Kekić, Adrijana

This review aims to provide a comprehensive framework for implementing precision sports medicine, integrating genetics, pharmacogenomics, digital health solutions, and multi-omics data. Literature review was conducted using MEDLINE, EMBASE, Web of Science, and Cochrane Library databases (January 2018–April 2024), focusing on precision medicine applications in sports medicine, utilizing key terms including “precision medicine”, “sports medicine”, “genetics”, and “multi-omics”, with forward and backward citation tracking. The review identified key gene variants affecting athletic performance: endurance (AMPD1, PPARGC1A), power (ACTN3, NOS3), strength (PPARG), and injury susceptibility (COL5A1, MMP3), while also examining inherited conditions like cardiomyopathies (MYH7, MYBPC3). Pharmacogenomic guidelines were established for optimizing common sports medications, including NSAIDs (CYP2C9), opioids (CYP2D6), and cardiovascular drugs (SLCO1B1, CYP2C19). Digital health technologies, including wearables and predictive analytics, showed potential for enhanced athlete monitoring and injury prevention, while multi-omics approaches integrated various molecular data to understand exercise capacity and injury predisposition, enabling personalized assessments, training regimens, and therapeutic interventions based on individual biomolecular profiles. This review provides sports medicine professionals with a framework to deliver personalized care tailored to each athlete’s unique profile, promising optimized performance, reduced injury risks, and improved recovery outcomes.

Abstract Coccidioidomycosis can cause severe meningitis, requiring lifelong treatment. In this study, we sought to better understand the potential effect of pharmacogenomic testing on treatment outcomes of patients with coccidioidal meningitis. Of 13 patients with coccidioidal meningitis who underwent pharmacogenomic testing, 11 had genetic variants of CYP2C19 and CYP3A5 that affect antifungal efficacy. These results led to real-time treatment changes and future antifungal planning. Routine pharmacogenomic testing helps to avoid antifungal treatments that are futile or lead to adverse effects.

Abstract Background Coccidioidomycosis is an endemic fungal infection in the desert southwestern USA. Less than 1% of infections are complicated by coccidioidal meningitis (CM), which requires lifetime treatment, and has high morbidity. IDSA guidelines recommend high dose fluconazole (flu) as first line treatment, but up to 31% of CM patients (pts) fail flu. Guidelines have not yet articulated best subsequent therapy, but options include itraconazole (itra), voriconazole (vori), posaconazole and isavuconazole (isa). Excellent adherence to medications is imperative, and therapeutic fluconazole (flu) serum levels correlate with successful CM outcome. Many azoles are substrates of P450/CYP enzymes, and genetic alterations may influence medication levels. We have observed many CM pts who swear to adherence yet have low therapeutic azole levels. Our aim was to summarize our experience with pharmacogenomic (PGx) testing to guide treatment of CM. Methods We conducted a retrospective review of CM pts in our Coccidioidomycosis Clinic who underwent 1 of 2 targeted gene queries, either an internal 9-gene query or an external vendor 27 gene test. A PGx pharmacist interpreted results. Results From 1/1/2021 – 4/30/2023, we identified 6 pts with poorly controlled CM as manifested by repeated hospitalizations, progressively abnormal findings on lumbar puncture and/or magnetic resonance imaging of the central nervous system. Among the 6, 3 (50%) were male, 5 (83%) white, mean age 45 (28-71) years, with 34-month mean duration of illness. None were immunosuppressed. CM was complicated by strokes in 3, and hydrocephalus requiring ventriculoperitoneal shunt in 2. Five failed initial high dose flu and most had some low therapeutic levels without other medications acting as CYP inducers/inhibitors. 3 pts had the 9 gene test and 3 had the 27 gene test. Clinically relevant PGx abnormalities were identified in 5, including variants of CYP 2C19, 2C9, 3A4 and 3A5, which confer altered metabolism of vori, itra and isa, respectively. Following PGx, treatment was adjusted in 4 pts. Conclusion PGx testing is a potential adjunctive tool to avoid ineffective therapies or medication toxicity in an infection whose treatment success strongly depends on consistent therapeutic medication levels over a lifetime. Disclosures All Authors: No reported disclosures

Abstract Background Pharmacogenomics is an emerging and affordable tool that may improve postoperative pain control. One challenge to successful pain control is the large interindividual variability among analgesics in their efficacy and adverse drug events. Whether preoperative pharmacogenomic testing is worthwhile for patients undergoing TKA is unclear. Questions/purposes (1) Are the results of preoperative pharmacogenetic testing associated with lower postoperative pain scores as measured by the Overall Benefit of Analgesic Score (OBAS)? (2) Do the results of preoperative pharmacogenomic testing lead to less total opioids given? (3) Do the results of preoperative pharmacogenomic testing lead to changes in opioid prescribing patterns? Methods Participants of this randomized trial were enrolled from September 2018 through December 2021 if they were aged 18 to 80 years and were undergoing primary TKA under general anesthesia. Patients were excluded if they had chronic kidney disease, a history of chronic pain or narcotic use before surgery, or if they were undergoing robotic surgery. Preoperatively, patients completed pharmacogenomic testing (RightMed, OneOME) and a questionnaire and were randomly assigned to the experimental group or control group. Of 99 patients screened, 23 were excluded, one before randomization; 11 allocated patients in each group did not receive their allocated interventions for reasons such as surgery canceled, patients ultimately undergoing spinal anesthesia, and change in surgery plan. Another four patients in each group were excluded from the analysis because they were missing an OBAS report. This left 30 patients for analysis in the control group and 38 patients in the experimental group. The control and experimental groups were similar in age, gender, and race. Pharmacogenomic test results for patients in the experimental group were reviewed before surgery by a pharmacist, who recommended perioperative medications to the clinical team. A pharmacist also assessed for clinically relevant drug-gene interactions and recommended drug and dose selection according to guidelines from the Clinical Pharmacogenomics Implementation Consortium for each patient enrolled in the study. Patients were unaware of their pharmacogenomic results. Pharmacogenomic test results for patients in the control group were not reviewed before surgery; instead, standard perioperative medications were administered in adherence to our institutional care pathways. The OBAS (maximum 28 points) was the primary outcome measure, recorded 24 hours postoperatively. A two-sample t-test was used to compare the mean OBAS between groups. Secondary measures were the mean 24-hour pain score, total morphine milligram equivalent, and frequency of opioid use. Postoperatively, patients were assessed for pain with a VAS (range 0 to 10). Opioid use was recorded preoperatively, intraoperatively, in the postanesthesia care unit, and 24 hours after discharge from the postanesthesia care unit. Changes in perioperative opioid use based on pharmacogenomic testing were recorded, as were changes in prescription patterns for postoperative pain control. Preoperative characteristics were also compared between patients with and without various phenotypes ascertained from pharmacogenomic test results. Results The mean OBAS did not differ between groups (mean ± SD 4.7 ± 3.7 in the control group versus 4.2 ± 2.8 in the experimental group, mean difference 0.5 [95% CI -1.1 to 2.1]; p = 0.55). Total opioids given did not differ between groups or at any single perioperative timepoint (preoperative, intraoperative, or postoperative). We found no difference in opioid prescribing pattern. After adjusting for multiple comparisons, no difference was observed between the treatment and control groups in tramadol use (41% versus 71%, proportion difference 0.29 [95% CI 0.05 to 0.53]; nominal p = 0.02; adjusted p > 0.99). Conclusion Routine use of pharmacogenomic testing for patients undergoing TKA did not lead to better pain control or decreased opioid consumption. Future studies might focus on at-risk populations, such as patients with chronic pain or those undergoing complex, painful surgical procedures, to test whether pharmacogenomic results might be beneficial in certain circumstances. Level of Evidence Level I, therapeutic study.

Background: There is a paucity of evidence to inform the value of pharmacogenomic (PGx) results in patients after kidney transplant and how these results differ between Indigenous Americans and Whites. This study aims to identify the frequency of recommended medication changes based on PGx results and compare the pharmacogenomic (PGx) results and patients’ perceptions of the findings between a cohort of Indigenous American and White kidney transplant recipients. Methods: Thirty-one Indigenous Americans and fifty White kidney transplant recipients were studied prospectively. Genetic variants were identified using the OneOme RightMed PGx test of 27 genes. PGx pharmacist generated a report of the genetic variation and recommended changes. Pre- and post-qualitative patient surveys were obtained. Results: White and Indigenous American subjects had a similar mean number of medications at the time of PGx testing (mean 13 (SD 4.5)). In the entire cohort, 53% received beta blockers, 30% received antidepressants, 16% anticoagulation, 47% pain medication, and 25% statin therapy. Drug–gene interactions that warranted a clinical action were present in 21.5% of patients. In 12.7%, monitoring was recommended. Compared to the Whites, the Indigenous American patients had more normal CYP2C19 (p = 0.012) and CYP2D6 (p = 0.012) activities. The Indigenous American patients had more normal CYP4F2 (p = 0.004) and lower VKORC (p = 0.041) activities, phenotypes for warfarin drug dosing, and efficacy compared to the Whites. SLC6A4, which affects antidepressant metabolism, showed statistical differences between the two cohorts (p = 0.017); specifically, SLC6A4 had reduced expression in 45% of the Indigenous American patients compared to 20% of the White patients. There was no significant difference in patient perception before and after PGx. Conclusions: Kidney transplant recipients had several drug–gene interactions that were clinically actionable; over one-third of patients were likely to benefit from changes in medications or drug doses based on the PGx results. The Indigenous American patients differed in the expression of drug-metabolizing enzymes and drug transporters from the White patients.

AbstractIntroductionAdverse reactions to pain medication and pain can delay discharge after outpatient knee arthroplasty (TKA). Pharmacogenomics is an emerging tool that might help reduce adverse events by tailoring medication use based on known genetic variations in the CYP genes determining drug metabolism. This study was undertaken to evaluate whether pre-operative pharmacogenomic testing could optimize peri-operative pain management in patients undergoing total knee arthroplasty (TKA).MethodsThis prospective, randomized study was performed in adults undergoing primary TKA. Patients in the experimental group underwent pre-operative pharmacogenomic evaluation and medication adjustments. Medications were not optimized for control patients. The Overall Benefit of Analgesic Score (OBAS) at 24 hours post-op was the primary outcome. Postoperative pain scores (VAS scale), total opioid use, time in recovery, and time to discharge were also compared.Results76 patients enrolled. 93% of patients had a poor-intermediate phenotype for at least one of four CYP genes. OBAS did not differ significantly between the two groups (4.2 control vs. 4.7 experimental; 95% CI −1.1 to 2.1) and was below the minimum clinically important difference of 2.0 points. Furthermore, there were no differences in any OBAS subscale including pain, satisfaction, or nausea. There were no differences in time in the recovery area or to discharge from hospital, or narcotic use.ConclusionsDespite many patients having a poor-intermediate phenotype for a CYP gene, pharmacogenomic testing prior to TKA and medication adjustment did not improve anesthesia or pain management outcomes, time to discharge or mean total opioid use after surgery.

e24114 Background: Pharmacogenomics (PGx) testing is used increasingly in cancer supportive care for drug and dose selection, and side effects prediction with antidepressants, antiemetics, and pain medications. Genetic variants in genes that encode for drug metabolizing enzymes (CYPs), transporters (SLC6A4) and drug receptors (HTR2A, OPRM1, etc) are well known for these medications. They contribute to inter-individual differences in medication safety and efficacy. We report on their frequency and effect on supportive care drugs in patients with solid tumors. Methods: Between 06/06/19 and 12/18/19, solid tumor cancer patients at Mayo Clinic Arizona were enrolled in a PGx prospective study. They were genotyped using a multi-gene panel, OneOme RightMed. The panel assessed 27 genes, including CYP2C9, CYP2C19, CYP2D6, CYP3A4, COMT, OPRM1, GRIK4, HTR2A, SLC6A4, associated with pain medications, antidepressants, and antiemetics. PGx pharmacist provided medication recommendations and dose adjustments based on PGx test results and concurrent medications. Results: 200 patients were swabbed and 196 patients were genotyped. The results were available within 5 days. All patients were also assessed for pheno-conversion (drug-drug-gene interactions) by a pharmacist. Recommendations were made based on predicted phenotype. Various solid tumor types were represented, including prostate (19.9%), colorectal (17.9%), melanoma (14.8%), and others (47.4%). Median age was 65 with 59.2% patients being male and 40.85% female. All had at least one actionable polymorphism related to these medications. The most significant findings were related to CYP2C19 and CYP2D6 genes. Of 196 patients, a total of 132 (67.3%) had other than normal CYP2D6 metabolizer phenotype and 112 (57.1%) had other than normal CYP2C19 metabolizer phenotype. Based on these genotypes, alternatives to pain medications were recommended for 37 patients, to ondansetron in 9 patients, and to anti-depressants in 51 patients. Conclusions: Genetic variants were commonly found that affect supportive care medications used in oncology practice and contribute to inter-individual differences associated with increased risk of adverse drug effects and reduced efficacy. PGx guided recommendation may help physicians in individualizing medication treatment outcomes for patients with different cancer types and with polypharmacy. PGx trained pharmacist can serve as a valuable asset in optimizing personalized medication management.

126 Background: Pharmacogenomics (PGx) is a developing field in individualized medicine concerned with understanding genetic polymorphisms that may explain inter-individual variation in drug efficacy and toxicity. Understanding these polymorphisms is a key tool in guiding clinician’s selection and dosing of specific medications to optimally manage patient symptoms. Common pharmacogenes that impact analgesic prescribing include: CYP2D6, OPRM1, and COMT; for mood disorders: CYP2C19. This cross-sectional study explored the activity of pharmacogenes of clinical significance in palliative medicine with either Level 1 or 2 evidence. Methods: We performed PGx testing on 50 new referrals to the palliative medicine clinic with an active malignancy. Each patient underwent PGx testing with clinical pharmacist review and interpretation prior to their initial office appointment. Results: In our cohort 54% were men and the mean age was 64.7 (24-87). The average number of medications, medication allergies, and creatinine clearance were 10.5 (1-22), 1.3 (0-13), and 78.4 (31-120), respectively. Among the pharmacogenes impacting opiate and antiemetic prescribing, 14% (7/50) of patients were poor metabolizers of CYP2D6 and 8% (4/50) were rapid or ultra-rapid metabolizers. Another 60% (30/50) showed intermediate metabolism which would impact initial dosing. Poor metabolism of COMT or OPRM1 was seen in 8% (4/50) with another 36% (18/50) demonstrating rapid metabolism. Activity for the pharmacogene CYP2C19, which impacts many psychotropics, revealed 32% (16/50) rapid or ultra-rapid metabolizers and no poor metabolizers. Overall, 66% (33/50) of patients had pharmacogene activity suggestive of significant clinical impact necessitating either drug avoidance due to toxicity risks or substantial dose adjustment to be efficacious. Conclusions: Polymorphisms impacting pharmacotherapy were common in our cohort. Patients with difficult-to-control symptoms or multiple medication toxicities can utilize PGx testing as a guide to symptom relief. As PGx technology becomes readily accessible and economical, opportunities for patients to have precision genomic information guide healthcare decisions is expected to increase.

A systematic review was conducted to examine the association between fish oil supplementation and the development of asthma exacerbations. Comprehensive literature reviews of recent fish oil studies were performed to evaluate alterations in asthma surrogate markers. Additionally, the relative compositions of the fish oils used in each study were analyzed. The results of the review were inconclusive, but provide a basis for future research methods.