Estimating the sensitivity of genomic newborn screening for treatable inherited metabolic disorders.

INTRODUCTION: Over 30 research groups and companies are exploring newborn screening using genomic sequencing (NBSeq), but the sensitivity of this approach is not well understood. METHODS: We identified individuals with treatable inherited metabolic disorders (IMDs) and ascertained the proportion whose DNA analysis revealed explanatory deleterious variants (EDVs). We examined variables associated with EDV detection and estimated the sensitivity of "DNA-first" NBSeq. We further predicted the annual rate of true positive and false negative NBSeq results in the United States for several conditions on the Recommended Uniform Screening Panel (RUSP). RESULTS: We identified 635 individuals with 80 unique IMDs. In univariate analyses, Black race (OR = 0.37, 95% CI: 0.16-0.89, p = 0.02) and public insurance (OR = 0.60, 95% CI: 0.39-0.91, p = 0.02) were less likely to be associated with finding EDVs. Had all individuals been screened with NBSeq, the sensitivity would have been 80.3%. We estimated that between 0 and 649.9 cases of RUSP IMDs would be missed annually by NBSeq in the United States. CONCLUSIONS: The overall sensitivity of NBSeq for treatable IMDs is estimated at 80.3%. That sensitivity will likely be lower for Black infants and those who are on public insurance.

The BabySeq Project: A clinical trial of genome sequencing in a diverse cohort of infants.

Efforts to implement and evaluate genome sequencing (GS) as a screening tool for newborns and infants are expanding worldwide. The first iteration of the BabySeq Project (2015-2019), a randomized controlled trial of newborn sequencing, produced novel evidence on medical, behavioral, and economic outcomes. The second iteration of BabySeq, which began participant recruitment in January 2023, examines GS outcomes in a larger, more diverse cohort of more than 500 infants up to one year of age recruited from pediatric clinics at several sites across the United States. The trial aims for families who self-identify as Black/African American or Hispanic/Latino to make up more than 50% of final enrollment, and key aspects of the trial design were co-developed with a community advisory board. All enrolled families receive genetic counseling and a family history report. Half of enrolled infants are randomized to receive GS with comprehensive interpretation of pathogenic and likely pathogenic variants in more than 4,300 genes associated with childhood-onset and actionable adult-onset conditions, as well as larger-scale chromosomal copy number variants classified as pathogenic or likely pathogenic. GS result reports include variants associated with disease (Mendelian disease risks) and carrier status of autosomal-recessive and X-linked disorders. Investigators evaluate the utility and impacts of implementing a GS screening program in a diverse cohort of infants using medical record review and longitudinal parent surveys. In this perspective, we describe the rationale for the second iteration of the BabySeq Project, the outcomes being assessed, and the key decisions collaboratively made by the study team and community advisory board.

Primary Care Providers' Experiences With an Active Elective Genetic Testing Program.

Elective genetic testing (EGT) programs that provide pharmacogenomic information to guide medication management and screen for medically actionable disease predispositions are emerging in a number of health systems. Primary care providers (PCPs) are at the forefront of test initiation, patient education, and management of EGT results. However, little research has examined the experiences of PCPs in health systems offering clinical EGT. We conducted semi-structured interviews, a sub-study of the larger mixed-methods Imagenetics Initiative, with 16 PCPs at a health system in the Midwest with a clinical EGT program supported by provider education, automated clinical decision support, and enhanced access to genetic specialists. The purpose of these interviews was to understand perceptions about the benefits and barriers of implementing EGT in clinical practice. Thematic analysis indicated that EGT is conceptualized similar to traditional diagnostic services. PCPs were generally favorable toward EGT; however, targeted education did not dispel misconceptions about the goals, results, and limitations of EGT. Most PCPs endorsed the potential utility of EGT. Pharmacogenomic profiling was seen as having more immediate impact for patients than screening for monogenic disease risks. PCPs reported that they weighed discussions about EGT against time limitations and the need to prioritize patients' existing health concerns. Regardless of their education levels and familiarity with genetics, PCPs desired additional educational resources and greater access to genetic specialists. Our study provides unique insight into PCPs' experiences with clinical EGT in health systems that have adopted EGT and highlights the practical challenges and potential opportunities of EGT integration.

Attitudes, knowledge, and risk perceptions of patients who received elective genomic testing as a clinical service.

PURPOSE: Elective genomic testing (EGT) is increasingly available clinically. Limited real-world evidence exists about attitudes and knowledge of EGT recipients. METHODS: After web-based education, patients who enrolled in an EGT program at a rural nonprofit health care system completed a survey that assessed attitudes, knowledge, and risk perceptions. RESULTS: From August 2020 to April 2022, 5920 patients completed the survey and received testing. Patients most frequently cited interest in learning their personal disease risks as their primary motivation. Patients most often expected results to guide medication management (74.0%), prevent future disease (70.4%), and provide information about risks to offspring (65.4%). Patients were "very concerned" most frequently about the privacy of genetic information (19.8%) and how well testing predicted disease risks (18.0%). On average, patients answered 6.7 of 11 knowledge items correctly (61.3%). They more often rated their risks for colon and breast cancers as lower rather than higher than the average person but more often rated their risk for a heart attack as higher rather than lower than the average person (all P < .001). CONCLUSION: Patients pursued EGT because of the utility expectations but often misunderstood the test's capabilities.

Familial communication and cascade testing following elective genomic testing.

Familial communication of results and cascade genetic testing (CGT) can extend the benefits of genetic screening beyond the patient to their at-risk relatives. While an increasing number of health systems are offering genetic screening as an elective clinical service, data are limited about how often results are shared and how often results lead to CGT. From 2018 to 2022, the Sanford Health system offered the Sanford Chip, an elective genomic test that included screening for medically actionable predispositions for disease recommended by the American College of Medical Genetics and Genomics for secondary findings disclosure, to its adult primary care patients. We analyzed patient-reported data about familial sharing of results and CGT among patients who received Sanford Chip results at least 1 year previously. Among the patients identified with medically actionable predispositions, 94.6% (53/56) reported disclosing their result to at least one family member, compared with 46.7% (423/906) of patients with uninformative findings (p < 0.001). Of the patients with actionable predispositions, 52.2% (12/23) with a monogenic disease risk and 12.1% (4/33) with a carrier status reported that their relatives underwent CGT. Results suggest that while the identification of monogenic risk during elective genomic testing motivates CGT in many at-risk relatives, there remain untested at-risk relatives who may benefit from future CGT. Findings identify an area that may benefit from increased genetic counseling and the development of tools and resources to encourage CGT for family members.

Evaluating the utility of multi-gene, multi-disease population-based panel testing accounting for uncertainty in penetrance estimates.

Panel germline testing allows for the efficient detection of deleterious variants for multiple conditions, but the benefits and harms of identifying these variants are not always well understood. We present a multi-gene, multi-disease aggregate utility formula that allows the user to consider adding or removing each gene in a panel based on variant frequency, estimated penetrances, and subjective disutilities for testing positive but not developing the disease and testing negative but developing the disease. We provide credible intervals for utility that reflect uncertainty in penetrance estimates. Rare, highly penetrant deleterious variants tend to contribute positive net utilities for a wide variety of user-specified disutilities, even when accounting for parameter estimation uncertainty. However, the clinical utility of deleterious variants with moderate, uncertain penetrance depends more on assumed disutilities. The decision to include a gene on a panel depends on variant frequency, penetrance, and subjective utilities and should account for uncertainties around these factors.

Data-driven prioritization of genetic disorders for global genomic newborn screening programs.

Genomic sequencing is poised to expand newborn screening for treatable childhood-onset disorders. Over 30 international research studies and companies are exploring its use, collectively aiming to screen more than 500,000 infants. A key challenge is determining which genes to include in screening. Among 27 newborn sequencing programs, the number of genes analyzed ranged from 134 to 4,299, with only 74 genes included by over 80% of programs. To understand this variability, we assembled a dataset with 25 characteristics of 4,389 genes included in any program and used a multivariate regression analysis to identify characteristics associated with inclusion across programs. These characteristics included presence on the US Recommended Uniform Screening panel, evidence regarding the natural history of disease, and efficacy of treatment. We then used a machine learning model to generate a ranked list of genes, offering a data-driven approach to the future prioritization of disorders for public health newborn screening efforts.

Managing differential performance of polygenic risk scores across groups: Real-world experience of the eMERGE Network.

The differential performance of polygenic risk scores (PRSs) by group is one of the major ethical barriers to their clinical use. It is also one of the main practical challenges for any implementation effort. The social repercussions of how people are grouped in PRS research must be considered in communications with research participants, including return of results. Here, we outline the decisions faced and choices made by a large multi-site clinical implementation study returning PRSs to diverse participants in handling this issue of differential performance. Our approach to managing the complexities associated with the differential performance of PRSs serves as a case study that can help future implementers of PRSs to plot an anticipatory course in response to this issue.

Maximizing matching, equity and survival in kidney transplantation using molecular HLA immunogenicity quantitation.

HLA matching improves long-term outcomes of kidney transplantation, yet implementation challenges persist, particularly within the African American (Black) patient demographic due to donor scarcity. Consequently, kidney survival rates among Black patients significantly lag behind those of other racial groups. A refined matching scheme holds promise for improving kidney survival, with prioritized matching for Black patients potentially bolstering rates of HLA-matched transplants. To facilitate quantity, quality and equity in kidney transplants, we propose two matching algorithms based on quantification of HLA immunogenicity using the hydrophobic mismatch score (HMS) for prospective transplants. We mined the national transplant patient database (SRTR) for a diverse group of donors and recipients with known racial backgrounds. Additionally, we use novel methods to infer survival assessment in the simulated transplants generated by our matching algorithms, in the absence of actual target outcomes, utilizing modified unsupervised clustering techniques. Our allocation algorithms demonstrated the ability to match 87.7% of Black and 86.1% of White recipients under the HLA immunogenicity threshold of 10. Notably, at the lowest HMS threshold of 0, 4.4% of Black and 12.1% of White recipients were matched, a marked increase from the 1.8% and 6.6% matched under the prevailing allocation scheme. Furthermore, our allocation algorithms yielded similar or improved survival rates, as illustrated by Kaplan-Meier (KM) curves, and enhanced survival prediction accuracy, evidenced by C-indices and Integrated Brier Scores.

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 Alzheimer's Disease Neuroimaging Initiative in the era of Alzheimer's disease treatment: A review of ADNI studies from 2021 to 2022.

The Alzheimer's Disease Neuroimaging Initiative (ADNI) aims to improve Alzheimer's disease (AD) clinical trials. Since 2006, ADNI has shared clinical, neuroimaging, and cognitive data, and biofluid samples. We used conventional search methods to identify 1459 publications from 2021 to 2022 using ADNI data/samples and reviewed 291 impactful studies. This review details how ADNI studies improved disease progression understanding and clinical trial efficiency. Advances in subject selection, detection of treatment effects, harmonization, and modeling improved clinical trials and plasma biomarkers like phosphorylated tau showed promise for clinical use. Biomarkers of amyloid beta, tau, neurodegeneration, inflammation, and others were prognostic with individualized prediction algorithms available online. Studies supported the amyloid cascade, emphasized the importance of neuroinflammation, and detailed widespread heterogeneity in disease, linked to genetic and vascular risk, co-pathologies, sex, and resilience. Biological subtypes were consistently observed. Generalizability of ADNI results is limited by lack of cohort diversity, an issue ADNI-4 aims to address by enrolling a diverse cohort.

Decoding Genetics, Ancestry, and Geospatial Context for Precision Health.

Mass General Brigham, an integrated healthcare system based in the Greater Boston area of Massachusetts, annually serves 1.5 million patients. We established the Mass General Brigham Biobank (MGBB), encompassing 142,238 participants, to unravel the intricate relationships among genomic profiles, environmental context, and disease manifestations within clinical practice. In this study, we highlight the impact of ancestral diversity in the MGBB by employing population genetics, geospatial assessment, and association analyses of rare and common genetic variants. The population structures captured by the genetics mirror the sequential immigration to the Greater Boston area throughout American history, highlighting communities tied to shared genetic and environmental factors. Our investigation underscores the potency of unbiased, large-scale analyses in a healthcare-affiliated biobank, elucidating the dynamic interplay across genetics, immigration, structural geospatial factors, and health outcomes in one of the earliest American sites of European colonization.

The GenoVA study: Equitable implementation of a pragmatic randomized trial of polygenic-risk scoring in primary care.

Polygenic risk scores (PRSs) hold promise for disease risk assessment and prevention. The Genomic Medicine at Veterans Affairs (GenoVA) Study is addressing three main challenges to the clinical implementation of PRSs in preventive care: defining and determining their clinical utility, implementing them in time-constrained primary care settings, and countering their potential to exacerbate healthcare disparities. The study processes used to test patients, report their PRS results to them and their primary care providers (PCPs), and promote the use of those results in clinical decision-making are modeled on common practices in primary care. The following diseases were chosen for their prevalence and familiarity to PCPs: coronary artery disease; type 2 diabetes; atrial fibrillation; and breast, colorectal, and prostate cancers. A randomized clinical trial (RCT) design and primary outcome of time-to-new-diagnosis of a target disease bring methodological rigor to the question of the clinical utility of PRS implementation. The study's pragmatic RCT design enhances its relevance to how PRS might reasonably be implemented in primary care. Steps the study has taken to promote health equity include the thoughtful handling of genetic ancestry in PRS construction and reporting and enhanced recruitment strategies to address underrepresentation in research participation. To date, enhanced recruitment efforts have been both necessary and successful: participants of underrepresented race and ethnicity groups have been less likely to enroll in the study than expected but ultimately achieved proportional representation through targeted efforts. The GenoVA Study experience to date offers insights for evaluating the clinical utility of equitable PRS implementation in adult primary care.

An Ethical Framework for Research Using Genetic Ancestry.

A wide range of research uses patterns of genetic variation to infer genetic similarity between individuals, typically referred to as genetic ancestry. This research includes inference of human demographic history, understanding the genetic architecture of traits, and predicting disease risk. Researchers are not just structuring an intellectual inquiry when using genetic ancestry, they are also creating analytical frameworks with broader societal ramifications. This essay presents an ethics framework in the spirit of virtue ethics for these researchers: rather than focus on rule following, the framework is designed to build researchers' capacities to react to the ethical dimensions of their work. The authors identify one overarching principle of intellectual freedom and responsibility, noting that freedom in all its guises comes with responsibility, and they identify and define four principles that collectively uphold researchers' intellectual responsibility: truthfulness, justice and fairness, anti-racism, and public beneficence. Researchers should bring their practices into alignment with these principles, and to aid this, the authors name three common ways research practices infringe these principles, suggest a step-by-step process for aligning research choices with the principles, provide rules of thumb for achieving alignment, and give a worked case. The essay concludes by identifying support needed by researchers to act in accord with the proposed framework.

Phenotypes of undiagnosed adults with actionable OTC and GLA variants.

Inherited metabolic disorders (IMDs) are variably expressive, complicating identification of affected individuals. A genotype-first approach can identify individuals at risk for morbidity and mortality from undiagnosed IMDs and can lead to protocols that improve clinical detection, counseling, and management. Using data from 57,340 participants in two hospital biobanks, we assessed the frequency and phenotypes of individuals with pathogenic/likely pathogenic variants (PLPVs) in two IMD genes: GLA, associated with Fabry disease, and OTC, associated with ornithine transcarbamylase deficiency. Approximately 1 in 19,100 participants harbored an undiagnosed PLPV in GLA or OTC. We identified three individuals (2 male, 1 female) with PLPVs in GLA, all of whom were undiagnosed, and three individuals (3 female) with PLPVs in OTC, two of whom were undiagnosed. All three individuals with PLPVs in GLA (100%) had symptoms suggestive of mild Fabry disease, and one individual (14.2%) had an ischemic stroke at age 33, likely indicating the presence of classic disease. No individuals with PLPVs in OTC had documented hyperammonemia despite exposure to catabolic states, but all (100%) had chronic symptoms suggestive of attenuated disease, including mood disorders and migraines. Our findings suggest that GLA and OTC variants identified via a genotype-first approach are of high penetrance and that population screening of these genes can be used to facilitate stepwise phenotyping and appropriate care.

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.

Actionability of unanticipated monogenic disease risks in newborn genomic screening: Findings from the BabySeq Project.

Newborn genomic sequencing (NBSeq) to screen for medically important genetic information is of considerable interest but data characterizing the actionability of such findings, and the downstream medical efforts in response to discovery of unanticipated genetic risk variants, are lacking. From a clinical trial of comprehensive exome sequencing in 127 apparently healthy infants and 32 infants in intensive care, we previously identified 17 infants (10.7%) with unanticipated monogenic disease risks (uMDRs). In this analysis, we assessed actionability for each of these uMDRs with a modified ClinGen actionability semiquantitative metric (CASQM) and created radar plots representing degrees of penetrance of the condition, severity of the condition, effectiveness of intervention, and tolerability of intervention. In addition, we followed each of these infants for 3-5 years after disclosure and tracked the medical actions prompted by these findings. All 17 uMDR findings were scored as moderately or highly actionable on the CASQM (mean 9, range: 7-11 on a 0-12 scale) and several distinctive visual patterns emerged on the radar plots. In three infants, uMDRs revealed unsuspected genetic etiologies for existing phenotypes, and in the remaining 14 infants, uMDRs provided risk stratification for future medical surveillance. In 13 infants, uMDRs prompted screening for at-risk family members, three of whom underwent cancer-risk-reducing surgeries. Although assessments of clinical utility and cost-effectiveness will require larger datasets, these findings suggest that large-scale comprehensive sequencing of newborns will reveal numerous actionable uMDRs and precipitate substantial, and in some cases lifesaving, downstream medical care in newborns and their family members.