Clinical impact of preemptive pharmacogenomic testing on antiplatelet therapy in a real-world setting.

CYP2C19 genotyping to guide antiplatelet therapy after patients develop acute coronary syndromes (ACS) or require percutaneous coronary interventions (PCIs) reduces the likelihood of major adverse cardiovascular events (MACE). Evidence about the impact of preemptive testing, where genotyping occurs while patients are healthy, is lacking. In patients initiating antiplatelet therapy for ACS or PCI, we compared medical records data from 67 patients who received CYP2C19 genotyping preemptively (results >7 days before need), against medical records data from 67 propensity score-matched patients who received early genotyping (results within 7 days of need). We also examined data from 140 patients who received late genotyping (results >7 days after need). We compared the impact of genotyping approaches on medication selections, specialty visits, MACE and bleeding events over 1 year. Patients with CYP2C19 loss-of-function alleles were less likely to be initiated on clopidogrel if they received preemptive rather than early or late genotyping (18.2%, 66.7%, and 73.2% respectively, p = 0.001). No differences were observed by genotyping approach in the number of specialty visits or likelihood of MACE or bleeding events (all p > 0.21). Preemptive genotyping had a strong impact on initial antiplatelet selection and a comparable impact on patient outcomes and healthcare utilization, compared to genotyping ordered after a need for antiplatelet therapy had been identified.

The Potential of Genetics in Identifying Women at Lower Risk of Breast Cancer.

Importance: Genetic information is not being used to identify women at lower risk of breast cancer or other diseases in clinical practice. With the new US Preventive Services Task Force guidelines lowering the age for mammogram screening for all, there is a potential benefit in identifying women at lower risk of disease who may defer the start of mammographic screening. This genetic risk-based approach would help mitigate overscreening, associated costs, and anxiety. Objective: To assess breast cancer incidence and age of onset among women at low genetic risk compared with women at average risk and evaluate the potential to delay mammography on the basis of genetic risk stratification. Design, Setting, and Participants: This retrospective case-control study included 25 591 women from the Healthy Nevada Project sequenced by Helix between 2018 and 2022. Data extracted from electronic health records at the end of 2022 (mean length of electronic health record available was 12 years) were used for the analysis in 2023. Main Outcomes and Measures: Breast cancer diagnosis was identified from electronic health records. Classification to the low-risk genetic group required (1) the absence of pathogenic variants or a variant of uncertain significance in BRCA1, BRCA2, PALB2, ATM, or CHEK2, and (2) a low polygenic risk score (bottom 10%) using a 313-single-nucleotide variant model. Results: Of 25 591 women in the study (mean [SD] age was 53.8 [16.9] years), 2338 women (9.1%) were classified as having low risk for breast cancer; 410 women (1.6%) were classified as high risk; and 22 843 women (89.3%) as average risk. There was a significant reduction in breast cancer diagnosis among the low-risk group (hazard ratio, 0.39; 95% CI, 0.29-0.52; P < .001). By 45 years of age, 0.69% of women in the average-risk group were diagnosed with breast cancer, whereas women in the low-risk group reached this rate at 51 years. By 50 years of age, 1.41% of those in the average-risk group were diagnosed with breast cancer, whereas those in the low-risk group reached this rate at age 58 years. These findings suggest that deferring mammogram screening by 5 to 10 years for women at low risk of breast cancer aligns with new draft recommendations. Conclusions and Relevance: The findings of this retrospective case-control study underscore the value of genetics in individualizing the onset of breast cancer screening. Improving breast cancer risk stratification by implementing both high-risk and low-risk strategies in screening can refine preventive measures and optimize health care resource allocation.

Attitudes about pharmacogenomic testing vary by healthcare specialty.

Aim: To understand how attitudes toward pharmacogenomic (PGx) testing among healthcare providers varies by specialty. Methods: Providers reported comfort ordering PGx testing and its perceived utility on web-based surveys before and after genetics education. Primary quantitative analyses compared primary care providers (PCPs) to specialty providers at both timepoints. Results: PCPs were more likely than specialty care providers to rate PGx testing as useful at both timepoints. Education increased comfort ordering PGx tests, with larger improvements among PCPs than specialty providers. Over 90% of cardiology and internal medicine providers rated PGx testing as useful at pre- and post-education. Conclusion: PCPs overwhelmingly perceive PGx to be useful, and provider education is particularly effective for improving PCPs' confidence. Education for all specialties will be essential to ensure appropriate integration into routine practice.

SLCO1B1 gene-based clinical decision support reduces statin-associated muscle symptoms risk with simvastatin.

Background: SLCO1B1 variants are known to be a strong predictor of statin-associated muscle symptoms (SAMS) risk with simvastatin. Methods: The authors conducted a retrospective chart review on 20,341 patients who had SLCO1B1 genotyping to quantify the uptake of clinical decision support (CDS) for genetic variants known to impact SAMS risk. Results: A total of 182 patients had 417 CDS alerts generated, and 150 of these patients (82.4%) received pharmacotherapy that did not increase risks for SAMS. Providers were more likely to cancel simvastatin orders in response to CDS alerts if genotyping had been done prior to the first simvastatin prescription than after (94.1% vs 28.5%, respectively; p < 0.001). Conclusion: CDS significantly reduces simvastatin prescribing at doses associated with SAMS.

Workforce Considerations When Building a Precision Medicine Program.

This paper describes one healthcare system's approach to strategically deploying genetic specialists and pharmacists to support the implementation of a precision medicine program. In 2013, Sanford Health initiated the development of a healthcare system-wide precision medicine program. Here, we report the necessary staffing including the genetic counselors, genetic counseling assistants, pharmacists, and geneticists. We examined the administrative and electronic medical records data to summarize genetic referrals over time as well as the uptake and results of an enterprise-wide genetic screening test. Between 2013 and 2020, the number of genetic specialists employed at Sanford Health increased by 190%, from 10.1 full-time equivalents (FTEs) to 29.3 FTEs. Over the same period, referrals from multiple provider types to genetic services increased by 423%, from 1438 referrals to 7517 referrals. Between 2018 and 2020, 11,771 patients received a genetic screening, with 4% identified with potential monogenic medically actionable predisposition (MAP) findings and 95% identified with at least one informative pharmacogenetic result. Of the MAP-positive patients, 85% had completed a session with a genetics provider. A strategic workforce staffing and deployment allowed Sanford Health to manage a new genetic screening program, which prompted a large increase in genetic referrals. This approach can be used as a template for other healthcare systems interested in the development of a precision medicine program.

Association of polygenic risk scores with incident atherosclerotic cardiovascular disease events among individuals with coronary artery calcium score of zero: The multi-ethnic study of atherosclerosis.

BACKGROUND: Polygenic risk scores (PRS) are associated with atherosclerotic cardiovascular disease (ASCVD) events. We studied incident ASCVD among individuals with absent coronary artery calcium (CAC = 0), to investigate the association of PRS with incident ASCVD among such individuals. METHODS: Data was used from Multi-Ethnic Study of Atherosclerosis (MESA), a prospective cohort study of participants free of clinical CVD at baseline. PRS were developed based on a literature-derived list of single-nucleotide polymorphisms (SNPs) weighted by effect size. The coronary heart disease (CHD) PRS contained 180 SNPs, and the stroke PRS had 32 SNPs. These SNPs were combined to compute an ASCVD PRS. The PRS were calculated among 3132 participants with CAC = 0. Multivariable-adjusted Cox proportional hazards models evaluated the association between each PRS (top 20% vs bottom 50%) and ASCVD. RESULTS: The study population included 3132 individuals with CAC = 0 [mean (SD) age 58 (9) years; 63% female, 33% White, 31% Black, 12% Chinese-American, 24% Hispanic]. Over a median follow-up of 16 years, there were 108 incident CHD events and 93 stroke events. ASCVD event rates were generally <7.5 per 1000-person years for all ASCVD events regardless of PRS risk stratum. The ASCVD PRS was significantly associated with incident ASCVD: (HR; 95% CI) (1.63; 1.11, 2.39). The CHD PRS was not associated with any ASCVD outcome, whereas the stroke PRS was significantly associated with ASCVD (1.84; 1.27, 2.68), CHD (1.79; 1.05, 3.06), and stroke (1.96; 1.19, 3.23). The stroke PRS results were significant among women and non-Whites. CONCLUSIONS: Among individuals with CAC = 0, the ASCVD PRS was associated with incident ASCVD events. This appears to be driven by genetic variants related to stroke but not CHD, and particularly among women and non-Whites. ASCVD event rates remained below the threshold recommended for consideration for initiation of statin therapy even in the high PRS groups.

Pharmacogenetic Review: Germline Genetic Variants Possessing Increased Cancer Risk With Clinically Actionable Therapeutic Relationships.

As our understanding of genomics and genetic testing continues to advance, the personalization of medical decision making is progressing simultaneously. By carefully crafting medical care to fit the specific needs of the individual, patients can experience better long-term outcomes, reduced toxicities, and improved healthcare experiences. Genetic tests are frequently ordered to help diagnose a clinical presentation and even to guide surveillance. Through persistent investigation, studies have begun to delineate further therapeutic implications based upon unique relationships with genetic variants. In this review, a pre-emptive approach is taken to understand the existing evidence of relationships between specific genetic variants and available therapies. The review revealed an array of diverse relationships, ranging from well-documented clinical approaches to investigative findings with potential for future application. Therapeutic agents identified in the study ranged from highly specific targeted therapies to agents possessing similar risk factors as a genetic variant. Working in conjunction with national standardized treatment approaches, it is critical that physicians appropriately consider these relationships when developing personalized treatment plans for their patients.

Establishing analytical validity of BeadChip array genotype data by comparison to whole-genome sequence and standard benchmark datasets.

BACKGROUND: Clinical use of genotype data requires high positive predictive value (PPV) and thorough understanding of the genotyping platform characteristics. BeadChip arrays, such as the Global Screening Array (GSA), potentially offer a high-throughput, low-cost clinical screen for known variants. We hypothesize that quality assessment and comparison to whole-genome sequence and benchmark data establish the analytical validity of GSA genotyping. METHODS: To test this hypothesis, we selected 263 samples from Coriell, generated GSA genotypes in triplicate, generated whole genome sequence (rWGS) genotypes, assessed the quality of each set of genotypes, and compared each set of genotypes to each other and to the 1000 Genomes Phase 3 (1KG) genotypes, a performance benchmark. For 59 genes (MAP59), we also performed theoretical and empirical evaluation of variants deemed medically actionable predispositions. RESULTS: Quality analyses detected sample contamination and increased assay failure along the chip margins. Comparison to benchmark data demonstrated that > 82% of the GSA assays had a PPV of 1. GSA assays targeting transitions, genomic regions of high complexity, and common variants performed better than those targeting transversions, regions of low complexity, and rare variants. Comparison of GSA data to rWGS and 1KG data showed > 99% performance across all measured parameters. Consistent with predictions from prior studies, the GSA detection of variation within the MAP59 genes was 3/261. CONCLUSION: We establish the analytical validity of GSA assays using quality analytics and comparison to benchmark and rWGS data. GSA assays meet the standards of a clinical screen although assays interrogating rare variants, transversions, and variants within low-complexity regions require careful evaluation.

SLCO1B1*5 Allele Is Associated With Atorvastatin Discontinuation and Adverse Muscle Symptoms in the Context of Routine Care.

The SLCO1B1 genotype is known to influence patient adherence to statin therapy, in part by increasing the risk for statin-associated musculoskeletal symptoms (SAMSs). The SLCO1B1*5 allele has previously been associated with simvastatin discontinuation and SAMSs. Prior analyses of the relationship between SLCO1B1*5 and atorvastatin muscle side effects have been inconclusive due to insufficient power. We now quantify the impact of SLCO1B1*5 on atorvastatin discontinuation and SAMSs in a large observational cohort using electronic medical record data from a single health care system. In our study cohort (n = 1,627 patients exposed to atorvastatin during the course of routine clinical care), 56% (n = 912 of 1,627 patients) discontinued atorvastatin and 18% (n = 303 of 1,627 patients) developed SAMSs. A univariate model revealed that SLCO1B1*5 increased the likelihood that patients would stop atorvastatin during routine care (odds ratio 1.2; 95% confidence interval (CI), 1.1-1.5; P = 0.04). A multivariate Cox proportional hazards model further demonstrated that this same variant was associated with time to atorvastatin discontinuation (hazard ratio 1.2; 95% CI, 1.1-1.4; P = 0.004). Additional time-to-event analyses also revealed that SCLO1B1*5 was associated with SAMSs (hazard ratio 1.4; 95% CI, 1.1-1.7; P = 0.02). Atorvastatin discontinuation was associated with SAMSs (odds ratio 1.67; P = 0.0001) in our cohort.

Improved provider preparedness through an 8-part genetics and genomic education program.

PURPOSE: Large-scale genetics education appropriate for general practice providers is a growing priority. We describe the content and impact of a mandatory system-wide program implemented at Sanford Health. METHODS: The Imagenetics Initiative at Sanford Health developed a 2-year genetics education program with quarterly web-based modules that were mandatory for all physicians and advanced practice providers. Scores of 0 to 5 were calculated for each module on the basis of the number of objectives that the participants reported as fulfilled. In addition, the participants completed surveys before starting and after finishing the education program, which included a 7-item measure scored 7 to 28 on the perceived preparedness to practice genetics. RESULTS: Between 2252 and 2822 Sanford Health employees completed each of the 8 quarterly education modules. The ratings were highest for the module about using genomics to improve patient management (mean score = 4.3) and lowest for the module about different types of genetic tests and specialists. The mean perceived preparedness scores increased from 15.7 at pre-education to 19.1 at post-education (P < .001). CONCLUSION: Web-based genetics education was highly effective in increasing health care providers' confidence about using genetics. Both comfort with personal knowledge and confidence regarding access to the system's genomic medicine experts increased significantly. The results demonstrate how scalable approaches can improve provider preparedness.

Cytochrome P450 2D6 Genotyping for Post-Operative Opioids.

Within most electronic medical records, automated decision support helps health care providers reduce the frequency of adverse drug reactions. Historically, this decision support has been used to prevent drug-drug interactions (DDIs). More recently, the clinical and scientific communities have been moving toward the use of this approach to predict and prevent drug-gene interactions (DGIs). Genetic variation in cytochrome P450 2D6 (CYP2D6) is known to impact clinical outcome for many drugs, including opioids. Randomized trials have been initiated to assess the utility of CYP2D6 gene-based dosing versus usual care. We review the use of this approach to guide opioid prescribing in the post-operative setting.

CYP2C19 genotype-directed P2Y12 inhibitor antiplatelet therapy normalizes risk for major adverse cardiovascular events after percutaneous coronary intervention.

OBJECTIVE: To study the use of CYP2C19 genotyping to guide P2Y12 inhibitor selection to maximize efficacy, and attenuate risk in appropriate patients who underwent PCI for CAD. METHODS: We performed a retrospective analysis of 868 patients with CAD who received CYP2C19 genotyping after PCI and changed P2Y12 inhibitor based on the results. Patients were divided into two groups based on clopidogrel metabolizer status. Group I: Intermediate (IM) and poor metabolizers (PM). Group II: Ultra-rapid (UM), rapid (RM) and normal metabolizers (NM). Each group was then categorized to one of two treatment arms guided by CYP2C19 genotype. Category 1: IM/PM started on clopidogrel, switched to ticagrelor or prasugrel; 2:IM/PM started on ticagrelor/prasugrel, continued these medications; 3: UM/RM/NM started on ticagrelor/prasugrel, switched to clopidogrel; 4: UM/RM/NM started on clopidogrel, continued clopidogrel. Death due to cardiac causes, bleeding events, non-fatal MI, target vessel revascularization (TVR), and MACE in all four categories were considered at 1, 6 and 12 months. RESULTS: We did not observe significant difference between phenotypes for MACE at 1 (p = 0.274), 6 (p = 0.387), and 12 months (p = 0.083). Death due to cardiac causes, MI, and bleeding events were not significant at 1, 6, and 12 months. There was no significant difference in TVR at 6 (p = 0.491), and 12 months (p = 0.423) except at 1 month (p = 0.012). CONCLUSION: CYP2C19 genotype-based intervention can be implemented effectively and reliably to guide selection of P2Y12 inhibitor to optimize patient quality and safety when appropriate in post PCI patients.

Primary care providers' responses to unsolicited Lynch syndrome secondary findings of varying clinical significance.

PURPOSE: How primary care providers (PCPs) respond to genomic secondary findings (SFs) of varying clinical significance (pathogenic, uncertain significance [VUS], or benign) is unknown. METHODS: We randomized 148 American Academy of Family Physicians members to review three reports with varying significance for Lynch syndrome. Participants provided open-ended responses about the follow-up they would address and organized the SF reports and five other topics in the order they would prioritize responding to them (1 = highest priority, 6 = lowest priority). RESULTS: PCPs suggested referrals more often for pathogenic variants or VUS than benign variants (72% vs. 16%, p < 0.001). PCPs were also more likely to address further workup, like a colonoscopy or esophagogastroduodenoscopy, in response to pathogenic variants or VUS than benign variants (43% vs. 4%, p < 0.001). The likelihoods of addressing referrals or further workup were similar when PCPs reviewed pathogenic variants and VUS (both p > 0.46). SF reports were prioritized highest for pathogenic variants (2.7 for pathogenic variants, 3.6 for VUS, 4.3 for benign variants, all p ≤ 0.014). CONCLUSION: Results suggest that while PCPs appreciated the differences in clinical significance, disclosure of VUS as SFs would substantially increase downstream health-care utilization.

Expanding the Phenotype of TUBB2A-Related Tubulinopathy: Three Cases of a Novel, Heterozygous TUBB2A Pathogenic Variant p.Gly98Arg.

Tubulinopathies are a group of conditions caused by variants in 6 tubulin genes that present with a spectrum of brain malformations. One of these conditions is TUBB2A-related tubulinopathy. Currently, there are 9 reported individuals with pathogenic variants within the TUBB2A gene, with common manifestations including, but not limited to, global developmental delay, seizures, cortical dysplasia, and dysmorphic corpus callosum. We report 3 patients identified by exome and genome sequencing to have a novel, pathogenic, missense variant in TUBB2A (p.Gly98Arg). They presented similarly with intellectual disability, hypotonia, and global developmental delay and varied with respect to the type of cortical brain malformation, seizure history, diagnosis of autism spectrum disorder, and other features. This case series expands the natural history of TUBB2A-related tubulinopathy while describing the presentation of a novel, pathogenic, missense variant in 3 patients.

Precision Population Medicine in Primary Care: The Sanford Chip Experience.

Genetic testing has the potential to revolutionize primary care, but few health systems have developed the infrastructure to support precision population medicine applications or attempted to evaluate its impact on patient and provider outcomes. In 2018, Sanford Health, the nation's largest rural nonprofit health care system, began offering genetic testing to its primary care patients. To date, more than 11,000 patients have participated in the Sanford Chip Program, over 90% of whom have been identified with at least one informative pharmacogenomic variant, and about 1.5% of whom have been identified with a medically actionable predisposition for disease. This manuscript describes the rationale for offering the Sanford Chip, the programs and infrastructure implemented to support it, and evolving plans for research to evaluate its real-world impact.

Implementation of wide-scale pharmacogenetic testing in primary care.

The convergence of translational genomics and biomedical informatics has changed healthcare delivery. Institutional consortia have begun implementing lab testing and decision support for drug-gene interactions. Aggregate datasets are now revealing the impact of clinical decision support for drug-gene interactions. Given the pleiotropic nature of pharmacogenes, interdisciplinary teams and robust clinical decision support tools must exist within an informatics framework built to be flexible and capable of cross-talk between clinical specialties. Navigation of the challenges presented with the implementation of five steps to build a genetics program infrastructure requires the expertise of multiple healthcare professionals. Ultimately, this manuscript describes our efforts to place pharmacogenomics in the hands of the primary care provider integrating this information into a patient's healthcare over their lifetime.

Expansion of the Human Phenotype Ontology (HPO) knowledge base and resources.

The Human Phenotype Ontology (HPO)-a standardized vocabulary of phenotypic abnormalities associated with 7000+ diseases-is used by thousands of researchers, clinicians, informaticians and electronic health record systems around the world. Its detailed descriptions of clinical abnormalities and computable disease definitions have made HPO the de facto standard for deep phenotyping in the field of rare disease. The HPO's interoperability with other ontologies has enabled it to be used to improve diagnostic accuracy by incorporating model organism data. It also plays a key role in the popular Exomiser tool, which identifies potential disease-causing variants from whole-exome or whole-genome sequencing data. Since the HPO was first introduced in 2008, its users have become both more numerous and more diverse. To meet these emerging needs, the project has added new content, language translations, mappings and computational tooling, as well as integrations with external community data. The HPO continues to collaborate with clinical adopters to improve specific areas of the ontology and extend standardized disease descriptions. The newly redesigned HPO website (www.human-phenotype-ontology.org) simplifies browsing terms and exploring clinical features, diseases, and human genes.

Interstitial Chromosome 3p13p14 Deletions: An Update and Review.

Deletions of proximal chromosome 3p13p14 are infrequent chromosomal alterations. Variable sizes and breakpoints have been reported in patients with a wide range of phenotypes that are evolving as additional cases are reported. The routine use of high-density chromosomal microarrays (CMA) has allowed the identification of many more cases of this disorder and clinical phenotyping shows evidence for an emerging profile among patients with overlapping deletions of 3p13p14. Here, we review the currently reported cases, their phenotypes and where available, the genomic intervals delineated by CMA. Surprisingly, we found that a significant number of proximal chromosome 3p deletions involve structural rearrangements, especially insertions, that have been identified in balanced parental chromosome complements. This region is historically known as a common human chromosomal fragile site, although an underlying genomic mechanism related to its architecture has not been identified. We conclude that identification of an interstitial 3p deletion in a proband by CMA should prompt consideration of further structural chromosomal evaluation using more traditional cytogenetic techniques. While the variability in breakpoints does not suggest a unifying underlying mechanism for these alterations, identification of the haploinsufficient genes in each patient's deletion interval and their developmental roles can guide genotype-phenotype correlations and impact clinical management.

Genomic Medicine in Primary Care.

Genomic medicine is a powerful tool with great potential to improve outcomes in the primary care setting. From a broad perspective, genomic medicine can be applied to rare disease, common disease and pharmacogenetics. There are applications in which it can be used to better identify rare disease, improve screening for common disease, reduce adverse drug effects and help to identify the right medication more quickly. This article provides specific examples of clinical applications for genomic medicine in the realm of cardiovascular disease to provide a better understanding of its potential use in primary care.