Biology subjects

Shirts, B. H.

Publications and source records attributed to Shirts, B. H..

5 recordsLinked to original sources

bioRxiv2023

Assigning credit where it's due: An information content score to capture the clinical value of Multiplexed Assays of Variant Effect

BackgroundA variant can be pathogenic or benign with relation to a human disease. Current classification categories from benign to pathogenic reflect a probabilistic summary of current understanding. A primary metric of clinical utility for multiplexed assays of variant effect (MAVE) is the number of variants that can be reclassified from uncertain significance (VUS). However, we hypothesized that this measure of utility underrepresents the information gained from MAVEs and that an information theory approach which includes data that does not reclassify variants will better reflect true information gain. We used this information theory approach to evaluate the information gain, in bits, for MAVEs of BRCA1, PTEN, and TP53. Here, one bit represents the amount of information required to completely classify a single variant starting from no information. ResultsBRCA1 MAVEs produced a total of 831.2 bits of information, 6.58% of the total missense information in BRCA1 and a 22-fold increase over the information that only contributed to VUS reclassification. PTEN MAVEs produced 2059.6 bits of information which represents 32.8% of the total missense information in PTEN and an 85-fold increase over the information that contributed to VUS reclassification. TP53 MAVEs produced 277.8 bits of information which represents 6.22% of the total missense information in TP53 and a 3.5-fold increase over the information that contributed to VUS reclassification. ConclusionsAn information content approach will more accurately portray information gained through MAVE mapping efforts than counting the number of variants reclassified. This information content approach may also help define the impact of modifying information definitions used to classify many variants, such as guideline rule changes.

genetics↗

bioRxiv2021

Quantifying the impact of data sharing on variant classification

ObjectiveMany genetic variants are classified, but many more are designated as variants of uncertain significance (VUS). Patient data may provide sufficient evidence to classify VUS. Understanding how long it would take to accumulate sufficient patient data to classify VUS can inform many important decisions such as data sharing, disease management, and functional assay development. Materials and MethodsOur software models accumulation of clinical data and their impact on variant interpretation to illustrate the time and probability for variants to be classified when clinical laboratories share evidence, when they silo evidence, and when they share only variant interpretations. ResultsOur models show that the probability of classifying a rare pathogenic variant with an allele frequency of 1/100,000 (1e-05) from less than 25% with no data sharing to nearly 80% after one year when labs share data, with nearly 100% classification after 5 years. Conversely, our models found that extremely rare (1/1,000,000 or 1e-06) variants have a low probability of classification using only clinical data. DiscussionThese results quantify the utility of data sharing and demonstrate the importance of alternative lines of evidence for the interpretation of rare variants. Understanding variant classification circumstances and timelines provides valuable insight for data owners, patients, and service providers. While our modeling parameters are based on assumptions of the rate of accumulation of clinical observations, users may experiment with the impact of these rates by downloading the software and rerunning the simulations with updated parameters. ConclusionThe modeling software is available at https://github.com/BRCAChallenge/classification-timelines.

genetics↗

bioRxiv2020

Multiplexing Mutation Rate Assessment: Determining Pathogenicity of Msh2 Variants in S. cerevisiae

Despite the fundamental importance of mutation rate as a driving force in evolution and disease risk, common methods to assay mutation rate are time consuming and tedious. Established methods such as fluctuation tests and mutation accumulation experiments are low-throughput and often require significant optimization to ensure accuracy. We established a new method to determine the mutation rate of many strains simultaneously by tracking mutation events in a chemostat continuous culture device and applying deep sequencing to link mutations to alleles of a DNA-repair gene. We applied this method to assay the mutation rate of hundreds of Saccharomyces cerevisiae strains carrying mutations in the gene encoding Msh2, a DNA repair enzyme in the mismatch repair pathway (MMR). Loss-of-function (LOF) mutations in MSH2 are associated with hereditary non-polyposis colorectal cancer (HNPCC), an inherited disorder that increases risk for many different cancers. However, the vast majority of MSH2 variants found in human populations have insufficient evidence to be classified as either pathogenic or benign. We first benchmarked our method against Luria-Delbruck fluctuation tests using a collection of published MSH2 variants. Our pooled screen successfully identified previously-characterized non-functional alleles as high mutators. We then created an additional 185 human variants in the yeast ortholog, including both characterized and uncharacterized alleles curated from ClinVar and other clinical testing data. In a set of alleles of known pathogenicity, our assay recapitulated ClinVars classification; we then estimated pathogenicity for 157 variants classified as uncertain or conflicting reports of significance. This method is capable of studying the mutation rate of many microbial species and can be applied to problems ranging from the generation of high-fidelity polymerases to measuring the rate of antibiotic resistance emergence.

genetics↗

bioRxiv2019

Markers of BRCAness in breast cancer

BackgroundMutations in BRCA1 and BRCA2 cause deficiencies in homologous recombination repair (HR), resulting in repair of DNA double-strand breaks by the alternative non-homologous end-joining pathway, which is more error prone. HR deficiency of breast tumors is important because it is associated with better responses to platinum salt therapies and PARP inhibitors. Among other consequences of HR deficiency are characteristic somatic-mutation signatures and gene-expression patterns. The term "BRCAness" describes tumors that harbor an HR defect but have no detectable germline mutation in BRCA1 or BRCA2. A better understanding of the genes and molecular events associated with BRCAness could provide mechanistic insights and guide development of targeted treatments. MethodsUsing data from The Cancer Genome Atlas (TCGA) for 1101 breast-cancer patients, we identified individuals with a germline mutation, somatic mutation, homozygous deletion, and/or hypermethylation event in BRCA1, BRCA2, and 59 other cancer-predisposition genes. Based on the assumption that BRCAness events would have similar downstream effects on tumor biology as BRCA1/BRCA2 germline mutations, we quantified these effects based on somatic-mutation signatures and gene-expression profiles. We reduced the dimensionality of the somatic-mutation signatures and expression data and used a statistical resampling approach to quantify similarities between patients who had a BRCA1/BRCA2 germline mutation, another type of aberration in BRCA1 or BRCA2, or any type of aberration in one of the other genes. ResultsSomatic-mutation signatures of tumors having a somatic mutation, homozygous deletion, or hypermethylation event in BRCA1/BRCA2 (n = 80) were generally similar to each other and to tumors from BRCA1/BRCA2 germline carriers (n = 44). Additionally, somatic-mutation signatures of tumors with germline or somatic events in ATR (n = 16) and BARD1 (n = 8) showed high similarity to tumors from BRCA1/BRCA2 carriers. Other genes also showed high similarity but only for a small number of events or for a single event type. Tumors with germline mutations or hypermethylation of BRCA1 had relatively similar gene-expression profiles and overlapped considerably with the Basal-like subtype; but the transcriptional effects of the other events lacked consistency. ConclusionsOur findings confirm previously known relationships between molecular signatures and germline or somatic events in BRCA1/BRCA2 and suggest additional genes that may be considered for inclusion in the definition of BRCAness.

cancer biology↗

bioRxiv2017

An interlaboratory study of complex variant detection

Next-generation sequencing (NGS) is widely used and cost-effective. Depending on the specific methods, NGS can have limitations detecting certain technically challenging variant types even though they are both prevalent in patients and medically important. These types are underrepresented in validation studies, hindering the uniform assessment of test methodologies by laboratory directors and clinicians. Specimens containing such variants can be difficult to obtain; thus, we evaluated a novel solution to this problem in which a diverse set of technically challenging variants was synthesized and introduced into a known genomic background. This specimen was sequenced by 7 laboratories using 10 different NGS workflows. The specimen was compatible with all 10 workflows and presented biochemical and bioinformatic challenges similar to those of patient specimens. Only 10 of 22 challenging variants were correctly identified by all 10 workflows, and only 3 workflows detected all 22. Many, but not all, of the sensitivity limitations were bioinformatic in nature. We conclude that Synthetic controls can provide an efficient and informative mechanism to augment studies with technically challenging variants that are difficult to obtain otherwise. Data from such specimens can facilitate inter-laboratory methodologic comparisons and can help establish standards that improve communication between clinicians and laboratories.

genetics↗