Workflow for the Implementation of Precision Genomics in Healthcare.
ABSTRACT: To enable the implementation of precise genomics in a local healthcare system, we devised a pipeline for filtering and reporting of relevant genetic information to healthy individuals based on exome or genome data. In our analytical pipeline, the first tier of filtering is variant-centric, and it is based on the selection of annotated pathogenic, protective, risk factor, and drug response variants, and their one-by-one detailed evaluation. This is followed by a second-tier gene-centric deconstruction and filtering of virtual gene lists associated with diseases, and VUS-centric filtering according to ACMG pathogenicity criteria and pre-defined deleteriousness criteria. By applying this filtering protocol, we were able to provide valuable insights regarding the carrier status, pharmacogenetic profile, actionable cardiovascular and cancer predispositions, and potentially pathogenic variants of unknown significance to our patients. Our experience demonstrates that genomic profiling can be implemented into routine healthcare and provide information of medical significance.
Project description:PURPOSE:We evaluated the American College of Medical Genetics and Genomics/Association for Molecular Pathology (ACMG/AMP) variant pathogenicity guidelines for internal consistency and compatibility with Bayesian statistical reasoning. METHODS:The ACMG/AMP criteria were translated into a naive Bayesian classifier, assuming four levels of evidence and exponentially scaled odds of pathogenicity. We tested this framework with a range of prior probabilities and odds of pathogenicity. RESULTS:We modeled the ACMG/AMP guidelines using biologically plausible assumptions. Most ACMG/AMP combining criteria were compatible. One ACMG/AMP likely pathogenic combination was mathematically equivalent to pathogenic and one ACMG/AMP pathogenic combination was actually likely pathogenic. We modeled combinations that include evidence for and against pathogenicity, showing that our approach scored some combinations as pathogenic or likely pathogenic that ACMG/AMP would designate as variant of uncertain significance (VUS). CONCLUSION:By transforming the ACMG/AMP guidelines into a Bayesian framework, we provide a mathematical foundation for what was a qualitative heuristic. Only 2 of the 18 existing ACMG/AMP evidence combinations were mathematically inconsistent with the overall framework. Mixed combinations of pathogenic and benign evidence could yield a likely pathogenic, likely benign, or VUS result. This quantitative framework validates the approach adopted by the ACMG/AMP, provides opportunities to further refine evidence categories and combining rules, and supports efforts to automate components of variant pathogenicity assessments.
Project description:BACKGROUND:Prior research has established that the prevalence of pathogenic/likely pathogenic (P/LP) variants across all of the American College of Medical Genetics (ACMG) Secondary Findings (SF) genes is approximately 0.8-5%. We investigated the prevalence of P/LP variants in the 24 ACMG SF v2.0 cancer genes in a family-based cancer research cohort (n?=?1173) and in cancer-free ethnicity-matched controls (n?=?982). METHODS:We used InterVar to classify variants and subsequently conducted a manual review to further examine variants of unknown significance (VUS). RESULTS:In the 24 genes on the ACMG SF v2.0 list associated with a cancer phenotype, we observed 8 P/LP unique variants (8 individuals; 0.8%) in controls and 11 P/LP unique variants (14 individuals; 1.2%) in cases, a non-significant difference. We reviewed 115 VUS. The median estimated per-variant review time required was 30?min; the first variant within a gene took significantly (p?=?0.0009) longer to review (median = 60?min) compared with subsequent variants (median = 30?min). The concordance rate was 83.3% for the variants examined by two reviewers. CONCLUSION:The 115 VUS required database and literature review, a time- and labor-intensive process hampered by the difficulty in interpreting conflicting P/LP determinations. By rigorously investigating the 24 ACMG SF v2.0 cancer genes, our work establishes a benchmark P/LP variant prevalence rate in a familial cancer cohort and controls.
Project description:Inherited retinal dystrophies (IRD) are a highly heterogeneous group of rare diseases with a molecular diagnostic rate of >50%. Reclassification of variants of uncertain significance (VUS) poses a challenge for IRD diagnosis. We collected 668 IRD cases analyzed by our geneticists using two different clinical exome-sequencing tests. We identified 114 unsolved cases pending reclassification of 125 VUS and studied their genomic, functional, and laboratory-specific features, comparing them to pathogenic and likely pathogenic variants from the same cohort (N?=?390). While the clinical exome used did not show differences in diagnostic rate, the more IRD-experienced geneticist reported more VUS (p?=?4.07e-04). Significantly fewer VUS were reported in recessive cases (p?=?2.14e-04) compared to other inheritance patterns, and of all the genes analyzed, ABCA4 and IMPG2 had the lowest and highest VUS frequencies, respectively (p?=?3.89e-04, p?=?6.93e-03). Moreover, few frameshift and stop-gain variants were found to be informed VUS (p?=?6.73e-08 and p?=?2.93e-06). Last, we applied five pathogenicity predictors and found there is a significant proof of deleteriousness when all score for pathogenicity in missense variants. Altogether, these results provided input for a set of rules that correctly reclassified ~70% of VUS as pathogenic in validation datasets. Disease- and setting-specific features influence VUS reporting. Comparison with pathogenic and likely pathogenic variants can prioritize VUS more likely to be reclassified as causal.
Project description:Additional variant interpretation tools are required to effectively harness genomic sequencing for clinical applications. The American College of Medical Genetics and Genomics (ACMG) and Association for Molecular Pathology (AMP) published guidelines for clinical sequence variant interpretation, incorporating different types of data that lend varying levels of support towards a benign or pathogenic interpretation. Variants of uncertain significance (VUS) are those with either contradictory or insufficient evidence, and their uncertainty complicates patient counseling and management. Functional assays may provide a solution to evidence gaps relegating variants to the VUS category, but the impact of functional evidence in this framework has not been assessed. We employ an algorithmic analysis of the ACMG/AMP combining rules to assess how the availability of strong functional evidence could theoretically improve the ability to make a benign or pathogenic assertion. We follow this with analysis of actual evidence combinations met by variants through expert curations as part of the Clinical Genome Resource (ClinGen). We also examine the impact of functional evidence in a Bayesian adaptation of the ACMG/AMP framework. This lays the groundwork for an evidence-based prioritization of assay development and variant assessment by identifying genes and variants that may benefit the most from functional data.
Project description:Sequencing tests assaying panels of genes or whole exomes are widely available for cancer risk evaluation. However, methods for classification of variants resulting from this testing are not well studied. We evaluated the ability of a variant-classification methodology based on American College of Medical Genetics and Genomics (ACMG) guidelines to define the rate of mutations and variants of uncertain significance (VUS) in 180 medically relevant genes, including all ACMG-designated reportable cancer and non-cancer-associated genes, in individuals who met guidelines for hereditary cancer risk evaluation. We performed whole-exome sequencing in 404 individuals in 253 families and classified 1,640 variants. Potentially clinically actionable (likely pathogenic [LP] or pathogenic [P]) versus nonactionable (VUS, likely benign, or benign) calls were 95% concordant with locus-specific databases and Clinvar. LP or P mutations were identified in 12 of 25 breast cancer susceptibility genes in 26 families without identified BRCA1/2 mutations (11%). Evaluation of 84 additional genes associated with autosomal-dominant cancer susceptibility identified LP or P mutations in only two additional families (0.8%). However, individuals from 10 of 253 families (3.9%) had incidental LP or P mutations in 32 non-cancer-associated genes, and 9% of individuals were monoallelic carriers of a rare LP or P mutation in 39 genes associated with autosomal-recessive cancer susceptibility. Furthermore, 95% of individuals had at least one VUS. In summary, these data support the clinical utility of ACMG variant-classification guidelines. Additionally, evaluation of extended panels of cancer-associated genes in breast/ovarian cancer families leads to only an incremental clinical benefit but substantially increases the complexity of the results.
Project description:Whole exome sequencing (WES) is increasingly being used for diagnosis without adequate information on predictive characteristics of reportable variants typically found on any given individual and correlation with clinical phenotype. In this study, we performed WES on 89 deceased individuals (mean age at death 74 years, range 28-93) from the Mayo Clinic Biobank. Significant clinical diagnoses were abstracted from electronic medical record via chart review. Variants [Single Nucleotide Variant (SNV) and insertion/deletion] were filtered based on quality (accuracy >99%, read-depth >20, alternate-allele read-depth >5, minor-allele-frequency <0.1) and available HGMD/OMIM phenotype information. Variants were defined as Tier-1 (nonsense, splice or frame-shifting) and Tier-2 (missense, predicted-damaging) and evaluated in 56 ACMG-reportable genes, 57 cancer-predisposition genes, along with examining overall genotype-phenotype correlations. Following variant filtering, 7046 total variants were identified (~79/person, 644 Tier-1, 6402 Tier-2), 161 among 56 ACMG-reportable genes (~1.8/person, 13 Tier-1, 148 Tier-2), and 115 among 57 cancer-predisposition genes (~1.3/person, 3 Tier-1, 112 Tier-2). The number of variants across 57 cancer-predisposition genes did not differentiate individuals with/without invasive cancer history (P > 0.19). Evaluating genotype-phenotype correlations across the exome, 202(3%) of 7046 filtered variants had some evidence for phenotypic correlation in medical records, while 3710(53%) variants had no phenotypic correlation. The phenotype associated with the remaining 44% could not be assessed from a typical medical record review. These data highlight significant continued challenges in the ability to extract medically meaningful predictive results from WES.
Project description:BACKGROUND:Catecholaminergic polymorphic ventricular tachycardia (CPVT) is often a life-threatening arrhythmia disorder with variable penetrance and expressivity. Little is known about the incidence or outcomes of CPVT patients with ?2 variants. METHODS:The phenotypes, genotypes and outcomes of patients in the Pediatric and Congenital Electrophysiology Society CPVT Registry with ?2 variants in genes linked to CPVT were ascertained. The American College of Medical Genetics & Genomics (ACMG) criteria and structural mapping were used to predict the pathogenicity of variants (3D model of pig RyR2 in open-state). RESULTS:Among 237 CPVT subjects, 193 (81%) had genetic testing. Fifteen patients (8%) with a median age of 9 years (IQR 5-12) had ?2 variants. Sudden cardiac arrest occurred in 11 children (73%), although none died during a median follow-up of 4.3 years (IQR 2.5-6.1). Thirteen patients (80%) had at least two RYR2 variants, while the remaining two patients had RYR2 variants plus variants in other CPVT-linked genes. Among all variants identified, re-classification of the commercial laboratory interpretation using ACMG criteria led to the upgrade from variant of unknown significance (VUS) to pathogenic/likely pathogenic (P/LP) for 5 variants, and downgrade from P/LP to VUS for 6 variants. For RYR2 variants, 3D mapping using the RyR2 model suggested that 2 VUS by ACMG criteria were P/LP, while 2 variants were downgraded to likely benign. CONCLUSIONS:This severely affected cohort demonstrates that a minority of CPVT cases are related to ?2 variants, which may have implications on family-based genetic counselling. While multi-variant CPVT patients were at high-risk for sudden cardiac arrest, there are insufficient data to conclude that this genetic phenomenon has prognostic implications at present. Further research is needed to determine the significance and generalizability of this observation. This study also shows that a rigorous approach to variant re-classification using the ACMG criteria and 3D mapping is important in reaching an accurate diagnosis, especially in the multi-variant population.
Project description:Primary familial brain calcification (PFBC) is a rare cerebral microvascular calcifying disorder with a wide spectrum of motor, cognitive, and neuropsychiatric symptoms. It is typically inherited as an autosomal-dominant trait with four causative genes identified so far: SLC20A2, PDGFRB, PDGFB, and XPR1. Our study aimed at screening the coding regions of these genes in a series of 177 unrelated probands that fulfilled the diagnostic criteria for primary brain calcification regardless of their family history. Sequence variants were classified as pathogenic, likely pathogenic, or of uncertain significance (VUS), based on the ACMG-AMP recommendations. We identified 45 probands (25.4%) carrying either pathogenic or likely pathogenic variants (n?=?34, 19.2%) or VUS (n?=?11, 6.2%). SLC20A2 provided the highest contribution (16.9%), followed by XPR1 and PDGFB (3.4% each), and PDGFRB (1.7%). A total of 81.5% of carriers were symptomatic and the most recurrent symptoms were parkinsonism, cognitive impairment, and psychiatric disturbances (52.3%, 40.9%, and 38.6% of symptomatic individuals, respectively), with a wide range of age at onset (from childhood to 81 years). While the pathogenic and likely pathogenic variants identified in this study can be used for genetic counseling, the VUS will require additional evidence, such as recurrence in unrelated patients, in order to be classified as pathogenic.
Project description:As the number of genes identified for linkage to hearing loss has been increasing and more public databases have become available, we aimed to systematically evaluate all variants reported for nonsyndromic hearing loss (NSHL) based on their allele frequencies (AFs) in the general population. Among the 3,549 variants in 97 NSHL genes reported as pathogenic/likely pathogenic in ClinVar and HGMD, 1,618 were found in public databases (gnomAD, ExAC, EVS, and 1000G). To evaluate the pathogenicity of these variants, we employed AF thresholds and NSHL-optimized ACMG guidelines. AF thresholds were determined using a high-resolution variant frequency framework and Hardy-Weinberg equilibrium calculation: 0.6% and 0.1% for recessive and dominant genes, respectively. Filtering AFs of variants linked to NSHL were obtained based on AFs reported in gnomAD and ExAC. We found that 48 variants in 23 genes had filtering AFs above the suggested thresholds and assumed that these variants might be benign based on their filtering AFs. 47 variants, except for one notorious high-frequency GJB2 mutation (c.109G?>?A; p.Val37Ile), were confirmed to be benign/likely benign by the NSHL-optimized ACMG guidelines. The proposed systematic approach will aid in precise evaluation of NSHL variant pathogenicity in the context of filtering AFs, AF thresholds, and NSHL-specific ACMG guidelines, thus improving NSHL diagnostics.
Project description:BACKGROUND:To validate the clinical application of chromosomal microarray analysis (CMA) as a first-tier clinical diagnostic test and to determine the impact of CMA results on patient clinical management, we conducted a multicenter prospective study in Korean patients diagnosed as having developmental delay/intellectual disability (DD/ID), autism spectrum disorders (ASD), and multiple congenital anomalies (MCA). METHODS:We performed both CMA and G-banding cytogenetics as the first-tier tests in 617 patients. To determine whether the CMA results directly influenced treatment recommendations, the referring clinicians were asked to complete a 39-item questionnaire for each patient separately after receiving the CMA results. RESULTS:A total of 122 patients (19.8%) had abnormal CMA results, with either pathogenic variants (N=65) or variants of possible significance (VPS, N=57). Thirty-five well-known diseases were detected: 16p11.2 microdeletion syndrome was the most common, followed by Prader-Willi syndrome, 15q11-q13 duplication, Down syndrome, and Duchenne muscular dystrophy. Variants of unknown significance (VUS) were discovered in 51 patients (8.3%). VUS of genes putatively associated with developmental disorders were found in five patients: IMMP2L deletion, PTCH1 duplication, and ATRNL1 deletion. CMA results influenced clinical management, such as imaging studies, specialist referral, and laboratory testing in 71.4% of patients overall, and in 86.0%, 83.3%, 75.0%, and 67.3% of patients with VPS, pathogenic variants, VUS, and benign variants, respectively. CONCLUSIONS:Clinical application of CMA as a first-tier test improves diagnostic yields and the quality of clinical management in patients with DD/ID, ASD, and MCA.