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Purpose CYP2D6 bioactivates codeine and tramadol, with intermediate and poor metabolizers (IMs and PMs) expected to have impaired analgesia. This pragmatic proof-of-concept trial tested the effects of CYP2D6-guided opioid prescribing on pain control. Methods Participants with chronic pain (94% on an opioid) from seven clinics were enrolled into CYP2D6-guided ( n  = 235) or usual care ( n  = 135) arms using a cluster design. CYP2D6 phenotypes were assigned based on genotype and CYP2D6 inhibitor use, with recommendations for opioid prescribing made in the CYP2D6-guided arm. Pain was assessed at baseline and 3 months using PROMIS ® measures. Results On stepwise multiple linear regression, the primary outcome of composite pain intensity (composite of current pain and worst and average pain in the past week) among IM/PMs initially prescribed tramadol/codeine ( n  = 45) had greater improvement in the CYP2D6-guided versus usual care arm (-1.01 ± 1.59 vs. -0.40 ± 1.20; adj P  = 0.016); 24% of CYP2D6-guided versus 0% of usual care participants reported ≥30% (clinically meaningful) reduction in the composite outcome. In contrast, among normal metabolizers prescribed tramadol or codeine at baseline, there was no difference in the change in composite pain intensity at 3 months between CYP2D6-guided (-0.61 ± 1.39) and usual care (-0.54 ± 1.69) groups (adj P  = 0.540). Conclusion These data support the potential benefits of CYP2D6-guided pain management.

Background Sepsis is a heterogenous syndrome with limited therapeutic options. Identifying immunological endotypes through gene expression patterns in septic patients may lead to targeted interventions. We investigated whether patients admitted to a surgical intensive care unit (ICU) with sepsis and with high risk of mortality express similar endotypes to non-septic, but still critically ill patients using two multiplex transcriptomic metrics obtained both on admission to a surgical ICU and at set intervals. Methods We analyzed transcriptomic data from 522 patients in two single-site, prospective, observational cohorts admitted to surgical ICUs over a 5-year period ending in July 2020. Using an FDA-cleared analytical platform (nCounter FLEX ® , NanoString, Inc.), we assessed a previously validated 29-messenger RNA transcriptomic classifier for likelihood of 30-day mortality (IMX-SEV-3) and a 33-messenger RNA transcriptomic endotype classifier. Clinical outcomes included all-cause mortality, development of chronic critical illness, and secondary infections. Univariate and multivariate analyses were performed to assess for true effect and confounding. Results Sepsis was associated with a significantly higher predicted and actual hospital mortality. At enrollment, the predominant endotype for both septic and non-septic patients was adaptive , though with significantly different distributions. Inflammopathic and coagulopathic septic patients, as well as inflammopathic non-septic patients, showed significantly higher frequencies of secondary infections compared to those with adaptive endotypes ( p  < 0.01). Endotypes changed during ICU hospitalization in 57.5% of patients. Patients who remained adaptive had overall better prognosis, while those who remained inflammopathic or coagulopathic had worse overall outcomes. For severity metrics, patients admitted with sepsis and a high predicted likelihood of mortality showed an inflammopathic (49.6%) endotype and had higher rates of cumulative adverse outcomes (67.4%). Patients at low mortality risk, whether septic or non-septic, almost uniformly presented with an adaptive endotype (100% and 93.4%, respectively). Conclusion Critically ill surgical patients express different and evolving immunological endotypes depending upon both their sepsis status and severity of their clinical course. Future studies will elucidate whether endotyping critically ill, septic patients can identify individuals for targeted therapeutic interventions to improve patient management and outcomes.

Introduction: Pharmacogenetics (PGx) has the potential to improve health outcomes but cost of testing is a barrier for equitable access. Reimbursement by insurance providers may lessen the financial burden for patients, but the extent to which PGx claims are covered in clinical practice has not been well-characterized in the literature. Methods: A retrospective analysis of outpatient claims submitted to payers for PGx tests from 1/1/2019 through 12/31/2021 was performed. A reimbursement rate was calculated and compared across specific test types (e.g., single genes, panel), payers, indication, and the year the claim was submitted. Results: A total of 1,039 outpatient claims for PGx testing were analyzed. The overall reimbursement rate was 46% and ranged from 36%–48% across payers. PGx panels were reimbursed at a significantly higher rate than single gene tests (74% vs. 43%, p < 0.001). Discussion: Reimbursement of claims for PGx testing is variable based on the test type, indication, year the claim was submitted, number of diagnosis codes submitted, and number of unique diagnosis codes submitted. Due to the highly variable nature of reimbursement, cost and affordability should be discussed with each patient.

Cytochrome P450 2D6 (CYP2D6) genotype–guided opioid prescribing is limited. The purpose of this type 2 hybrid implementation-effectiveness trial was to evaluate the feasibility of clinically implementing CYP2D6-guided postsurgical pain management and determine that such an approach did not worsen pain control. Adults undergoing total joint arthroplasty were randomized 2:1 to genotype-guided or usual pain management. For participants in the genotype-guided arm with a CYP2D6 poor (PM), intermediate (IM), or ultrarapid (UM) metabolizer phenotype, recommendations were to avoid hydrocodone, tramadol, codeine, and oxycodone. The primary endpoints were feasibility metrics and opioid use; pain intensity was a secondary endpoint. Effectiveness outcomes were collected 2 weeks postsurgery. Of 282 patients approached, 260 (92%) agreed to participate. In the genotype-guided arm, 20% had a high-risk (IM/PM/UM) phenotype, of whom 72% received an alternative opioid versus 0% of usual care participants (p < 0.001). In an exploratory analysis, there was less opioid consumption (200 [104–280] vs. 230 [133–350] morphine milligram equivalents; p = 0.047) and similar pain intensity (2.6±0.8 vs. 2.5 ± 0.7; p = 0.638) in the genotype-guided vs. usual care arm, respectively. Implementing CYP2D6 to guide postoperative pain management is feasible and may lead to lower opioid use without compromising pain control.

Despite the critical role of DNA methylation, clinical implementations harnessing its promise have not been described in acute myeloid leukemia. Utilizing DNA methylation from 3314 leukemia patient samples across 11 harmonized cohorts, we describe the Acute Leukemia Methylome Atlas, which includes robust models capable of accurately predicting AML subtypes. A genome-wide prognostic model as well as a targeted panel of 38 CpGs significantly predict five-year survival in our pediatric and adult test cohorts. To accelerate rapid clinical utility, we develop a specimen-to-result protocol that uses long-read nanopore sequencing and machine learning to characterize patients’ whole genomes and epigenomes. Clinical validation on patient samples confirms high concordance between epigenomic signatures and genomic lesions, though uniquely rare karyotypes remained challenging due to limited available training data. These results unveil the potential for increased affordability, speed, and accuracy for patients in need of complex molecular diagnosis and prognosis. The prognostic and diagnostic roles of DNA methylation in acute myeloid leukemia remains to be explored. Here, the authors develop DNA methylation-based models for the prediction of five-year survival and clinical molecular subtypes in both pediatric and adult test cohorts.

Background The CYP2C19 nonfunctional genotype reduces clopidogrel effectiveness after percutaneous coronary intervention (PCI). Following clinical implementation of CYP2C19 genotyping at University Florida (UF) Health Shands Hospital in 2012, where genotype results are available approximately 3 days after PCI, testing was expanded to UF Health Jacksonville in 2016 utilizing a rapid genotyping approach. We describe metrics with this latter implementation. Methods Patients at UF Health Jacksonville undergoing left heart catheterization with intent to undergo PCI were targeted for genotyping using the Spartan RX™ system. Testing metrics and provider acceptance of testing and response to genotype results were examined, as was antiplatelet therapy over the 6 months following genotyping. Results In the first year, 931 patients, including 392/505 (78%) total patients undergoing PCI, were genotyped. The median genotype test turnaround time was 96 min. Genotype results were available for 388 (99%) PCI patients prior to discharge. Of 336 genotyped PCI patients alive at discharge and not enrolled in an antiplatelet therapy trial, 1/6 (17%) poor metabolizers (PMs, with two nonfunctional alleles), 38/93 (41%) intermediate metabolizers (IMs, with one nonfunctional allele), and 119/237 (50%) patients without a nonfunctional allele were prescribed clopidogrel (p = 0.110). Clopidogrel use was higher among non-ACS versus ACS patients (78.6% vs. 42.2%, p < 0.001). Six months later, among patients with follow-up data, clopidogrel was prescribed in 0/4 (0%) PMs, 33/65 (51%) IMs, and 115/182 (63%) patients without a nonfunctional allele (p = 0.008 across groups; p = 0.020 for PMs versus those without a nonfunctional allele). Conclusion These data demonstrate that rapid genotyping is clinically feasible at a high volume cardiac catheterization facility and allows informed chronic antiplatelet prescribing, with lower clopidogrel use in PMs at 6 months. Trial registration ClinicalTrials.gov Identifier: NCT02724319; registered March 31, 2016; https://www.clinicaltrials.gov/ct2/show/NCT02724319?term=angiolillo&rank=7

Both severe SARS-CoV-2 infections and bacterial sepsis exhibit an immunological dyscrasia and propensity for secondary infections. The nature of the immunological dyscrasias for these differing etiologies and their time course remain unclear. In this study, thirty hospitalized patients with SARS-CoV-2 infection were compared with ten critically ill patients with bacterial sepsis over 21 days, as well as ten healthy control subjects. Blood was sampled between days 1 and 21 after admission for targeted plasma biomarker analysis, cellular phenotyping, and leukocyte functional analysis via enzyme-linked immunospot assay. We found that circulating inflammatory markers were significantly higher early after bacterial sepsis compared with SARS-CoV-2. Both cohorts exhibited profound immune suppression through 21 days (suppressed HLA-DR expression, reduced mononuclear cell IFN-gamma production), and expanded numbers of myeloid-derived suppressor cells (MDSCs). In addition, MDSC expansion and ex vivo production of IFN-gamma and TNF-alpha were resolving over time in bacterial sepsis, whereas in SARS-CoV-2, immunosuppression and inflammation were accelerating. Despite less severe initial physiologic derangement, SARS-CoV-2 patients had similar incidence of secondary infections (23% vs 30%) as bacterial sepsis patients. Finally, COVID patients who developed secondary bacterial infections exhibited profound immunosuppression evident by elevated sPD-L1 and depressed HLA-DR. Although both bacterial sepsis and SARS-CoV-2 are associated with inflammation and immune suppression, their immune dyscrasia temporal patterns and clinical outcomes are different. SARS-CoV-2 patients had less severe early inflammation and organ dysfunction but had persistent inflammation and immunosuppression and suffered worse clinical outcomes, especially when SARS-CoV-2 infection was followed by secondary bacterial infection.

The Precision Medicine Program (PMP) at the University of Florida (UF) focuses on advancing pharmacogenomics (PGx) to improve patient care. The UF PMP, in collaboration with the UF Health Pathology Laboratory (UFHPL), utilized Health Level Seven (HL7) standards to integrate PGx data into Epic's Genomic Module to enhance the management and utilization of PGx data in clinical practice. A key feature of the Genomic Module is the introduction of genomic indicators-innovative tools that flag actionable genetic information directly within the electronic health record (EHR). These indicators enable the effective presentation of phenotypic information and, when leveraged with existing clinical decision support (CDS) alerts, help provide timely and informed therapeutic decisions based on genomic data. This advancement represents a significant shift in the utilization of genetic data, moving beyond traditional PDF reports to provide a comprehensive understanding of PGx data. Ultimately, this integration empowers healthcare providers with genomics-guided recommendations, enhancing precision and personalization in patient care, contributing significantly to the advancement of personalized medicine.

Pharmacogenetic (PGx) testing can individualize pharmacotherapy, but many current panels lack inclusivity for diverse populations and are often cost‐prohibitive for medically underserved communities. This study aimed to develop and validate GatorPGx Plus, a low‐cost, preemptive PGx panel tailored for diverse patient populations. Pharmacogenes were selected based on the drug/drug classes potentially influenced by their variants, the clinical severity of drug‐gene interactions, or the strength of guideline recommendations or emerging evidence. Variants within the pharmacogenes were included if their allele frequencies were approximately 1% or greater in any major ancestral population. The panel was validated for accuracy, precision, and analytical sensitivity and applied to 124 participants from an ongoing pharmacogenetic clinical implementation trial. To reduce costs, a high‐throughput platform was chosen, laboratory technician hands‐on time was minimized, and result translation and reporting were automated. The panel comprised tests for 62 variants in 14 genes/gene regions, including a CYP2D6 copy number assay. It demonstrated 100% concordance with reference methods. The average turnaround time between test order and results was 14.3 (±6.4) days. Among the 124 genotyped trial participants (mean age 60 years, 57.3% female), 99% had at least one non‐normal function (less common or higher‐risk) phenotype. The most frequently identified non‐normal function phenotypes were in CYP2C19 (69.4%). CYP2D6 *17, *29, and CYP2C19 *9 were captured at higher frequencies than reported in European populations. GatorPGx Plus is a low per‐test cost, clinically validated, preemptive PGx panel that effectively captures key variants in a mixed‐ancestry population, underscoring its potential clinical utility in diverse, medically underserved populations.

The University of Florida (UF) Health Personalized Medicine Program launched in 2012 with genotyping for clopidogrel response at UF Health Shands Hospital. We have since expanded genotyping to UF Health Jacksonville and established the infrastructure at UF Health to support clinical implementation for five additional gene-drug pairs: -thiopurines, ( )-PEG IFN-α-based regimens, -opioids, -antidepressants and -proton pump inhibitors. We are contributing to the evidence based on outcomes with genotype-guided therapy through pragmatic studies of our clinical implementations. In addition, we have developed a broad array of educational programs for providers, trainees and students that incorporate personal genotype evaluation to enhance participant learning.