Genetics in Medicine Open

Neural networks have shown strong potential to aid the practice of healthcare. Mainly due to the need for large datasets, these applications have focused on common medical conditions, where much more data is typically available. Leveraging publicly available data, we trained a neural network classifier on images of rare genetic conditions with skin findings. We used approximately100 images per condition to classify 6 different genetic conditions. Unlike other work related to these types of images, we analyzed both preprocessed images that were cropped to show only the skin lesions, as well as more complex images showing features such as the entire body segment, patient, and/or the background. The classifier construction process included attribution methods to visualize which pixels were most important for computer-based classification. Our classifier was significantly more accurate than pediatricians or medical geneticists for both types of images. Next, we trained two generative adversarial networks to generate new images. The first involved all of the genetic conditions and was used for style-mixing to demonstrate how the diversity of small datasets can be increased. The second focused on different disease stages for one condition and depicted how morphing can illustrate the disease progression of this condition. Overall, our findings show how computational techniques can be applied in multiple ways to small datasets to enhance the study of rare genetic diseases.

Background: Pretest genetic counseling (GC) is recommended in conjunction with genetic testing (GT) for cardiovascular (CV) indications, yet access to CVGC is limited leading to delayed GT. Posttest GC could increase GC and GT access but requires efficient pretest education that supports both informed GT decision-making and robust GT uptake. Methods: We developed four indication-tailored online CV genetics education videos and deployed them in a 3-arm randomized trial comparing pretest vs. posttest outpatient CVGC (RESEQUENCE-GC, NCT05422573). Participants were 1:1:1 randomized to pretest video education plus an optional (efficiency arm) or required (flipped arm) phone call with a genetic counselor and planned posttest CVGC or to standard pretest CVGC (SOC arm). Questionnaires administered at baseline and post-education included the CV Multidimensional Model of Informed Choice [MMIC] to quantify GT knowledge and informed GT choice. Results: 389/767 (50.7%) adults aged 18-80 (mean 51.2{+/-}14.9 years) scheduling a first CVGC appointment consented to RESEQUENCE-GC and completed the baseline questionnaire. Efficiency arm participants (video education + optional phone call) were most likely to complete pretest education (134, 97.4% efficiency; 107, 85.6% flipped; 111, 87.4% SOC, p=0.0012) and elect GT (131, 95.6% efficiency; 105, 84.0% flipped; 107, 84.2% SOC, p=0.0036). Few (4, 2.9%) efficiency arm participants requested an optional pretest phone call. Most flipped arm participants (90, 84.1%) had no post-video questions, consistent with the 97 second [IQR: 65s-145s] median call duration. CV genetics knowledge was high post-education (median 8 [IQR 7,8]/8 MMIC items correct). Only video-based pretest education was associated with a significant increase in knowledge (p<0.0001). Nearly all participants made an informed GT choice with no difference between intervention (95.6%) and SOC (90.4%) arms (p=0.074). Conclusions: Tailored, online video pretest education can enhance CV GT uptake, support informed GT decision-making, and be integrated into efficient pretest workflows, suggesting utility in scalable posttest CVGC.

BackgroundA vision of lifelong genomic medicine, in which stored genomic data can inform a lifetime of care has long animated the field of genomic medicine. Component pieces of this vision are being researched or are already in clinical practice, including dozens of projects around the world sequencing healthy newborns, along with reanalysis of stored genomic data. Whether lifelong genomic medicine is desirable, and, if so, whether it is feasible, has not been explored in the literature. Methods and FindingsWe conducted and thematically analyzed interviews with over 50 US-based healthcare professionals, including clinical geneticists, genetic counselors, primary care clinicians, laboratory personnel, and those who have implemented genomic screening in health systems. We found broad endorsement of the value of lifelong genomic medicine across groups. Perceived clinical value stemmed from the existence of genomic information relevant at multiple stages of life, the ability to query the genome if an individuals medical circumstances change, and the ability to inform patients about relevant evolving scientific advances. Participants also articulated an efficiency argument for reanalyzing stored genomic data rather than retesting. The clinical value was contested by a few participants, who argued for more targeted testing for the clinical situation and disputed the efficiency argument. Many participants viewed the model as inevitable, with operational precedent already established for many component activities. The feasibility of lifelong genomic medicine was limited not by scientific barriers but by governance gaps spanning delivery models, consent, data stewardship, recontact, and the pediatric-to-adult transition. These gaps have equity implications that are cumulative and mutually reinforcing. ConclusionsThe concept of lifelong genomic medicine was widely viewed as acceptable and desired. However, until the governance infrastructure is established, including accountability, funding, data stewardship, and recontact mechanisms, population-scale genomic sequencing risks proceeding faster than the frameworks needed to make it responsible.

Electronic consultation (e-Consult) programs serve as a conduit between healthcare providers and specialized genetic experts. This retrospective chart review and summary report presents the experience of implementing a Genetics e-Consult Service at the University of California San Francisco (UCSF) from 2016 through 2024 across multiple disciplines. The study examines 622 requests managed by the Genetics team, resulting in the completion of 360 e-Consults (57.8%) and the decline of 262 e-Consults (42.1%). Provider-to-provider consultations, conducted by board-certified geneticists, were completed within 3 days (83.9%), with consultation times ranging from 5 to 20 minutes in most cases (67%). Most requests originated from general practitioners in primary care, pediatrics, and family medicine (48.1%). Analysis of a subset of e-Consults (n=144) revealed that diagnostic queries accounted for 50.6% of requests, followed by management of symptoms (17%) and test interpretation (11%). Providers adhered to geneticists recommendations in 84% of cases. These findings underscore the potential of e-Consult frameworks as a viable strategy to enhance accessibility to genetic healthcare services.

BackgroundPatients are increasingly obtaining genetic health information and integrating it into their care with the help of their primary care provider (PCP). However, PCPs may not be adequately prepared to effectively utilize genetic results . Across the VA health system, the Million Veteran Program-Return of Actionable Results-Familial Hypercholesterolemia (MVP-ROAR) study clinically confirms and returns genetic results associated with familial hypercholesterolemia (FH), identified in a national biobank program. MethodsPCPs who received their patients genetic results through the MVP-ROAR Study were invited to participate in semi-structured interviews, which explored PCPs familiarity with FH, how the results impacted medical management, and suggestions for process improvement. Interviews were transcribed and analyzed using directed content analysis and constant comparison methods to identify key themes. ResultsInterviews with nine PCPs revealed varied levels of familiarity with genetic testing and FH. Most PCPs did not distinguish FH from common high cholesterol issues and already used similar treatment approaches. Many PCPs did not recall receiving results from the MVP-ROAR Study. Alerts in medical records were deemed effective for communicating results. PCPs valued genetics in informing patient care and identifying at-risk family members but noted several implementation barriers, such as additional workload and unclear medical management benefits. Recommendations for improving results disclosure included simplifying the genetic testing report and associated support documents. ConclusionThe study represents the first investigation into PCPs experiences with receiving genetic test results from a biobank linked to a national healthcare system. Results suggest that PCPs generally view genetic testing as beneficial, though they may not significantly alter medical management. PCPs expressed that integrating genetics into routine care may be burdensome and require additional training, which may not be practical. The study underscores the need for accessible genetic information, which could be aided by specialized support roles or different clinical specialties assisting with incorporating genetic results into patient care.

Approximately 200 critically ill infants and children in New Zealand are in high-dependency neonatal/paediatric acute care at any given time, many with suspected genetic conditions, necessitating a scalable distributed solution for rapid genomic testing. We adopt the existing acute care genomics protocol of an accredited laboratory and established an expandable acute care clinical pipeline based around the Oxford Nanopore Technologies PromethION 2 solo system connected to a Bayesian AI-based clinical decision support tool (Fabric GEM software). In the establishment phase, we performed benchmarking using Global Alliance for Genomics and Health (GA4GH) benchmarking tools and Genome in a Bottle samples HG002-HG007. We evaluated single nucleotide variants (SNVs) and small insertions-deletions (indels) calls and achieved SNV precision and recall of 0.997 {+/-} 0.0006 and 0.992 {+/-} 0.001, respectively. Small indel identification approached a precision of 0.922 {+/-} 0.019 and recall of 0.838 {+/-} 0.043. Rarefaction analyses demonstrated that SNV identification plateaus at [~]20X coverage, while small indels plateaus at [~]40X coverage. Large genomic variations from Coriell Copy Number Variation Reference Panel 1 (CNVPANEL01) were reliably detected with [~]2M long reads. Finally, we present results obtained from ten trio samples that were processed through the pipeline validation phase, averaging a 5-day turnaround time, conducted in parallel with a clinically accredited short-read rapid genomic testing pipeline.

BackgroundGermline cancer genetic testing has become a standard evidence-based practice, with established risk reduction and cancer screening guidelines for genetic carriers. There are also targeted treatments for some genetic carriers with cancers such as breast and ovarian cancer. Yet, many at-risk patients do not have access to genetic services, leaving many genetic carriers unidentified. The eREACH 2 study (A Randomized Hybrid Type I Effectiveness-Implementation Study of an eReach Delivery Alternative for Cancer Genetic Testing for Hereditary Cancer) evaluates whether an interactive, patient-centered digital alternative for genetic education and disclosure of results is non-inferior compared to the traditional model of pre-and post-test counseling with a genetic counselor. MethodsThis is a Hybrid Type 1 effectiveness implementation study in which participants are randomized using a 2x2 design to test a self-directed, patient-informed, digital intervention to deliver clinical genetic testing versus the traditional pre-test (visit 1) and post-test (visit 2: disclosure) counseling delivered by a genetic counselor. The 4 arms include A) genetic counselor for visit 1 and visit 2, B) genetic counselor for visit 1 and digital intervention for visit 2, C) digital intervention for visit 1 and genetic counselor for visit 2, and D) digital intervention for both visits. Participants are adults who meet National Comprehensive Cancer Network and/or American Society of Clinical Oncology guidelines for germline genetic testing and are recruited from both community and medical sites across the United States by way of clinician referral as well as patient self-referral. The primary outcomes are non-inferiority in uptake of genetic testing and change in genetic knowledge and general anxiety from baseline to post-disclosure. DiscussionWith many barriers to accessing genetic services, innovative delivery models are needed to address these gaps and increase uptake of genetic services. The eREACH2 study evaluates the effectiveness of an interactive patient-centered digital intervention to deliver clinical genetic testing. We expect this work will inform evidence-based guidelines and the standard-of-care for delivery of genetic testing and is designed to be broadly applicable and easily adaptable for other populations and settings even beyond oncology (e.g. Alzheimers disease). Trial registrationThis protocol was registered at clinicaltrials.gov (NCT05427240) on 6/7/2022.

ObjectiveTo develop and implement a pipeline for integrated breast cancer risk assessment using the BOADICEA model within the eMERGE study, incorporating polygenic risk scores (PRS), monogenic variants, family history, and clinical factors. Materials and MethodsA pipeline was deployed across ten eMERGE clinical sites, integrating data from REDCap surveys, PRS reports, monogenic reports, and pedigrees via CanRisk Application Programming Interface (API). The process included design, customization, technical implementation, testing, and refinement. ResultsThe pipeline successfully generated integrated risk scores for >10,000 females. Of these, 3.6% were classified as high-risk ([&ge;]25% lifetime risk), and 0.9% harbored rare pathogenic variants in BRCA1, BRCA2, PALB2, or PTEN. High PRS only scores were identified in 5.6% of participants. Among those with high PRS, 34% also had high-risk based on integrated scores. API and User Interface (UI) results were highly concordant, with an average difference of 0.13%. DiscussionKey challenges included integrating diverse data sources, handling missing data, and standardizing pedigree formats. Risk classification discrepancies highlighted the need for refined communication strategies. ConclusionThis study demonstrates the feasibility of PRS-integrated breast cancer risk assessment in clinical settings but underscores challenges in data integration and risk communication. Future work should enhance recalibration for diverse populations and streamline workflows for risk interpretation and update.

Canavan disease (CD) is a neurodegenerative disorder caused by biallelic disease-causing variants in the ASPA gene. Here, we utilized long-read sequencing (LRS) to investigate eight individuals clinically diagnosed with Canavan disease but without definitive genetic diagnoses. Our analyses identified a recurring previously unreported intronic SVA_E retrotransposon insertion within ASPA in all eight individuals. Surprisingly, the frequency of this variant in population databases suggests it is the most common pathogenic variant in ASPA and should be evaluated in diagnostic testing and carrier screening for CD. Additionally, this finding has implications for the broader rare disease community, as it highlights a substantial blind spot in standard short-read diagnostic pipelines, which historically have missed or overlooked these types of insertions. This discovery highlights the power of emerging technologies, such as LRS and RNA-sequencing (RNA-seq), to bring new classes of variants into diagnostic utility for genetic disorders like CD.

PurposeThe pathogenicity of intragenic duplications depends on their structural configuration. Tandem duplications often disrupt reading frames and cause gene loss-of-function, whereas interspersed (non-tandem) duplications are largely benign. When the configuration cannot be determined, current guidelines presume a tandem structure, leading to some laboratories automatically classifying such variants as likely pathogenic or pathogenic. This study evaluates the validity of this presumption for DMD, in patients with and without clinical indications of dystrophinopathy. MethodsWe performed high-coverage whole-genome long-read sequencing on 15 patients with intragenic DMD duplications. Four patients had clinically indicated dystrophinopathy testing, while in the remaining 11 patients, the duplications were detected without clear indications of dystrophinopathy (e.g., "incidentally detected" through carrier screening). ResultsAll four patients with clinical indications had tandem duplications. In contrast, 64% (7/11) of the incidentally detected cases had interspersed duplications, with four subsequently re-classified as likely benign, two likely pathogenic, and one uncertain. These duplications were often complex, involving co-duplications or co-deletions with other regions. ConclusionOur findings challenge the presumption that intragenic DMD duplications are predominantly tandem. This highlights the need for a cautious variant interpretation approach, particularly in carrier screening and other settings where variants are identified without indications of dystrophinopathy.

Changes in genetics and genomics sequencing in recent years have created increased demand for genetics professionals, including clinical geneticists and genetic counselors. A significant workforce shortage of these professionals has become widely recognized. This shortage is driven by several factors, including the increased role of genetics in healthcare due to precision medicine initiatives and demand outside of medical practices in clinical and direct-to-consumer genetic testing companies that require genetics professionals for education and counseling. We developed the Consultagene virtual platform for delivery of genetic care, counseling, and education to address some of these issues that have become global challenges in the field of clinical genetics and to bridge existing gaps at the point of care. The platform provides access to specific content based upon the referral indication including educational videos and resource links, allows document sharing, health and history information gathering and appointment scheduling with persistent access to the materials via secure data infrastructure. Having the platform coupled with access to our tele- and video consultation service allows clients convenient on-demand access to genetic education and services as needed. This report describes the Consultagene platform development and use prior to and during the COVID-19 pandemic, some of the identified strengths and weaknesses of such a platform, and the current applications in the new environment where telemedicine practice has rapidly expanded. Topic SummaryConsultagene is the first academic virtual platform to integrate a comprehensive range of genetics services including genetics education, genetics consultation, and genetic counseling. Consultagene addresses the increasing demands and unmet, evolving needs for genetic services due to widely available genomic sequencing and the platform seamlessly adapted to the pandemic-induced adjustments to clinical practice.

PurposeWe previously developed Haploseek, a clinically-validated, variant-agnostic comprehensive preimplantation genetic testing (PGT) solution. Haploseek is based on microarray genotyping of the embryos parents and relatives, combined with low-pass sequencing of the embryos. Here, to increase throughput and versatility, we aimed to develop a sequencing-only implementation of Haploseek. MethodsWe developed SHaploseek, a universal PGT method to determine genome-wide haplotypes of each embryo based on low-pass ([&le;]5x) sequencing of the parents and relative(s) along with ultra-low pass (0.2-0.4x) sequencing of the embryos. We used SHaploseek to analyze five single lymphoblast cells and 31 embryos from 14 families. We validated the genome-wide haplotype predictions against either bulk DNA, Haploseek, or, at focal genomic sites, PCR-based PGT results. ResultsSHaploseek achieved >99% concordance with bulk DNA in two families from which single cells were derived from grown-up children. In embryos from 12 PGT families, all of SHaploseeks focal site haplotype predictions were concordant with clinical PCR-based PGT results. Genome-wide, there was >99% median concordance between Haploseek and SHaploseeks haplotype predictions. Concordance remained high at all assayed sequencing depths [&ge;]2x, as well as with only 1ng of parental DNA input. In subtelomeric regions, significantly more haplotype predictions were high-confidence in SHaploseek compared to Haploseek. ConclusionAs a single-platform comprehensive PGT solution with higher sensitivity in subtelomeric regions, SHaploseek constitutes a significantly improved, accurate, and cost-effective re-embodiment of Haploseek.

With FDA approval of targeted therapies in patients with germline BRCA1/2-related advanced cancers there is a need to evaluate efficient and effective delivery models for germline cancer genetic testing. We sought to evaluate the effectiveness of replacing traditional pretest and posttest counseling with a genetic counselor (GC) with a digital intervention in patients with metastatic cancers. eREACH is a 4-arm randomized non-inferiority trial with a 2x2 design conducted from 2020-2024 and participants were followed for 6 months. Participants were recruited from the community and academic and community medical sites across the United States. A referred sample of adults with advanced or metastatic breast, prostate, ovarian or pancreatic cancer. The digital pretest intervention consists of 8 modules including purpose of genetic testing and implications of results. The digital post-test intervention consists of 4 modules including test results and explanation of results. The primary endpoint was non-inferiority in change in knowledge and anxiety from baseline to post-disclosure. Secondary analyses evaluated patient-reported outcomes (PROs) such as depression and distress, and moderators of PROs such as socioeconomic status. 229 participants were recruited from 14 states and 37% were male, 17% were non-white, 43% had less than a college education and 21% were from community sites or national recruitment. We met non-inferiority for all short-term PROs for both one visit arms (GC/Digital, Digital/GC). We met non-inferiority for all short-term PROs in the fully digital arm except knowledge which was inconclusive, although differences were small. Uptake of visit 1 was lower in the digital arms, although uptake of testing after visit 1 did not differ between arms. Patients living in poorer areas had greater reductions in anxiety in the visit 1 GC arms and rural patients had greater increase in knowledge in digital arms. Men had greater decreases in anxiety with digital disclosure, while women had greater reductions with GC disclosure. The eREACH patient-centered digital delivery intervention with one GC visit is an evidence-based alternative to two visits with a GC for patients with metastatic cancer. The fully digital model may be acceptable for some patients.

Digital interventions are potentially promising to improve accessibility and efficiency of genetic counselling services. However, current literature on stakeholder perspectives towards digital tools for cascade testing is limited. Therefore, this focus group study aimed to gain insights into the attitude and perspectives of probands, at-risk relatives (ARR), and genetic healthcare professionals (HCP) towards digital innovations for assistance with both pre-test and post-test counselling and cascade genetic testing in cardiogenetics. We conducted seven online focus groups, which where transcribed and thematically analysed. In total, 37 individuals participated (10 probands, 11 ARR and 16 HCP). Thematic analysis of focus group transcripts showed a first theme of (1) acceptability of digital tools. Other identified themes were defined as domains where digital tools impact traditional, in-person clinical genetic care, being: (2) family communication, (3) decision-making, (4) care relations, and (5) the genetic care system. Stakeholders expressed a predominantly positive attitude towards digitisation of (parts of) the predictive genetic counselling in cardiogenetics, under the condition that access to human contact is preserved. In the clinical setting of predictive counselling, efforts should be made to ensure access to genetic services for all ARR and to protect in-person involvement of HCP.

Splice variants are known to cause diseases by utilizing alternative splice sites, potentially resulting in protein truncation or mRNA degradation by nonsense-mediated decay. Splice variants are verified when altered mature mRNA sequences are identified in RNA analyses or minigene assays. Using a quantitative minigene assay, qMini, we uncovered a previously overlooked class of disease-associated splice variants that did not alter mRNA sequence but decreased mature mRNA level, suggesting a potentially new pathogenic mechanism.

PurposeArtificial intelligence (AI) applications for clinical genetics hold the potential to improve patient care through supporting diagnostics and management as well as automating administrative tasks, thus enhancing and potentially enabling clinician/patient interactions. While the introduction of AI into clinical genetics is increasing, there remain unclear questions about risks and benefits, and the readiness of the workforce. MethodsTo assess the current clinical genetics workforces use, knowledge, and attitudes toward available medical AI applications, we conducted a survey involving 215 US-based genetics clinicians and trainees. ResultsOver half (51.2%) of participants report little to no knowledge of AI in clinical genetics and 64.3% reported no formal training in AI applications. Formal training directly correlated with self-reported knowledge of AI in clinical genetics, with 69.3% of respondents with formal training reporting intermediate to extensive knowledge of AI vs. 37.5% without formal training. Most participants reported that they lacked sufficient knowledge of clinical AI (83.4%) and agreed that there should be more education in this area (97.6%) and would take a course if offered (89.3%). The majority (51.6%) of clinician participants said they never used AI applications in the clinic. However, after a tutorial describing clinical AI applications, 75.8% reported some use of AI applications in the clinic. When asked specifically about clinical AI application usage, the majority of clinician participants used facial diagnostic applications (54.9%) and AI-generated genomic testing results (62.1%), whereas other applications such as chatbots, large language models (LLMs), pedigree or medical summary generators, and risk assessment were only used by a fraction of the clinicians, ranging from 11.1 to 12.5%. Nearly all participants (94.6%) reported clinical genetics professionals as being overburdened. ConclusionFurther clinician education is both desired and needed to optimally utilize clinical AI applications with the potential to enhance patient care and alleviate the current strain on genetics clinics.

PurposeThe Clinical Genome Resource (ClinGen) CDH1 Variant Curation Expert Panel (VCEP) developed specifications for CDH1 variant curation with a goal to resolve variants of uncertain significance (VUS) and with ClinVar conflicting interpretations for effective medical care. In addition, the CDH1 VCEP continues to update these specifications in keeping with evolving clinical practice and variant interpretation guidelines. MethodsCDH1 variant classification specifications were modified based on updated genetic testing clinical criteria, new recommendations from ClinGen, and expert knowledge from ongoing CDH1 variant curations. Trained biocurators curated 273 variants using updated CDH1 interpretation guidelines and incorporated published and unpublished data provided by diagnostic laboratories. All variants were reviewed by the ClinGen VCEP and classifications submitted to ClinVar. ResultsUpdated CDH1-specific variant interpretation guidelines include eleven major modifications since the initial specifications from 2018. Using the refined guidelines, 97% (36/37) of variants with ClinVar conflicting interpretations were resolved into benign, likely benign, likely pathogenic, or pathogenic, and 35% (15/43) of VUS were resolved into benign or likely benign. Overall, 88% (239/273) of curated variants had non-VUS classifications. ConclusionThe development and evolution of CDH1-specific criteria by the expert panel results in decreased uncertain and conflicting interpretations of variants in this clinically actionable gene.

Clinical genetic testing demand has increased in the era of precision medicine. However, availability of cancer genetic services remains limited in the US, prompting a rise in telehealth delivery. This report describes the Penn Telegenetics Program experience using a local healthcare provider collaborative model. From 2018-2025, 473 providers (89.4%) successfully registered. Providers were predominately MD/DO licensed (85.0%). Family medicine was the most frequent speciality (54.3%), followed by internal medicine (20.9%) and clinical oncology (11.8%). Most providers were in suburban locations by zip codes (56.2%), 20.1% were in rural zip codes. Only 56 providers declined collaboration (10.6%); the most common reasons reported were preferring local genetic services (22.5%) and not being comfortable as the ordering provider (22.5%). Our data demonstrate that most local providers are willing to collaborate with a centralized telegenetics program. Refining procedures to increase collaborative care and engagement may provide opportunities to increase access to cancer genetic testing.

The sequencing of the first human genome led to expectations of the widespread use of genetics in medicine. However, assessing the true impact of genetic testing on clinical practice is challenging due to the lack of integration in the electronic health record (EHR). We extracted clinical genetic tests from the EHRs of over 1.8 million patients seen at Vanderbilt University Medical Center from 2002 to 2022, using both automated and manual methods. Using these data, we quantified the extent of clinical genetic testing in healthcare and described how testing patterns have changed over time, including utilization rate, test comprehensiveness, diagnoses made, and the number of variants of uncertain significance (VUS) returned. We also assessed genetic testing rates across medical specialties and introduce a measure - the genetic attributed fraction (GAF) - to compute the proportion of observed phenotypes attributable to a genetic diagnosis. We identified 104,392 tests, 32% of which were only reported in unstructured text, and 19,032 molecularly confirmed diagnoses or risk factors. The proportion of patients genetic testing recorded in their EHRs from 1.0% in 2002 to 6.1% in 2022, and testing became more comprehensive with the growing use of multigene panels. This corresponded with a substantial increase in the variety of diseases diagnosed with genetic testing, from 51 unique diseases in 2002 to 509 in 2022, alongside a growing number of VUS. The phenome-wide GAF for 6,505,620 diagnoses made in 2022 was 0.46%, with 74 phenotypes having a GAF greater than 5%, including pancreatic insufficiency (67%), chorea (64%), atrial septal defect (24%), Microcephaly (17%), paraganglioma (17%), and ovarian cancer (6.8%). Our study provides a comprehensive quantification of the increasing role of genetic testing at a major academic medical institution. These results demonstrate the now pervasive use of genetic testing across diverse medical contexts and its growing utility in explaining observed medical phenome.

PURPOSEThis study aimed to evaluate the concordance of genetic ancestry reports from different providers, assess the accuracy of genetic ancestry compared to self-identified race and ethnicity (SIRE), and explore patient and provider perspectives on the potential utility and integration of genetic ancestry data into the electronic health record (EHR). METHODSGenetic ancestry results from two commercial providers and two 3rd-party analyses were compared for concordance using data from 451 participants in the UCSF 3D Health Study. Genetic ancestry was also compared to SIRE. Surveys were administered to gather perspectives on genetic ancestry testing, its accuracy, and potential integration into the EHR. RESULTSThe overall mean concordance between the two commercial providers was 58.41%. Ancestry from one provider had the highest concordance with SIRE, ranging from 80.05% to 94.78% across different thresholds. The majority of participants and providers were neutral regarding the integration of genetic ancestry into the EHR. CONCLUSIONSignificant discordance exists between genetic ancestry reports from different providers, highlighting the need for standardization in the calculation of genetic ancestry. While participants and providers acknowledge the potential utility of genetic ancestry in personalized medicine, concerns regarding data privacy, accuracy, and the potential for discrimination must be addressed before integration into the EHR.