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.
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.
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.
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.
Number of pathogenic or likely pathogenic (P/LP) variants identified.
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.
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.
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.
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.
Some clinically important genes and variants are not easily detected with standard next‐generation sequencing (NGS) methods due to technical challenges arising from high‐similarity copies, repetitive short sequences, and other complexities. When the chemistries and bioinformatics of NGS are jointly refined, even technically challenging genes and variants can be evaluated, including the Gaucher disease‐associated GBA, which has a high‐similarity pseudogene.
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.
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.
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.
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.
Implementation of the chatbot in clinics was funded by industry support from commercial genetic testing laboratories Ambry, Invitae, and Progenity.
IntroductionProfessional societies recommend genetic testing to improve diagnosis and inform management of inherited cardiovascular disease, yet genetic testing is not widely utilized in ...cardiovascular practice. To reduce barriers to genetic testing and facilitate following of existing guidelines, we initiated a program of sponsored genetic testing with genetic counseling at no cost to patients suspected of having a genetic arrhythmia or cardiomyopathy. Here, we describe unanticipated molecular diagnoses provided by a comprehensive analysis of cardiomyopathy and arrhythmia genes.MethodsWith IRB approval, de-identified genetic and clinical data provided by ordering clinicians were reviewed from 1,606 individuals referred for testing through the sponsored, no-charge Detect Cardiomyopathy and Arrhythmia genetic testing program between July 2019 and January 2020. Testing consisted of a cardiomyopathy and arrhythmia panel of up to 150 genes detecting single nucleotide, small indel, and exon-level deletion and duplication variants.ResultsOverall, 20.5% (329/1606) of patients had a pathogenic or likely pathogenic (P/LP) variant identified. The most common reasons for referral were hypertrophic cardiomyopathy (40%), dilated cardiomyopathy (24%), and long QT syndrome (13%). The diagnostic yield was 25% (130/527) among patients whose healthcare provider reported a high or moderate index of clinical suspicion for a genetic cardiomyopathy, of whom 2% (2/130) had P/LP variants only in the arrhythmia gene KCNQ1. Conversely, among patients with a high or moderate index of clinical suspicion for a genetic arrhythmia, the diagnostic yield was 20% (28/137), of which 18% (5/28) had P/LP variants only in the cardiomyopathy-associated genes MYBPC3 (2) and TTR (3).ConclusionsThese data demonstrate that comprehensive genetic testing, without cost as a barrier, identifies clinically-relevant variants in 1 in 5 suspected cardiomyopathy or arrhythmia patients. Notably, genetic testing with a multi-condition panel yielded unanticipated molecular findings likely to change clinical management in up to 18% of genetically-positive patients. These unanticipated findings would have likely been missed by targeted, disease-specific panels.
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.
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.
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.
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.
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.
•Pathogenic or likely pathogenic germline variants (PGVs) were found in 13.6% of uterine cancer patients tested.•Nearly 40% of PGVs were found outside of Lynch syndrome genes and PTEN.•The prevalences of PGVs in patients <50 years and ≥ 50 years at the time of testing were similar (15.1% vs 13.2%).•Sixty percent of PGVs were associated with FDA-approved therapies and 35% with precision therapy clinical trials.
Abstract only
Introduction:
Genetic testing for heritable cardiomyopathy and arrhythmia syndromes has evolved rapidly and is now recommended by cardiology professional societies to establish a ...genetic etiology, guide clinical management, and identify at-risk family members through cascade screening. However, the advantages of comprehensive, multi-condition gene panels versus condition-specific gene panels are debated.
Objective:
To assess the yield and clinical management implications of combined cardiomyopathy and arrhythmia genetic testing in a diverse cohort of patients referred for a suspected inherited cardiomyopathy or arrhythmia using a no-charge, sponsored genetic testing program.
Methods:
De-identified clinical histories and genetic test results were reviewed from a no-charge cardiomyopathy and arrhythmia genetic testing program. Up to 150 genes associated with cardiomyopathies and arrhythmias were evaluated, and positive findings were compared to provider diagnoses at the time of testing request.
Results:
In a cohort of 4,782 patients, a positive result (molecular diagnosis) was observed in 961 (20%). Of the positive results, 670/961 (70%) conferred clinical management implications, including genes associated with targeted therapy (6%; 57/961) or increased risk of ventricular arrhythmia (18%; 169/961). Positive results for 11% (75/691) of evaluable patients would have been missed by condition-specific panels based on clinician-provided diagnoses.
Conclusions:
Combined cardiomyopathy and arrhythmia genetic testing identified clinically-relevant variants for 1 in 5 patients suspected of a cardiomyopathy or arrhythmia. Over two-thirds of positive findings had clinical management implications. Combined disease testing captures >10% of patients who would be missed with condition-specific panels and this greater clinical utility may outweigh the burden of uncertain results.
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.
Truty et al. describe mosaic sequence and copy number variants identified through genetic testing. Nearly 6,000 variants across >500 genes contributed to ∼2% of molecular diagnoses. Mosaic variants were mostly in cancer-related genes, at higher levels in younger individuals, and appeared to correlate with later disease onset or milder phenotypes.
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