Functional Analysis of G6PD Variants Associated With Low G6PD Activity in the All of Us Research Program

Glucose-6-phosphate dehydrogenase (G6PD) protects red blood cells against oxidative damage through regeneration of NADPH. Individuals with G6PD polymorphisms (variants) that produce an impaired G6PD enzyme are usually asymptomatic, but at risk of hemolytic anemia from oxidative stressors, including certain drugs and foods. Prevention of G6PD deficiency-related hemolytic anemia is achievable through G6PD genetic testing or whole-genome sequencing (WGS) to identify affected individuals who should avoid hemolytic triggers. However, accurately predicting the clinical consequence of G6PD variants is limited by over 800 G6PD variants which remain of uncertain significance. There also remains significant variability in which deficiency-causing variants are included in pharmacogenomic testing arrays across institutions: many panels only include c.202G>A, even though dozens of other variants can also cause G6PD deficiency. Here, we seek to improve G6PD genotype interpretation using data available in the All of Us Research Program and using a yeast functional assay. We confirm that G6PD coding variants are the main contributor to decreased G6PD activity, and that 13% of individuals in the All of Us data with deficiency-causing variants would be missed if only the c.202G>A variant were tested for. We expand clinical interpretation for G6PD variants of uncertain significance; reporting that c.595A>G, known as G6PD Dagua or G6PD Açores, and the newly identified variant c.430C>G, reduce activity sufficiently to lead to G6PD deficiency. We also provide evidence that five missense variants of uncertain significance are unlikely to lead to G6PD deficiency, since they were seen in hemi- or homozygous individuals without a reduction in G6PD activity. We also applied the new WHO guidelines and were able to classify two synonymous variants as WHO class C. We anticipate these results will improve the accuracy, and prompt increased use, of G6PD genetic tests through a more complete clinical interpretation of G6PD variants. As the All of Us data increases from 245,000 to 1 million participants, and additional functional assays are carried out, we expect this research to serve as a template to enable complete characterization of G6PD deficiency genotypes. With an increased number of interpreted variants, genetic testing of G6PD will be more informative for preemptively identifying individuals at risk for drug- or food-induced hemolytic anemia.

Genebe.net: Implementation and validation of an automatic ACMG variant pathogenicity criteria assignment

We present GeneBe, an online platform streamlining the automated application of American College of Medical Genetics and Genomics (ACMG), Association for Molecular Pathology (AMP), and the College of American Pathologists (CAP) criteria for assessment of pathogenicity of genetic variants. GeneBe utilizes automated algorithms that evaluate 17 criteria from 28, closely aligning with current guidelines and leveraging data from diverse sources, including ClinVar. The user-friendly web interface enables manual refinement of assignments for specific criteria based on site-collected data. Our algorithm demonstrates a high correlation (r = 0.90) of assigned pathogenicity scores compared to expert assessments from the ClinGen Evidence Repository and substantial concordance with ClinVar verdict assignments (κ = 0.69). Comparative analysis with other published tools reveals that GeneBe performs similarly to VarSome while being superior over TAPES and InterVar. In contrast to some other tools, GeneBe's web implementation is tracker-free and third-party request-free, safeguarding user privacy. Additionally, GeneBe offers an Application Programming Interface (API) for enhanced flexibility and integration into existing workflows and is provided free of charge for research purposes. GeneBe is available at https://genebe.net.

Pathogenic monoallelic variants in GLIS3 increase type 2 diabetes risk and identify a subgroup of patients sensitive to sulfonylureas

AIMS/HYPOTHESIS

GLIS3 encodes a transcription factor involved in pancreatic beta cell development and function. Rare pathogenic, bi-allelic mutations in GLIS3 cause syndromic neonatal diabetes whereas frequent SNPs at this locus associate with common type 2 diabetes risk. Because rare, functional variants located in other susceptibility genes for type 2 diabetes have already been shown to strongly increase individual risk for common type 2 diabetes, we aimed to investigate the contribution of rare pathogenic GLIS3 variants to type 2 diabetes.

METHODS

GLIS3 was sequenced in 5471 individuals from the Rare Variants Involved in Diabetes and Obesity (RaDiO) study. Variant pathogenicity was assessed following the criteria established by the American College of Medical Genetics and Genomics (ACMG). To address the pathogenic strong criterion number 3 (PS3), we conducted functional investigations of these variants using luciferase assays, focusing on capacity of GLIS family zinc finger 3 (GLIS3) to bind to and activate the INS promoter. The association between rare pathogenic or likely pathogenic (P/LP) variants and type 2 diabetes risk (and other metabolic traits) was then evaluated. A meta-analysis combining association results from RaDiO, the 52K study (43,125 individuals) and the TOPMed study (44,083 individuals) was finally performed.

RESULTS

Through targeted resequencing of GLIS3, we identified 105 rare variants that were carried by 395 participants from RaDiO. Among them, 49 variants decreased the activation of the INS promoter. Following ACMG criteria, 18 rare variants were classified as P/LP, showing an enrichment in the last two exons compared with the remaining exons (p<5×10-6; OR>3.5). The burden of these P/LP variants was strongly higher in individuals with type 2 diabetes (p=3.0×10-3; OR 3.9 [95% CI 1.4, 12]), whereas adiposity, age at type 2 diabetes diagnosis and cholesterol levels were similar between variant carriers and non-carriers with type 2 diabetes. Interestingly, all carriers with type 2 diabetes were sensitive to oral sulfonylureas. A total of 7 P/LP variants were identified in both 52K and TOPMed studies. The meta-analysis of association studies obtained from RaDiO, 52K and TOPMed showed an enrichment of P/LP GLIS3 variants in individuals with type 2 diabetes (p=5.6×10-5; OR 2.1 [95% CI 1.4, 2.9]).

CONCLUSIONS/INTERPRETATION

Rare P/LP GLIS3 variants do contribute to type 2 diabetes risk. The variants located in the distal part of the protein could have a direct effect on its functional activity by impacting its transactivation domain, by homology with the mouse GLIS3 protein. Furthermore, rare P/LP GLIS3 variants seem to have a direct clinical effect on beta cell function, which could be improved by increasing insulin secretion via the use of sulfonylureas.

Hemizygous splicing variant in CNKSR2 results in X-linked intellectual developmental disorder

BACKGROUND

Intellectual disability (ID) refers to a childhood-onset neurodevelopmental disorder with a prevalence of approximately 1%-3%.

METHODS

We performed whole exome sequencing for the patient with ID. And the splicing variant we found was validated by minigene assay.

RESULTS

Here, we report a boy with ID caused by a variant of CNKSR2. His neurological examination revealed hypsarrhythmia via electroencephalography and a right temporal polar arachnoid cyst via brain magnetic resonance imaging. A novel splicing variant in the CNKSR2 gene (NM_014927.5, c.1657+1G>A) was discovered by exome sequencing. The variant caused a 166 bp intron retention between exons 14 and 15, which was validated by a minigene assay. The variant was not reported in public databases such as gnomAD and the Exome Aggregation Consortium.

CONCLUSIONS

The variant was predicted to be damaging to correct the translation of the CNKRS2 protein and was classified as likely pathogenic according to the ACMG guidelines.

The Global ALPL gene variant classification project: Dedicated to deciphering variants

BACKGROUND

Hypophosphatasia (HPP) is an inherited multisystem disorder predominantly affecting the mineralization of bones and teeth. HPP is caused by pathogenic variants in ALPL, which encodes tissue non-specific alkaline phosphatase (TNSALP). Variants of uncertain significance (VUS) cause diagnostic delay and uncertainty amongst patients and health care providers.

RESULTS

The ALPL gene variant database (https://alplmutationdatabase.jku.at/) is an open-access archive for interpretation of the clinical significance of variants reported in ALPL. The database contains coding and non-coding variants, including single nucleotide variants, insertions/deletions and structural variants affecting coding or non-coding sequences of ALPL. Each variant in the database is displayed with details explaining the corresponding pathogenicity, and all reported genotypes and phenotypes, including references. In 2021, the ALPL gene variant classification project was established to reclassify VUS and continuously assess and update genetic, phenotypic, and functional variant information in the database. For this purpose, the database provides a unique submission system for clinicians, geneticists, genetic counselors, and researchers to submit VUS within ALPL for classification. An international, multidisciplinary consortium of HPP experts has been established to reclassify the submitted VUS using a multi-step process adhering to the stringent ACMG/AMP variant classification guidelines. These steps include a clinical phenotype assessment, deep literature research including artificial intelligence technology, molecular genetic assessment, and in-vitro functional testing of variants in a co-transfection model to measure ALP residual activity.

CONCLUSION

This classification project and the ALPL gene variant database will serve the global medical community, widen the genotypic and phenotypic HPP spectrum by reporting and characterizing new ALPL variants based on ACMG/AMP criteria and thus facilitate improved genetic counseling and medical decision-making for affected patients and families. The project may also serve as a gold standard framework for multidisciplinary collaboration for variant interpretation in other rare diseases.

Genetic analysis and natural history of Charcot-Marie-Tooth disease CMTX1 due to GJB1 variants

Charcot-Marie-Tooth disease (CMT) due to GJB1 variants (CMTX1) is the second most common form of CMT. It is an X-linked disorder characterized by progressive sensory and motor neuropathy with males affected more severely than females. Many reported GJB1 variants remain classified as variants of uncertain significance (VUS). In this large, international, multicentre study we prospectively collected demographic, clinical and genetic data on patients with CMT associated with GJB1 variants. Pathogenicity for each variant was defined using adapted American College of Medical Genetics criteria. Baseline and longitudinal analyses were conducted to study genotype-phenotype correlations, to calculate longitudinal change using the CMT Examination Score (CMTES), to compare males versus females, and pathogenic/likely pathogenic (P/LP) variants versus VUS. We present 387 patients from 295 families harbouring 154 variants in GJB1. Of these, 319 patients (82.4%) were deemed to have P/LP variants, 65 had VUS (16.8%) and three benign variants (0.8%; excluded from analysis); an increased proportion of patients with P/LP variants compared with using ClinVar's classification (74.6%). Male patients (166/319, 52.0%, P/LP only) were more severely affected at baseline. Baseline measures in patients with P/LP variants and VUS showed no significant differences, and regression analysis suggested the disease groups were near identical at baseline. Genotype-phenotype analysis suggested c.-17G>A produces the most severe phenotype of the five most common variants, and missense variants in the intracellular domain are less severe than other domains. Progression of disease was seen with increasing CMTES over time up to 8 years follow-up. Standard response mean (SRM), a measure of outcome responsiveness, peaked at 3 years with moderate responsiveness [change in CMTES (ΔCMTES) = 1.3 ± 2.6, P = 0.00016, SRM = 0.50]. Males and females progressed similarly up to 8 years, but baseline regression analysis suggested that over a longer period, females progress more slowly. Progression was most pronounced for mild phenotypes (CMTES = 0-7; 3-year ΔCMTES = 2.3 ± 2.5, P = 0.001, SRM = 0.90). Enhanced variant interpretation has yielded an increased proportion of GJB1 variants classified as P/LP and will aid future variant interpretation in this gene. Baseline and longitudinal analysis of this large cohort of CMTX1 patients describes the natural history of the disease including the rate of progression; CMTES showed moderate responsiveness for the whole group at 3 years and higher responsiveness for the mild group at 3, 4 and 5 years. These results have implications for patient selection for upcoming clinical trials.

A heterozygous pathogenic variant in the ATP6V1A gene triggering epilepsy in a large Chinese pedigree

Epilepsy is one of the most common disorders in children, with an incidence rate of approximately 5%. Although an increasing number of genes have been demonstrated to be pathogenic factors in epilepsy, evidence for a potential pathogenic role of ATP6V1A remains limited. Herein, the clinical and genetic data of a 5-year-old boy who experienced seizures at 9 months of age are collected. Genetic variants are screened using whole-exome sequencing (WES), and the effects of the candidate variants are further validated at both the RNA and protein levels. WES reveals a heterozygous variant [NM_001690.4: c .1132 C>T, p.Leu378Phe] of the ATP6V1A gene. This variant is not reported in the public database, but is predicted to be deleterious by multiple software packages, and classified as a variant of unknown significance following the American College of Medical Genetics and Genomics guidelines. Quantitative PCR and western blotting further confirm its down-regulatory role in both the RNA and protein expression of ATP6V1A. This case report confirms the pathogenicity of ATP6V1A in epilepsy with solid experimental evidence, thereby expanding the phenotype spectrum of ATP6V1A variants. More importantly, we show that seizures triggered by ATP6V1A variants could be controlled by Levetiracetam, crucially rescuing the development of the patient.

Multi-dimensional Insight into the Coexistence of Pathogenic Genes for ADAR1 and TSC2: Careful Consideration is Essential for Interpretation of ADAR1 Variants

Aicardi-Goutières syndrome 6 (AGS6) is a serious auto-immunization-associated acute neurologic decompensation. AGS6 manifests as acute onset of severe generalized dystonia of limbs and developmental regression secondary to febrile illness mostly. Dyschromatosis symmetrica hereditaria (DSH), as pigmentary genodermatosis, is a characterized mixture of hyperpigmented and hypopigmented macules. Both AGS6 and DSH are associated with ADAR1 pathogenic variants. To explore the etiology of a proband with developmental regression with mixture of hyperpigmentation and hypopigmentation macules, we used the trio-WES. Later, to clarify the association between variants and diseases, we used guidelines of ACMG for variants interpretation and quantitative Real-time PCR for verifying elevated expression levels of interferon-stimulated genes, separately. By WES, we detected 2 variants in ADAR1 and a variant in TSC2, respectively, were NM_001111.5:c.1096_1097del, NM_001111.5:c.518A>G, and NM_000548.5:c.1864C>T. Variants interpretation suggested that these 3 variants were both pathogenic. Expression levels of interferon-stimulated genes also elevated as expected. We verified the co-occurrence of pathogenic variants of ADAR1 and TSC2 in AGS6 patients with DSH. Our works contributed to the elucidation of ADAR1 pathogenic mechanism, given the specific pathogenic mechanism of ADAR1, and it is necessary to consider with caution when variants were found in ADAR1.

GABAA receptors in epilepsy: Elucidating phenotypic divergence through functional analysis of genetic variants

Normal brain function requires a tightly regulated balance between excitatory and inhibitory neurotransmissions. γ-Aminobutyric acid type A (GABAA ) receptors represent the major class of inhibitory ion channels in the mammalian brain. Dysregulation of these receptors and/or their associated pathways is strongly implicated in the pathophysiology of epilepsy. To date, hundreds of different GABAA receptor subunit variants have been associated with epilepsy, making them a prominent cause of genetically linked epilepsy. While identifying these genetic variants is crucial for accurate diagnosis and effective genetic counselling, it does not necessarily lead to improved personalised treatment options. This is because the identification of a variant does not reveal how the function of GABAA receptors is affected. Genetic variants in GABAA receptor subunits can cause complex changes to receptor properties resulting in various degrees of gain-of-function, loss-of-function or a combination of both. Understanding how variants affect the function of GABAA receptors therefore represents an important first step in the ongoing development of precision therapies. Furthermore, it is important to ensure that functional data are produced using methodologies that allow genetic variants to be classified using clinical guidelines such as those developed by the American College of Medical Genetics and Genomics. This article will review the current knowledge in the field and provide recommendations for future functional analysis of genetic GABAA receptor variants.

A Heterozygous Variant of FGF13 Caused X-Linked Developmental and Epileptic Encephalopathy 90 in a Chinese Family

Developmental and epileptic encephalopathy (DEE) refers to a group of severe epilepsy encephalopathy and development disorders, and its typical clinical features include seizures, drug resistance, and developmental delay or regression. To date, limited studies have reported DEEs driven by FGF13. Here, we reported a girl with developmental and epileptic encephalopathy 90 caused by variant of FGF13. Her electroencephalogram (EEG) showed discontinuous hypsarrhythmia, and a heterozygous nonsynonymous variant in FGF13 [NM_004114.4: c.5C>G, p.(Ala2Gly)] was identified from the proband. The variant was not reported in public databases such as gnomAD and Exome Aggregation Consortium (ExAC), and was predicted to be damaging to proteins and classified as likely pathogenic according to the ACMG guidelines. The seizure was finally controlled by a combination of ACTH + zonisamide (10 mg/kg.d) + levetiracetam (52 mg/kg.d) + clonazepam (0.7 mg/kg.d).

Prevalence of DDC genotypes in patients with aromatic L-amino acid decarboxylase (AADC) deficiency and in silico prediction of structural protein changes

Aromatic L-amino acid decarboxylase (AADC) deficiency is a rare autosomal recessive genetic disorder affecting the biosynthesis of dopamine, a precursor of both norepinephrine and epinephrine, and serotonin. Diagnosis is based on the analysis of CSF or plasma metabolites, AADC activity in plasma and genetic testing for variants in the DDC gene. The exact prevalence of AADC deficiency, the number of patients, and the variant and genotype prevalence are not known. Here, we present the DDC variant (n = 143) and genotype (n = 151) prevalence of 348 patients with AADC deficiency, 121 of whom were previously not reported. In addition, we report 26 new DDC variants, classify them according to the ACMG/AMP/ACGS recommendations for pathogenicity and score them based on the predicted structural effect. The splice variant c.714+4A>T, with a founder effect in Taiwan and China, was the most common variant (allele frequency = 32.4%), and c.[714+4A>T];[714+4A>T] was the most common genotype (genotype frequency = 21.3%). Approximately 90% of genotypes had variants classified as pathogenic or likely pathogenic, while 7% had one VUS allele and 3% had two VUS alleles. Only one benign variant was reported. Homozygous and compound heterozygous genotypes were interpreted in terms of AADC protein and categorized as: i) devoid of full-length AADC, ii) bearing one type of AADC homodimeric variant or iii) producing an AADC protein population composed of two homodimeric and one heterodimeric variant. Based on structural features, a score was attributed for all homodimers, and a tentative prediction was advanced for the heterodimer. Almost all AADC protein variants were pathogenic or likely pathogenic.

Community data-driven approach to identify pathogenic founder variants for pan-ethnic carrier screening panels

BACKGROUND

The American College of Medical Genetics and Genomics (ACMG) recently published new tier-based carrier screening recommendations. While many pan-ethnic genetic disorders are well established, some genes carry pathogenic founder variants (PFVs) that are unique to specific ethnic groups. We aimed to demonstrate a community data-driven approach to creating a pan-ethnic carrier screening panel that meets the ACMG recommendations.

METHODS

Exome sequencing data from 3061 Israeli individuals were analyzed. Machine learning determined ancestries. Frequencies of candidate pathogenic/likely pathogenic (P/LP) variants based on ClinVar and Franklin were calculated for each subpopulation based on the Franklin community platform and compared with existing screening panels. Candidate PFVs were manually curated through community members and the literature.

RESULTS

The samples were automatically assigned to 13 ancestries. The largest number of samples was classified as Ashkenazi Jewish (n = 1011), followed by Muslim Arabs (n = 613). We detected one tier-2 and seven tier-3 variants that were not included in existing carrier screening panels for Ashkenazi Jewish or Muslim Arab ancestries. Five of these P/LP variants were supported by evidence from the Franklin community. Twenty additional variants were detected that are potentially pathogenic tier-2 or tier-3.

CONCLUSIONS

The community data-driven and sharing approaches facilitate generating inclusive and equitable ethnically based carrier screening panels. This approach identified new PFVs missing from currently available panels and highlighted variants that may require reclassification.

Case report: Novel ETFDH compound heterozygous mutations identified in a patient with late-onset glutaric aciduria type II

Glutaric aciduria type II (GA II) is an autosomal recessive metabolic disorder of fatty acid, amino acid, and choline metabolism. The late-onset form of this disorder is caused by a defect in the mitochondrial electron transfer flavoprotein dehydrogenase or the electron transfer flavoprotein dehydrogenase (ETFDH) gene. Thus far, the high clinical heterogeneity of late-onset GA II has brought a great challenge for its diagnosis. In this study, we reported a 21-year-old Chinese man with muscle weakness, vomiting, and severe pain. Muscle biopsy revealed myopathological patterns of lipid storage myopathy, and urine organic acid analyses showed a slight increase in glycolic acid. All the aforementioned results were consistent with GA II. Whole-exome sequencing (WES), followed by bioinformatics and structural analyses, revealed two compound heterozygous missense mutations: c.1034A > G (p.H345R) on exon 9 and c.1448C>A (p.P483Q) on exon 11, which were classified as "likely pathogenic" according to American College of Medical Genetics and Genomics (ACMG). In conclusion, this study described the phenotype and genotype of a patient with late-onset GA II. The two novel mutations in ETFDH were found in this case, which further expands the list of mutations found in patients with GA II. Because of the treatability of this disease, GA II should be considered in all patients with muscular symptoms and acute metabolism decompensation such as hypoglycemia and acidosis.

Reduced penetrance of MODY-associated HNF1A/HNF4A variants but not GCK variants in clinically unselected cohorts

The true prevalence and penetrance of monogenic disease variants are often not known because of clinical-referral ascertainment bias. We comprehensively assess the penetrance and prevalence of pathogenic variants in HNF1A, HNF4A, and GCK that account for >80% of monogenic diabetes. We analyzed clinical and genetic data from 1,742 clinically referred probands, 2,194 family members, clinically unselected individuals from a US health system-based cohort (n = 132,194), and a UK population-based cohort (n = 198,748). We show that one in 1,500 individuals harbor a pathogenic variant in one of these genes. The penetrance of diabetes for HNF1A and HNF4A pathogenic variants was substantially lower in the clinically unselected individuals compared to clinically referred probands and was dependent on the setting (32% in the population, 49% in the health system cohort, 86% in a family member, and 98% in probands for HNF1A). The relative risk of diabetes was similar across the clinically unselected cohorts highlighting the role of environment/other genetic factors. Surprisingly, the penetrance of pathogenic GCK variants was similar across all cohorts (89%-97%). We highlight that pathogenic variants in HNF1A, HNF4A, and GCK are not ultra-rare in the population. For HNF1A and HNF4A, we need to tailor genetic interpretation and counseling based on the setting in which a pathogenic monogenic variant was identified. GCK is an exception with near-complete penetrance in all settings. This along with the clinical implication of diagnosis makes it an excellent candidate for the American College of Medical Genetics secondary gene list.

Comparison of the frequency of loss-of-function LZTR1 variants between Schwannomatosis patients and the general population

Schwannomatosis is a rare tumour predisposition syndrome that causes multiple schwannomas. Germline loss-of-function LZTR1 variants were only recently identified as disease-causing, so relatively few variants have been identified in patients. In addition, many loss-of-function variants exist in gnomAD in people who do not have clinical symptoms of schwannomatosis. These factors, and the incomplete penetrance seen in this condition, hinder definitive interpretation of the clinical significance of novel loss-of-function variants identified in schwannomatosis patients. We collated published loss-of-function LZTR1 variants identified in schwannomatosis patients and classified them according to current ACMG/AMP/ACGS guidelines. Subsequently, pathogenic/likely pathogenic schwannomatosis-associated loss-of-function variants were compared with loss-of-function LZTR1 variants reported in gnomAD data. This article is protected by copyright. All rights reserved.

Suspected clonal hematopoiesis as a natural functional assay of TP53 germline variant pathogenicity

PURPOSE

Some variants identified by multigene panel testing of DNA from blood present with low variant allele fraction (VAF), often a manifestation of clonal hematopoiesis. Research has shown that the proportion of variants with low VAF is especially high in TP53, the Li-Fraumeni syndrome gene. Based on the hypothesis that variants with low VAF are positively selected as drivers of clonal hematopoiesis, we investigated the use of VAF as a predictor of TP53 germline variant pathogenicity.

METHODS

We used data from 260,681 TP53 variants identified at 2 laboratories to compare the distribution of pathogenic and benign variants at different VAF intervals.

RESULTS

Likelihood ratios toward pathogenicity associated with a VAF < 26% equated to the American College of Medical Genetics/Association of Molecular Pathology strong strength level and were applicable for 1 in 5 variants of unknown significance.

CONCLUSION

In conclusion, detection of variants with low VAF in blood can be considered an in vivo functional assay to aid assessment of TP53 variant pathogenicity.

Variant Selection and Interpretation: An Example of Modified VarSome Classifier of ACMG Guidelines in the Diagnostic Setting

Variant interpretation is challenging as it involves combining different levels of evidence in order to evaluate the role of a specific variant in the context of a patient's disease. Many in-depth refinements followed the original 2015 American College of Medical Genetics (ACMG) guidelines to overcome subjective interpretation of criteria and classification inconsistencies. Here, we developed an ACMG-based classifier that retrieves information for variant interpretation from the VarSome Stable-API environment and allows molecular geneticists involved in clinical reporting to introduce the necessary changes to criterion strength and to add or exclude criteria assigned automatically, ultimately leading to the final variant classification. We also developed a modified ACMG checklist to assist molecular geneticists in adjusting criterion strength and in adding literature-retrieved or patient-specific information, when available. The proposed classifier is an example of integration of automation and human expertise in variant curation, while maintaining the laboratory analytical workflow and the established bioinformatics pipeline.

Quantifying prediction of pathogenicity for within-codon concordance (PM5) using 7541 functional classifications of BRCA1 and MSH2 missense variants

PURPOSE

Conditions and thresholds applied for evidence weighting of within-codon concordance (PM5) for pathogenicity vary widely between laboratories and expert groups. Because of the sparseness of available clinical classifications, there is little evidence for variation in practice.

METHODS

We used as a truthset 7541 dichotomous functional classifications of BRCA1 and MSH2, spanning 311 codons of BRCA1 and 918 codons of MSH2, generated from large-scale functional assays that have been shown to correlate excellently with clinical classifications. We assessed PM5 at 5 stringencies with incorporation of 8 in silico tools. For each analysis, we quantified a positive likelihood ratio (pLR, true positive rate/false positive rate), the predictive value of PM5-lookup in ClinVar compared with the functional truthset.

RESULTS

pLR was 16.3 (10.6-24.9) for variants for which there was exactly 1 additional colocated deleterious variant on ClinVar, and the variant under examination was equally or more damaging when analyzed using BLOSUM62. pLR was 71.5 (37.8-135.3) for variants for which there were 2 or more colocated deleterious ClinVar variants, and the variant under examination was equally or more damaging than at least 1 colocated variant when analyzed using BLOSUM62.

CONCLUSION

These analyses support the graded use of PM5, with potential to use it at higher evidence weighting where more stringent criteria are met.

A phenotype-enhanced variant classification framework to decrease the burden of missense variants of uncertain significance in type 1 long QT syndrome

BACKGROUND

Pathogenic/likely pathogenic (P/LP) variants in the KCNQ1-encoded Kv7.1 potassium channel cause type 1 long QT syndrome (LQT1). Despite the revamped 2015 American College of Medical Genetics (ACMG) variant interpretation guidelines, the burden of KCNQ1 variants of uncertain significance (VUS) in patients with LQTS remains ∼30%.

OBJECTIVE

The purpose of this study was to determine whether a phenotype-enhanced (PE) variant classification approach could reduce the VUS burden in LQTS genetic testing.

METHODS

Retrospective analysis was performed on 79 KCNQ1 missense variants in 356 patients from Mayo Clinic and an independent cohort of 42 variants in 225 patients from Amsterdam University Medical Center (UMC). Each variant was classified initially using the ACMG guidelines and then readjudicated using a PE-ACMG framework that incorporated the LQTS clinical diagnostic Schwartz score plus 4 "LQT1-defining features": broad-based/slow upstroke T waves, syncope/seizure during exertion, swimming-associated events, and a maladaptive LQT1 treadmill stress test.

RESULTS

According to the ACMG guidelines, Mayo Clinic variants were classified as follows: 17 of 79 P variants (22%), 34 of 79 LP variants (43%), and 28 of 79 VUS (35%). Similarly, for Amsterdam UMC, the variant distribution was 9 of 42 P variants (22%), 14 of 42 LP variants (33%), and 19 of 42 variants VUS (45%). After PE-ACMG readjudication, the total VUS burden decreased significantly from 28 (35%) to 13 (16%) (P = .0007) for Mayo Clinic and from 19 (45%) to 12 (29%) (P = .02) for Amsterdam UMC.

CONCLUSION

Phenotype-guided variant adjudication decreased significantly the VUS burden of LQT1 case-derived KCNQ1 missense variants in 2 independent cohorts. This study demonstrates the value of incorporating LQT1-specific phenotype/clinical data to aid in the interpretation of KCNQ1 missense variants identified during genetic testing for LQTS.

A guidelines-consistent carrier screening panel that supports equity across diverse populations

PURPOSE

The American College of Obstetricians and Gynecologists (ACOG) and the American College of Medical Genetics and Genomics (ACMG) suggest carrier screening panel design criteria intended to ensure meaningful results. This study used a data-driven approach to interpret the criteria to identify guidelines-consistent panels.

METHODS

Carrier frequencies in >460,000 individuals across 11 races/ethnicities were used to assess carrier frequency. Other criteria were interpreted on the basis of published data. A total of 176 conditions were then evaluated. Stringency thresholds were set as suggested by ACOG and/or ACMG or by evaluating conditions already recommended by ACOG and ACMG.

RESULTS

Forty and 75 conditions had carrier frequencies of ≥1 in 100 and ≥1 in 200, respectively; 175 had a well-defined phenotype; and 165 met at least 1 severity criterion and had an onset early in life. Thirty-seven conditions met conservative thresholds, including a carrier frequency of ≥1 in 100, and 74 conditions met permissive thresholds, including a carrier frequency of ≥1 in 200; thus, both were identified as guidelines-consistent panels.

CONCLUSION

Clear panel design criteria are needed to ensure quality and consistency among carrier screening panels. Evidence-based analyses of criteria resulted in the identification of guidelines-consistent panels of 37 and 74 conditions.

Actionable genomic variants in 6045 participants from the Qatar Genome Program

In a clinical setting, DNA sequencing can uncover findings unrelated to the purpose of genetic evaluation. The American College of Medical Genetics and Genomics (ACMG) recommends the evaluation and reporting of 59 genes from clinic genomic sequencing. While the prevalence of secondary findings is available from large population studies, these data lack Arab and other Middle Eastern populations. The Qatar Genome Program (QGP) generates whole-genome sequencing (WGS) data and combines it with phenotypic information to create a comprehensive database for studying the Qatari and wider Arab and Middle Eastern populations at the molecular level. This study identified and analyzed medically actionable variants in the 59 ACMG genes using WGS data from 6045 QGP participants. Our results identified a total of 60 pathogenic and likely pathogenic variants in 25 ACMG genes in 141 unique individuals. Overall, 2.3% of the QGP sequenced participants carried a pathogenic or likely pathogenic variant in one of the 59 ACMG genes. We evaluated the QGP phenotype-genotype association of additional nonpathogenic ACMG variants. These variants were found in patients from the Hamad Medical Corporation or reported incidental findings data in Qatar. We found a significant phenotype association for two variants, c.313+3A>C in LDLR, and c.58C>T (p.Gln20*) in the TPM1.

Refinement of the clinical variant interpretation framework by statistical evidence and machine learning

BACKGROUND

Although the American College of Medical Genetics and Genomics/Association for Molecular Pathology (ACMG/AMP) guidelines for variant interpretation are used widely in clinical genetics, there is room for improvement of these knowledge-based guidelines.

METHODS

Statistical assessment of average deleteriousness of start-lost, stop-lost, and in-frame insertion and deletion (indel) variants and extraction of deleterious subsets was performed, being informed by proportions of rare variants in the general population of the Genome Aggregation Database (gnomAD). A machine learning-based model scoring the pathogenicity of start-lost variants (the PoStaL model) was constructed by predicting possible translation initiation sites on transcripts by deep learning and training a random forest on known pathogenic and likely benign variants.

FINDINGS

The proportion of rare variants was highest in stop-lost variants, followed by in-frame indels and start-lost variants, suggesting that the criteria in the ACMG/AMP guidelines assigning PVS (pathogenic very strong) to start-lost variants and PM (pathogenic moderate) to stop-lost and in-frame indel variants would not be appropriate. Regarding deleterious subsets, stop-lost variants introducing extensions of more than 30 amino acids and in-frame indels computationally predicted to be damaging are enriched for rare and known pathogenic variants. For start-lost variants, we developed the PoStaL model, which outperforms existing tools. We also provide comprehensive lists of the PoStaL scores for start-lost variants and the length of extended amino acids by stop-lost variants.

CONCLUSIONS

Our study could contribute to refinement of the ACMG/AMP guidelines, provides resources for future investigation, and provides an example of how to improve knowledge-based frameworks by data-driven approaches.

FUNDING

The study was supported by grants from the Japan Agency for Medical Research and Development (AMED) and the Japan Society for the Promotion of Science (JSPS).

Patients with coronary heart disease, dilated cardiomyopathy and idiopathic ventricular tachycardia share overlapping patterns of pathogenic variation in cardiac risk genes

Background

Ventricular tachycardia (VT) is a major cause of sudden cardiac death (SCD). Clinical investigations can sometimes fail to identify the underlying cause of VT and the event is classified as idiopathic (iVT). VT contributes significantly to the morbidity and mortality in patients with coronary artery disease (CAD) and dilated cardiomyopathy (DCM). Since mutations in arrhythmia-associated genes frequently determine arrhythmia susceptibility screening for disease-predisposing variants could improve VT diagnostics and prevent SCD in patients.

Methods

Ninety-two patients diagnosed with coronary heart disease (CHD), DCM, or iVT were included in our study. We evaluated genetic profiles and variants in known cardiac risk genes by targeted next generation sequencing (NGS) using a newly designed custom panel of 96 genes. We hypothesized that shared morphological and phenotypical features among these subgroups may have an overlapping molecular base. To our knowledge, this was the first study of the deep sequencing of 96 targeted cardiac genes in Kazakhstan. The clinical significance of the sequence variants was interpreted according to the guidelines developed by the American College of Medical Genetics and Genomics (ACMG) and the Association for Molecular Pathology (AMP) in 2015. The ClinVar and Varsome databases were used to determine the variant classifications.

Results

Targeted sequencing and stepwise filtering of the annotated variants identified a total of 307 unique variants in 74 genes, totally 456 variants in the overall study group. We found 168 mutations listed in the Human Genome Mutation Database (HGMD) and another 256 rare/unique variants with elevated pathogenic potential. There was a predominance of high- to intermediate pathogenicity variants in LAMA2, MYBPC3, MYH6, KCNQ1, GAA, and DSG2 in CHD VT patients. Similar frequencies were observed in DCM VT, and iVT patients, pointing to a common molecular disease association. TTN, GAA, LAMA2, and MYBPC3 contained the most variants in the three subgroups which confirm the impact of these genes in the complex pathogenesis of cardiomyopathies and VT. The classification of 307 variants according to ACMG guidelines showed that nine (2.9%) variants could be classified as pathogenic, nine (2.9%) were likely pathogenic, 98 (31.9%) were of uncertain significance, 73 (23.8%) were likely benign, and 118 (38.4%) were benign. CHD VT patients carry rare genetic variants with increased pathogenic potential at a comparable frequency to DCM VT and iVT patients in genes related to sarcomere function, nuclear function, ion flux, and metabolism.

Conclusions

In this study we showed that in patients with VT secondary to coronary artery disease, DCM, or idiopathic etiology multiple rare mutations and clinically significant sequence variants in classic cardiac risk genes associated with cardiac channelopathies and cardiomyopathies were found in a similar pattern and at a comparable frequency.

Fitting a naturally scaled point system to the ACMG/AMP variant classification guidelines

Recently, we demonstrated that the qualitative American College of Medical Genetics and Genomics/Association for Medical Pathology (ACMG/AMP) guidelines for evaluation of Mendelian disease gene variants are fundamentally compatible with a quantitative Bayesian formulation. Here, we show that the underlying ACMG/AMP "strength of evidence categories" can be abstracted into a point system. These points are proportional to Log(odds), are additive, and produce a system that recapitulates the Bayesian formulation of the ACMG/AMP guidelines. The strengths of this system are its simplicity and that the connection between point values and odds of pathogenicity allows empirical calibration of the strength of evidence for individual data types. Weaknesses include that a narrow range of prior probabilities is locked in and that the Bayesian nature of the system is inapparent. We conclude that a points-based system has the practical attribute of user-friendliness and can be useful so long as the underlying Bayesian principles are acknowledged.

Suggested application of HER2+ breast tumor phenotype for germline TP53 variant classification within ACMG/AMP guidelines

Early onset breast cancer is the most common malignancy in women with Li-Fraumeni syndrome, caused by germline TP53 pathogenic variants. It has repeatedly been suggested that breast tumors from TP53 carriers are more likely to be HER2+ than those of noncarriers, but this information has not been incorporated into variant interpretation models for TP53. Breast tumor pathology is already being used quantitatively for assessing pathogenicity of germline variants in other genes, and it has been suggested that this type of evidence can be incorporated into current American College of Medical Genetics and Genomics/Association for Molecular Pathology (ACMG/AMP) guidelines for germline variant classification. Here, by reviewing published data and using internal datasets separated by different age groups, we investigated if breast tumor HER2+ status has utility as a predictor of TP53 germline variant pathogenicity, considering age at diagnosis. Overall, our results showed that the identification of HER2+ breast tumors diagnosed before the age of 40 can be conservatively incorporated into the current TP53-specific ACMG/AMP PP4 criterion, following a point system detailed in this manuscript. Further larger studies will be needed to reassess the value of HER2+ breast tumors diagnosed at a later age.

Reclassification of genetic variants in children with long QT syndrome

Background

Genes encoding cardiac ion channels or regulating proteins have been associated with the inherited form of long QT syndrome (LQTS). Complex pathophysiology and missing functional studies, however, often bedevil variant interpretation and classification. We aimed to evaluate the rate of change in variant classification based on current interpretation standards and dependent on clinical findings.

Methods

Medical charts of children with a molecular genetic diagnosis of LQTS presenting at our centers were retrospectively reviewed. Reinterpretation of originally reported variants in genes associated with LQTS was performed based on current knowledge (March 2019) and according to the “Standards and Guidelines for the Interpretation of Sequence Variants” by the ACMG 2015.

Results

About 84 distinct (likely) pathogenic variants identified in 127 patients were reinterpreted. In 12 variants (12/84, 14.3%), classification changed from (likely) pathogenic to variant of unknown significance (VUS). One of these variants was a hypomorphic allele escaping the standard variant classification. Individuals with variants that downgraded to VUS after reevaluation showed significantly lower Schwartz scores and QTc intervals compared to individuals with unchanged variant characterization.

Conclusion

This finding confirms genetic variant interpretation as a dynamic process and underlines the importance of ongoing genetic counseling, especially in LQTS patients with minor clinical criteria.

Differences in patient ascertainment affect the use of gene-specified ACMG/AMP phenotype-related variant classification criteria: Evidence for TP53

The American College of Medical Genetics and Genomics/Association for Molecular Pathology (ACMG/AMP) guidelines for variant classification are widely used for clinical interpretation of gene test results. These guidelines may be specified to genes/syndromes of interest to improve their utility in the clinical setting. As part of these specifications, phenotype-related criteria can be detailed and weighted depending on the personal history of disease for a given variant carrier. We investigated how ascertainment can affect the significance and/or weight of patient phenotype as a predictor of germline-variant pathogenicity, using the Li-Fraumeni Syndrome gene TP53 as an example. Likelihood ratios in favor of variant pathogenicity were determined for a report of the personal history of several TP53-related cancers, using data from 2,656 probands undergoing single-gene testing (SGT) and 15,483 undergoing multi-gene panel testing (MGPT). Overall, TP53-associated cancers were more predictive of pathogenicity, and demonstrated greater evidence weight, in the MGPT versus SGT dataset. This observation is almost certainly explained by differences in proband ascertainment for the two streams of testing, and these findings have implications for germline-variant classification using ACMG/AMP guidelines.

Systematic misclassification of missense variants in BRCA1 and BRCA2 "coldspots"

Purpose

Guidelines for variant interpretation incorporate variant hotspots in critical functional domains as evidence for pathogenicity (e.g., PM1 and PP2), but do not use “coldspots,” that is, regions without essential functions that tolerate variation, as evidence a variant is benign. To improve variant classification we evaluated BRCA1 and BRCA2 missense variants reported in ClinVar to identify regions where pathogenic missenses are extremely infrequent, defined as coldspots.

Methods

We used Bayesian approaches to model variant classification in these regions.

Results

BRCA1 exon 11 (~60% of the coding sequence), and BRCA2 exons 10 and 11 (~65% of the coding sequence), are coldspots. Of 89 pathogenic (P) or likely pathogenic (LP) missense variants in BRCA1, none are in exon 11 (odds <0.01, 95% confidence interval [CI] 0.0–0.01). Of 34 P or LP missense variants in BRCA2, none are in exons 10–11 (odds <0.01, 95% CI 0.0–0.01). More than half of reported missense variants of uncertain significance (VUS) in BRCA1 and BRCA2 are in coldspots (3115/5301 = 58.8%). Reclassifying these 3115 VUS as likely benign would substantially improve variant classification.

Conclusion

In BRCA1 and BRCA2 coldspots, missense variants are very unlikely to be pathogenic. Classification schemes that incorporate coldspots can reduce the number of VUS and mitigate risks from reporting benign variation as VUS.

Comprehensive Assessment of BARD1 Messenger Ribonucleic Acid Splicing With Implications for Variant Classification

Introduction: Case-control analyses have shown BARD1 variants to be associated with up to >2-fold increase in risk of breast cancer, and potentially greater risk of triple negative breast cancer. BARD1 is included in several gene sequencing panels currently marketed for the prediction of risk of cancer, however there are no gene-specific guidelines for the classification of BARD1 variants. We present the most comprehensive assessment of BARD1 messenger RNA splicing, and demonstrate the application of these data for the classification of truncating and splice site variants according to American College of Medical Genetics and Genomics and the Association for Molecular Pathology (ACMG/AMP) guidelines. Methods: Nanopore sequencing, short-read RNA-seq (whole transcriptome and targeted), and capillary electrophoresis analysis were performed by four laboratories to investigate alternative BARD1 splicing in blood, breast, and fimbriae/ovary related specimens from non-cancer affected tissues. Splicing data were also collated from published studies of nine different tissues. The impact of the findings for PVS1 annotation was assessed for truncating and splice site variants. Results: We identified 62 naturally occurring alternative spliced BARD1 splicing events, including 19 novel events found by next generation sequencing and/or reverse transcription PCR analysis performed for this study. Quantitative analysis showed that naturally occurring splicing events causing loss of clinically relevant domains or nonsense mediated decay can constitute up to 11.9% of overlapping natural junctions, suggesting that aberrant splicing can be tolerated up to this level. Nanopore sequencing of whole BARD1 transcripts characterized 16 alternative isoforms from healthy controls, revealing that the most complex transcripts combined only two alternative splicing events. Bioinformatic analysis of ClinVar submitted variants at or near BARD1 splice sites suggest that all consensus splice site variants in BARD1 should be considered likely pathogenic, with the possible exception of variants at the donor site of exon 5. Conclusions: No BARD1 candidate rescue transcripts were identified in this study, indicating that all premature translation-termination codons variants can be annotated as PVS1. Furthermore, our analysis suggests that all donor and acceptor (IVS+/-1,2) variants can be considered PVS1 or PVS1_strong, with the exception of variants targeting the exon 5 donor site, that we recommend considering as PVS1_moderate.

Toward automation of germline variant curation in clinical cancer genetics

Purpose:

Cancer care professionals are confronted with interpreting results from multiplexed gene sequencing of patients at hereditary risk for cancer. Assessments for variant classification now require orthogonal data searches and aggregation of multiple lines of evidence from diverse resources. The clinical genetics community needs a fast algorithm that automates ACMG based variant classification and provides uniform results.

Methods:

Pathogenicity of Mutation Analyzer (PathoMAN) automates germline genomic variant curation from clinical sequencing based on ACMG guidelines. PathoMAN aggregates multiple tracks of genomic, protein and disease specific information from public sources. We compared expertly curated variant data from clinical laboratories to assess performance.

Results:

PathoMAN achieved a high overall concordance of 94.4% for pathogenic and 81.1% for benign variants. We observed negligible discordance (0.3% pathogenic, 0% benign) when contrasted against expert curated variants. Some loss of resolution (5.3% pathogenic, 18.9% benign) and gain of resolution (1.6% pathogenic, 3.8% benign) was also observed.

Conclusion:

Automation of variant curation enables unbiased, fast, efficient delivery of results in both clinical and laboratory research. We highlight the advantages and weaknesses related to the programmable automation of variant classification. PathoMAN will aid in rapid variant classification by generating robust models using a knowledge-base of diverse genetic data. https://pathoman.mskcc.org

CardioVAI: An automatic implementation of ACMG-AMP variant interpretation guidelines in the diagnosis of cardiovascular diseases

Variant interpretation for the diagnosis of genetic diseases is a complex process. The American College of Medical Genetics and Genomics, with the Association for Molecular Pathology, have proposed a set of evidence-based guidelines to support variant pathogenicity assessment and reporting in Mendelian diseases. Cardiovascular disorders are a field of application of these guidelines, but practical implementation is challenging due to the genetic disease heterogeneity and the complexity of information sources that need to be integrated. Decision support systems able to automate variant interpretation in the light of specific disease domains are demanded. We implemented CardioVAI (Cardio Variant Interpreter), an automated system for guidelines based variant classification in cardiovascular-related genes. Different omics-resources were integrated to assess pathogenicity of every genomic variant in 72 cardiovascular diseases related genes. We validated our method on benchmark datasets of high-confident assessed variants, reaching pathogenicity and benignity concordance up to 83 and 97.08%, respectively. We compared CardioVAI to similar methods and analyzed the main differences in terms of guidelines implementation. We finally made available CardioVAI as a web resource (http://cardiovai.engenome.com/) that allows users to further specialize guidelines recommendations.

Improved, ACMG-compliant, in silico prediction of pathogenicity for missense substitutions encoded by TP53 variants

Clinical interpretation of germline missense variants represents a major challenge, including those in the TP53 Li-Fraumeni syndrome gene. Bioinformatic prediction is a key part of variant classification strategies. We aimed to optimize the performance of the Align-GVGD tool used for p53 missense variant prediction, and compare its performance to other bioinformatic tools (SIFT, PolyPhen-2) and ensemble methods (REVEL, BayesDel). Reference sets of assumed pathogenic and assumed benign variants were defined using functional and/or clinical data. Area under the curve and Matthews correlation coefficient (MCC) values were used as objective functions to select an optimized protein multisequence alignment with best performance for Align-GVGD. MCC comparison of tools using binary categories showed optimized Align-GVGD (C15 cut-off) combined with BayesDel (0.16 cut-off), or with REVEL (0.5 cut-off), to have the best overall performance. Further, a semi-quantitative approach using multiple tiers of bioinformatic prediction, validated using an independent set of nonfunctional and functional variants, supported use of Align-GVGD and BayesDel prediction for different strength of evidence levels in ACMG/AMP rules. We provide rationale for bioinformatic tool selection for TP53 variant classification, and have also computed relevant bioinformatic predictions for every possible p53 missense variant to facilitate their use by the scientific and medical community.

Genomic sequencing identifies secondary findings in a cohort of parent study participants

PURPOSE

Clinically relevant secondary variants were identified in parents enrolled with a child with developmental delay and intellectual disability.

METHODS

Exome/genome sequencing and analysis of 789 "unaffected" parents was performed.

RESULTS

Pathogenic/likely pathogenic variants were identified in 21 genes within 25 individuals (3.2%), with 11 (1.4%) participants harboring variation in a gene defined as clinically actionable by the American College of Medical Genetics and Genomics. These 25 individuals self-reported either relevant clinical diagnoses (5); relevant family history or symptoms (13); or no relevant family history, symptoms, or clinical diagnoses (7). A limited carrier screen was performed yielding 15 variants in 48 (6.1%) parents. Parents were also analyzed as mate pairs (n = 365) to identify cases in which both parents were carriers for the same recessive disease, yielding three such cases (0.8%), two of which had children with the relevant recessive disease. Four participants had two findings (one carrier and one noncarrier variant). In total, 71 of the 789 enrolled parents (9.0%) received secondary findings.

CONCLUSION

We provide an overview of the rates and types of clinically relevant secondary findings, which may be useful in the design and implementation of research and clinical sequencing efforts to identify such findings.

Identification of Misclassified ClinVar Variants via Disease Population Prevalence

There is a significant interest in the standardized classification of human genetic variants. We used whole-genome sequence data from 10,495 unrelated individuals to contrast population frequency of pathogenic variants to the expected population prevalence of the disease. Analyses included the ACMG-recommended 59 gene-condition sets for incidental findings and 463 genes associated with 265 OrphaNet conditions. A total of 25,505 variants were used to identify patterns of inflation (i.e., excess genetic risk and misclassification). Inflation increases as the level of evidence supporting the pathogenic nature of the variant decreases. We observed up to 11.5% of genetic disorders with inflation in pathogenic variant sets and up to 92.3% for the variant set with conflicting interpretations. This improved to 7.7% and 57.7%, respectively, after filtering for disease-specific allele frequency. The patterns of inflation were replicated using public data from more than 138,000 genomes. The burden of rare variants was a main contributing factor of the observed inflation, indicating collective misclassified rare variants. We also analyzed the dynamics of re-classification of variant pathogenicity in ClinVar over time, which indicates progressive improvement in variant classification. The study shows that databases include a significant proportion of wrongly ascertained variants; however, it underscores the critical role of ClinVar to contrast claims and foster validation across submitters.

Evaluation of in silico algorithms for use with ACMG/AMP clinical variant interpretation guidelines

BACKGROUND

The American College of Medical Genetics and American College of Pathologists (ACMG/AMP) variant classification guidelines for clinical reporting are widely used in diagnostic laboratories for variant interpretation. The ACMG/AMP guidelines recommend complete concordance of predictions among all in silico algorithms used without specifying the number or types of algorithms. The subjective nature of this recommendation contributes to discordance of variant classification among clinical laboratories and prevents definitive classification of variants.

RESULTS

Using 14,819 benign or pathogenic missense variants from the ClinVar database, we compared performance of 25 algorithms across datasets differing in distinct biological and technical variables. There was wide variability in concordance among different combinations of algorithms with particularly low concordance for benign variants. We also identify a previously unreported source of error in variant interpretation (false concordance) where concordant in silico predictions are opposite to the evidence provided by other sources. We identified recently developed algorithms with high predictive power and robust to variables such as disease mechanism, gene constraint, and mode of inheritance, although poorer performing algorithms are more frequently used based on review of the clinical genetics literature (2011-2017).

CONCLUSIONS

Our analyses identify algorithms with high performance characteristics independent of underlying disease mechanisms. We describe combinations of algorithms with increased concordance that should improve in silico algorithm usage during assessment of clinically relevant variants using the ACMG/AMP guidelines.

Clinical application of ACMG-AMP guidelines in HNF1A and GCK variants in a cohort of MODY families

Maturity-onset diabetes of the young (MODY) is a form of monogenic diabetes with autosomal dominant inheritance. GCK -MODY and HNF1A -MODY are the prevalent subtypes. Currently, there is growing concern regarding the correct interpretation of molecular genetic findings. The American College of Medical Genetics and Genomics (ACMG) updated guidelines to interpret and classify molecular variants. This study aimed to determine the prevalence of MODY ( GCK / HNF1A ) in a large cohort of Brazilian families, to report variants related to phenotype, and to classify them according to ACMG guidelines. One hundred and nine probands were investigated, 45% with clinical suspicion of GCK -MODY and 55% with suspicion of HNF1A -MODY. Twenty-five different variants were identified in GCK gene (30 probands-61% of positivity), and 7 variants in HNF1A (10 probands-17% of positivity). Fourteen of them were novel (12- GCK /2- HNF1A ). ACMG guidelines were able to classify a large portion of variants as pathogenic (36%- GCK /86%- HNF1A ) and likely pathogenic (44%- GCK /14%- HNF1A ), with 16% (5/32) as uncertain significance. This allows us to determine the pathogenicity classification more efficiently, and also reinforces the suspected associations with the phenotype among novel variants.

InterVar: Clinical Interpretation of Genetic Variants by the 2015 ACMG-AMP Guidelines

In 2015, the American College of Medical Genetics and Genomics (ACMG) and the Association for Molecular Pathology (AMP) published updated standards and guidelines for the clinical interpretation of sequence variants with respect to human diseases on the basis of 28 criteria. However, variability between individual interpreters can be extensive because of reasons such as the different understandings of these guidelines and the lack of standard algorithms for implementing them, yet computational tools for semi-automated variant interpretation are not available. To address these problems, we propose a suite of methods for implementing these criteria and have developed a tool called InterVar to help human reviewers interpret the clinical significance of variants. InterVar can take a pre-annotated or VCF file as input and generate automated interpretation on 18 criteria. Furthermore, we have developed a companion web server, wInterVar, to enable user-friendly variant interpretation with an automated interpretation step and a manual adjustment step. These tools are especially useful for addressing severe congenital or very early-onset developmental disorders with high penetrance. Using results from a few published sequencing studies, we demonstrate the utility of InterVar in significantly reducing the time to interpret the clinical significance of sequence variants.

Integration of 60,000 exomes and ACMG guidelines question the role of Catecholaminergic Polymorphic Ventricular Tachycardia-associated variants

Catecholaminergic Polymorphic Ventricular Tachycardia (CPVT) is a highly lethal cardiac arrhythmia disease occurring during exercise or psychological stress. CPVT has an estimated prevalence of 1:10,000 and has mainly been associated with variants in calcium-regulating genes. Identification of potential false-positive pathogenic variants was conducted by searching the Exome Aggregation Consortium (ExAC) database (n = 60,706) for variants reported to be associated with CPVT. The pathogenicity of the interrogated variants was assessed using guidelines from the American College of Medical Genetics and Genomics (ACMG) and in silico prediction tools. Of 246 variants 38 (15%) variants previously associated with CPVT were identified in the ExAC database. We predicted the CPVT prevalence to be 1:132. The ACMG standards classified 29% of ExAC variants as pathogenic or likely pathogenic. The in silico predictions showed a reduced probability of disease-causing effect for the variants identified in the exome database (p < 0.001). We have observed a large overrepresentation of previously CPVT-associated variants in a large exome database. Based on the frequency of CPVT in the general population, it is less likely that the previously proposed variants are associated with a highly penetrant monogenic form of the disease.

Prevention for those who can pay: insurance reimbursement of genetic-based preventive interventions in the liminal state between health and disease

Clinical use of genetic testing to predict adult onset conditions allows individuals to minimize or circumvent disease when preventive medical interventions are available. Recent policy recommendations and changes expand patient access to information about asymptomatic genetic conditions and create mechanisms for expanded insurance coverage for genetic tests. The American College of Medical Genetics and Genomics (ACMG) recommends that laboratories provide incidental findings of medically actionable genetic variants after whole genome sequencing. The Patient Protection and Affordable Care Act (ACA) established mechanisms to mandate coverage for genetic tests, such as BRCA. The ACA and ACMG, however, do not address insurance coverage for preventive interventions. These policies equate access to testing as access to prevention, without exploring the accessibility and affordability of interventions. In reality, insurance coverage for preventive interventions in asymptomatic adults is variable given the US health insurance system's focus on treatment. Health disparities will be exacerbated if only privileged segments of society can access preventive interventions, such as prophylactic surgeries, screenings, or medication. To ensure equitable access to interventions, federal or state legislatures should mandate insurance coverage for both predictive genetic testing and recommended follow-up interventions included in a list established by an expert panel or regulatory body.

Return of Results from Genomic Sequencing: A Policy Discussion of Secondary Findings for Cancer Predisposition

Advances in DNA sequencing technology now allow for the rapid genome-wide identification of inherited and acquired genetic variants including those that have been identified as pathogenic alleles for a number of diseases including cancer. Whole genome and exome sequencing are increasingly becoming a part of both clinical practice and research studies. In 2013 the American College of Medical Genetics and Genomics (ACMG) recommended that results of pathogenic genetic variants in 56 genes, nearly half of which comprise cancer genes (including BRCA1, BRCA2, TP53, MLH1, MLH2, MSH6, PMS2, and APC),be returned to patients who have their genome sequenced independent of the purpose for the test. This recommendation has been highly controversial for several reasons, particularly the recommendation that individuals be returned secondary findings of disease causing variants for adult onset conditions regardless of age and without consideration of patient preferences. In addition, the policy regarding returning results of secondary findings from genomic sequencing studies in research settings is currently unclear. In response to these emerging ethical issues, the Washington University Brown School in St. Louis, MO, United Stateshosted a policy forum entitled "First do no harm: Genetic privacy in the age of genomic sequencing" on February 25^th, 2014. The forum included a panel of experts to discuss their views on ethical issues related to return of results in both the clinical and research settings. In this report, we highlight key issues related to return of results from genome sequencing tests that emerged during the forum.