High-throughput Sequencing in the Diagnosis of Inherited Bleeding and Clotting Disorders: Technical and Interpretive Considerations Necessary for Accurate Reporting and Clinical Application.

Importance of reliable variant calling and clear phenotyping when reporting on gene panel testing in renal disease

Rapid advances in high-throughput DNA sequencing technologies have enabled the conduct of whole genome sequencing (WGS) studies, and several bioinformatics pipelines have become available. The aim of this study was the comparison of 6 WGS data pre-processing pipelines, involving two mapping and alignment approaches (GATK utilizing BWA-MEM2 2.2.1, and DRAGEN 3.8.4) and three variant calling pipelines (GATK 4.2.4.1, DRAGEN 3.8.4 and DeepVariant 1.1.0). We sequenced one genome in a bottle (GIAB) sample 70 times in different runs, and one GIAB trio in triplicate. The truth set of the GIABs was used for comparison, and performance was assessed by computation time, F1 score, precision, and recall. In the mapping and alignment step, the DRAGEN pipeline was faster than the GATK with BWA-MEM2 pipeline. DRAGEN showed systematically higher F1 score, precision, and recall values than GATK for single nucleotide variations (SNVs) and Indels in simple-to-map, complex-to-map, coding and non-coding regions. In the variant calling step, DRAGEN was fastest. In terms of accuracy, DRAGEN and DeepVariant performed similarly and both superior to GATK, with slight advantages for DRAGEN for Indels and for DeepVariant for SNVs. The DRAGEN pipeline showed the lowest Mendelian inheritance error fraction for the GIAB trios. Mapping and alignment played a key role in variant calling of WGS, with the DRAGEN outperforming GATK.

Neonatal genetic disease is currently screened mainly based on metabolite biochemical technology. The false positive rate of biochemical screening technology is relatively high, and there are certain false negatives, and only few types of diseases can be screened. The genetic techniques have been gradually used for neonatal genetic disease screening in recent years. Gene detection technology includes quantitative PCR (qPCR) and high-throughput sequencing. High-throughput sequencing includes gene panel sequencing, whole-exome sequencing and whole-genome sequencing. At present, qPCR and gene panel sequencing are the main technologies to be used for newborn genetic disease screening. Genetic screening diseases range from single disease such as hearing loss, spinal muscular atrophy and severe combined immunodeficiency to multiple diseases. Besides standards and guidelines for the interpretation of sequence variants proposed by the American College of Medical Genetics and Genomics and the Association for Molecular Pathology in 2015, the interpretation of genetic screening results should also consider biochemical results and other results. The development of newborn genetic screening needs to follow ethical principles, including the ethics of newborn genetic screening as a public health project, the privacy ethics of newborns and their family members, and the ethics of bioinformatics. The development of newborn genetic screening will enable more patients with inherited diseases to receive early diagnosis and treatment and improve their prognosis, which is a milestone in the field of neonatal screening.

Whole genome sequencing provides the highest resolution for characterizing pathogen evolution, epidemiology, and diagnostics. Genome assemblies contain information on the identity and potential phenotypes of a pathogen. Likewise, variant calling can inform on transmission patterns and evolutionary relationships. Recent improvements in Oxford Nanopore long-read sequencing have made its use attractive for genomic epidemiology. However, the accuracy and optimal strategy for analysis of Nanopore reads remains to be determined. We compared the use of Illumina short reads and Oxford Nanopore long reads for genome assembly and variant calling of phytopathogenic bacteria. We generated short- and long-read datasets for diverse phytopathogenic Agrobacterium strains. We then analyzed these data using multiple pipelines designed for either short or long reads and compared the results. We found that assemblies made from long reads were more complete than those made from short-read data and contained few sequence errors. Variant calling pipelines differed in their ability to accurately call variants and infer genotypes from long reads. Results suggest that computationally fragmenting long reads can improve the accuracy of variant calling in population-level studies. Using fragmented long reads, pipelines designed for short reads were more accurate at recovering genotypes than pipelines designed for long reads. Further, short- and long-read datasets can be analyzed together with the same pipelines. These findings show that Oxford Nanopore sequencing is accurate and can be sufficient for microbial pathogen genomics and epidemiology. Ultimately, this enhances the ability of researchers and clinicians to understand and mitigate the spread of pathogens.

Genome assembly and variant calling are important steps in microbial population studies and epidemiology. Most variant calling and genotyping pipelines are designed for Illumina short sequencing reads. Oxford Nanopore Technology long-read sequencing results in more complete genome assemblies but has historically been of lower quality. Here, we show that Nanopore long reads are now of sufficient quality for bacterial whole-genome assembly and epidemiology. We benchmarked the accuracy of multiple variant calling pipelines with short and long reads. Using an optimized variant calling approach, variant calls and genotypes inferred from long reads are as accurate as those inferred from short reads. Importantly, we found that gold-standard variant calling pipelines designed for short reads are also accurate with long reads when long reads are first fragmented into shorter sequences. This finding allows researchers to incorporate the advantages of Nanopore sequencing for genome assembly while maintaining high accuracy in epidemiology and population analyses.

Tumor mutational burden (TMB) measured via next-generation sequencing (NGS)-based gene panel is a promising biomarker for response to immune checkpoint inhibitors (ICIs) in solid tumors. However, little is known about the preanalytical factors that can affect the TMB score. Data of 199 patients with solid tumors who underwent multiplex NGS gene panel (OncoPrime), which was commercially provided by a Clinical Laboratory Improvement Amendments-licensed laboratory and covered 0.78 megabase (Mb) of capture size relevant to the TMB calculation, were reviewed. Associations between the TMB score and preanalytical factors, including sample DNA quality, sample type, sampling site, and storage period, were analyzed. Clinical outcomes of patients with a high TMB score (≥10 mutations per megabase) who received anti-programmed cell death protein 1 antibodies (n = 22) were also analyzed. Low DNA library concentration (<5 nM), formalin-fixed paraffin-embedded tissue (FFPE), and the prolonged sample storage period (range, 0.9-58.1 months) correlated with a higher TMB score. After excluding low DNA library samples from the analysis, FFPE samples, but not the sample storage period, exhibited a marked correlation with a high TMB score. Of 22 patients with a high TMB score, we observed the partial response in 2 patients (9.1%). Our results indicate that the TMB score estimated via NGS-based gene panel could be affected by the DNA library concentration and sample type. These factors could potentially increase the false-positive and/or artifactual variant calls. As each gene panel has its own pipeline for variant calling, it is unknown whether these factors have a significant effect in other platforms. A high tumor mutational burden score, as estimated via next-generation sequencing-based gene panel testing, should be carefully interpreted as it could be affected by the DNA library concentration and sample type.

Points to consider: is there evidence to support BRCA1/2 and other inherited breast cancer genetic testing for all breast cancer patients? A statement of the American College of Medical Genetics and Genomics (ACMG)

Genetic counseling is “the process of helping people understand and adapt to the medical, psychological, and familial implications of genetic contributions to disease.” Traditionally, this process includes collecting and interpreting the family and medical history, risk assessment, a comprehensive educational process for potential genetic testing, informed consent, and psychosocial assessment and support (National Society of Genetic Counselors' Definition Task Force et al. 2006). While genetic counseling falls within the scope of many health care professionals, clinical geneticists (physicians) and masters level genetic counselors have been working in the United States for more than 40 years, providing genetic counseling primarily for single-gene conditions. Debate about what “genomic counseling” will include and who will practice it has been fueled by the transition from single-gene focused genetic counseling and testing to a full genomic medicine approach. The routine incorporation of genomic medicine will likely induce differences in the scope, approach and process of genetic counseling (Table ​(Table1).1). In this commentary, I will discuss the several areas where practice will likely change as we move toward “genomic” counseling, with a focus on the unique skills and roles that genetic counselors and clinical geneticists provide. Table 1 Changes that will impact the transition to “genomic counseling.”

U.S. supreme court decision paves way for better genetic testing

The impact of next-generation sequencing technology on preimplantation genetic diagnosis and screening

The American College of Medical Genetics and Genomics (ACMG) previously developed guidance for the interpretation of sequence variants.1 In the past decade, sequencing technology has evolved rapidly with the advent of high-throughput next generation sequencing. By adopting and leveraging next generation sequencing, clinical laboratories are now performing an ever increasing catalogue of genetic testing spanning genotyping, single genes, gene panels, exomes, genomes, transcriptomes and epigenetic assays for genetic disorders. By virtue of increased complexity, this paradigm shift in genetic testing has been accompanied by new challenges in sequence interpretation. In this context, the ACMG convened a workgroup in 2013 comprised of representatives from the ACMG, the Association for Molecular Pathology (AMP) and the College of American Pathologists (CAP) to revisit and revise the standards and guidelines for the interpretation of sequence variants. The group consisted of clinical laboratory directors and clinicians. This report represents expert opinion of the workgroup with input from ACMG, AMP and CAP stakeholders. These recommendations primarily apply to the breadth of genetic tests used in clinical laboratories including genotyping, single genes, panels, exomes and genomes. This report recommends the use of specific standard terminology: ‘pathogenic’, ‘likely pathogenic’, ‘uncertain significance’, ‘likely benign’, and ‘benign’ to describe variants identified in Mendelian disorders. Moreover, this recommendation describes a process for classification of variants into these five categories based on criteria using typical types of variant evidence (e.g. population data, computational data, functional data, segregation data, etc.). Because of the increased complexity of analysis and interpretation of clinical genetic testing described in this report, the ACMG strongly recommends that clinical molecular genetic testing should be performed in a CLIA-approved laboratory with results interpreted by a board-certified clinical molecular geneticist or molecular genetic pathologist or equivalent.

Advances in sequencing technology and the movement of genetic testing into all areas of medicine will increase opportunities for molecular confirmation of a clinical diagnosis. For health-care professionals without formal genetics training, there is a need to know what patients understand about genetics and genetic testing and their information needs and preferences for the disclosure of genetic testing results. These topics were explored during face-to-face interviews with 50 adults with inherited retinal disease, selected in order to provide a diversity of opinions. Participants had variable understanding of genetics and genetic testing, including basic concepts such as inheritance patterns and the risk to dependents, and many did not understand the term 'genetic counselling'. Most were keen for extra information on the risk to others, the process for genetic testing and how to share the information with other family members. Participants were divided as to whether genetic testing should be offered at the time of the initial diagnosis or later. Many would prefer the results to be given by face-to-face consultation, supplemented by further information in a format accessible to those with visual impairment. Health-care professionals and either leaflets or websites of trusted agencies were the preferred sources of information. Permission should be sought for disclosure of genetic information to other family members. The information needs of many patients with inherited retinal disease appear to be unmet. An understanding of their information needs and preferences is required to help health-care professionals provide optimal services that meet patient expectations.

Using Molecular Diagnostics for Inherited Retinal Dystrophies: The 6 "I"s That Are Necessary to Diagnose 2 Eyes Genetically.

The use of fetal exome sequencing in prenatal diagnosis: a points to consider document of the American College of Medical Genetics and Genomics (ACMG)

In most industrialized countries breast cancer will affect one out of eight women during her lifetime. In the USA, after continuously increasing for more than two decades, incidence rates are slowly decreasing since 2001. Since 1990, death rates from breast cancer have steadily decreased in women, which is attributed to both earlier detection and improved treatment. Still, it is second only to lung cancer as a cause of cancer death in women. In this work we set out to improve early detection of breast cancer via quantitative analysis of magnetic resonance images (MRI). Screening and diagnosis of breast cancer are generally performed using X-ray mammography, possibly in conjunction with ultrasonography. However, MRI is becoming an important modality for screening of women at high-risk due to for instance hereditary gene mutations, as a problem-solving tool in case of indecisive mammographic and / or ultrasonic imaging, and for anti-cancer therapy assessment. In this work, we focused on MR imaging of the breast. More specifically, the dynamic contrast-enhanced (DCE) part of the protocol was highlighted, as well as radiological assessment of DCE-MRI data. The T_1-weighted (T_1: longitudinal relaxation time, a tissue property) signal-versus-time curve that can be extracted from the DCE-MRI series that is acquired at the time of and after injection of a T_1-shortening (shorter T_1 results in higher signal) contrast agent, is usually visually assessed by the radiologist. For example, a fast initial rise to the peak (1-2 minutes post injection) followed by loss of signal within a time frame of about 5-6 minutes is a sign for malignancy, whereas a curve showing persistent (slow) uptake within the same time frame is a sign for benignity. This difference in contrast agent uptake pattern is related to physiological changes in tumorous tissue that for instance result in a stronger uptake of the contrast agent. However, this descriptive way of curve type classification is based on clinical statistics, not on knowledge about tumor physiology. We investigated pharmacokinetic modeling as a quantitative image analysis tool. Pharmacokinetics describes what happens to a substance (e.g. drug or contrast agent) after it has been administered to a living organism. This includes the mechanisms of absorption and distribution. The terms in which these mechanisms are described are physiological and can therefore provide parameters describing the functioning of the tissue. This physiological aspect makes it an attractive approach to investigate (aberrant) tissue functioning. In addition, this type of analysis excludes confounding factors due to inter- and intra-patient differences in the systemic blood circulation, as well as differences in the injection protocol. In this work, we discussed the physiological basis and details of different types of pharmacokinetic models, with the focus on compartmental models. Practical implications such as obtaining an arterial input function and model parameter estimation were taken into account as well. A simulation study of the data-imposed limitations – in terms of temporal resolution and noise properties – on the complexity of pharmacokinetic models led to the insight that only one of the tested models, the basic Tofts model, is applicable to DCE-MRI data of the breast. For the basic Tofts model we further investigated the aspect of temporal resolution, because a typical diagnostic DCE-MRI scan of the breast is acquired at a rate of about 1 image volume every minute; whereas pharmacokinetic modeling usually requires a sampling time of less than 10 s. For this experiment we developed a new downsampling method using high-temporal-resolution raw k-space data to simulate what uptake curves would have looked like if they were acquired at lower temporal resolutions. We made use of preclinical animal data. With this data we demonstrated that the limit of 10 s can be stretched to about 1 min if the arterial input function (AIF, the input to the pharmacokinetic model) is inversely derived from a healthy reference tissue, instead of measured in an artery or taken from the literature. An important precondition for the application of pharmacokinetic modeling is knowledge of the relationship between the acquired DCE-MRI signal and the actual concentration of the contrast agent in the tissue. This relationship is not trivial because with MRI we measure the indirect effect of the contrast agent on water protons. To establish this relationship via calculation of T_1 (t), we investigated both a theoretical and an empirical approach, making use of an in-house (University of Chicago) developed reference object that is scanned concurrently with the patient. The use of the calibration object can shorten the scan duration (an empirical approach requires less additional scans than an approach using a model of the acquisition technique), and can demonstrate if theoretical approaches are valid. Moreover we produced concentration images and estimated tissue proton density, also making use of the calibration object. Finally, via pharmacokinetic modeling and other MRI-derived measures we partly revealed the actions of a novel therapeutic in a preclinical study. In particular, the anti-tumor activity of a single dose of liposomal prednisolone phosphate was investigated, which is an anti-inflammatory drug that has demonstrated tumor growth inhibition. The work presented in this thesis contributes to a meaningful clinical application and interpretation of quantitative DCE-MRI of the breast.