Rapid, ultra low coverage copy number profiling of cell-free DNA as a precision oncology screening strategy.

Current cell-free DNA (cfDNA) next generation sequencing (NGS) precision oncology workflows are typically limited to targeted and/or disease-specific applications. In advanced cancer, disease burden and cfDNA tumor content are often elevated, yielding unique precision oncology opportunities. We sought to demonstrate the utility of a pan-cancer, rapid, inexpensive, whole genome NGS of cfDNA approach (PRINCe) as a precision oncology screening strategy via ultra-low coverage (~0.01x) tumor content determination through genome-wide copy number alteration (CNA) profiling. We applied PRINCe to a retrospective cohort of 124 cfDNA samples from 100 patients with advanced cancers, including 76 men with metastatic castration-resistant prostate cancer (mCRPC), enabling cfDNA tumor content approximation and actionable focal CNA detection, while facilitating concordance analyses between cfDNA and tissue-based NGS profiles and assessment of cfDNA alteration associations with mCRPC treatment outcomes. Therapeutically relevant focal CNAs were present in 42 (34%) cfDNA samples, including 36 of 93 (39%) mCRPC patient samples harboring AR amplification. PRINCe identified pre-treatment cfDNA CNA profiles facilitating disease monitoring. Combining PRINCe with routine targeted NGS of cfDNA enabled mutation and CNA assessment with coverages tuned to cfDNA tumor content. In mCRPC, genome-wide PRINCe cfDNA and matched tissue CNA profiles showed high concordance (median Pearson correlation = 0.87), and PRINCe detectable AR amplifications predicted reduced time on therapy, independent of therapy type (Kaplan-Meier log-rank test, chi-square = 24.9, p < 0.0001). Our screening approach enables robust, broadly applicable cfDNA-based precision oncology for patients with advanced cancer through scalable identification of therapeutically relevant CNAs and pre-/post-treatment genomic profiles, enabling cfDNA- or tissue-based precision oncology workflow optimization

Combined genetic and high-throughput strategies for the molecular diagnosis of inherited retinal dystrophies

Most diagnostic laboratories are confronted with the increasing demand for molecular diagnosis from patients and families and the ever-increasing genetic heterogeneity of visual disorders. Concerning Retinal Dystrophies (RD), almost 200 causative genes have been reported to date, and most families carry private mutations. We aimed to approach RD genetic diagnosis using all the available genetic information to prioritize candidates for mutational screening, and then restrict the number of cases to be analyzed by massive sequencing. We constructed and optimized a comprehensive cosegregation RD-chip based on SNP genotyping and haplotype analysis. The RD-chip allows to genotype 768 selected SNPs (closely linked to 100 RD causative genes) in a single cost-, time-effective step. Full diagnosis was attained in 17/36 Spanish pedigrees, yielding 12 new and 12 previously reported mutations in 9 RD genes. The most frequently mutated genes were USH2A and CRB1. Notably, RD3-up to now only associated to Leber Congenital Amaurosis- was identified as causative of Retinitis Pigmentosa. The main assets of the RD-chip are: i) the robustness of the genetic information that underscores the most probable candidates, ii) the invaluable clues in cases of shared haplotypes, which are indicative of a common founder effect, and iii) the detection of extended haplotypes over closely mapping genes, which substantiates cosegregation, although the assumptions in which the genetic analysis is based could exceptionally lead astray. The combination of the genetic approach with whole exome sequencing (WES) greatly increases the diagnosis efficiency, and revealed novel mutations in USH2A and GUCY2D. Overall, the RD-chip diagnosis efficiency ranges from 16% in dominant, to 80% in consanguineous recessive pedigrees, with an average of 47%, well within the upper range of massive sequencing approaches, highlighting the validity of this time- and cost-effective approach whilst high-throughput methodologies become amenable for routine diagnosis in medium sized labs

Gene Discovery in Mendelian and Complex Diseases

Through the Finding of Rare Disease Genes in Canada (FORGE Canada) initiative, individuals affected with rare Mendelian diseases were clinically ascertained with a goal of identifying the genetic origin of their disease. Herein, I describe the methods for identifying the genetic basis of four Mendelian diseases. The application of next generation sequencing led to the discovery of non-synonymous variation in the DNA of individuals affected by rare diseases. The effects of the candidate variants were assessed using a series of functional experiments to complement the human genetics data. The variants observed in patients’ cells are extremely rare, were consistently predicted to be pathogenic by multiple in silico predictive programs, segregated with disease status in the family, and affected the biological properties of their respective gene products, as measured by functional assays. Having successfully identified genetic variants underlying the Mendelian diseases, we sought to use the same approach to extract the genetic variation that may predispose individuals to complex diseases, primarily neurodegenerative disorders. We designed a neurodegeneration specific gene panel that utilizes next generation sequencing chemistry. We sequenced patients diagnosed with one of five neurodegenerative diseases: 1) Alzheimer’s disease; 2) amyotrophic lateral sclerosis (ALS); 3) frontotemporal dementia (FTD); 4) Parkinson’s disease; or 5) vascular cognitive impairment, as part of the Ontario Neurodegenerative Disease Research Initiative (ONDRI). We were successful in detecting rare variants in a large fraction of cases that may be related to the neurodegenerative phenotypes. We also independently ascertained three large, unique families affected with familial ALS and FTD across multiple generations. The three families are diagnosed with ALS and/or FTD and in which the same hexanucleotide repeat expansion in the C9orf72 gene has been observed in all three pedigrees, but their phenotypes vary significantly. We sequenced affected individuals and observed several, distinct variants in these families that may explain the additional neurodegenerative phenotypes observed. In summary, the application of next generation sequencing has successfully identified novel genetic loci in both Mendelian and complex diseases

Systems Analysis Implicates WAVE2 Complex in the Pathogenesis of Developmental Left-Sided Obstructive Heart Defects.

Genetic variants are the primary driver of congenital heart disease (CHD) pathogenesis. However, our ability to identify causative variants is limited. To identify causal CHD genes that are associated with specific molecular functions, the study used prior knowledge to filter de novo variants from 2,881 probands with sporadic severe CHD. This approach enabled the authors to identify an association between left ventricular outflow tract obstruction lesions and genes associated with the WAVE2 complex and regulation of small GTPase-mediated signal transduction. Using CRISPR zebrafish knockdowns, the study confirmed that WAVE2 complex proteins brk1, nckap1, and wasf2 and the regulators of small GTPase signaling cul3a and racgap1 are critical to cardiac development

Deep-coverage whole genome sequences and blood lipids among 16,324 individuals.

Large-scale deep-coverage whole-genome sequencing (WGS) is now feasible and offers potential advantages for locus discovery. We perform WGS in 16,324 participants from four ancestries at mean depth >29X and analyze genotypes with four quantitative traits-plasma total cholesterol, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol, and triglycerides. Common variant association yields known loci except for few variants previously poorly imputed. Rare coding variant association yields known Mendelian dyslipidemia genes but rare non-coding variant association detects no signals. A high 2M-SNP LDL-C polygenic score (top 5th percentile) confers similar effect size to a monogenic mutation (~30 mg/dl higher for each); however, among those with severe hypercholesterolemia, 23% have a high polygenic score and only 2% carry a monogenic mutation. At these sample sizes and for these phenotypes, the incremental value of WGS for discovery is limited but WGS permits simultaneous assessment of monogenic and polygenic models to severe hypercholesterolemia