Characterisation and validation of insertions and deletions in 173 patient exomes

Precision Molecular Diagnosis Defines Specific Therapy in Combined Immunodeficiency with Megaloblastic Anemia Secondary to MTHFD1 Deficiency

BACKGROUND

Methylenetetrahydrofolate dehydrogenase (MTHFD1) deficiency has recently been reported to cause a folate-responsive syndrome displaying a phenotype that includes megaloblastic anemia and severe combined immunodeficiency.

OBJECTIVE

To describe our investigative approach to the molecular diagnosis and evaluation of immune dysfunction in a family with MTHFD1 deficiency.

METHODS

The methods used were exome sequencing and analysis of variants in genes involved in the folate metabolic pathway in a family with 2 affected siblings. Routine laboratory and research data were analyzed to gain an in-depth understanding of innate, humoral, and cell-mediated immune function before and after folinic acid supplementation.

RESULTS

Interrogation of exome data for concordant variants between the siblings in the genes involved in folate metabolic pathway identified a heterozygous mutation in exon 3 of the MTHFD1 gene that was shared with their mother. In view of highly suggestive phenotype, we extended our bioinformatics interrogation for structural variants in the MTHFD1 gene by manual evaluation of the exome data for sequence depth coverage of all the exons. A deletion involving exon 13 that was shared with their father was identified. Routine laboratory data showed lymphopenia involving all subsets and poor response to vaccines. In vitro analysis of dendritic cell and lymphocyte function was comparable to that in healthy volunteers. Treatment with folinic acid led to immune reconstitution, enabling discontinuation of all prophylactic therapies.

CONCLUSIONS

Exome sequencing demonstrated MTHFD1 deficiency as a novel cause of a combined immunodeficiency. Folinic acid was established as precision therapy to reverse the clinical and laboratory phenotype of this primary immunodeficiency.

Whole-exome sequencing of over 4100 men of African ancestry and prostate cancer risk

Prostate cancer is the most common non-skin cancer in males, with a ∼1.5-2-fold higher incidence in African American men when compared with whites. Epidemiologic evidence supports a large heritable contribution to prostate cancer, with over 100 susceptibility loci identified to date that can explain ∼33% of the familial risk. To explore the contribution of both rare and common variation in coding regions to prostate cancer risk, we sequenced the exomes of 2165 prostate cancer cases and 2034 controls of African ancestry at a mean coverage of 10.1×. We identified 395 220 coding variants down to 0.05% frequency [57% non-synonymous (NS), 42% synonymous and 1% gain or loss of stop codon or splice site variant] in 16 751 genes with the strongest associations observed in SPARCL1 on 4q22.1 (rs13051, Ala49Asp, OR = 0.78, P = 1.8 × 10(-6)) and PTPRR on 12q15 (rs73341069, Val239Ile, OR = 1.62, P = 2.5 × 10(-5)). In gene-level testing, the two most significant genes were C1orf100 (P = 2.2 × 10(-4)) and GORAB (P = 2.3 × 10(-4)). We did not observe exome-wide significant associations (after correcting for multiple hypothesis testing) in single variant or gene-level testing in the overall case-control or case-case analyses of disease aggressiveness. In this first whole-exome sequencing study of prostate cancer, our findings do not provide strong support for the hypothesis that NS coding variants down to 0.5-1.0% frequency have large effects on prostate cancer risk in men of African ancestry. Higher-coverage sequencing efforts in larger samples will be needed to study rarer variants with smaller effect sizes associated with prostate cancer risk.

Clinical validation of KRAS, BRAF, and EGFR mutation detection using next-generation sequencing

OBJECTIVES

To validate next-generation sequencing (NGS) technology for clinical diagnosis and to determine appropriate read depth.

METHODS

We validated the KRAS, BRAF, and EGFR genes within the Ion AmpliSeq Cancer Hotspot Panel using the Ion Torrent Personal Genome Machine (Life Technologies, Carlsbad, CA).

RESULTS

We developed a statistical model to determine the read depth needed for a given percent tumor cellularity and number of functional genomes. Bottlenecking can result from too few input genomes. By using 16 formalin-fixed, paraffin-embedded (FFPE) cancer-free specimens and 118 cancer specimens with known mutation status, we validated the six traditional analytic performance characteristics recommended by the Next-Generation Sequencing: Standardization of Clinical Testing Working Group. Baseline noise is consistent with spontaneous and FFPE-induced C:G→T:A deamination mutations.

CONCLUSIONS

Redundant bioinformatic pipelines are essential, since a single analysis pipeline gave false-negative and false-positive results. NGS is sufficiently robust for the clinical detection of gene mutations, with attention to potential artifacts.

Identification and validation of loss of function variants in clinical contexts

The choice of an appropriate variant calling pipeline for exome sequencing data is becoming increasingly more important in translational medicine projects and clinical contexts. Within GOSgene, which facilitates genetic analysis as part of a joint effort of the University College London and the Great Ormond Street Hospital, we aimed to optimize a variant calling pipeline suitable for our clinical context. We implemented the GATK/Queue framework and evaluated the performance of its two callers: the classical UnifiedGenotyper and the new variant discovery tool HaplotypeCaller. We performed an experimental validation of the loss-of-function (LoF) variants called by the two methods using Sequenom technology. UnifiedGenotyper showed a total validation rate of 97.6% for LoF single-nucleotide polymorphisms (SNPs) and 92.0% for insertions or deletions (INDELs), whereas HaplotypeCaller was 91.7% for SNPs and 55.9% for INDELs. We confirm that GATK/Queue is a reliable pipeline in translational medicine and clinical context. We conclude that in our working environment, UnifiedGenotyper is the caller of choice, being an accurate method, with a high validation rate of error-prone calls like LoF variants. We finally highlight the importance of experimental validation, especially for INDELs, as part of a standard pipeline in clinical environments.

XLID-causing mutations and associated genes challenged in light of data from large-scale human exome sequencing

Because of the unbalanced sex ratio (1.3-1.4 to 1) observed in intellectual disability (ID) and the identification of large ID-affected families showing X-linked segregation, much attention has been focused on the genetics of X-linked ID (XLID). Mutations causing monogenic XLID have now been reported in over 100 genes, most of which are commonly included in XLID diagnostic gene panels. Nonetheless, the boundary between true mutations and rare non-disease-causing variants often remains elusive. The sequencing of a large number of control X chromosomes, required for avoiding false-positive results, was not systematically possible in the past. Such information is now available thanks to large-scale sequencing projects such as the National Heart, Lung, and Blood (NHLBI) Exome Sequencing Project, which provides variation information on 10,563 X chromosomes from the general population. We used this NHLBI cohort to systematically reassess the implication of 106 genes proposed to be involved in monogenic forms of XLID. We particularly question the implication in XLID of ten of them (AGTR2, MAGT1, ZNF674, SRPX2, ATP6AP2, ARHGEF6, NXF5, ZCCHC12, ZNF41, and ZNF81), in which truncating variants or previously published mutations are observed at a relatively high frequency within this cohort. We also highlight 15 other genes (CCDC22, CLIC2, CNKSR2, FRMPD4, HCFC1, IGBP1, KIAA2022, KLF8, MAOA, NAA10, NLGN3, RPL10, SHROOM4, ZDHHC15, and ZNF261) for which replication studies are warranted. We propose that similar reassessment of reported mutations (and genes) with the use of data from large-scale human exome sequencing would be relevant for a wide range of other genetic diseases.

Implications of genetic testing in noncompaction/hypertrabeculation

Noncompaction/hypertrabeculation is increasingly being recognized in children and adults, yet we understand little about the causes of disease. Genes associated with noncompaction/hypertrabeculation have been identified, but how can these assist in clinical management? Genomic technologies have also expanded tremendously, making testing more comprehensive, but they also present new questions given the tremendous diversity of phenotypes and variability of genomes. Here we present genetic evaluation strategies and assess clinical testing options for noncompaction/hypertrabeculation. We assess genes/gene panels offered by clinical laboratories and the potential for high-throughput sequencing to fuel further discovery. We discuss challenges in cardiovascular genetics, such as interpretation of genomic variants, prediction and disease penetrance.

Interpretation, stratification and evidence for sequence variants affecting mRNA splicing in complete human genome sequences

Information theory-based methods have been shown to be sensitive and specific for predicting and quantifying the effects of non-coding mutations in Mendelian diseases. We present the Shannon pipeline software for genome-scale mutation analysis and provide evidence that the software predicts variants affecting mRNA splicing. Individual information contents (in bits) of reference and variant splice sites are compared and significant differences are annotated and prioritized. The software has been implemented for CLC-Bio Genomics platform. Annotation indicates the context of novel mutations as well as common and rare SNPs with splicing effects. Potential natural and cryptic mRNA splicing variants are identified, and null mutations are distinguished from leaky mutations. Mutations and rare SNPs were predicted in genomes of three cancer cell lines (U2OS, U251 and A431), which were supported by expression analyses. After filtering, tractable numbers of potentially deleterious variants are predicted by the software, suitable for further laboratory investigation. In these cell lines, novel functional variants comprised 6–17 inactivating mutations, 1–5 leaky mutations and 6–13 cryptic splicing mutations. Predicted effects were validated by RNA-seq analysis of the three aforementioned cancer cell lines, and expression microarray analysis of SNPs in HapMap cell lines.