How might members of a large, multi-institutional research and resource consortium foster justice, equity, diversity, and inclusion as central to its mission, goals, governance, and culture? These four principles, often referred to as JEDI, can be aspirational—but to be operationalized, they must be supported by concrete actions, investments, and a persistent long-term commitment to the principles themselves, which often requires self-reflection and course correction. We present here the iterative design process implemented across the Clinical Genome Resource (ClinGen) that led to the development of an action plan to operationalize JEDI principles across three major domains, with specific deliverables and commitments dedicated to each. Active involvement of consortium leadership, buy-in from its members at all levels, and support from NIH program staff at pivotal stages were essential to the success of this effort. The ClinGen JEDI action plan that resulted from our process is a living document and roadmap whose target goals and deliverables will continue to evolve. Here, we offer a transparent account of how a large, multi-site biomedical research consortium achieved this, as well as the challenges and opportunities we encountered on this first step in our journey toward enacting JEDI principles in our sphere of influence. We hope that others seeking to engage in this work will gain valuable insights from our process, experience, and lessons learned.

Pharmacogenomics (PGx) is focused on the relationship between an individual's genetic makeup and their response to medications, with the overarching aim of guiding prescribing decisions to improve drug efficacy and reduce adverse events. The PGx and genomic medicine communities have worked independently for over 2 decades, developing separate standards and terminology, making implementation of PGx across all areas of genomic medicine difficult. To address this issue, the Clinical Genome Resource (ClinGen) Pharmacogenomics Working Group (PGxWG) was established by the National Institutes of Health (NIH)-funded ClinGen to initially create frameworks for evaluating gene-drug response clinical validity and actionability aligned with the ClinGen frameworks for evaluating monogenic gene-disease relationships, and a framework for classifying germline PGx variants similar to the American College of Medical Genetics (ACMG) and Association of Molecular Pathology (AMP) system for interpretation of disease-causing variants. These frameworks will leverage decades of work from well-established PGx resources facilitating buy-in among PGx stakeholders. In this report, we describe the background and major activities of the ClinGen PGxWG, and how this initiative will facilitate the critical inclusion of PGx into the larger context of genomic medicine.

The 2025 Pacific Symposium on Biocomputing (PSB) represents a remarkable milestone, as it is the thirtieth anniversary of PSB. We use this opportunity to analyze the bibliometric output of 30 years of PSB publications in a wide range of analyses with a focus on various eras that represent important disruptive breakpoints in the field of bioinformatics and biocomputing. These include an analysis of paper topics and keywords, flight emissions produced by travel to PSB by authors, citation and co-authorship networks and metrics, and a broad assessment of diversity and representation in PSB authors. We use the results of these analyses to identify insights that we can carry forward to the upcoming decades of PSB.

Pharmacogenetics represents one of the most promising areas of precision medicine, with several guidelines for genetics-guided treatment ready for clinical use. Despite this, implementation has been slow, with few health systems incorporating the technology into their standard of care. One major barrier to uptake is the lack of education and awareness of pharmacogenetics among clinicians and patients. The introduction of large language models (LLMs) like GPT-4 has raised the possibility of medical chatbots that deliver timely information to clinicians, patients, and researchers with a simple interface. Although state-of-the-art LLMs have shown impressive performance at advanced tasks like medical licensing exams, in practice they still often provide false information, which is particularly hazardous in a clinical context. To quantify the extent of this issue, we developed a series of automated and expert-scored tests to evaluate the performance of chatbots in answering pharmacogenetics questions from the perspective of clinicians, patients, and researchers. We applied this benchmark to state-of-the-art LLMs and found that newer models like GPT-4o greatly outperform their predecessors, but still fall short of the standards required for clinical use. Our benchmark will be a valuable public resource for subsequent developments in this space as we work towards better clinical AI for pharmacogenetics.

African Americans (AAs) are underrepresented in pharmacogenomics which has led to a significant gap in knowledge. AAs are admixed and can inherit specific loci from either their African or European ancestor, known as local ancestry (LA). A previous study in AAs identified single nucleotide polymorphisms (SNPs) located in the CYP2C cluster that are associated with warfarin dose. However, LA was not considered in this study. An IWPC cohort (N=340) was used to determine the LA-adjusted association with warfarin dose. Ancestry-specific GWAS's were conducted with TRACTOR and ancestry tracts were meta-analyzed using METAL. We replicated top associations in the independent ACCOuNT cohort of AAs (N=309) and validated associations in a warfarin pharmacokinetic study in AAs. To elucidate functional roles of top associations, we performed short-read RNA-sequencing from AA hepatocytes carrying each genotype for expression of CYP2C9 and CYP2C19. We identified 6 novel genome-wide significant SNPs (P<5E-8) in the CYP2C locus (lead SNP, rs7906871 (P=3.14E-8)). These associations were replicated (P≤2.76E-5) and validated with a pharmacokinetic association for S-Warfarin concentration in plasma (P=0.048). rs7906871 explains 6.0% of the variability in warfarin dose in AAs. Multivariate regression including rs7906871, previously associated SNPs, clinical and demographic factors explain 37% of dose variability, greater than previously reported studies in AAs. RNA-seq data in AA hepatocytes identified a significant alternate exon inclusion event between exons 6 and 7 in CYP2C19 for carriers of rs7906871. In conclusion, we have found and replicated a novel CYP2C variant associated with warfarin dose requirement and potential functional consequences to CYP2C19.

The Clinical Pharmacogenetics Implementation Consortium (CPIC) has advanced clinical pharmacogenomics since 2009 by developing freely available, evidence-based gene/drug guidelines. Covering 34 genes and 164 drugs, CPIC guidelines have become the global standard for translating pharmacogenomic test results into actionable prescribing decisions. This paper summarizes data highlighting CPIC's pivotal role in accelerating the global adoption of pharmacogenomics and establishing itself as the leading resource for clinical implementation. To assess CPIC's growth and impact, we analyzed member demographics, guideline characteristics, author composition, bibliometric data, database/API usage, and real-world implementation using internal tracking, external databases (Scopus, iCite), website analytics, PubMed review (2019-2024), and CPIC member surveys (2012, 2024). CPIC has 28 active guidelines with international authorship and widespread adoption, garnering over 10,000 citations and 1.4 million views. Robust implementation is evident, with 85% of PubMed-indexed pharmacogenomic implementation studies referencing CPIC guidelines. Additionally, 128 healthcare institutions and 40 commercial laboratories report using CPIC content. The CPIC API supports over 80,000 monthly queries, increasingly integrated into EHRs, including Epic's foundational genomics module. Member surveys show a shift from scientific evidence concerns to practical barriers like clinician education, reimbursement, and EHR integration. CPIC has evolved from a guideline development initiative into a global leader in pharmacogenomics implementation, fostering collaboration, standardization, and sustainable integration into diverse healthcare settings.

Clopidogrel, an anti-platelet drug, used to prevent thrombosis after percutaneous coronary intervention. Clopidogrel resistance results in recurring ischemic episodes, with African Americans suffering disproportionately. The aim of this study was to identify biomarkers of clopidogrel resistance in African American patients. We conducted a genome-wide association study, including local ancestry adjustment, in 141 African Americans on clopidogrel to identify associations with high on-treatment platelet reactivity (HTPR). We validated genome-wide and suggestive hits in an independent cohort of African American clopidogrel patients (N = 823) from the Million Veteran's Program (MVP) along with in vitro functional follow up. We performed differential gene expression (DGE) analysis in whole blood with functional follow-up in MEG-01 cells. We identified rs7807369, within thrombospondin 7A (THSD7A), as significantly associated with increasing risk of HTPR (p = 4.56 × 10-9). Higher THSD7A expression was associated with HTPR in an independent gene expression cohort of clopidogrel treated patients (p = 0.004) and supported by increased gene expression on THSD7A in primary human endothelial cells carrying the risk haplotype. Two SNPs (rs1149515 and rs191786) were validated in the MVP cohort. DGE analysis identified an association with decreased LAIR1 expression to HTPR. LAIR1 knockdown in a MEG-01 cells resulted in increased expression of SYK and AKT1, suggesting an inhibitory role of LAIR1 in the Glycoprotein VI pathway. Notably, the CYP2C19 variants showed no association with clopidogrel response in the discovery or MVP cohorts. In summary, these finding suggest that other variants outside of CYP2C19 star alleles play an important role in clopidogrel response in African Americans.

PURPOSE:Pharmacogenomics (PGx) is a critical component of precision health care that aims to improve drug efficacy and reduce adverse events. Terminologies and standards have not always aligned between PGx and broader genomic medicine communities, which is a barrier to PGx implementation. An updated assessment of community barriers, needs, and perspectives is critical to enable more standardized terminologies and interpretation frameworks. METHODS:The Clinical Genome Resource's PGx Interpretation Committee (PGxIC, formerly referred to as the PGx Working Group, PGxWG) conducted 2 surveys targeting the PGx and genomic medicine communities (n = 508) to evaluate perspectives on PGx clinical validity and actionability frameworks, as well as other barriers to PGx implementation. Surveys were tailored toward self-reported familiarity with PGx. Data primarily consisted of free text, which were analyzed using qualitative content analysis methods. RESULTS:Survey responses indicated conflation of terminology across disciplines, including confusion around differing definitions of terms in PGx and non-PGx contexts. Data also indicated broad support for leveraging existing PGx guidelines and framework structures alongside the standardization of approaches and centralization of resources. CONCLUSION:These novel survey results demonstrate broad consensus on the importance of integrating PGx into clinical practice, including support for development of gene-drug response clinical validity and actionability frameworks aligned with Clinical Genome Resource's frameworks for gene-disease relationships.

Hydralazine is a vasodilator typically used in the treatment of resistant hypertension and heart failure. N-acetyltransferase 2 (NAT2) catalyzes the metabolism of hydralazine into inactive metabolites. NAT2 poor metabolizers (historically referred to as "slow acetylators") are predicted to have increased plasma hydralazine concentrations compared with NAT2 rapid and intermediate metabolizers (historically referred to as "rapid acetylators" and "intermediate acetylators," respectively), which may lead to both increased clinical efficacy and adverse effects, including drug-induced systemic lupus erythematosus. This guideline summarizes the evidence from the literature relevant to NAT2/hydralazine and provides recommendations for hydralazine prescribing based on NAT2 genotype-predicted acetylator phenotype (updates at www.cpicpgx.org).

The Pharmacogene Variation Consortium (PharmVar) provides nomenclature for the human CYP2A gene locus containing the highly polymorphic CYP2A6 gene. CYP2A6 plays a role in the metabolism of nicotine and various drugs. Thus, genetic variation can substantially contribute to the function of this enzyme and associated efficacy and safety. This GeneFocus provides an overview of the clinical significance of CYP2A6, including its genetic variation and function. We also highlight and discuss caveats in the identification and characterization of allelic variation of this complex pharmacogene, a prerequisite for accurate genotype determination and prediction of phenotype status.

All authors declared no competing interests for this work.

Pharmacogenomics (PGx) is a rapidly advancing field that studies the relationship between an individual's genetic makeup and their response to medications, with goals to guide prescribing decisions to prevent toxicity and improve drug efficacy. Although clinical pharmacogenomic testing is increasingly available, the field currently does not have a structured framework to define PGx gene validity and variant classification, which is widely used in diagnostic genetic testing. The annotation and interpretation of pharmacogenomic data remain complex, time-consuming and require significant domain expertise.

The Gene Curation Coalition (GenCC) was formed in 2017 to bring together international resources reporting the validity of gene-disease relationships. It comprises organizations that currently provide online gene-level resources (ClinGen, Genomics England PanelApp, OMIM, Orphanet, PanelApp Australia, Gene2Phenotype Database), as well as diagnostic laboratories and platforms that have committed to sharing their internal curated gene-level knowledge (Ambry Genetics, Illumina Inc., Invitae, Franklin, King Faisal, Myriad Women’s Health, Mass General Brigham Laboratory for Molecular Medicine).

The Clinical Genome Resource (ClinGen) is a National Institutes of Health (NIH) funded effort (launched in 2013) to create a central resource of clinically relevant genes and variants for use in precision medicine and research. ClinGen relies on a large international network of participants such as clinicians, laboratory staff, and researchers to systematically evaluate genes and variants across multiple domains. As of November 2023, ClinGen includes over 2300 participants from 874 institutions in 65 countries.