Purpose: Neuroendocrine neoplasms (NENs) are increasingly recognized to have a hereditary predilection, yet the prevalence and clinical relevance of pathogenic germline variants (PGVs) in unselected patients with NEN remain poorly defined. This prospective, multicenter study aimed to evaluate the prevalence and clinical utility of PGVs through universal multigene panel testing in a diverse cohort of patients with NENs. Patients and Methods: Between 2018 and 2024, we enrolled unselected patients with NENs from 3 Mayo Clinic Cancer Centers. Germline genetic testing was performed using a next-generation sequencing panel of up to 84 cancer predisposition genes. Patients were not selected based on age, disease stage, ethnicity, or family history. Variants were classified as PGVs, variants of uncertain significance (VUS), or negative. Clinical and demographic data were analyzed descriptively. Results: Among 88 patients, PGVs were identified in 15.9% (n=14), most frequently in high- or moderate-penetrance genes including MEN1 , CHEK2 , MITF , and MUTYH . PGVs were most commonly found in pancreatic NENs [n=12/55 (21.8%)], followed by small bowel NENs [n=2/20 (10%)], with no PGVs detected in lung NENs. Mismatch repair (MMR) gene alterations were identified in 5.7% of patients, including 1 MLH1 PGV and 4 MSH2/MSH6 VUS, 2 of which demonstrated MMR deficiency by protein testing. VUS were reported in 34.1% of patients. Notably, 35.7% of PGV-positive patients did not meet current NCCN or ACMG testing criteria, and 53.9% had PGVs in genes outside of cancer-specific guideline recommendations. Conclusions: Universal germline testing in unselected patients with NEN identified clinically relevant PGVs in over 15% of cases. These findings support broader genetic testing approaches to guide treatment, enhance familial risk assessment, and inform cascade testing—regardless of traditional clinical selection criteria.

PURPOSE:Genomic screening (GS) can identify the risk of medically actionable, monogenic conditions in individuals who would otherwise not be considered for genetic testing. The yield of pathogenic variants and associated health care utilization among at-risk individuals have not been well-studied in real-world settings. METHODS:Physicians ordered GS panels for up to 167 genes. Calculations included the positive yield overall and for 81 genes on the American College of Medical Genetics and Genomics' secondary findings list. Health care utilization and costs were analyzed using insurance claims from 12 months before and after the genetic test results. RESULTS:Among 50,063 individuals, 8.6% had pathogenic/likely pathogenic variants conferring monogenic risk. Relevant health care utilization was higher in individuals with positive results than in those with non-positive results. There was a small but significant increase in median cost of all-cause health care utilization post-test compared with pre-test in participants with positive ($340 vs $215, P = .02) but not negative results ($308 vs $252, P = .12). CONCLUSION:These findings suggest that GS in real-world settings can identify at-risk individuals and prompt intervention without significantly increasing health care costs or utilization.

Variants of Uncertain Significance (VUS) in genetic testing for hereditary diseases burden patients and clinicians, yet clinical data that could reduce VUS are underutilized due to a lack of scalable strategies. We assessed whether a machine learning approach using genotype and phenotype data could improve variant classification and reduce VUS. In this cohort study of a multi-step machine learning approach, patient data from test requisition forms were used to distinguish patients with molecular diagnoses from controls (“patient score”). A generative Bayesian model then used patient scores and variant classifications to infer variant pathogenicity (“variant score”). The study included 3.5 million patients referred for clinical genetic testing across various conditions. Primary outcomes were model- and gene-level discrimination, classification performance, probabilistic calibration, and concordance with orthogonal pathogenicity measures. Integration into a semi-quantitative classification framework was based on posterior pathogenicity probabilities matching PPV ≥ 0.99/NPV ≥ 0.95 thresholds, followed by expert review. We generated 1,334 clinical variant models (CVMs); 595 showed high performance in both machine learning steps (AUROCpatient ≥ 0.8 and AUROCvariant ≥ 0.8) on held-out data. High-confidence predictions from these CVMs provided evidence for 5,362 VUS observed in 200,174 patients, representing 23.4

The advent of the full sequence of the genomes of a large number of humans and the wide application of tools for genomic analysis have revolutionized our ability to find and understand genetic contributors to disease, including disorders of the nervous system. This chapter summarizes human DNA variation and how to assess the clinical impact of DNA changes that affect gene products essential for normal neurological development and homeostasis. Comparative genomics, delineating species conservation of critical DNA regions; functional genomics, encompassing the regulation of gene expression as well as DNA motifs that are used repeatedly to encode structural or enzymatic elements of proteins; linkage analysis, genome-wide association, and whole-exome or -genome sequencing are discussed as approaches to finding genetic basis for Mendelian and complex disorders; and the different types of disease-associated mutations in DNA are discussed.

Various scientific and professional groups, including the American Medical Association (AMA), American Society of Human Genetics (ASHG), American College of Medical Genetics (ACMG), and the National Academies of Sciences, Engineering, and Medicine (NASEM), have appropriately clarified that certain population descriptors, such as race and ethnicity, are social and cultural constructs with no basis in genetics. Nevertheless, these conventional population descriptors are routinely collected during the course of clinical genetic testing and may be used to interpret test results. Experts who have examined the use of population descriptors, both conventional and ancestry based, in human genetics and genomics have offered guidance on using these descriptors in research but not in clinical laboratory settings. This perspective piece is based on a decade of experience in a clinical genomics laboratory and provides insight into the relevance of conventional and ancestry-based population descriptors for clinical genetic testing, reporting, and clinical research on aggregated data. As clinicians, laboratory geneticists, genetic counselors, and researchers, we describe real-world experiences collecting conventional population descriptors in the course of clinical genetic testing and expose challenges in ensuring clarity and consistency in the use of population descriptors. Current practices in clinical genomics laboratories that are influenced by population descriptors are identified and discussed through case examples. In relation to this, we describe specific types of clinical research projects in which population descriptors were used and helped derive useful insights related to practicing and improving genomic medicine.

Clinical implementation of whole-genome and whole-exome sequencing by next-generation sequencing (NGS) allows for comprehensive detection of genomic alterations. However, with the growing number of clinically relevant genes and variants, there is an urgent need for reference materials to optimize, validate, and quality control NGS tests. This pilot study documents the paucity of physical reference materials for widely tested genes and demonstrates the utility of in silico mutagenized reference materials to supplement physical samples when developing NGS tests. We examined published, expert curated lists of clinically relevant variants for these widely tested genes and found that publicly available reference materials were available for only 29.4%. We outline the steps for generating in silico resources and used 49 curated variants to conduct a blinded proof-of-concept study with three experienced NGS laboratories. One laboratory detected all added variants, and two detected all but one. This study revealed common scenarios that could lead to false-negative results when common pathogenic variants cannot be tested during analytical validation. This work highlights the need to establish centralized knowledge bases for common, pathogenic variants, demonstrates the utility of in silico reference materials, and provides guidance for generating in silico reference materials in-house. Additional work will be needed to generate turnkey processes for novice laboratories without in-house bioinformatics expertise.

Sarcomas are rare heterogenous mesenchymal tumors with over seventy-five different subtypes, with varying biology and outcomes, with no clear inciting factor in the vast majority. To determine the prevalence of pathogenic germline variants (PGV) in patients with sarcomas, we undertook a prospective multi-site study of germline sequencing using an 84-gene next-generation sequencing panel among patients receiving care at the four Mayo Clinic Cancer Centers. Of 115 patients with bone and soft tissue sarcoma, the median age was 60 years, 49.6% were female, 82.6% were White. The anatomical location of the primary tumor included extremities (34.8%), retroperitoneum (19.1%), trunk (13.0%), and head and neck (7.8%). Family history of cancer was present in 62.6% of the study population. Ten patients (8.7%) had a pathogenic/likely pathogenic variant (PGV). Of these, three had stage IV sarcoma, and seven had earlier-stage sarcoma (stages I–III). Among the 55 (48.7%) patients who had variant of uncertain significance (VUS), 41.1% (22/55) had stage IV sarcoma and 58.9% (33/55) had earlier-stage disease. Of the ten patients with PGV, high-to-moderate penetrance gene abnormalities were identified in eight patients (80%) involving TP53 (3), BRCA1 (1), SDHA (1), ATM (2), and NBN (1) genes. The vast majority of the PGVs (70%) would not have been detected using the current guidelines. Because of the paucity of sarcomas and lack of effective treatment options for advanced disease, germline testing in sarcomas represents a potentially impactful strategy to assess therapeutic options and for assessment of familial risk.

BACKGROUND:Although germline genetic testing can inform medical management for patients with prostate cancer (PCa), data are limited regarding patient-reported outcomes (PROs) after germline genetic testing for PCa. Recall and comprehension of germline genetic testing results, uptake of post-test clinical recommendations, and psychological impact of germline genetic testing among patients with PCa were evaluated. METHODS:This is a secondary analysis of data from the PROCLAIM trial. PROs were analyzed overall and by germline genetic testing results. Differences between groups were determined by two-tailed Fisher's exact test with significance set at p < 0.05. RESULTS:Among 494 patients with informative survey responses, 60% and 71% accurately recalled and interpreted their germline genetic testing results, respectively, with the highest rates among patients with negative results and the lowest among those with variant of uncertain significance-only (VUS) results. Among 42/55 (76%) patients with positive results for whom clinicians made germline genetic testing-informed recommendations, 39 (93%) completed or planned to complete >1 clinical recommendation. Conversely, no further recommendations were made for 160/221 (72%) and 211/218 (97%) patients with VUS and negative results, respectively. However, 57% (213/371) of these patients indicated that they or their family members intended to pursue clinical management strategies that were not recommended by their clinicians. Of the patients who responded to the survey, >90% of patients reported no post-germline genetic testing increase in their level of concern for themselves or their family members. CONCLUSION:germline genetic testing for patients with PCa did not cause appreciable psychological harm to the tested patients. Furthermore, patients with positive results had a high uptake of clinician-recommended management strategies. Of note, there were inconsistencies in the understanding of VUS results, with some clinicians making recommendations not warranted by personal/family history; conversely, some patients pursued management strategies not recommended by their clinicians. This suggests that educational efforts are needed in the communication of germline genetic testing results and clinical recommendations to patients.

You have accessJournal of UrologyProstate Cancer: Markers I (MP41)1 May 2024MP41-08 UTILIZING PATIENT-REPORTED OUTCOMES TO ASSESS THE IMPACT OF UNIVERSAL GERMLINE GENETIC TESTING FOR PROSTATE CANCER Neal Shore, Christopher M. Pieczonka, Sean Heron, Mukaram Gazi, David J. Cahn, Laurence Belkoff, Aaron D. Berger, Brian Mazzarella, David Morris, Joseph Veys, Richard Bevan-Thomas, Alexander Engelman, Paul Dato, Robert Cornell, David R. Wise, Mary Kay Hardwick, Kathryn E. Hatchell, Brandie Heald, Robert L. Nussbaum, Sarah M. Nielsen, and Edward D. Esplin Neal ShoreNeal Shore , Christopher M. PieczonkaChristopher M. Pieczonka , Sean HeronSean Heron , Mukaram GaziMukaram Gazi , David J. CahnDavid J. Cahn , Laurence BelkoffLaurence Belkoff , Aaron D. BergerAaron D. Berger , Brian MazzarellaBrian Mazzarella , David MorrisDavid Morris , Joseph VeysJoseph Veys , Richard Bevan-ThomasRichard Bevan-Thomas , Alexander EngelmanAlexander Engelman , Paul DatoPaul Dato , Robert CornellRobert Cornell , David R. WiseDavid R. Wise , Mary Kay HardwickMary Kay Hardwick , Kathryn E. HatchellKathryn E. Hatchell , Brandie HealdBrandie Heald , Robert L. NussbaumRobert L. Nussbaum , Sarah M. NielsenSarah M. Nielsen , and Edward D. EsplinEdward D. Esplin View All Author Informationhttps://doi.org/10.1097/01.JU.0001008896.93851.5b.08AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Germline genetic testing (GGT) affords prostate cancer (PCa) patients (pts) opportunities for targeted therapies, personalized management, and cascade family testing. Patient-reported outcomes (PRO) evaluate physician effectiveness in promoting pt test comprehension and clinical decision making, which are essential components of GGT. PROs from a large prospective PCa study were analyzed. METHODS: The PROCLAIM trial (NCT05447637) enrolled unselected PCa pts from 15 US urology practices. Pts underwent 84-gene GGT at Invitae® with PROs collected >1-month post-GGT. PROs were analyzed overall and by GGT result: positive (≥1 pathogenic germline variant), negative, and variant(s) of uncertain significance (VUS). Differences in proportions were determined using two-tailed Fisher's exact test and significance was set at <0.05. RESULTS: Half (494/982) of study pts had informative PRO responses, and were: 86% White, 84% non-metastatic, median age 70 years. 11% of pts had positive results, 44% negative and 45% VUS. Negative pts were significantly more likely than those with positive or VUS results to accurately recall their result (80% vs. 64% and 40%, respectively; p<0.0192) and to correctly understand if their result was associated with cancer risk or not (86% vs. 67% and 60%; p<0.0034). Compared to pts with positive or negative results, pts with VUS were significantly less likely to have both accurate recall and understanding of their result (22% vs. 63% and 86%, p<0.0001). Among 170 pts who reported receiving >1 clinical recommendation from their physician, most (76%) had completed or planned to complete >1 of them (Table 1). Positive pts who complied with recommendations were more likely to have demonstrated comprehension of their GGT result compared to pts who were non-compliant (p=0.006). Most pts reported that their GGT result either reduced (42%) or did not impact (51%) their concern regarding their PCa diagnosis, treatment or followup. 7% of all patients, and 18% of positive patients, reported increased concern. CONCLUSIONS: Implementation of universal GGT for PCa did not appear to cause undue harm to pts and resulted in adherence to clinical recommendations. There still remains educational opportunities to improve how test results and recommendations are communicated to pts. Source of Funding: Invitae Corp © 2024 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 211Issue 5SMay 2024Page: e675 Advertisement Copyright & Permissions© 2024 by American Urological Association Education and Research, Inc.Metrics Author Information Neal Shore More articles by this author Christopher M. Pieczonka More articles by this author Sean Heron More articles by this author Mukaram Gazi More articles by this author David J. Cahn More articles by this author Laurence Belkoff More articles by this author Aaron D. Berger More articles by this author Brian Mazzarella More articles by this author David Morris More articles by this author Joseph Veys More articles by this author Richard Bevan-Thomas More articles by this author Alexander Engelman More articles by this author Paul Dato More articles by this author Robert Cornell More articles by this author David R. Wise More articles by this author Mary Kay Hardwick More articles by this author Kathryn E. Hatchell More articles by this author Brandie Heald More articles by this author Robert L. Nussbaum More articles by this author Sarah M. Nielsen More articles by this author Edward D. Esplin More articles by this author Expand All Advertisement PDF downloadLoading ...

Abstract Introduction: Current variant classification (VC) frameworks rely on rules-based approaches that use heuristic weighting of various types of evidence, resulting in > 50% of variants being classified as variants of uncertain significance (VUS), and leaving many patients with uncertainty about their disease risk or diagnosis. We propose a probabilistic and scalable Bayesian approach to model the causal relationships between various types of evidence. A fully quantitative system maximizes the utility and integration of various evidence types, empowering clinicians to make more nuanced management decisions. Methods: Probabilistic graphical models (PGMs) are uniquely suited to the needs of clinical VC. Two different component PGMs were developed to model two of the evidence categories that will ultimately be used in a comprehensive VC system: population allele frequency (Population PGM) and reported phenotype observations (Reported Phenotype PGM). Results: The Population PGM treats population allele frequency observations as a binomial process. By conditioning the model on partial observations, the probabilistic relationships between pathogenicity and allele frequencies can be estimated while stochastic variational inference allows uncertainty to be efficiently propagated. The resulting model performs well across a large number of genes at inferring pathogenicity of a variant from its allele frequency, with an average precision of >99% for benign variants. In the Reported Phenotype PGM, phenotypic features characteristic of a disorder are learned from patients expected to be affected based on genotype. Patient-level predictions are in turn combined at the variant level to derive variant pathogenicity likelihoods. To date, models representing at least 102 inherited conditions and 259 genes have demonstrated high predictive performance (>0.8 AUROC) for both patient-level and variant-level predictions. Finally, as a proof-of-concept, we demonstrate how each component PGM can be combined into a probabilistic Bayesian VC framework that also includes protein structure and stability, evolutionary conservation, and sequence context. This framework has high concordance with known, well-accepted pathogenic and benign variants classified with rules-based systems, and could make high-confidence predictions for many variants currently classified as VUS. Conclusion: We present a Bayesian approach that can integrate diverse types of evidence to achieve high VC accuracy while quantifying uncertainty. Future expansion of this Bayesian framework to all evidence types relevant to VC may allow for more accurate risk management guidelines and further inform medical and genetic counseling recommendations. Citation Format: Wolfgang Michael Korn, Yuya Kobayashi, Flavia M. Facio, Arun Nampally, Keith Nykamp, Robert Nussbaum, Alexandre Colavin, Britt Johnson, Toby Manders. Continuous, probabilistic variant interpretation with Bayesian graphical models [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 792.

Objective We implemented a chatbot consent tool to shift the time burden from study staff in support of a national genomics research study. Materials and Methods We created an Institutional Review Board-approved script for automated chat-based consent. We compared data from prospective participants who used the tool or had traditional consent conversations with study staff. Results Chat-based consent, completed on a user’s schedule, was shorter than the traditional conversation. This did not lead to a significant change in affirmative consents. Within affirmative consents and declines, more prospective participants completed the chat-based process. A quiz to assess chat-based consent user understanding had a high pass rate with no reported negative experiences. Conclusion Our report shows that a structured script can convey important information while realizing the benefits of automation and burden shifting. Analysis suggests that it may be advantageous to use chatbots to scale this rate-limiting step in large research projects.

Background We previously reported that impaired type I IFN activity, due to inborn errors of TLR3- and TLR7-dependent type I interferon (IFN) immunity or to autoantibodies against type I IFN, account for 15–20% of cases of life-threatening COVID-19 in unvaccinated patients. Therefore, the determinants of life-threatening COVID-19 remain to be identified in ~ 80% of cases. Methods We report here a genome-wide rare variant burden association analysis in 3269 unvaccinated patients with life-threatening COVID-19, and 1373 unvaccinated SARS-CoV-2-infected individuals without pneumonia. Among the 928 patients tested for autoantibodies against type I IFN, a quarter (234) were positive and were excluded. Results No gene reached genome-wide significance. Under a recessive model, the most significant gene with at-risk variants was TLR7 , with an OR of 27.68 (95%CI 1.5–528.7, P = 1.1 × 10 −4 ) for biochemically loss-of-function (bLOF) variants. We replicated the enrichment in rare predicted LOF (pLOF) variants at 13 influenza susceptibility loci involved in TLR3-dependent type I IFN immunity (OR = 3.70[95%CI 1.3–8.2], P = 2.1 × 10 −4 ). This enrichment was further strengthened by (1) adding the recently reported TYK2 and TLR7 COVID-19 loci, particularly under a recessive model (OR = 19.65[95%CI 2.1–2635.4], P = 3.4 × 10 −3 ), and (2) considering as pLOF branchpoint variants with potentially strong impacts on splicing among the 15 loci (OR = 4.40[9%CI 2.3–8.4], P = 7.7 × 10 −8 ). Finally, the patients with pLOF/bLOF variants at these 15 loci were significantly younger (mean age [SD] = 43.3 [20.3] years) than the other patients (56.0 [17.3] years; P = 1.68 × 10 −5 ). Conclusions Rare variants of TLR3- and TLR7-dependent type I IFN immunity genes can underlie life-threatening COVID-19, particularly with recessive inheritance, in patients under 60 years old.

PURPOSE:Identification of pathogenic germline variants in patients with prostate cancer can help inform treatment selection, screening for secondary malignancies, and cascade testing. Limited real-world data are available on clinician recommendations following germline genetic testing in patients with prostate cancer. MATERIALS AND METHODS:Patient data and clinician recommendations were collected from unselected patients with prostate cancer who underwent germline testing through the PROCLAIM trial. Differences among groups of patients were determined by 2-tailed Fisher's exact test with significance set at P < .05. Logistic regression was performed to assess the influence of test results in clinical decision-making while controlling for time of diagnosis (newly vs previously diagnosed). RESULTS:Among 982 patients, 100 (10%) were positive (≥1 pathogenic germline variant), 482 (49%) had uncertain results (≥1 variant of uncertain significance), and 400 (41%) were negative. Patients with positive results were significantly more likely than those with negative or uncertain results to receive recommendations for treatment changes (18% vs 1.4%, P < .001), follow-up changes (64% vs 11%, P < .001), and cascade testing (71% vs 5.4%, P < .001). Logistic regression demonstrated that positive and uncertain results were significantly associated with both changes to treatment and follow-up (P < .001) when controlling for new or previous diagnosis. CONCLUSIONS:Germline genetic testing results informed clinical recommendations for patients with prostate cancer, especially in patients with positive results. Higher than anticipated rates of clinical management changes in patients with uncertain results highlight the need for increased genetic education of clinicians treating patients with prostate cancer.

PURPOSE Germline genetic testing (GGT) significantly affects cancer care. While universal testing has been studied in Western societies, less is known about adoption elsewhere. MATERIALS AND METHODS In this study, 3,319 unselected, pan-cancer Jordanian patients diagnosed between April 2021 and September 2022 received GGT. Pathogenic germline variant (PGV) frequency among patients who were in-criteria (IC) or out-of-criteria (OOC; 2020 National Comprehensive Cancer Network criteria) and changes in clinical management in response to GGT results were evaluated. Statistical analysis was performed using two-tailed Fisher's exact test with significance level P < .05. RESULTS The cohort was predominantly female (69.9%), with a mean age of 53.7 years at testing, and 53.1% were IC. While patients who were IC were more likely than patients who were OOC to have a PGV (15.8% v 9.6%; P < .0001), 149 (34.8%) patients with PGVs were OOC. Clinical management recommendations in response to GGT, including changes to treatment and/or follow-up, were made for 57.3% (161 of 281) of patients with high- or moderate-risk PGVs, including 26.1% (42 of 161) of patients who were OOC. CONCLUSION Universal GGT of patients with newly diagnosed cancer was successfully implemented in Jordan and led to identification of actionable PGVs that would have been missed with guidelines-based testing.

Cancer genetic data from Sub-Saharan African (SSA) are limited. Patients with female breast (fBC), male breast (mBC), and prostate cancer (PC) in Rwanda underwent germline genetic testing and counseling. Demographic and disease-specific information was collected. A multi-cancer gene panel was used to identify germline Pathogenic Variants (PV) and Variants of Uncertain Significance (VUS). 400 patients (201 with BC and 199 with PC) were consented and recruited to the study. Data was available for 342 patients: 180 with BC (175 women and 5 men) and 162 men with PC. PV were observed in 18.3% fBC, 4.3% PC, and 20% mBC. BRCA2 was the most common PV. Among non-PV carriers, 65% had ≥1 VUS: 31.8% in PC and 33.6% in BC (female and male). Our findings highlight the need for germline genetic testing and counseling in cancer management in SSA.

Current guidelines recommend single variant testing in relatives of patients with known pathogenic or likely pathogenic germline variants in cancer predisposition genes. This approach may preclude the use of risk-reducing strategies in family members who have pathogenic or likely pathogenic germline variants in other cancer predisposition genes. Cascade testing using multigene panels was performed in 3696 relatives of 7433 probands. Unexpected pathogenic or likely pathogenic germline variants were identified in 230 (6.2%) relatives, including 144 who were negative for the familial pathogenic or likely pathogenic variant but positive for a pathogenic or likely pathogenic variant in a different gene than the proband and 74 who tested positive for the familial pathogenic or likely pathogenic variant and had an additional pathogenic or likely pathogenic variant in a different gene than the proband. Of the relatives with unexpected pathogenic or likely pathogenic germline variants, 36.3% would have qualified for different or additional cancer screening recommendations. Limiting cascade testing to only the familial pathogenic or likely pathogenic variant would have resulted in missed, actionable findings for a subset of relatives.

Association results between minor alleles of 467 variants incorportated in cross tissue gene expression prediction model for the gene of CRHR1.