Analyzing and Reanalyzing the Genome: Findings from the MedSeq Project

Systematic reanalysis of genomic data by diagnostic laboratories: a scoping review of ethical, economic, legal and (psycho)social implications

With the introduction of Next Generation Sequencing (NGS) techniques increasing numbers of disease-associated variants are being identified. This ongoing progress might lead to diagnoses in formerly undiagnosed patients and novel insights in already solved cases. Therefore, many studies suggest introducing systematic reanalysis of NGS data in routine diagnostics. Introduction will, however, also have ethical, economic, legal and (psycho)social (ELSI) implications that Genetic Health Professionals (GHPs) from laboratories should consider before possible implementation of systematic reanalysis. To get a first impression we performed a scoping literature review. Our findings show that for the vast majority of included articles ELSI aspects were not mentioned as such. However, often these issues were raised implicitly. In total, we identified nine ELSI aspects, such as (perceived) professional responsibilities, implications for consent and cost-effectiveness. The identified ELSI aspects brought forward necessary trade-offs for GHPs to consciously take into account when considering responsible implementation of systematic reanalysis of NGS data in routine diagnostics, balancing the various strains on their laboratories and personnel while creating optimal results for new and former patients. Some important aspects are not well explored yet. For example, our study shows GHPs see the values of systematic reanalysis but also experience barriers, often mentioned as being practical or financial only, but in fact also being ethical or psychosocial. Engagement of these GHPs in further research on ELSI aspects is important for sustainable implementation.

Next Generation Sequencing of Red Blood Cell Antigens in Transfusion Medicine: Systematic Review and Meta-Analysis

Molecular analysis of blood groups is important in transfusion medicine, allowing the prediction of red blood cell (RBC) antigens. Many blood banks use single nucleotide variant (SNV) based methods for blood group analysis. While this is a well-established approach, it is limited to the polymorphisms included in genotyping panels. Thus, variants that alter antigenic expression may be ignored, resulting in incorrect prediction of phenotypes. The popularization of next-generation sequencing (NGS) has led to its application in transfusion medicine, including for RBC antigens determination. The present review/meta-analysis aimed to evaluate the applicability of the NGS for the prediction of RBC antigens. A systematic review was conducted following a comprehensive literature search in accordance with the Preferred Reporting Items for Systematic Review and Meta-Analysis guidelines. Studies were selected based on predefined criteria and evaluated using Strengthening the Reporting of Observational studies in Epidemiology guidelines. The characteristics and results of the studies were extracted and meta-analysis was performed to verify the agreement between results from standard molecular methods and NGS. Kell (rs8176058), Duffy (rs2814778, rs12078), or Kidd (rs1085396) alleles were selected as a model for comparisons. Additionally, results are presented for other blood group systems. Of the 864 eligible studies identified, 10 met the inclusion criteria and were selected for meta-analysis. The pooled concordance proportion for NGS compared to other methods ranged from 0.982 to 0.994. The sequencing depth coverage was identified as crucial parameters for the reliability of the results. Some studies reported difficulty in analyzing more complex systems, such as Rh and MNS, requiring the adoption of specific strategies. NGS is a technology capable of predicting blood group phenotypes and has many strengths such as the possibility of simultaneously analyzing hundred individuals and gene regions, and the ability to provide comprehensive genetic analysis, which is useful in the description of new alleles and a better understanding of the genetic basis of blood groups. The implementation of NGS in the routine of blood banks depends on several factors such as cost reduction, the availability of widely validated panels, the establishment of clear quality parameters and access to bioinformatics analysis tools that are easy to access and operate.

Practical considerations for reinterpretation of individual genetic variants

With the growing use of genetic testing in medicine, the question of when genetic findings should be reinterpreted in light of new data has become inescapable. The generation of population and disease-specific data, development of computational tools, and new understandings of the relationship of specific genes to disorders can all trigger changes in variant classification that may have important implications for patients and the clinicians caring for them. This is a particular concern for patients from groups underrepresented in current reference datasets, since they have higher rates of uncertain findings. Here we identify the challenges to implementing a systematic approach to variant reinterpretation and propose solutions. In particular, we address (a) the infrastructure needed to support implementation of systematic variant reinterpretation, (b) the issues around obtaining consent from patients for reinterpretation, (c) the process for triggering reinterpretation, (d) pathways for the flow of reinterpreted data, (e) considerations for how to cover the costs of reinterpretation, and (f) practical issues related to implementation of processes and policies that address these issues, including the importance of a fixed duration during which there is an expectation that variants will be reinterpreted.

Elective genomic testing: Practice resource of the National Society of Genetic Counselors

Genetic counseling for patients who are pursuing genetic testing in the absence of a medical indication, referred to as elective genomic testing (EGT), is becoming more common. This type of testing has the potential to detect genetic conditions before there is a significant health impact permitting earlier management and/or treatment. Pre- and post-test counseling for EGT is similar to indication-based genetic testing. Both require a complete family and medical history when ordering a test or interpreting a result. However, EGT counseling has some special considerations including greater uncertainties around penetrance and clinical utility and a lack of published guidelines. While certain considerations in the selection of a high-quality genetic testing laboratory are universal, there are some considerations that are unique to the selection of a laboratory performing EGT. This practice resource intends to provide guidance for genetic counselors and other healthcare providers caring for adults seeking pre- or post-test counseling for EGT. Genetic counselors and other genetics trained healthcare providers are the ideal medical professionals to supply accurate information to individuals seeking counseling about EGT enabling them to make informed decisions about testing and follow-up.

VariantAlert: A web-based tool to notify updates in genetic variant annotations

The reinterpretation of variants based on updated annotations is part of the routine work of research laboratories: the more data is collected about a specific variant, the higher the probability to reinterpret its classification. To support this task, we developed VariantAlert, a web-based tool to help researchers and clinicians to be constantly informed about changes in variant annotations extracted from multiple sources. VariantAlert provides daily re-annotation of variants using external resources accessed through application programming interface, such as MyVariant.info providing in turn links to gnomAD, catalogue of somatic mutations In cancer (COSMIC), ClinVar, CIViC, and many others. Researchers and clinicians can submit one or more lists of variants. If a change is detected for the annotation of a variant due to the upgrade of the underlying resource (e.g., change in gnomAD allele frequency, presence in COSMIC database, change in ClinVar classification) the user is notified by email and updated annotations are stored on the web-site. VariantAlert is freely available at https://github.com/next-crs4/VariantAlert. Installation and deployment are easy thanks to the use of the Docker platform. A Makefile allows you to easily bootstrap VariantAlert. VariantAlert is also available as a web service at https://variant-alert.crs4.it/.

Comprehensive genetic testing approaches as the basis for personalized management of growth disturbances: current status and perspectives

The implementation of high-throughput and deep sequencing methods in routine genetic diagnostics has significantly improved the diagnostic yield in patient cohorts with growth disturbances and becomes increasingly important as the prerequisite of personalized medicine. They provide considerable chances to identify even rare and unexpected situations; nevertheless, we must be aware of their limitations. A simple genetic test in the beginning of a testing cascade might also help to identify the genetic cause of specific growth disorders. However, the clinical picture of genetically caused growth disturbance phenotypes can vary widely, and there is a broad clinical overlap between different growth disturbance disorders. As a consequence, the clinical diagnosis and therewith connected the decision on the appropriate genetic test is often a challenge. In fact, the clinician asking for genetic testing has to weigh different aspects in this decision process, including appropriateness (single gene test, stepwise procedure, comprehensive testing), turnaround time as the basis for rapid intervention, and economic considerations. Therefore, a frequent question in that context is 'what to test when'. In this review, we aim to review genetic testing strategies and their strengths and limitations and to raise awareness for the future implementation of interdisciplinary genome medicine in diagnoses, treatment, and counselling of growth disturbances.

Implementation of individualised polygenic risk score analysis: a test case of a family of four

Background

Polygenic risk scores (PRS) have been widely applied in research studies, showing how population groups can be stratified into risk categories for many common conditions. As healthcare systems consider applying PRS to keep their populations healthy, little work has been carried out demonstrating their implementation at an individual level.

Case presentation

We performed a systematic curation of PRS sources from established data repositories, selecting 15 phenotypes, comprising an excess of 37 million SNPs related to cancer, cardiovascular, metabolic and autoimmune diseases. We tested selected phenotypes using whole genome sequencing data for a family of four related individuals. Individual risk scores were given percentile values based upon reference distributions among 1000 Genomes Iberians, Europeans, or all samples. Over 96 billion allele effects were calculated in order to obtain the PRS for each of the individuals analysed here.

Conclusions

Our results highlight the need for further standardisation in the way PRS are developed and shared, the importance of individual risk assessment rather than the assumption of inherited averages, and the challenges currently posed when translating PRS into risk metrics.

Recommendations for next generation sequencing data reanalysis of unsolved cases with suspected Mendelian disorders: A systematic review and meta-analysis

PURPOSE

The study aimed to determine the diagnostic yield, optimal timing, and methodology of next generation sequencing data reanalysis in suspected Mendelian disorders.

METHODS

We conducted a systematic review and meta-analysis of studies that conducted data reanalysis in patients with suspected Mendelian disorders. Random effects model was used to pool the estimated outcome with subgroup analysis stratified by timing, sequencing methodology, sample size, segregation, use of research validation, and artificial intelligence (AI) variant curation tools.

RESULTS

A search of PubMed, Embase, Scopus, and Web of Science between 2007 and 2021 yielded 9327 articles, of which 29 were selected. Significant heterogeneity was noted between studies. Reanalysis had an overall diagnostic yield of 0.10 (95% CI = 0.06-0.13). Literature updates accounted for most new diagnoses. Diagnostic yield was higher after 24 months, although this was not statistically significant. Increased diagnoses were obtained with research validation and data sharing. AI-based tools did not adversely affect reanalysis diagnostic rate.

CONCLUSION

Next generation sequencing data reanalysis can improve diagnostic yield. Owing to the heterogeneity of the studies, the optimal time to reanalysis and the impact of AI-based tools could not be determined with confidence. We propose standardized guidelines for future studies to reduce heterogeneity and improve the quality of the conclusions.

Interest in Cancer Predisposition Testing and Carrier Screening Offered as Part of Routine Healthcare Among an Ethnically Diverse Sample of Young Women

Sequencing technologies can inform individuals’ risks for multiple conditions, supporting population-level screening approaches. Prior research examining interest in genetic testing has not generally examined the context of population-based approaches offered in routine healthcare or among ethnically diverse populations. Cancer predisposition testing and carrier screening could be offered broadly to women of reproductive age. This study therefore examined interest in these tests when offered as part of routine care, and predictors of interest, among an ethnically diverse sample of women aged 20–35. We conducted an online English-language survey of 450 women; 39% identified as Latina. We examined predictors of interest for two outcomes, interest in testing in the next year and level of interest, in multivariable logistic regression models and stratified analyses by Latina ethnicity. More than half of respondents reported being interested in cancer predisposition testing (55%) and carrier screening (56%) in the next year; this did not differ by ethnicity. About 26% reported being very interested in cancer predisposition testing and 27% in carrier screening. Latina respondents (32%) were more likely to be very interested in cancer predisposition testing than non-Latina respondents (22%; p < 0.03). In multivariable models, having higher worry about genetic risks, higher genetic knowledge, and higher perceived importance of genetic information were associated with higher interest across multiple models. Predictors of interest were generally similar by ethnicity. Our findings show substantial interest in both cancer predisposition testing and carrier screening among young women as part of routine healthcare with similar interest between Latina and non-Latina women. Efforts to broadly offer such testing could be important in improving access to genetic information. It will be critical to develop tools to help healthcare providers communicate about genetic testing and to address the needs of those who have less prior knowledge about genetics to support informed decision making.

Best practices for the interpretation and reporting of clinical whole genome sequencing

Whole genome sequencing (WGS) shows promise as a first-tier diagnostic test for patients with rare genetic disorders. However, standards addressing the definition and deployment practice of a best-in-class test are lacking. To address these gaps, the Medical Genome Initiative, a consortium of leading health care and research organizations in the US and Canada, was formed to expand access to high quality clinical WGS by convening experts and publishing best practices. Here, we present best practice recommendations for the interpretation and reporting of clinical diagnostic WGS, including discussion of challenges and emerging approaches that will be critical to harness the full potential of this comprehensive test.

Re-analysis of genomic data: An overview of the mechanisms and complexities of clinical adoption

Re-analyzing genomic information from a patient suspected of having an underlying genetic condition can improve the diagnostic yield of sequencing tests, potentially providing significant benefits to the patient and to the health care system. Although a significant number of studies have shown the clinical potential of re-analysis, less work has been performed to characterize the mechanisms responsible for driving the increases in diagnostic yield. Complexities surrounding re-analysis have also emerged. The terminology itself represents a challenge because "re-analysis" can refer to a range of different concepts. Other challenges include the increased workload that re-analysis demands of curators, adequate reimbursement pathways for clinical and diagnostic services, and the development of systems to handle large volumes of data. Re-analysis also raises ethical implications for patients and families, most notably when re-classification of a variant alters diagnosis, treatment, and prognosis. This review highlights the possibilities and complexities associated with the re-analysis of existing clinical genomic data. We propose a terminology that builds on the foundation presented in a recent statement from the American College of Medical Genetics and Genomics and describes each re-analysis process. We identify mechanisms for increasing diagnostic yield and provide perspectives on the range of challenges that must be addressed by health care systems and individual patients.

Automated Pharmacogenomic Reports for Clinical Genome Sequencing

Clinical laboratories offering genome sequencing have the opportunity to return pharmacogenomic findings to patients, providing the added benefit of preemptive testing that could help inform medication selection or dosing throughout the lifespan. Implementation of pharmacogenomic reporting must address several challenges, including inherent limitations in short-read genome sequencing methods, gene and variant selection, standardization of genotype and phenotype nomenclature, and choice of guidelines and drugs to report. An automated pipeline, lmPGX, was developed as an end-to-end solution that produces two versions of a pharmacogenomic report, presenting either Clinical Pharmacogenetics Implementation Consortium or US Food and Drug Administration guidelines for 12 genes. The pipeline was validated for performance using reference samples and pharmacogenetic data from the Genetic Testing Reference Materials Coordination Program. To determine performance and limitations, lmPGX was compared with three additional publicly available pharmacogenomic pipelines. The lmPGX pipeline offers clinical laboratories an opportunity for seamless integration of pharmacogenomic results with genome reporting.

Reanalysis of eMERGE phase III sequence variants in 10,500 participants and infrastructure to support the automated return of knowledge updates

PURPOSE

The clinical genomics knowledgebase is dynamic with variant classifications changing as newly identified cases, additional population data, and other evidence become available. This is a challenge for the clinical laboratory because of limited resource availability for variant reassessment.

METHODS

Throughout the Electronic Medical Records and Genomics phase III program, clinical sites associated with the Mass General Brigham/Broad sequencing center received automated, real-time notifications when reported variants were reclassified. In this study, we summarized the nature of these reclassifications and described the proactive reassessment framework we used for the Electronic Medical Records and Genomics program data set to identify variants most likely to undergo reclassification.

RESULTS

Reanalysis of 1855 variants led to the reclassification of 2% (n = 45) of variants, affecting 0.6% (n = 67) of participants. Of these reclassifications, 78% (n = 35) were high-impact changes affecting reportability, with 8 variants downgraded from likely pathogenic/pathogenic to variants of uncertain significance (VUS) and 27 variants upgraded from VUS to likely pathogenic/pathogenic. Most upgraded variants (67%) were initially classified as VUS-Favor Pathogenic, highlighting the benefit of VUS subcategorization. The most common reason for reclassification was new published case data and/or functional evidence.

CONCLUSION

Our results highlight the importance of periodic sequence variant reevaluation and the need for automated approaches to advance routine implementation of variant reevaluations in clinical practice.

Simulating the Genetics Clinic of the Future — whether undergoing whole-genome sequencing shapes professional attitudes

Whole-genome sequencing (WGS) can provide valuable health insight for research participants or patients. Opportunities to be sequenced are increasing as direct-to-consumer (DTC) testing becomes more prevalent, but it is still fairly unusual to have been sequenced. We offered WGS to fourteen professionals with pre-existing familiarity with an interest in human genetics — healthcare, science, policy and art. Participants received a hard drive containing their personal sequence data files (.BAM,.gvcf), without further explanation or obligation, to consider how experiencing WGS firsthand might influence their professional attitudes. We performed semi-structured pre- and post-sequencing interviews with each participant to identify key themes that they raised after being sequenced. To evaluate how their experience of the procedure evolved over time, we also conducted a questionnaire to gather their views 3 years after receiving their genomic data. Participants were generally satisfied with the experience (all 14 participants would choose to participate again). They mostly decided to participate out of curiosity (personal) and to learn from the experience (professional). Whereas most participants slightly developed their original perspective on genetic data, a small selection of them radically changed their views over the course of the project. We conclude that personal experience of sequencing provides an interesting alternative perspective for experts involved in leading, planning, implementing or researching genome sequencing services. Moreover, the personal experience may provide professionals with a better understanding of the challenges visitors of the Genetics Clinic of the Future may face.

Behavioral and psychological impact of genome sequencing: a pilot randomized trial of primary care and cardiology patients

Many expect genome sequencing (GS) to become routine in patient care and preventive medicine, but uncertainties remain about its ability to motivate participants to improve health behaviors and the psychological impact of disclosing results. In a pilot trial with exploratory analyses, we randomized 100 apparently healthy, primary-care participants and 100 cardiology participants to receive a review of their family histories of disease, either alone or in addition to GS analyses. GS results included polygenic risk information for eight cardiometabolic conditions. Overall, no differences were observed between the percentage of participants in the GS and control arms, who reported changes to health behaviors such as diet and exercise at 6 months post disclosure (48% vs. 36%, respectively, p = 0.104). In the GS arm, however, the odds of reporting a behavior change increased by 52% per high-risk polygenic prediction (p = 0.032). Mean anxiety and depression scores for GS and control arms had confidence intervals within equivalence margins of ±1.5. Mediation analyses suggested an indirect impact of GS on health behaviors by causing positive psychological responses (p ≤ 0.001). Findings suggest that GS did not distress participants. Future research on GS in more diverse populations is needed to confirm that it does not raise risks for psychological harms and to confirm the ability of polygenic risk predictions to motivate preventive behaviors.

A study of elective genome sequencing and pharmacogenetic testing in an unselected population

BACKGROUND

Genome sequencing (GS) of individuals without a medical indication, known as elective GS, is now available at a number of centers around the United States. Here we report the results of elective GS and pharmacogenetic panel testing in 52 individuals at a private genomics clinic in Alabama.

METHODS

Individuals seeking elective genomic testing and pharmacogenetic testing were recruited through a private genomics clinic in Huntsville, AL. Individuals underwent clinical genome sequencing with a separate pharmacogenetic testing panel.

RESULTS

Six participants (11.5%) had pathogenic or likely pathogenic variants that may explain one or more aspects of their medical history. Ten participants (19%) had variants that altered the risk of disease in the future, including two individuals with clonal hematopoiesis of indeterminate potential. Forty-four participants (85%) were carriers of a recessive or X-linked disorder. All individuals with pharmacogenetic testing had variants that affected current and/or future medications.

CONCLUSION

Our study highlights the importance of collecting detailed phenotype information to interpret results in elective GS.

A framework for automated gene selection in genomic applications

Purpose

An efficient framework to identify disease associated genes is needed to evaluate genomic data for both individuals with an unknown disease etiology and those undergoing genomic screening. Here, we propose a framework for gene selection used in genomic analyses, including applications limited to genes with strong or established evidence levels and applications including genes with less or emerging evidence of disease association.

Methods

We extracted genes with evidence for gene-disease association from the Human Gene Mutation Database, Online Mendelian Inheritance in Man, and ClinVar to build a comprehensive gene list of 6,145 genes. Next, we applied stringent filters in conjunction with computationally curated evidence (DisGeNET) to create a restrictive list limited to 3,929 genes with stronger disease associations.

Results

When compared to manual gene curation efforts, including the Clinical Genome Resource, genes with strong or definitive disease associations are included in both gene lists at high percentages, while genes with limited evidence are largely removed. We further confirmed the utility of this approach in identifying pathogenic and likely pathogenic variants in 45 genomes.

Conclusion

Our approach efficiently creates highly sensitive gene lists for genomic applications, while remaining dynamic and updatable, enabling time savings in genomic applications.

Clinically Actionable Findings Derived From Predictive Genomic Testing Offered in a Medical Practice Setting

OBJECTIVE

To assess the presence of clinically actionable results and other genetic findings in an otherwise healthy population of adults seen in a medical practice setting and offered "predictive" genomic testing.

PATIENTS AND METHODS

In 2014, a predictive genomics clinic for generally healthy adults was launched through the Mayo Clinic Executive Health Program. Self-identified interested patients met with a genomic nurse and genetic counselor for pretest advice and education. Two genome sequencing platforms and one gene panel-based health screen were offered. Posttest genetic counseling was available for patients who elected testing. From March 1, 2014, through June 1, 2019, 1281 patients were seen and 301 (23.5%) chose testing. Uptake rates increased to 36.3% [70 of 193]) in 2019 from 11.8% [2 of 17] in 2014. Clinically actionable results and genetic findings were analyzed using descriptive statistics.

RESULTS

Clinically actionable results were detected in 11.6% of patients (35 of 301), and of those, 51.7% (15 of 29) with a cancer or cardiovascular result = did not have a personal or family history concerning for a hereditary disorder. The most common actionable results were in the BCHE, BRCA2, CHEK2, LDLR, MUTYH, and MYH7 genes. A carrier of at least one recessive condition was found in 53.8% of patients (162 of 301). At least one variant associated with multifactorial disease was found in 44.5% (134 of 301) (eg, 25 patients were heterozygous for the F5 factor V Leiden variant associated with thrombophilia risk).

CONCLUSION

Our predictive screening revealed that 11.6% of individuals will test positive for a clinically actionable, likely pathogenic/pathogenic variant. This finding suggests that wider knowledge and adoption of predictive genomic services could be beneficial in medical practice, although additional studies are needed.

Genetic health professionals' experiences with initiating reanalysis of genomic sequence data

Despite the increased diagnostic yield associated with genomic sequencing (GS), a sizable proportion of patients do not receive a genetic diagnosis at the time of the initial GS analysis. Systematic data reanalysis leads to considerable increases in genetic diagnosis rates yet is time intensive and leads to questions of feasibility. Few policies address whether laboratories have a duty to reanalyse and it is unclear how this impacts clinical practice. To address this, we interviewed 31 genetic health professionals (GHPs) across Europe, Australia and Canada about their experiences with data reanalysis and variant reinterpretation practices after requesting GS for their patients. GHPs described a range of processes required to initiate reanalysis of GS data for their patients and often practices involved a combination of reanalysis initiation methods. The most common mechanism for reanalysis was a patient-initiated model, where they instruct patients to return to the genetic service for clinical reassessment after a period of time or if new information comes to light. Yet several GHPs expressed concerns about patients' inabilities to understand the need to return to trigger reanalysis, or advocate for themselves, which may exacerbate health inequities. Regardless of the reanalysis initiation model that a genetic service adopts, patients' and clinicians' roles and responsibilities need to be clearly outlined so patients do not miss the opportunity to receive ongoing information about their genetic diagnosis. This requires consensus on the delineation of these roles for clinicians and laboratories to ensure clear pathways for reanalysis and reinterpretation to be performed to improve patient care.

Next-generation sequencing for constitutional variants in the clinical laboratory, 2021 revision: a technical standard of the American College of Medical Genetics and Genomics (ACMG)

Next-generation sequencing (NGS) technologies are now established in clinical laboratories as a primary testing modality in genomic medicine. These technologies have reduced the cost of large-scale sequencing by several orders of magnitude. It is now cost-effective to analyze an individual with disease-targeted gene panels, exome sequencing, or genome sequencing to assist in the diagnosis of a wide array of clinical scenarios. While clinical validation and use of NGS in many settings is established, there are continuing challenges as technologies and the associated informatics evolve. To assist clinical laboratories with the validation of NGS methods and platforms, the ongoing monitoring of NGS testing to ensure quality results, and the interpretation and reporting of variants found using these technologies, the American College of Medical Genetics and Genomics (ACMG) has developed the following technical standards.

Whole Genome Interpretation for a Family of Five

Although best practices have emerged on how to analyse and interpret personal genomes, the utility of whole genome screening remains underdeveloped. A large amount of information can be gathered from various types of analyses via whole genome sequencing including pathogenicity screening, genetic risk scoring, fitness, nutrition, and pharmacogenomic analysis. We recognize different levels of confidence when assessing the validity of genetic markers and apply rigorous standards for evaluation of phenotype associations. We illustrate the application of this approach on a family of five. By applying analyses of whole genomes from different methodological perspectives, we are able to build a more comprehensive picture to assist decision making in preventative healthcare and well-being management. Our interpretation and reporting outputs provide input for a clinician to develop a healthcare plan for the individual, based on genetic and other healthcare data.

Whole-Exome Sequencing in Patients Affected by Stevens-Johnson Syndrome and Toxic Epidermal Necrolysis Reveals New Variants Potentially Contributing to the Phenotype

Background

Adverse drug reactions (ADRs) are frequent occurring events that can essentially be defined as harmful or unpleasant symptoms secondary to the use of a medicinal product. ADRs involve a wide spectrum of clinical manifestations ranging from minor itching and rash to life-threatening reactions. Stevens-Johnson syndrome (SJS) and toxic epidermal necrolysis (TEN) are rare ADRs. SJS-TEN may be considered a polygenic pathology due to additive/epistatic effects caused by sequence variants in numerous genes. Next-generation sequencing (NGS) represents a potentially interesting exploration tool in such scenario as it facilitates the simultaneous analysis of large genomic regions and genes at affordable cost.

Methods

The present study has involved using whole-exome sequencing (WES) for the first time on SJS-TEN patients. It involved robust and innovative multistep bioinformatics analysis focusing on 313 candidate genes potentially participating in the disease’s aetiology, specific drugs’ metabolism and gene regulation.

Results

We identified combinations of frequently occurring and rare variants that may contribute to the disease’s pathogenesis. Depending on the specific drug being taken, different variants (and alleles) in NAT2, CYP2D8, CYP2B6, ABCC2, UGT2B7 and TCF3 were identified as coherent candidates representing potential future markers for SJS-TEN.

Conclusion

The present study proposed and has described (for the first time) a large-scale genomic analysis of patients affected by SJS-TEN. The genes and variants identified represent relevant candidates potentially participating in the disease’s pathogenesis. Corroborating that proposed by others, we found that complex combinations of frequently occurring and rare variants participating in particular drug metabolism molecular cascades could be associated with the phenotype. TCF3 TF may be considered a coherent candidate for SJS-TEN that should be analysed in new cohorts of patients having ADRs.

Transcriptome-directed analysis for Mendelian disease diagnosis overcomes limitations of conventional genomic testing

BACKGROUNDTranscriptome sequencing (RNA-seq) improves diagnostic rates in individuals with suspected Mendelian conditions to varying degrees, primarily by directing the prioritization of candidate DNA variants identified on exome or genome sequencing (ES/GS). Here we implemented an RNA-seq-guided method to diagnose individuals across a wide range of ages and clinical phenotypes.METHODSOne hundred fifteen undiagnosed adult and pediatric patients with diverse phenotypes and 67 family members (182 total individuals) underwent RNA-seq from whole blood and skin fibroblasts at the Baylor College of Medicine (BCM) Undiagnosed Diseases Network clinical site from 2014 to 2020. We implemented a workflow to detect outliers in gene expression and splicing for cases that remained undiagnosed despite standard genomic and transcriptomic analysis.RESULTSThe transcriptome-directed approach resulted in a diagnostic rate of 12% across the entire cohort, or 17% after excluding cases solved on ES/GS alone. Newly diagnosed conditions included Koolen-de Vries syndrome (KANSL1), Renpenning syndrome (PQBP1), TBCK-associated encephalopathy, NSD2- and CLTC-related intellectual disability, and others, all with negative conventional genomic testing, including ES and chromosomal microarray (CMA). Skin fibroblasts exhibited higher and more consistent expression of clinically relevant genes than whole blood. In solved cases with RNA-seq from both tissues, the causative defect was missed in blood in half the cases but none from fibroblasts.CONCLUSIONSFor our cohort of undiagnosed individuals with suspected Mendelian conditions, transcriptome-directed genomic analysis facilitated diagnoses, primarily through the identification of variants missed on ES and CMA.TRIAL REGISTRATIONNot applicable.FUNDINGNIH Common Fund, BCM Intellectual and Developmental Disabilities Research Center, Eunice Kennedy Shriver National Institute of Child Health & Human Development.

Moving Genomics to Routine Care

Background:

Whole-genome sequencing (WGS) costs are falling, yet, outside oncology, this information is seldom used in adult clinics. We piloted a rapid WGS (rWGS) workflow, focusing initially on estimating power for a feasibility study of introducing genome information into acute cardiovascular care.

Methods:

A prospective implementation study was conducted to test the feasibility and clinical utility of rWGS in acute cardiovascular care. rWGS was performed on 50 adult patients with acute cardiovascular events and cardiac arrest survivors, testing for primary and secondary disease-causing variants, cardiovascular-related pharmacogenomics, and carrier status for recessive diseases. The impact of returning rWGS results on short-term clinical care of participants was investigated. The utility of polygenic risk scores to stratify coronary artery disease was also assessed.

Results:

Pathogenic variants, typically secondary findings, were identified in 20% (95% CI, 11.7–34.3). About 60% (95% CI, 46.2–72.4) of participants were carriers for one or more recessive traits, most commonly inHFEandSERPINA1genes. Although 64% (95% CI, 50.1–75.9) of participants carried at least one pharmacogenetic variant of cardiovascular relevance, these were actionable in only 14% (95% CI, 7–26.2). Coronary artery disease prevalence among participants at the 95th percentile of polygenic risk score was 88.2% (95% CI, 71.8–95.7).

Conclusions:

We demonstrated the feasibility of rWGS integration into the inpatient management of adults with acute cardiovascular events. Our pilot identified pathogenic variants in one out of 5 acute vascular patients. Integrating rWGS in clinical care will progressively increase actionability.

Genomic Sequencing for Newborn Screening: Results of the NC NEXUS Project

Newborn screening (NBS) was established as a public health program in the 1960s and is crucial for facilitating detection of certain medical conditions in which early intervention can prevent serious, life-threatening health problems. Genomic sequencing can potentially expand the screening for rare hereditary disorders, but many questions surround its possible use for this purpose. We examined the use of exome sequencing (ES) for NBS in the North Carolina Newborn Exome Sequencing for Universal Screening (NC NEXUS) project, comparing the yield from ES used in a screening versus a diagnostic context. We enrolled healthy newborns and children with metabolic diseases or hearing loss (106 participants total). ES confirmed the participant's underlying diagnosis in 15 out of 17 (88%) children with metabolic disorders and in 5 out of 28 (∼18%) children with hearing loss. We discovered actionable findings in four participants that would not have been detected by standard NBS. A subset of parents was eligible to receive additional information for their child about childhood-onset conditions with low or no clinical actionability, clinically actionable adult-onset conditions, and carrier status for autosomal-recessive conditions. We found pathogenic variants associated with hereditary breast and/or ovarian cancer in two children, a likely pathogenic variant in the gene associated with Lowe syndrome in one child, and an average of 1.8 reportable variants per child for carrier results. These results highlight the benefits and limitations of using genomic sequencing for NBS and the challenges of using such technology in future precision medicine approaches.

Evaluating systematic reanalysis of clinical genomic data in rare disease from single center experience and literature review

Background

Our primary aim was to evaluate the systematic reanalysis of singleton exome sequencing (ES) data for unsolved cases referred for any indication. A secondary objective was to undertake a literature review of studies examining the reanalysis of genomic data from unsolved cases.

Methods

We examined data from 58 unsolved cases referred between June 2016 and March 2017. First reanalysis at 4–13 months after the initial report considered genes newly associated with disease since the original analysis; second reanalysis at 9–18 months considered all disease‐associated genes. At 25–34 months we reviewed all cases and the strategies which solved them.

Results

Reanalysis of existing ES data alone at two timepoints did not yield new diagnoses. Over the same timeframe, 10 new diagnoses were obtained (17%) from additional strategies, such as microarray detection of copy number variation, repeat sequencing to improve coverage, and trio sequencing. Twenty‐seven peer‐reviewed articles were identified on the literature review, with a median new diagnosis rate via reanalysis of 15% and median reanalysis timeframe of 22 months.

Conclusion

Our findings suggest that an interval of greater than 18 months from the original report may be optimal for reanalysis. We also recommend a multi‐faceted strategy for cases remaining unsolved after singleton ES.

Leukodystrophies and Genetic Leukoencephalopathies in Children Specified by Exome Sequencing in an Expanded Gene Panel

The overlapping clinical and neuroimaging phenotypes of leukodystrophies pose a diagnostic challenge to both clinicians and researchers alike. Studies on the application of exome sequencing in the diagnosis of leukodystrophies are emerging. We used targeted gene panel sequencing of 6440 genes to investigate the genetic etiology in a cohort of 50 children with neuroimaging diagnosis of leukodystrophy/genetic leukoencephalopathy of unknown etiology. These 50 patients without a definite biochemical or genetic diagnosis were derived from a cohort of 88 patients seen during a 2.5-year period (2015 January-2017 June). Patients who had diagnosis by biochemical or biopsy confirmation (n = 17) and patients with incomplete data or lack of follow-up (n = 21) were excluded. Exome sequencing identified variants in 30 (60%) patients, which included pathogenic or likely pathogenic variants in 28 and variants of unknown significance in 2. Among the patients with pathogenic or likely pathogenic variants, classic leukodystrophies constituted 13 (26%) and genetic leukoencephalopathies 15 (30%). The clinical and magnetic resonance imaging (MRI) findings and genetic features of the identified disorders are discussed.

Frequency of ClinVar Pathogenic Variants in Chronic Kidney Disease Patients Surveyed for Return of Research Results at a Cleveland Public Hospital

Return of results is not common in research settings as standards are not yet in place for what to return, how to return, and to whom. As a pioneer of large-scale of return of research results, the Precision Medicine Initiative Cohort now known of All of Us plans to return pharmacogenomic results and variants of clinical significance to its participants starting late 2019. To better understand the local landscape of possibilities regarding return of research results, we assessed the frequency of pathogenic variants and APOL1 renal risk variants in a small diverse cohort of chronic kidney disease patients (CKD) ascertained from a public hospital in Cleveland, Ohio genotyped on the Illumina Infinium MegaEX. Of the 23,720 ClinVar-designated variants directly assayed by the MegaEX, 8,355 (35%) had at least one alternate allele in the 130 participants genotyped. Of these, 18 ClinVar variants deemed pathogenic by multiple submitters with no conflicts in interpretation were distributed across 27 participants. The majority of these pathogenic ClinVar variants (14/18) were associated with autosomal recessive disorders. Of note were four African American carriers of TTR rs76992529 associated with amyloidogenic transthyretin amyloidosis, otherwise known as familial transthyretin amyloidosis (FTA). FTA, an autosomal dominant disorder with variable penetrance, is more common among African-descent populations compared with European-descent populations. Also common in this CKD population were APOL1 renal risk alleles G1 (rs73885319) and G2 (rs71785313) with 60% of the study population carrying at least one renal risk allele. Both pathogenic ClinVar variants and APOL1 renal risk alleles were distributed among participants who wanted actionable genetic results returned, wanted genetic results returned regardless of actionability, and wanted no results returned. Results from this local genetic study highlight challenges in which variants to report, how to interpret them, and the participant's potential for follow-up, only some of the challenges in return of research results likely facing larger studies such as All of Us.