The current state of clinical interpretation of sequence variants

Challenges of Providing Concordant Interpretation of Somatic Variants in Non-Small Cell Lung Cancer: A Multicenter Study

Background: Success of multiple-gene mutation tests by next-generation sequencing (NGS), associated with molecular targeting therapies for cancers, depending on the accuracy and consistency of interpreting variants. Here, we summarized reports from clinical laboratories for cases with non-small cell lung cancer (NSCLC) and discussed conflicting interpretations of somatic variants. Methods: Three mimetic DNA samples, containing six somatic mutations, were prepared based on three clinical case reports of NSCLC. Clinical reports and genetic testing questionnaires were collected from 67 laboratories enrolled in this investigation. Results: Thirty-four laboratories with correct variant results identified two variants, based on FDA approval of targeted drugs for the same tumor, consistently, with strong clinical significance, whereas the other variants were classified with conflicting interpretations. Discordant interpretations were reported for ERBB2 with three different classifications, including strong clinical significance (53.0%, 18/34), potential clinical significance (38.2%, 13/34), and unknown significance (8.8%, 3/34). In the variant therapeutic drug recommendation section, 32.4% of the laboratories (11/34) did not recommend all the available therapeutic drugs designated by the National Comprehensive Cancer Network (NCCN). In the remaining group of 33 laboratories with incorrect variant results, less correct classifications were acquired for the variants with strong clinical significance. Conclusions: Owing to numerous reasons, the interpretation of variants differed greatly, which might in turn lead to the inappropriate clinical care of patients with NSCLC. By analyzing the limitations of different databases used by laboratories, we integrated various types of databases with different levels of evidence to form a comprehensive and detailed variant interpretation pipeline, aiming to standardize the variant classification and provide accurate and sufficient therapeutic drug recommendation to clinicians for minimal-inappropriate therapeutic options.

Risk Factor Genes in Patients with Dystonia: A Comprehensive Review

Background

Dystonia is a movement disorder with high heterogeneity regarding phenotypic appearance and etiology that occurs in both sporadic and familial forms. The etiology of the disease remains unknown. However, there is increasing evidence suggesting that a small number of gene alterations may lead to dystonia. Although pathogenic variants to the familial type of dystonia have been extensively reviewed and discussed, relatively little is known about the contribution of single-nucleotide polymorphisms (SNPs) to dystonia. This review focuses on the potential role of SNPs and other variants in dystonia susceptibility.

Methods

We searched the PubMed database for peer-reviewed articles published in English, from its inception through January 2018, that concerned human studies of dystonia and genetic variants. The following search terms were included: “dystonia” in combination with the following terms: 1) “polymorphisms” and 2) “SNPs” as free words.

Results

A total of 43 published studies regarding TOR1A, BDNF, DRD5, APOE, ARSG, NALC, OR4X2, COL4A1, TH, DDC, DBH, MAO, COMT, DAT, GCH1, PRKRA, MR-1, SGCE, ATP1A3, TAF1, THAP1, GNAL, DRD2, HLA-DRB, CBS, MTHFR, and MS genes, were included in the current review.

Discussion

To date, a few variants, which are possibly involved in several molecular pathways, have been related to dystonia. Large cohort studies are needed to determine robust associations between variants and dystonia with adjustment for other potential cofounders, in order to elucidate the pathogenic mechanisms of dystonia and the net effect of the genes.

Adapting crowdsourced clinical cancer curation in CIViC to the ClinGen minimum variant level data community-driven standards

Harmonization of cancer variant representation, efficient communication, and free distribution of clinical variant-associated knowledge are central problems that arise with increased usage of clinical next-generation sequencing. The Clinical Genome Resource (ClinGen) Somatic Working Group (WG) developed a minimal variant level data (MVLD) representation of cancer variants, and has an ongoing collaboration with Clinical Interpretations of Variants in Cancer (CIViC), an open-source platform supporting crowdsourced and expert-moderated cancer variant curation. Harmonization between MVLD and CIViC variant formats was assessed by formal field-by-field analysis. Adjustments to the CIViC format were made to harmonize with MVLD and support ClinGen Somatic WG curation activities, including four new features in CIViC: (1) introduction of an assertions feature for clinical variant assessment following the Association of Molecular Pathologists (AMP) guidelines, (2) group-level curation tracking for organizations, enabling member transparency, and curation effort summaries, (3) introduction of ClinGen Allele Registry IDs to CIViC, and (4) mapping of CIViC assertions into ClinVar submission with automated submissions. A generalizable workflow utilizing MVLD and new CIViC features is outlined for use by ClinGen Somatic WG task teams for curation and submission to ClinVar, and provides a model for promoting harmonization of cancer variant representation and efficient distribution of this information.

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.

Genomic Landscape and Mutational Signatures of Deafness-Associated Genes

The classification of genetic variants represents a major challenge in the post-genome era by virtue of their extraordinary number and the complexities associated with ascribing a clinical impact, especially for disorders exhibiting exceptional phenotypic, genetic, and allelic heterogeneity. To address this challenge for hearing loss, we have developed the Deafness Variation Database (DVD), a comprehensive, open-access resource that integrates all available genetic, genomic, and clinical data together with expert curation to generate a single classification for each variant in 152 genes implicated in syndromic and non-syndromic deafness. We evaluate 876,139 variants and classify them as pathogenic or likely pathogenic (more than 8,100 variants), benign or likely benign (more than 172,000 variants), or of uncertain significance (more than 695,000 variants); 1,270 variants are re-categorized based on expert curation and in 300 instances, the change is of medical significance and impacts clinical care. We show that more than 96% of coding variants are rare and novel and that pathogenicity is driven by minor allele frequency thresholds, variant effect, and protein domain. The mutational landscape we define shows complex gene-specific variability, making an understanding of these nuances foundational for improved accuracy in variant interpretation in order to enhance clinical decision making and improve our understanding of deafness biology.

Homozygosity mapping provides supporting evidence of pathogenicity in recessive Mendelian disease

PURPOSE

One of the greatest challenges currently facing those studying Mendelian disease is identifying the pathogenic variant from the long list produced by a next-generation sequencing test. We investigate the predictive ability of homozygosity mapping for identifying the regions likely to contain the causative variant.

METHODS

We use 179 homozygous pathogenic variants from three independent cohorts to investigate the predictive power of homozygosity mapping.

RESULTS

We demonstrate that homozygous pathogenic variants in our cohorts are disproportionately likely to be found within one of the largest regions of homozygosity: 80% of pathogenic variants are found in a homozygous region that is in the ten largest regions in a sample. The maximal predictive power is achieved in patients with <8% homozygosity and variants >3 Mb from a telomere; this gives an area under the curve (AUC) of 0.735 and results in 92% of the causative variants being in one of the ten largest homozygous regions.

CONCLUSION

This predictive power can be used to prioritize the list of candidate variants in gene discovery studies. When classifying a homozygous variant the size and rank of the region of homozygosity in which the candidate variant is located can also be considered as supporting evidence for pathogenicity.

The High-Throughput Analyses Era: Are We Ready for the Data Struggle?

Recent and rapid technological advances in molecular sciences have dramatically increased the ability to carry out high-throughput studies characterized by big data production. This, in turn, led to the consequent negative effect of highlighting the presence of a gap between data yield and their analysis. Indeed, big data management is becoming an increasingly important aspect of many fields of molecular research including the study of human diseases. Now, the challenge is to identify, within the huge amount of data obtained, that which is of clinical relevance. In this context, issues related to data interpretation, sharing and storage need to be assessed and standardized. Once this is achieved, the integration of data from different -omic approaches will improve the diagnosis, monitoring and therapy of diseases by allowing the identification of novel, potentially actionably biomarkers in view of personalized medicine.

Observed frequency and challenges of variant reclassification in a hereditary cancer clinic

PurposeEfforts have been made by the American College of Medical Genetics and Genomics and the Association for Molecular Pathology to make variant classification more uniform, but many limitations remain. Reclassification of a variant of uncertain significance (VUS) is expected, but other more certain calls, like pathogenic or benign, can also be reclassified once additional information is gathered. Variant reclassification can create difficult circumstances for both patients and clinicians.MethodsRetrospective review of all variant reclassifications in genes associated with hereditary cancer syndromes at one clinic between September 2013 and February 2017 was completed. All variant reclassifications were completed and reported by the original testing laboratory.ResultsA total of 1,103 hereditary cancer tests were ordered. Fewer than 5% (40/1,103) of the initial reports were updated during that time period. Most reclassifications (29/40) were downgrades of VUS to likely benign. Only three reclassifications could potentially alter medical management.ConclusionThe majority of variant reclassifications do not impact medical management. Upgrading a variant call to pathogenic could be important for a patient's care and shows the importance of open communication between laboratories and clinicians. A variant downgrade from pathogenic can be a significant reclassification as well, especially if prophylactic surgery has been completed.

The Promise of Molecular Autopsy in Forensic Pathology Practice

Molecular autopsy is changing the practice of forensic pathology. Under some circumstances, one must contemplate the involvement of genetic factors to help explain why someone has died unexpectedly. Such considerations most commonly occur when a young person dies by natural means. However, there are deaths that occur by nonnatural means that the forensic pathologist will be asked to investigate, which could involve natural disease that has a significant genetic underpinning. Elucidation of genetic mutations may not only further an understanding of the pathophysiology at hand, but also speak to underlying susceptibilities in an individual who dies that may not have been recognized. In addition, one may occasionally identify pathological findings that are confused for trauma that may actually be better explained by an underlying disease process. Using molecular medicine as a tool to explore such possibilities can improve the quality of death investigations and provide a new lens to probe challenging and contentious forensic cases that have proved resistant to traditional methods.

Universal Genomic Testing: The next step in oncological decision-making or a dead end street?

The concept of 'personalised medicine' aims at allocating patients to different treatment options based on individual characteristics to optimise treatment benefit and side effects. In oncology, personalised treatments coupled to biomarkers have led to the approval of targeted agents with high anti-tumour activity. However, these therapies are often limited to narrow, molecularly defined subsets of patients with a specific morphomolecular tumour profile. Recently, it became obvious that the same molecular alteration might drive oncogenesis in many different tumours, and it might be beneficial to target the alteration in a histology informed but entity-overarching way. Consequently, Universal Genomic Testing (UGT) of tumours encompassing panel sequencing to whole-exome and transcriptome sequencing is propagated to revolutionise oncology. This article will describe the developments leading to identification and application of potential biomarkers using UGT. On this basis, it will review the clinical evidence of this approach and summarise recommendations for the ongoing evaluation of UGT as the next step in oncological decision-making.

[New developments in molecularbiological diagnostic]

Today, we have access to excellent and advanced molecular methods that are already widely used. This requires rules to control the quality of the methods as well as the laboratory. Both aspects will be discussed in the article. Following the isolation of nucleic acids they are used for genotyping which allows to address several questions: diagnosis of inherited diseases, inherited predispositions, forensic analyses, identification and typing of bacteria or viruses, elucidation of evolutionary aspects. Importantly, it has to be realized that the type and heterogeneity of phenotypically relevant mutations determines the method used for testing. Today, most laboratories use either PCR analyses or Sanger sequencing for diagnostic applications. However, increasingly next generation sequencing (NGS) is applied. The clinical use of NGS is still very challenging, but we can expect that the switch to regular application of this method will be coming in the very near future. The price for NGS has gone down to approx. USD 1000,- which makes the routine diagnostic use feasible. Nevertheless, several challenges have yet to be solved, such as the processing of the large data volume as well as storage of the data. Supporting data bases exist already and some will be discussed in the article. The understanding of the clinical relevance of many polymorphisms is another issue that has yet to be solved, particularly as in the context of personalized medicine polymorphisms have become increasingly important.