Validation and clinical discovery demonstration of breast cancer data from a real-world data extraction platform.

Objective: To validate and demonstrate the clinical discovery utility of a novel patient-mediated, medical record collection and data extraction platform developed to improve access and utilization of real-world clinical data. Materials and Methods: Clinical variables were extracted from the medical records of 1011 consented patients with breast cancer. To validate the extracted data, case report forms completed using the structured data output of the platform were compared to manual chart review for 50 randomly-selected patients with metastatic breast cancer. To demonstrate the platform's clinical discovery utility, we identified 194 patients with early-stage clinical data who went on to develop distant metastases and utilized the platform-extracted data to assess associations between time to distant metastasis (TDM) and early-stage tumor histology, molecular type, and germline BRCA status. Results: The platform-extracted data for the validation cohort had 97.6% precision (91.98%-100% by variable type) and 81.48% recall (58.15%-95.00% by variable type) compared to manual chart review. In our discovery cohort, the shortest TDM was significantly associated with metaplastic (739.0 days) and inflammatory histologies (1005.8 days), HR-/HER2- molecular types (1187.4 days), and positive BRCA status (1042.5 days) as compared to other histologies, molecular types, and negative BRCA status, respectively. Multivariable analyses did not produce statistically significant results. Discussion: The precision and recall of platform-extracted clinical data are reported, although specificity could not be assessed. The data can generate clinically-relevant insights. Conclusion: The structured real-world data produced by a novel patient-mediated, medical record-extraction platform are reliable and can power clinical discovery.

Rates and Classification of Variants of Uncertain Significance in Hereditary Disease Genetic Testing.

Importance: Variants of uncertain significance (VUSs) are rampant in clinical genetic testing, frustrating clinicians, patients, and laboratories because the uncertainty hinders diagnoses and clinical management. A comprehensive assessment of VUSs across many disease genes is needed to guide efforts to reduce uncertainty. Objective: To describe the sources, gene distribution, and population-level attributes of VUSs and to evaluate the impact of the different types of evidence used to reclassify them. Design, Setting, and Participants: This cohort study used germline DNA variant data from individuals referred by clinicians for diagnostic genetic testing for hereditary disorders. Participants included individuals for whom gene panel testing was conducted between September 9, 2014, and September 7, 2022. Data were analyzed from September 1, 2022, to April 1, 2023. Main Outcomes and Measures: The outcomes of interest were VUS rates (stratified by age; clinician-reported race, ethnicity, and ancestry groups; types of gene panels; and variant attributes), percentage of VUSs reclassified as benign or likely benign vs pathogenic or likely pathogenic, and enrichment of evidence types used for reclassifying VUSs. Results: The study cohort included 1 689 845 individuals ranging in age from 0 to 89 years at time of testing (median age, 50 years), with 1 203 210 (71.2%) female individuals. There were 39 150 Ashkenazi Jewish individuals (2.3%), 64 730 Asian individuals (3.8%), 126 739 Black individuals (7.5%), 5539 French Canadian individuals (0.3%), 169 714 Hispanic individuals (10.0%), 5058 Native American individuals (0.3%), 2696 Pacific Islander individuals (0.2%), 4842 Sephardic Jewish individuals (0.3%), and 974 383 White individuals (57.7%). Among all individuals tested, 692 227 (41.0%) had at least 1 VUS and 535 385 (31.7%) had only VUS results. The number of VUSs per individual increased as more genes were tested, and most VUSs were missense changes (86.6%). More VUSs were observed per sequenced gene in individuals who were not from a European White population, in middle-aged and older adults, and in individuals who underwent testing for disorders with incomplete penetrance. Of 37 699 unique VUSs that were reclassified, 30 239 (80.2%) were ultimately categorized as benign or likely benign. A mean (SD) of 30.7 (20.0) months elapsed for VUSs to be reclassified to benign or likely benign, and a mean (SD) of 22.4 (18.9) months elapsed for VUSs to be reclassified to pathogenic or likely pathogenic. Clinical evidence contributed most to reclassification. Conclusions and Relevance: This cohort study of approximately 1.6 million individuals highlighted the need for better methods for interpreting missense variants, increased availability of clinical and experimental evidence for variant classification, and more diverse representation of race, ethnicity, and ancestry groups in genomic databases. Data from this study could provide a sound basis for understanding the sources and resolution of VUSs and navigating appropriate next steps in patient care.

Efficacy of National Comprehensive Cancer Network Guidelines in Identifying Pathogenic Germline Variants Among Unselected Patients with Prostate Cancer: The PROCLAIM Trial.

BACKGROUND: Prostate cancer (PCa) patients with pathogenic/likely pathogenic germline variants (PGVs) in cancer predisposition genes may be eligible for U.S. Food and Drug Administration-approved targeted therapies, clinical trials, or enhanced screening. Studies suggest that eligible patients are missing genetics-informed care due to restrictive testing criteria. OBJECTIVE: To establish the prevalence of actionable PGVs among prospectively accrued, unselected PCa patients, stratified by their guideline eligibility. DESIGN, SETTING, AND PARTICIPANTS: Consecutive, unselected PCa patients were enrolled at 15 sites in the USA from October 2019 to August 2021, and had multigene cancer panel testing. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Correlates between the prevalence of PGVs and clinician-reported demographic and clinical characteristics were examined. RESULTS AND LIMITATIONS: Among 958 patients (median [quartiles] age at diagnosis 65 [60, 71] yr), 627 (65%) had low- or intermediate-risk disease (grade group 1, 2, or 3). A total of 77 PGVs in 17 genes were identified in 74 patients (7.7%, 95% confidence interval [CI] 6.2-9.6%). No significant difference was found in the prevalence of PGVs among patients who met the 2019 National Comprehensive Cancer Network Prostate criteria (8.8%, 43/486, 95% CI 6.6-12%) versus those who did not (6.6%, 31/472, 95% CI 4.6-9.2%; odds ratio 1.38, 95% CI 0.85-2.23), indicating that these criteria would miss 42% of patients (31/74, 95% CI 31-53%) with PGVs. The criteria were less effective at predicting PGVs in patients from under-represented populations. Most PGVs (81%, 60/74) were potentially clinically actionable. Limitations include the inability to stratify analyses based on individual ethnicity due to low numbers of non-White patients with PGVs. CONCLUSIONS: Our results indicate that almost half of PCa patients with PGVs are missed by current testing guidelines. Comprehensive germline genetic testing should be offered to all patients with PCa. PATIENT SUMMARY: One in 13 patients with prostate cancer carries an inherited variant that may be actionable for the patient's current care or prevention of future cancer, and could benefit from expanded testing criteria.

Patterns of mosaicism for sequence and copy-number variants discovered through clinical deep sequencing of disease-related genes in one million individuals.

DNA variants that arise after conception can show mosaicism, varying in presence and extent among tissues. Mosaic variants have been reported in Mendelian diseases, but further investigation is necessary to broadly understand their incidence, transmission, and clinical impact. A mosaic pathogenic variant in a disease-related gene may cause an atypical phenotype in terms of severity, clinical features, or timing of disease onset. Using high-depth sequencing, we studied results from one million unrelated individuals referred for genetic testing for almost 1,900 disease-related genes. We observed 5,939 mosaic sequence or intragenic copy number variants distributed across 509 genes in nearly 5,700 individuals, constituting approximately 2% of molecular diagnoses in the cohort. Cancer-related genes had the most mosaic variants and showed age-specific enrichment, in part reflecting clonal hematopoiesis in older individuals. We also observed many mosaic variants in genes related to early-onset conditions. Additional mosaic variants were observed in genes analyzed for reproductive carrier screening or associated with dominant disorders with low penetrance, posing challenges for interpreting their clinical significance. When we controlled for the potential involvement of clonal hematopoiesis, most mosaic variants were enriched in younger individuals and were present at higher levels than in older individuals. Furthermore, individuals with mosaicism showed later disease onset or milder phenotypes than individuals with non-mosaic variants in the same genes. Collectively, the large compendium of variants, disease correlations, and age-specific results identified in this study expand our understanding of the implications of mosaic DNA variation for diagnosis and genetic counseling.

Scalable detection of technically challenging variants through modified next-generation sequencing.

BACKGROUND: Some clinically important genetic variants are not easily evaluated with next-generation sequencing (NGS) methods due to technical challenges arising from high- similarity copies (e.g., PMS2, SMN1/SMN2, GBA1, HBA1/HBA2, CYP21A2), repetitive short sequences (e.g., ARX polyalanine repeats, FMR1 AGG interruptions in CGG repeats, CFTR poly-T/TG repeats), and other complexities (e.g., MSH2 Boland inversions). METHODS: We customized our NGS processes to detect the technically challenging variants mentioned above with adaptations including target enrichment and bioinformatic masking of similar sequences. Adaptations were validated with samples of known genotypes. RESULTS: Our adaptations provided high-sensitivity and high-specificity detection for most of the variants and provided a high-sensitivity primary assay to be followed with orthogonal disambiguation for the others. The sensitivity of the NGS adaptations was 100% for all of the technically challenging variants. Specificity was 100% for those in PMS2, GBA1, SMN1/SMN2, and HBA1/HBA2, and for the MSH2 Boland inversion; 97.8%-100% for CYP21A2 variants; and 85.7% for ARX polyalanine repeats. CONCLUSIONS: NGS assays can detect technically challenging variants when chemistries and bioinformatics are jointly refined. The adaptations described support a scalable, cost-effective path to identifying all clinically relevant variants within a single sample.

Assessment of the Diagnostic Yield of Combined Cardiomyopathy and Arrhythmia Genetic Testing.

Importance: Genetic testing can guide management of both cardiomyopathies and arrhythmias, but cost, yield, and uncertain results can be barriers to its use. It is unknown whether combined disease testing can improve diagnostic yield and clinical utility for patients with a suspected genetic cardiomyopathy or arrhythmia. Objective: To evaluate the diagnostic yield and clinical management implications of combined cardiomyopathy and arrhythmia genetic testing through a no-charge, sponsored program for patients with a suspected genetic cardiomyopathy or arrhythmia. Design, Setting, and Participants: This cohort study involved a retrospective review of DNA sequencing results for cardiomyopathy- and arrhythmia-associated genes. The study included 4782 patients with a suspected genetic cardiomyopathy or arrhythmia who were referred for genetic testing by 1203 clinicians; all patients participated in a no-charge, sponsored genetic testing program for cases of suspected genetic cardiomyopathy and arrhythmia at a single testing site from July 12, 2019, through July 9, 2020. Main Outcomes and Measures: Positive gene findings from combined cardiomyopathy and arrhythmia testing were compared with findings from smaller subtype-specific gene panels and clinician-provided diagnoses. Results: Among 4782 patients (mean [SD] age, 40.5 [21.3] years; 2551 male [53.3%]) who received genetic testing, 39 patients (0.8%) were Ashkenazi Jewish, 113 (2.4%) were Asian, 571 (11.9%) were Black or African American, 375 (7.8%) were Hispanic, 2866 (59.9%) were White, 240 (5.0%) were of multiple races and/or ethnicities, 138 (2.9%) were of other races and/or ethnicities, and 440 (9.2%) were of unknown race and/or ethnicity. A positive result (molecular diagnosis) was confirmed in 954 of 4782 patients (19.9%). Of those, 630 patients with positive results (66.0%) had the potential to inform clinical management associated with adverse clinical outcomes, increased arrhythmia risk, or targeted therapies. Combined cardiomyopathy and arrhythmia gene panel testing identified clinically relevant variants for 1 in 5 patients suspected of having a genetic cardiomyopathy or arrhythmia. If only patients with a high suspicion of genetic cardiomyopathy or arrhythmia had been tested, at least 137 positive results (14.4%) would have been missed. If testing had been restricted to panels associated with the clinician-provided diagnostic indications, 75 of 689 positive results (10.9%) would have been missed; 27 of 75 findings (36.0%) gained through combined testing involved a cardiomyopathy indication with an arrhythmia genetic finding or vice versa. Cascade testing of family members yielded 402 of 958 positive results (42.0%). Overall, 2446 of 4782 patients (51.2%) had only variants of uncertain significance. Patients referred for arrhythmogenic cardiomyopathy had the lowest rate of variants of uncertain significance (81 of 176 patients [46.0%]), and patients referred for catecholaminergic polymorphic ventricular tachycardia had the highest rate (48 of 76 patients [63.2%]). Conclusions and Relevance: In this study, comprehensive genetic testing for cardiomyopathies and arrhythmias revealed diagnoses that would have been missed by disease-specific testing. In addition, comprehensive testing provided diagnostic and prognostic information that could have potentially changed management and monitoring strategies for patients and their family members. These results suggest that this improved diagnostic yield may outweigh the burden of uncertain results.

Unexpected actionable genetic variants revealed by multigene panel testing of patients with uterine cancer.

OBJECTIVE: Hereditary uterine cancer (UC) is traditionally associated with pathogenic/likely pathogenic germline variants (PGVs) in Lynch syndrome genes or PTEN; however, growing evidence supports a role for other genes that may reveal new clinical management options. In this study we assessed the prevalence and potential clinical impact of PGVs identified in UC patients referred for comprehensive germline genetic testing that combined testing for Lynch syndrome, PTEN, and other cancer predisposition genes. METHODS: Prevalence of PGVs in patients referred to a single clinical lab for germline genetic testing with an indication of uterine or endometrial cancer were retrospectively assessed and compared by syndrome type, patient age at testing, and self-reported ancestry. Potential clinical actionability of PGVs was based on established guidelines for clinical management, targeted therapies, and clinical trial eligibility. RESULTS: PGVs were detected in 13.6% of the cohort (880/6490). PGVs were most frequently observed in Lynch syndrome genes (60.4%) and PTEN (1.5%), with 38.1% in another cancer predisposition gene (i.e., CHEK2, BRCA1/BRCA2). PGV prevalence was similar for patients <50 years and those ≥50 years (15.1% vs 13.2%). Nearly all PGVs (97.2%) were associated with guideline-recommended management, including cascade testing; 60.5% were associated with FDA-approved therapies; and 35.2% were associated with clinical trials. CONCLUSIONS: Focusing germline testing on Lynch syndrome genes and PTEN and limiting testing to patients <50 years of age at diagnosis may overlook a substantial proportion of UC patients who harbor actionable PGVs. Universal comprehensive genetic testing of UC patients could benefit many patients and at-risk family members.

Systematic use of phenotype evidence in clinical genetic testing reduces the frequency of variants of uncertain significance.

Guidelines for variant interpretation include criteria for incorporating phenotype evidence, but this evidence is inconsistently applied. Systematic approaches to using phenotype evidence are needed. We developed a method for curating disease phenotypes as highly or moderately predictive of variant pathogenicity based on the frequency of their association with disease-causing variants. To evaluate this method's accuracy, we retrospectively reviewed variants with clinical classifications that had evolved from uncertain to definitive in genes associated with curated predictive phenotypes. To demonstrate the clinical validity and utility of this approach, we compared variant classifications determined with and without predictive phenotype evidence. The curation method was accurate for 93%-98% of eligible variants. Among variants interpreted using highly predictive phenotype evidence, the percentage classified as pathogenic or likely pathogenic was 80%, compared with 46%-54% had the evidence not been used. Positive results among individuals harboring variants with highly predictive phenotype-guided interpretations would have been missed in 25%-37% of diagnostic tests and 39%-50% of carrier screens had other approaches to phenotype evidence been used. In summary, predictive phenotype evidence associated with specific curated genes can be systematically incorporated into variant interpretation to reduce uncertainty and increase the clinical utility of genetic testing.

Comprehensive Genetic Testing for Pediatric Hypertrophic Cardiomyopathy Reveals Clinical Management Opportunities and Syndromic Conditions.

Hypertrophic cardiomyopathy (HCM) has historically been diagnosed phenotypically. Through genetic testing, identification of a molecular diagnosis (MolDx) is increasingly common but the impact on pediatric patients is unknown. This was a retrospective study of next-generation sequencing data for 602 pediatric patients with a clinician-reported history of HCM. Diagnostic yield was stratified by gene and self-reported race/ethnicity. A MolDx of HCM was identified in 242 (40%) individuals. Sarcomeric genes were the highest yielding, but pathogenic and/or likely pathogenic (P/LP) variants in syndromic genes were found in 36% of individuals with a MolDx, often in patients without documented clinical suspicion for a genetic syndrome. Among all MolDx, 73% were in genes with established clinical management recommendations and 2.9% were in genes that conferred eligibility for clinical trial enrollment. Black patients were the least likely to receive a MolDx. In the current era, genetic testing can impact management of HCM, beyond diagnostics or prognostics, through disease-specific guidelines or clinical trial eligibility. Genetic testing frequently can help identify syndromes in patients for whom syndromes may not be suspected. These findings highlight the importance of pursuing broad genetic testing, independent of suspicion based on phenotype. Lower rates of MolDx in Black patients may contribute to health inequities. Further research is needed evaluating the genetics of HCM in underrepresented/underserved populations. Additionally, research related to the impact of genetic testing on clinical management of other diseases is warranted.

Hereditary Cancer Risk Using a Genetic Chatbot Before Routine Care Visits.

OBJECTIVE: To examine user uptake and experience with a clinical chatbot that automates hereditary cancer risk triage by collecting personal and family cancer history in routine women's health care settings. METHODS: We conducted a multicenter, retrospective observational study of patients who used a web-based chatbot before routine care appointments to assess their risk for hereditary breast and ovarian cancer, Lynch syndrome, and adenomatous polyposis syndromes. Outcome measures included uptake and completion of the risk-assessment and educational section of the chatbot interaction and identification of hereditary cancer risk as evaluated against National Comprehensive Cancer Network criteria. RESULTS: Of the 95,166 patients invited, 61,070 (64.2%) engaged with the clinical chatbot. The vast majority completed the cancer risk assessment (89.4%), and most completed the genetic testing education section (71.4%), indicating high acceptability among those who opted to engage. The mean duration of use was 15.4 minutes (SD 2 hours, 56.2 minutes) when gaps of inactivity longer than 5 minutes were excluded. A personal history of cancer was reported by 19.1% (10,849/56,656) and a family history of cancer was reported by 66.7% (36,469/54,652) of patients who provided the relevant information. One in four patients (14,850/54,547) screened with the chatbot before routine care appointments met National Comprehensive Cancer Network criteria for genetic testing. Among those who were tested, 5.6% (73/1,313) had a disease-causing pathogenic variant. CONCLUSION: A chatbot digital health tool can help identify patients at high risk for hereditary cancer syndromes before routine care appointments. This scalable intervention can effectively provide cancer risk assessment, engage patients with educational information, and facilitate a path toward preventive genetic testing. FUNDING SOURCE: Implementation of the chatbot in clinics was funded by industry support from commercial genetic testing laboratories Ambry, Invitae, and Progenity.

Unmanaged Pharmacogenomic and Drug Interaction Risk Associations with Hospital Length of Stay among Medicare Advantage Members with COVID-19: A Retrospective Cohort Study.

Unmanaged pharmacogenomic and drug interaction risk can lengthen hospitalization and may have influenced the severe health outcomes seen in some COVID-19 patients. To determine if unmanaged pharmacogenomic and drug interaction risks were associated with longer lengths of stay (LOS) among patients hospitalized with COVID-19, we retrospectively reviewed medical and pharmacy claims from 6025 Medicare Advantage members hospitalized with COVID-19. Patients with a moderate or high pharmacogenetic interaction probability (PIP), which indicates the likelihood that testing would identify one or more clinically actionable gene-drug or gene-drug-drug interactions, were hospitalized for 9% (CI: 4-15%; p < 0.001) and 16% longer (CI: 8-24%; p < 0.001), respectively, compared to those with low PIP. Risk adjustment factor (RAF) score, a commonly used measure of disease burden, was not associated with LOS. High PIP was significantly associated with 12-22% longer LOS compared to low PIP in patients with hypertension, hyperlipidemia, diabetes, or chronic obstructive pulmonary disease (COPD). A greater drug-drug interaction risk was associated with 10% longer LOS among patients with two or three chronic conditions. Thus, unmanaged pharmacogenomic risk was associated with longer LOS in these patients and managing this risk has the potential to reduce LOS in severely ill patients, especially those with chronic conditions.

Limited-Variant Screening vs Comprehensive Genetic Testing for Familial Hypercholesterolemia Diagnosis.

Importance: Familial hypercholesterolemia (FH) is the most common inherited cardiovascular disease and carries significant morbidity and mortality risks. Genetic testing can identify affected individuals, but some array-based assays screen only a small subset of known pathogenic variants. Objective: To identify the number of clinically significant variants associated with FH that would be missed by an array-based, limited-variant screen when compared with next-generation sequencing (NGS)-based comprehensive testing. Design, Setting, and Participants: This cross-sectional study compared comprehensive genetic test results for clinically significant variants associated with FH with results for a subset of 24 variants screened by a limited-variant array. Data were deidentified next-generation sequencing results from indication-based or proactive gene panels. Individuals receiving next-generation sequencing-based genetic testing, either for an FH indication between November 2015 and June 2020 or as proactive health screening between February 2016 and June 2020 were included. Ancestry was reported by clinicians who could select from preset options or enter free text on the test requisition form. Main Outcomes and Measures: Number of pathogenic or likely pathogenic (P/LP) variants identified. Results: This study included 4563 individuals who were referred for FH diagnostic testing and 6482 individuals who received next-generation sequencing of FH-associated genes as part of a proactive genetic test. Among individuals in the indication cohort, the median (interquartile range) age at testing was 49 (32-61) years, 55.4% (2528 of 4563) were female, and 63.6% (2902 of 4563) were self-reported White/Caucasian. In the indication cohort, the positive detection rate would have been 8.4% (382 of 4563) for a limited-variant screen compared with the 27.0% (1230 of 4563) observed with the next-generation sequencing-based comprehensive test. As a result, 68.9% (848 of 1230) of individuals with a P/LP finding in an FH-associated gene would have been missed by the limited screen. The potential for missed findings in the indication cohort varied by ancestry; among individuals with a P/LP finding, 93.7% (59 of 63) of self-reported Black/African American individuals and 84.7% (122 of 144) of Hispanic individuals would have been missed by the limited-variant screen, compared with 33.3% (4 of 12) of Ashkenazi Jewish individuals. In the proactive cohort, the prevalence of clinically significant FH variants was approximately 1:191 per the comprehensive test, and 61.8% (21 of 34) of individuals with an FH-associated P/LP finding would have been missed by a limited-variant screen. Conclusions and Relevance: Limited-variant screens may falsely reassure the majority of individuals at risk for FH that they do not carry a disease-causing variant, especially individuals of self-reported Black/African American and Hispanic ancestry.

Spectrum of splicing variants in disease genes and the ability of RNA analysis to reduce uncertainty in clinical interpretation.

The complexities of gene expression pose challenges for the clinical interpretation of splicing variants. To better understand splicing variants and their contribution to hereditary disease, we evaluated their prevalence, clinical classifications, and associations with diseases, inheritance, and functional characteristics in a 689,321-person clinical cohort and two large public datasets. In the clinical cohort, splicing variants represented 13% of all variants classified as pathogenic (P), likely pathogenic (LP), or variants of uncertain significance (VUSs). Most splicing variants were outside essential splice sites and were classified as VUSs. Among all individuals tested, 5.4% had a splicing VUS. If RNA analysis were to contribute supporting evidence to variant interpretation, we estimated that splicing VUSs would be reclassified in 1.7% of individuals in our cohort. This would result in a clinically significant result (i.e., P/LP) in 0.1% of individuals overall because most reclassifications would change VUSs to likely benign. In ClinVar, splicing VUSs were 4.8% of reported variants and could benefit from RNA analysis. In the Genome Aggregation Database (gnomAD), splicing variants comprised 9.4% of variants in protein-coding genes; most were rare, precluding unambiguous classification as benign. Splicing variants were depleted in genes associated with dominant inheritance and haploinsufficiency, although some genes had rare variants at essential splice sites or had common splicing variants that were most likely compatible with normal gene function. Overall, we describe the contribution of splicing variants to hereditary disease, the potential utility of RNA analysis for reclassifying splicing VUSs, and how natural variation may confound clinical interpretation of splicing variants.