGENIOUS trial (NCT02297126). Results: Within 60 days of receiving tramadol or codeine, clinicians more frequently prescribed an alternative opioid in ultrarapid and poor metabolizers (odds ratio: 19.0; 95% CI: 2.8-160.4) as compared with normal or indeterminate metabolizers (p = 0.01). After adjusting the CYP2D6 activity score for drug-drug interactions, uncontrolled pain was reported more frequently in individuals with reduced CYP2D6 activity (odds ratio: 0.50; 95% CI: 0.25-0.94). Conclusion: Phenoconversion for drug-drug and drug-gene interactions is an important consideration in pharmacogenomic implementation; drug-drug interactions may obscure the potential benefits of genotyping

Implementation of a pharmacogenomics consult service to support the INGENIOUS trial

Hospital systems increasingly utilize pharmacogenomic testing to inform clinical prescribing. Successful implementation efforts have been modeled at many academic centers. In contrast, this report provides insights into the formation of a pharmacogenomics consultation service at a safety-net hospital, which predominantly serves low-income, uninsured, and vulnerable populations. The report describes the INdiana GENomics Implementation: an Opportunity for the UnderServed (INGENIOUS) trial and addresses concerns of adjudication, credentialing, and funding

Drugst.One -- A plug-and-play solution for online systems medicine and network-based drug repurposing

In recent decades, the development of new drugs has become increasingly expensive and inefficient, and the molecular mechanisms of most pharmaceuticals remain poorly understood. In response, computational systems and network medicine tools have emerged to identify potential drug repurposing candidates. However, these tools often require complex installation and lack intuitive visual network mining capabilities. To tackle these challenges, we introduce Drugst.One, a platform that assists specialized computational medicine tools in becoming user-friendly, web-based utilities for drug repurposing. With just three lines of code, Drugst.One turns any systems biology software into an interactive web tool for modeling and analyzing complex protein-drug-disease networks. Demonstrating its broad adaptability, Drugst.One has been successfully integrated with 21 computational systems medicine tools. Available at https://drugst.one, Drugst.One has significant potential for streamlining the drug discovery process, allowing researchers to focus on essential aspects of pharmaceutical treatment research.Comment: 45 pages, 6 figures, 7 table

Multi-Institutional Implementation of Clinical Decision Support for APOL1, NAT2, and YEATS4 Genotyping in Antihypertensive Management

(1) Background: Clinical decision support (CDS) is a vitally important adjunct to the implementation of pharmacogenomic-guided prescribing in clinical practice. A novel CDS was sought for the APOL1, NAT2, and YEATS4 genes to guide optimal selection of antihypertensive medications among the African American population cared for at multiple participating institutions in a clinical trial. (2) Methods: The CDS committee, made up of clinical content and CDS experts, developed a framework and contributed to the creation of the CDS using the following guiding principles: 1. medical algorithm consensus; 2. actionability; 3. context-sensitive triggers; 4. workflow integration; 5. feasibility; 6. interpretability; 7. portability; and 8. discrete reporting of lab results. (3) Results: Utilizing the principle of discrete patient laboratory and vital information, a novel CDS for APOL1, NAT2, and YEATS4 was created for use in a multi-institutional trial based on a medical algorithm consensus. The alerts are actionable and easily interpretable, clearly displaying the purpose and recommendations with pertinent laboratory results, vitals and links to ordersets with suggested antihypertensive dosages. Alerts were either triggered immediately once a provider starts to order relevant antihypertensive agents or strategically placed in workflow-appropriate general CDS sections in the electronic health record (EHR). Detailed implementation instructions were shared across institutions to achieve maximum portability. (4) Conclusions: Using sound principles, the created genetic algorithms were applied across multiple institutions. The framework outlined in this study should apply to other disease-gene and pharmacogenomic projects employing CDS

Behavioural activation to mitigate the psychological impacts of COVID-19 restrictions on older people in England and Wales (BASIL+) : a pragmatic randomised controlled trial

BACKGROUND: Older adults were more likely to be socially isolated during the COVID-19 pandemic, with increased risk of depression and loneliness. We aimed to investigate whether a behavioural activation intervention delivered via telephone could mitigate depression and loneliness in at-risk older people during the COVID-19 pandemic. METHODS: BASIL+ (Behavioural Activation in Social Isolation) was a pragmatic randomised controlled trial conducted among patients recruited from general practices in England and Wales, and was designed to assess the effectiveness of behavioural activation in mitigating depression and loneliness among older people during the COVID-19 pandemic. Eligible participants were aged 65 years and older, socially isolated, with a score of 5 or higher on the Patient Health Questionnaire-9 (PHQ-9), and had multiple long-term conditions. Participants were allocated in a 1:1 ratio to the intervention (behavioural activation) or control groups by use of simple randomisation without stratification. Behavioural activation was delivered by telephone; participants were offered up to eight weekly sessions with trained BASIL+ Support Workers. Behavioural activation was adapted to maintain social connections and encourage socially reinforcing activities. Participants in the control group received usual care with existing COVID-19 wellbeing resources. The primary clinical outcome was self-reported depression severity, assessed by the PHQ-9, at 3 months. Outcomes were assessed masked to allocation and analysis was by treatment allocation. This trial is registered with the ISRCTN registry (ISRCTN63034289). FINDINGS: Between Feb 8, 2021, and Feb 28, 2022, 449 eligible participants were identified and 435 from 26 general practices were recruited and randomly assigned (1:1) to the behavioural activation intervention (n=218) or to the control group (usual care with signposting; n=217). The mean age of participants was 75·7 years (SD 6·7); 270 (62·1%) of 435 participants were female, and 418 (96·1%) were White. Participants in the intervention group attended an average of 5·2 (SD 2·9) of eight remote behavioural activation sessions. The adjusted mean difference in PHQ-9 scores between the control and intervention groups at 3 months was -1·65 (95% CI -2·54 to -0·75, p=0·0003). No adverse events were reported that were attributable to the behavioural activation intervention. INTERPRETATION: Behavioural activation is an effective and potentially scalable intervention that can reduce symptoms of depression and emotional loneliness in at-risk groups in the short term. The findings of this trial add to the range of strategies to improve the mental health of older adults with multiple long-term conditions. These results can be helpful to policy makers beyond the pandemic in reducing the global burden of depression and addressing the health impacts of loneliness, particularly in at-risk groups. FUNDING: UK National Institute for Health and Care Research

Establishing the value of genomics in medicine: the IGNITE Pragmatic Trials Network.

PURPOSE: A critical gap in the adoption of genomic medicine into medical practice is the need for the rigorous evaluation of the utility of genomic medicine interventions. METHODS: The Implementing Genomics in Practice Pragmatic Trials Network (IGNITE PTN) was formed in 2018 to measure the clinical utility and cost-effectiveness of genomic medicine interventions, to assess approaches for real-world application of genomic medicine in diverse clinical settings, and to produce generalizable knowledge on clinical trials using genomic interventions. Five clinical sites and a coordinating center evaluated trial proposals and developed working groups to enable their implementation. RESULTS: Two pragmatic clinical trials (PCTs) have been initiated, one evaluating genetic risk APOL1 variants in African Americans in the management of their hypertension, and the other to evaluate the use of pharmacogenetic testing for medications to manage acute and chronic pain as well as depression. CONCLUSION: IGNITE PTN is a network that carries out PCTs in genomic medicine; it is focused on diversity and inclusion of underrepresented minority trial participants; it uses electronic health records and clinical decision support to deliver the interventions. IGNITE PTN will develop the evidence to support (or oppose) the adoption of genomic medicine interventions by patients, providers, and payers

Implementing a pragmatic clinical trial to tailor opioids for acute pain on behalf of the IGNITE ADOPT PGx investigators.

Opioid prescribing for postoperative pain management is challenging because of inter-patient variability in opioid response and concern about opioid addiction. Tramadol, hydrocodone, and codeine depend on the cytochrome P450 2D6 (CYP2D6) enzyme for formation of highly potent metabolites. Individuals with reduced or absent CYP2D6 activity (i.e., intermediate metabolizers [IMs] or poor metabolizers [PMs], respectively) have lower concentrations of potent opioid metabolites and potentially inadequate pain control. The primary objective of this prospective, multicenter, randomized pragmatic trial is to determine the effect of postoperative CYP2D6-guided opioid prescribing on pain control and opioid usage. Up to 2020 participants, age ≥8 years, scheduled to undergo a surgical procedure will be enrolled and randomized to immediate pharmacogenetic testing with clinical decision support (CDS) for CYP2D6 phenotype-guided postoperative pain management (intervention arm) or delayed testing without CDS (control arm). CDS is provided through medical record alerts and/or a pharmacist consult note. For IMs and PM in the intervention arm, CDS includes recommendations to avoid hydrocodone, tramadol, and codeine. Patient-reported pain-related outcomes are collected 10 days and 1, 3, and 6 months after surgery. The primary outcome, a composite of pain intensity and opioid usage at 10 days postsurgery, will be compared in the subgroup of IMs and PMs in the intervention (n = 152) versus the control (n = 152) arm. Secondary end points include prescription pain medication misuse scores and opioid persistence at 6 months. This trial will provide data on the clinical utility of CYP2D6 phenotype-guided opioid selection for improving postoperative pain control and reducing opioid-related risks

Cyclostratigraphy of shallow-marine carbonates – limitations and opportunities

The sedimentary record of ancient shallow-marine carbonate platforms commonly displays a stacking of different facies, which reflects repetitive changes of depositional environments through time. These changes can be induced by external factors such as cyclical changes in climate and/or sea level, but also by internal factors such as lateral migration of sediment bodies and/or changes in the ecology of the carbonate- producing organisms. If it can be demonstrated that the facies changes formed in tune with the orbital (Milankovitch) cycles of known duration, then a high-resolution time framework can be established. This demonstration is not an easy task because the orbital signal may be too weak to be recorded, or it may be distorted and/or overprinted by local or regional processes. The limitations of the cyclostratigraphical approach are discussed, but a case study from the Oxfordian of the Swiss Jura Mountains also shows its potential. A well-established chrono- and sequence- stratigraphic framework and detailed facies analysis allow identification of elementary, small-scale, and medium-scale depositional sequences that formed in tune with the precession, the short eccentricity, and the long eccentricity cycles, respectively. In the best case, a depositional sequence attributed to the precession cycle with a duration of 20'000 years can be interpreted in terms of sequence stratigraphy. This then allows estimating rates of sea-level change and sedimentation within a relatively narrow time window, thus facilitating comparisons between ancient carbonate platforms and Holocene or Recent shallow-marine environments where such rates are well quantified