Benoît Leclair

Enhanced Kinship Analysis and STR-based DNA Typing for Human Identification in Mass Fatality Incidents: The Swissair Flight 111 Disaster

A bioinformatic tool was developed to assist with the victim identification initiative that followed the Swissair Flight 111 disaster. Making use of short tandem repeat (STR) DNA typing data generated with AmpFlSTR Profiler Plus (PP) and AmpFlSTR COfiler(CO) kits, the software systematically compared each available STR genotype with every other genotype. The matching algorithm was based on the search for: (i) direct matches to genotypes derived from personal effects; and (ii) potential kinship associations between victims and next-of-kin, as measured by allele sharing at individual loci. The software greatly assisted parentage analysis by enabling kinship evaluation in situations where complete parentage trios were unavailable and, in some situations, with distantly related relatives. Exclusion of fortuitous kinship associations (FKA) was made possible through the recovery at the disaster site of at least one remains for every sought-after victim, and was incorporated into the kinship software. The data from the 13 combined STR loci produced 6 and 23 times fewer FKAs when compared with PP alone and AmpFlSTR Profiler (PR) alone, respectively. Identification leads or confirmations of identification were obtained for 218 victims for which DNA reference samples (personal effects and kin) had been submitted. Confirmation of an inferred kinship association was sought through frequency and likelihood calculations, as well as corroborative data from other identification modalities. The use of a simple, yet powerful, automated genotype comparison approach and the use of megaplexes with high power of discrimination (PD) values extended considerably the identification capabilities in the case of the Swissair disaster. The DNA typing identification modality proved to be a valuable component of the large arsenal of identification tools deployed in the aftermath of this disaster.

Prevalence of five previously reported and recurrent BRCA1 genetic rearrangement mutations in 20,000 patients from hereditary breast/ovarian cancer families

Many rearrangement mutations in the BRCA1 gene have been identified. It is becoming clear that some of these mutations are prevalent, and therefore their detection is necessary in order for clinical genetic tests to have high sensitivity. Published information on particular rearrangements is frequently limited to a single patient, small groups of patients, or patients of a particular ethnicity. The objectives of this work included characterizing the prevalence of five specific rearrangement mutations in a large North American patient population. A mutation‐specific multiplex PCR assay was used for determining the prevalence of five BRCA1 rearrangement mutations that previously had been reported to occur in unrelated patients. The mutation status of these rearrangements, which came from 20,712 patients at high risk for hereditary breast and/or ovarian cancers who had submitted specimens for clinical genetic testing, is presented. The results, obtained from 2,634 mutation carriers, showed a 6‐kb duplication of exon 13, identified in 53 patients (2.01%); a 26‐kb deletion encompassing exons 14–20, detected in seven patients (0.27%); a 510‐bp deletion of exon 22, detected in 5 patients (0.19%); and a 3.4‐kb deletion of exon 13, detected in one patient (0.04%). A previously reported 7.1‐kb deletion of exons 8–9 was not found. The high frequency of the exon 13 duplication makes it the fourth most prevalent mutation in these patients. These results provide an accurate picture of the prevalence of these mutations in hereditary breast/ovarian cancer patients undergoing genetic testing in North America.

Development and analytical validation of a 25-gene next generation sequencing panel that includes the BRCA1 and BRCA2 genes to assess hereditary cancer risk

BackgroundGermline DNA mutations that increase the susceptibility of a patient to certain cancers have been identified in various genes, and patients can be screened for mutations in these genes to assess their level of risk for developing cancer. Traditional methods using Sanger sequencing focus on small groups of genes and therefore are unable to screen for numerous genes from several patients simultaneously. The goal of the present study was to validate a 25-gene panel to assess genetic risk for cancer in 8 different tissues using next generation sequencing (NGS) techniques.MethodsTwenty-five genes associated with hereditary cancer syndromes were selected for development of a panel to screen for risk of these cancers using NGS. In an initial technical assessment, NGS results for BRCA1 and BRCA2 were compared with Sanger sequencing in 1864 anonymized DNA samples from patients who had undergone previous clinical testing. Next, the entire gene panel was validated using parallel NGS and Sanger sequencing in 100 anonymized DNA samples. Large rearrangement analysis was validated using NGS, microarray comparative genomic hybridization (CGH), and multiplex ligation-dependent probe amplification analyses (MLPA).ResultsNGS identified 15,877 sequence variants, while Sanger sequencing identified 15,878 in the BRCA1 and BRCA2 comparison study of the same regions. Based on these results, the NGS process was refined prior to the validation of the full gene panel. In the validation study, NGS and Sanger sequencing were 100% concordant for the 3,923 collective variants across all genes for an analytical sensitivity of the NGS assay of >99.92% (lower limit of 95% confidence interval). NGS, microarray CGH and MLPA correctly identified all expected positive and negative large rearrangement results for the 25-gene panel.ConclusionThis study provides a thorough validation of the 25-gene NGS panel and indicates that this analysis tool can be used to collect clinically significant information related to risk of developing hereditary cancers.

Application of Embryonic Lethal or Other Obvious Phenotypes to Characterize the Clinical Significance of Genetic Variants Found in Trans with Known Deleterious Mutations

This work describes an approach to characterize the clinical significance of genetic variants detected during the genetic testing of BRCA1 in patients from hereditary breast/ovarian cancer families. Results from transgenic mice and extensive clinical testing support the hypothesis that biallelic BRCA1 mutations result in embryonic lethality. Therefore, it is reasonable to conclude that variants of uncertain clinical significance found to reside in trans with known deleterious mutations impart reduced risk for cancer. This approach was applied to a large data set of 55,630 patients who underwent clinical BRCA1 screening by whole gene direct DNA sequencing. Fourteen common single nucleotide polymorphisms (SNPs) were used to assign 10 previously defined common, recurrent, or canonical haplotypes in 99% of these cases. From a total of 1,477 genetic variants detected in these patients, excluding haplotype-tagging SNPs, 877 (59%) could be unambiguously assigned to one or more haplotypes. In 41 instances, variants previously classified as being of uncertain clinical significance, mostly missense variants, were excluded as fully penetrant mutations due to their coincidence in trans with known deleterious mutations. From a total of 1,150 patients that harbored these 41 variants, 956 carried one as the sole variant of uncertain clinical significance reported. This approach could have widespread application to other disease genes where compound heterozygous mutations are incompatible with life or result in obvious phenotypes. This largely computational technique is advantageous because it relies upon existing clinical data and is likely to prove informative for prevalent genetic variants in large data sets.

Bioinformatics and human identification in mass fatality incidents : The world trade center disaster

Abstract:  Victim identification initiatives undertaken in the wake of Mass Fatality Incidents (MFIs) where high‐body fragmentation has been sustained are often dependent on DNA typing technologies to complete their mandate. The success of these endeavors is linked to the choice of DNA typing methods and the bioinformatic tools required to make the necessary associations. Several bioinformatic tools were developed to assist with the identification of the victims of the World Trade Center attacks, one of the most complex incidents to date. This report describes one of these tools, the Mass Disaster Kinship Analysis Program (MDKAP), a pair‐wise comparison software designed to handle large numbers of complete or partial Short Tandem Repeats (STR) genotypes, and infer identity of, or biological relationships between tested samples. The software performs all functions required to take full advantage of the information content of processed genotypic data sets from large‐scale MFIs, including the collapse of victims data sets, remains re‐association, virtual genotype generation through gap‐filling, parentage trio searching, and a consistency check of reported/inferred biological relationships within families. Although very few WTC victims were genetically related, the software can detect parentage trios from within a victim’s genotype data set through a nontriangulated approach that screens all possible parentage trios. All software‐inferred relationships from WTC data were confirmed by independent statistical analysis. With a 13 STR loci complement, a fortuitous parentage trio (FPT) involving nonrelated individuals was detected. Additional STR loci would be required to reduce the risk of an FPT going undetected in large‐scale MFIs involving related individuals among the victims. Kinship analysis has proven successful in this incident but its continued success in larger scale MFIs is contingent on the use of a sufficient number of STR loci to reduce the risk of undetected FPTs, the use of mtDNA and Y‐STRs to confirm parentage and of bioinformatics that can support large‐scale comparative genotyping schemes capable of detecting parentage trios from within a group of related victims.

Application of automation and information systems to forensic genetic specimen processing

During the last 10 years, the introduction of PCR-based DNA typing technologies in forensic applications has been highly successful. This technology has become pervasive throughout forensic laboratories and it continues to grow in prevalence. For many criminal cases, it provides the most probative evidence. Criminal genotype data banking and victim identification initiatives that follow mass-fatality incidents have benefited the most from the introduction of automation for sample processing and data analysis. Attributes of offender specimens including large numbers, high quality and identical collection and processing are ideal for the application of laboratory automation. The magnitude of kinship analysis required by mass-fatality incidents necessitates the application of computing solutions to automate the task. More recently, the development activities of many forensic laboratories are focused on leveraging experience from these two applications to casework sample processing. The trend toward increased prevalence of forensic genetic analysis will continue to drive additional innovations in high-throughput laboratory automation and information systems.

Hereditary cancer testing challenges: assembling the analytical pieces to solve the patient clinical puzzle

Expanded genetic test utilization to guide cancer management has driven the development of larger gene panels and greater diversity in the patient population pursuing testing, resulting in increased identification of atypical or technically challenging genetic findings. To ensure appropriate patient care, it is critical that genetic tests adequately identify and characterize these findings. We describe genetic testing challenges frequently encountered by our laboratory and the methodologies we employ to improve test accuracy for the identification and characterization of atypical genetic findings. While these findings may be individually rare, 15,745 (9%) individuals tested by our laboratory for hereditary cancer risk had an atypical genetic finding, highlighting the importance of employing highly accurate and comprehensive methods in clinical genetic testing.