Whole exome and genome sequencing in mendelian disorders: a diagnostic and health economic analysis

Bayesian cost-effectiveness analysis of Whole genome sequencing versus Whole exome sequencing in a pediatric population with suspected genetic disorders

Genetic diseases are medical conditions caused by sequence or structural changes in an individual's genome. Whole exome sequencing (WES) and whole genome sequencing (WGS) are increasingly used for diagnosing suspected genetic conditions in children to reduce the diagnostic delay and accelerating the implementation of appropriate treatments. While more information is becoming available on clinical efficacy and economic sustainability of WES, the broad implementation of WGS is still hindered by higher complexity and economic issues. The aim of this study is to estimate the cost-effectiveness of WGS versus WES and standard testing for pediatric patients with suspected genetic disorders. A Bayesian decision tree model was set up. Model parameters were retrieved both from hospital administrative datasets and scientific literature. The analysis considered a lifetime time frame and adopted the perspective of the Italian National Health Service (NHS). Bayesian inference was performed using the Markov Chain Monte Carlo simulation method. Uncertainty was explored through a probabilistic sensitivity analysis (PSA) and a value of information analysis (VOI). The present analysis showed that implementing first-line WGS would be a cost-effective strategy, against the majority of the other tested alternatives at a threshold of €30,000-50,000, for diagnosing outpatient pediatric patients with suspected genetic disorders. According to the sensitivity analyses, the findings were robust to most assumption and parameter uncertainty. Lessons learnt from this modeling study reinforces the adoption of first-line WGS, as a cost-effective strategy, depending on actual difficulties for the NHS to properly allocate limited resources.

First copy number variant in trans with single nucleotide variant in CCN6 causing progressive pseudorheumatoid dysplasia revealed by genome sequencing and deep phenotyping in monozygotic twins

Biallelic pathogenic variants in CCN6 cause progressive pseudorheumatoid dysplasia (PPD), a rare skeletal dysplasia. The predominant features include noninflammatory progressive joint stiffness and enlargement, which are not unique to this condition. Nearly 100% of the reported variants are single nucleotide variants or small indels, and missing of a second variant has been reported. Genome sequencing (GS) covers various types of variants and deep phenotyping (DP) provides detailed and precise information facilitating genetic data interpretation. The combination of GS and DP improves diagnostic yield, especially in rare and undiagnosed diseases. We identified a novel compound heterozygote involving a disease-causing copy number variant (g.112057664_112064205del) in trans with a single nucleotide variant (c.624dup(p.Cys209MetfsTer21)) in CCN6 in a pair of monozygotic twins, through the methods of GS and DP. The twins had received three nondiagnostic results before. The g.112057664_112064205del variant was missed by all the tests, and the recorded phenotypes were inaccurate or even misleading. The twins were diagnosed with PPD, ending a 13-year diagnostic odyssey. There may be other patients with PPD experiencing underdiagnosis and misdiagnosis due to inadequate genetic testing or phenotyping methods. This case highlights the critical role of GS and DP in facilitating an accurate and timely diagnosis.

Genomic Testing in Patients with Kidney Failure of an Unknown Cause: A National Australian Study

Key Points

Twenty-five percent of those with unexplained kidney failure have a monogenic cause. Whole genome sequencing with broad gene panel analysis is a feasible diagnostic approach in nephrology.

Background

The cause of kidney failure is unknown in approximately 10% of patients with stage 5 chronic kidney disease (CKD). For those who first present to nephrology care with kidney failure, standard investigations of serology, imaging, urinalysis, and kidney biopsy are limited differentiators of etiology. We aimed to determine the diagnostic utility of whole genome sequencing (WGS) with analysis of a broad kidney gene panel in patients with kidney failure of unknown cause.

Methods

We prospectively recruited 100 participants who reached CKD stage 5 at the age of ≤50 years and had an unknown cause of kidney failure after standard investigation. Clinically accredited WGS was performed in this national cohort after genetic counseling. The primary analysis was targeted to 388 kidney-related genes with second-tier, genome-wide, and mitochondrial analysis.

Results

The cohort was 61% male and the average age of participants at stage 5 CKD was 32 years (9 months to 50 years). A genetic diagnosis was made in 25% of participants. Disease-causing variants were identified across autosomal dominant tubulointerstitial kidney disease (6), glomerular disorders (4), ciliopathies (3), tubular disorders (2), Alport syndrome (4), and mitochondrial disease (1). Most diagnoses (80%) were in autosomal dominant, X-linked, or mitochondrial conditions (UMOD ; COL4A5 ; INF2 ; CLCN5 ; TRPC6 ; COL4A4 ; EYA1 ; HNF1B ; WT1 ; NBEA ; m.3243A>G ). Participants with a family history of CKD were more likely to have a positive result (odds ratio, 3.29; 95% confidence interval, 1.10 to 11.29). Thirteen percent of participants without a CKD family history had a positive result. In those who first presented in stage 5 CKD, WGS with broad analysis of a curated kidney disease gene panel was diagnostically more informative than kidney biopsy, with biopsy being inconclusive in 24 of the 25 participants.

Conclusions

In this prospectively ascertained Australian cohort, we identified a genetic diagnosis in 25% of patients with kidney failure of unknown cause.

Whole genome sequencing of families diagnosed with cardiac channelopathies reveals structural variants missed by whole exome sequencing

Cardiac channelopathies are a group of heritable disorders that affect the heart's electrical activity due to genetic variations present in genes coding for ion channels. With the advent of new sequencing technologies, molecular diagnosis of these disorders in patients has paved the way for early identification, therapeutic management and family screening. The objective of this retrospective study was to understand the efficacy of whole-genome sequencing in diagnosing patients with suspected cardiac channelopathies who were reported negative after whole exome sequencing and analysis. We employed a 3-tier analysis approach to identify nonsynonymous variations and loss-of-function variations missed by exome sequencing, and structural variations that are better resolved only by sequencing whole genomes. By performing whole genome sequencing and analyzing 25 exome-negative cardiac channelopathy patients, we identified 3 pathogenic variations. These include a heterozygous likely pathogenic nonsynonymous variation, CACNA1C:NM_000719:exon19:c.C2570G:p. P857R, which causes autosomal dominant long QT syndrome in the absence of Timothy syndrome, a heterozygous loss-of-function variation CASQ2:NM_001232.4:c.420+2T>C classified as pathogenic, and a 9.2 kb structural variation that spans exon 2 of the KCNQ1 gene, which is likely to cause Jervell-Lange-Nielssen syndrome. In addition, we also identified a loss-of-function variation and 16 structural variations of unknown significance (VUS). Further studies are required to elucidate the role of these identified VUS in gene regulation and decipher the underlying genetic and molecular mechanisms of these disorders. Our present study serves as a pilot for understanding the utility of WGS over clinical exomes in diagnosing cardiac channelopathy disorders.

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.

Long-read genome sequencing reveals a novel intronic retroelement insertion in NR5A1 associated with 46,XY differences of sexual development

Despite significant advancements in rare genetic disease diagnostics, many patients with rare genetic disease remain without a molecular diagnosis. Novel tools and methods are needed to improve the detection of disease-associated variants and understand the genetic basis of many rare diseases. Long-read genome sequencing provides improved sequencing in highly repetitive, homologous, and low-complexity regions, and improved assessment of structural variation and complex genomic rearrangements compared to short-read genome sequencing. As such, it is a promising method to explore overlooked genetic variants in rare diseases with a high suspicion of a genetic basis. We therefore applied PacBio HiFi sequencing in a large multi-generational family presenting with autosomal dominant 46,XY differences of sexual development (DSD), for whom extensive molecular testing over multiple decades had failed to identify a molecular diagnosis. This revealed a rare SINE-VNTR-Alu retroelement insertion in intron 4 of NR5A1, a gene in which loss-of-function variants are an established cause of 46,XY DSD. The insertion segregated among affected family members and was associated with loss-of-expression of alleles in cis, demonstrating a functional impact on NR5A1. This case highlights the power of long-read genome sequencing to detect genomic variants that have previously been intractable to detection by standard short-read genomic testing.

Narrowing the diagnostic gap: Genomes, episignatures, long-read sequencing, and health economic analyses in an exome-negative intellectual disability cohort

PURPOSE

Genome sequencing (GS)-specific diagnostic rates in prospective tightly ascertained exome sequencing (ES)-negative intellectual disability (ID) cohorts have not been reported extensively.

METHODS

ES, GS, epigenetic signatures, and long-read sequencing diagnoses were assessed in 74 trios with at least moderate ID.

RESULTS

The ES diagnostic yield was 42 of 74 (57%). GS diagnoses were made in 9 of 32 (28%) ES-unresolved families. Repeated ES with a contemporary pipeline on the GS-diagnosed families identified 8 of 9 single-nucleotide variations/copy-number variations undetected in older ES, confirming a GS-unique diagnostic rate of 1 in 32 (3%). Episignatures contributed diagnostic information in 9% with GS corroboration in 1 of 32 (3%) and diagnostic clues in 2 of 32 (6%). A genetic etiology for ID was detected in 51 of 74 (69%) families. Twelve candidate disease genes were identified. Contemporary ES followed by GS cost US$4976 (95% CI: $3704; $6969) per diagnosis and first-line GS at a cost of $7062 (95% CI: $6210; $8475) per diagnosis.

CONCLUSION

Performing GS only in ID trios would be cost equivalent to ES if GS were available at $2435, about a 60% reduction from current prices. This study demonstrates that first-line GS achieves higher diagnostic rate than contemporary ES but at a higher cost.

Shwachman-Diamond syndrome mimicking mitochondrial hepatopathy

Shwachman-Diamond syndrome (SDS) is a genetic disorder caused by mutations in the Shwachman-Bodian-Diamond syndrome (SBDS) gene. The syndrome is characterized by multiorgan dysfunction primarily involving the bone marrow and exocrine pancreas. Frequently overlooked is the hepatic dysfunction seen in early childhood which tends to improve by adulthood. Here, we report a child who initially presented with failure to thrive and elevated transaminases, and was ultimately diagnosed with SDS. A liver biopsy electron micrograph revealed hepatocytes crowded with numerous small mitochondria, resembling the hepatic architecture from patients with inborn errors of metabolism, including mitochondrial diseases. To our knowledge, this is the first report of the mitochondrial phenotype in an SDS patient. These findings are compelling given the recent cellular and molecular research studies which have identified SBDS as an essential regulator of mitochondrial function and have also implicated SBDS in the maintenance of mitochondrial DNA.

A novel method for simultaneous detection of hematological tumors and infectious pathogens by metagenomic next generation sequencing of plasma

BACKGROUND

Metagenomic next-generation sequencing (mNGS) is valuable for pathogen identification; however, distinguishing between infectious diseases and conditions with potentially similar clinical manifestations, including malignant tumors, is challenging. Therefore, we developed a method for simultaneous detection of infectious pathogens and cancer in blood samples.

METHODS

Plasma samples (n = 244) were collected from 150 and 94 patients with infections and hematological malignancies, respectively, and analyzed by mNGS for pathogen detection, alongside human tumor chromosomal copy number variation (CNV) analysis (≥5Mbp or 10Mbp CNV region). Further, an evaluation set, comprising 87 plasma samples, was analyzed by mNGS and human CNV analysis, to validate the feasibility of the method.

RESULTS

Among 94 patients with hematological malignancy, sensitivity values of CNV detection for tumor diagnosis were 69.15 % and 32.98 % for CNV region 5Mbp and 10Mbp, respectively, with corresponding specificities of 92.62 % and 100 % in the infection group. Area under the ROC curve (AUC) values for 5Mbp and 10Mbp region were 0.825 and 0.665, respectively, which was a significant difference of 0.160 (95 % CI: 0.110-0.210; p < 0.001), highlighting the superiority of 5Mbp output region data. Six patients with high-risk CNV results were identified in the validation study: three with history of tumor treatment, two eventually newly-diagnosed with hematological malignancies, and one with indeterminate final diagnosis.

CONCLUSIONS

Concurrent CNV analysis alongside mNGS for infection diagnosis is promising for detecting malignant tumors. We recommend adopting a CNV region of 10Mbp over 5Mbp for our model, because of the lower false-positive rate (FPR).

From Data to Cure: A Comprehensive Exploration of Multi-omics Data Analysis for Targeted Therapies

In the dynamic landscape of targeted therapeutics, drug discovery has pivoted towards understanding underlying disease mechanisms, placing a strong emphasis on molecular perturbations and target identification. This paradigm shift, crucial for drug discovery, is underpinned by big data, a transformative force in the current era. Omics data, characterized by its heterogeneity and enormity, has ushered biological and biomedical research into the big data domain. Acknowledging the significance of integrating diverse omics data strata, known as multi-omics studies, researchers delve into the intricate interrelationships among various omics layers. This review navigates the expansive omics landscape, showcasing tailored assays for each molecular layer through genomes to metabolomes. The sheer volume of data generated necessitates sophisticated informatics techniques, with machine-learning (ML) algorithms emerging as robust tools. These datasets not only refine disease classification but also enhance diagnostics and foster the development of targeted therapeutic strategies. Through the integration of high-throughput data, the review focuses on targeting and modeling multiple disease-regulated networks, validating interactions with multiple targets, and enhancing therapeutic potential using network pharmacology approaches. Ultimately, this exploration aims to illuminate the transformative impact of multi-omics in the big data era, shaping the future of biological research.

Updates on Genetic Hearing Loss: From Diagnosis to Targeted Therapies

Sensorineural hearing loss (SNHL) is the most common sensory disorder, with a high Mendelian genetic contribution. Considering the genotypic and phenotypic heterogeneity of SNHL, the advent of next-generation sequencing technologies has revolutionized knowledge on its genomic architecture. Nonetheless, the conventional application of panel and exome sequencing in real-world practice is being challenged by the emerging need to explore the diagnostic capability of whole-genome sequencing, which enables the detection of both noncoding and structural variations. Small molecules and gene therapies represent good examples of how breakthroughs in genetic understanding can be translated into targeted therapies for SNHL. For example, targeted small molecules have been used to ameliorate autoinflammatory hearing loss caused by gain-of-function variants of NLRP3 and inner ear proteinopathy with OSBPL2 variants underlying dysfunctional autophagy. Strikingly, the successful outcomes of the first-in-human trial of OTOF gene therapy highlighted its potential in the treatment of various forms of genetic hearing loss. clustered regularly interspaced short palindromic repeats (CRISPR)-based technologies are currently being developed for site-specific genome editing to treat human genetic disorders. These advancements have led to an era of genotype- and mechanism-based precision medicine in SNHL practice.

A Practical Guide to Whole Genome Sequencing in the NICU

The neonatal period is a peak time for the presentation of genetic disorders that can be diagnosed using whole genome sequencing (WGS). While any one genetic disorder is individually rare, they collectively contribute to significant morbidity, mortality, and health-care costs. As the cost of WGS continues to decline and becomes increasingly available, the ordering of rapid WGS for NICU patients with signs or symptoms of an underlying genetic condition is now feasible. However, many neonatal clinicians are not comfortable with the testing, and unfortunately, there is a dearth of geneticists to facilitate testing for every patient that needs it. Here, we will review the science behind WGS, diagnostic capabilities, limitations of testing, time to consider testing, test initiation, interpretation of results, developing a plan of care that incorporates genomic information, and returning WGS results to families.

Genetic Advancements in Infantile Epileptic Spasms Syndrome and Opportunities for Precision Medicine

Infantile epileptic spasms syndrome (IESS) is a devastating developmental epileptic encephalopathy (DEE) consisting of epileptic spasms, as well as one or both of developmental regression or stagnation and hypsarrhythmia on EEG. A myriad of aetiologies are associated with the development of IESS; broadly, 60% of cases are thought to be structural, metabolic or infectious in nature, with the remainder genetic or of unknown cause. Epilepsy genetics is a growing field, and over 28 copy number variants and 70 single gene pathogenic variants related to IESS have been discovered to date. While not exhaustive, some of the most commonly reported genetic aetiologies include trisomy 21 and pathogenic variants in genes such as TSC1, TSC2, CDKL5, ARX, KCNQ2, STXBP1 and SCN2A. Understanding the genetic mechanisms of IESS may provide the opportunity to better discern IESS pathophysiology and improve treatments for this condition. This narrative review presents an overview of our current understanding of IESS genetics, with an emphasis on animal models of IESS pathogenesis, the spectrum of genetic aetiologies of IESS (i.e., chromosomal disorders, single-gene disorders, trinucleotide repeat disorders and mitochondrial disorders), as well as available genetic testing methods and their respective diagnostic yields. Future opportunities as they relate to precision medicine and epilepsy genetics in the treatment of IESS are also explored.

Genetic Testing of Movements Disorders: A Review of Clinical Utility

Currently, pathogenic variants in more than 500 different genes are known to cause various movement disorders. The increasing accessibility and reducing cost of genetic testing has resulted in increasing clinical use of genetic testing for the diagnosis of movement disorders. However, the optimal use case(s) for genetic testing at a patient level remain ill-defined. Here, we review the utility of genetic testing in patients with movement disorders and also highlight current challenges and limitations that need to be considered when making decisions about genetic testing in clinical practice.

Highlights

The utility of genetic testing extends across multiple clinical and non-clinical domains. Here we review different aspects of the utility of genetic testing for movement disorders and the numerous associated challenges and limitations. These factors should be weighed on a case-by-case basis when requesting genetic tests in clinical practice.

Cost-Effectiveness of Whole-Genome vs Whole-Exome Sequencing Among Children With Suspected Genetic Disorders

Importance

The diagnosis of rare diseases and other genetic conditions can be daunting due to vague or poorly defined clinical features that are not recognized even by experienced clinicians. Next-generation sequencing technologies, such as whole-genome sequencing (WGS) and whole-exome sequencing (WES), have greatly enhanced the diagnosis of genetic diseases by expanding the ability to sequence a large part of the genome, rendering a cost-effectiveness comparison between them necessary.

Objective

To assess the cost-effectiveness of WGS compared with WES and conventional testing in children with suspected genetic disorders.

Design, Setting, and Participants

In this economic evaluation, a bayesian Markov model was implemented from January 1 to June 30, 2023. The model was developed using data from a cohort of 870 pediatric patients with suspected genetic disorders who were enrolled and underwent testing in the Ospedale Pediatrico Bambino Gesù, Rome, Italy, from January 1, 2015, to December 31, 2022. The robustness of the model was assessed through probabilistic sensitivity analysis and value of information analysis.

Main Outcomes and Measures

Overall costs, number of definitive diagnoses, and incremental cost-effectiveness ratios per diagnosis were measured. The cost-effectiveness analyses involved 4 comparisons: first-tier WGS with standard of care; first-tier WGS with first-tier WES; first-tier WGS with second-tier WES; and first-tier WGS with second-tier WGS.

Results

The ages of the 870 participants ranged from 0 to 18 years (539 [62%] girls). The results of the analysis suggested that adopting WGS as a first-tier strategy would be cost-effective compared with all other explored options. For all threshold levels above €29 800 (US $32 408) per diagnosis that were tested up to €50 000 (US $54 375) per diagnosis, first-line WGS vs second-line WES strategy (ie, 54.6%) had the highest probability of being cost-effective, followed by first-line vs second-line WGS (ie, 54.3%), first-line WGS vs the standard of care alternative (ie, 53.2%), and first-line WGS vs first-line WES (ie, 51.1%). Based on sensitivity analyses, these estimates remained robust to assumptions and parameter uncertainty.

Conclusions and Relevance

The findings of this economic evaluation encourage the development of policy changes at various levels (ie, macro, meso, and micro) of international health systems to ensure an efficient adoption of WGS in clinical practice and its equitable access.

Evidence from 2100 index cases supports genome sequencing as a first-tier genetic test

PURPOSE

Genome sequencing (GS) is one of the most comprehensive assays that interrogate single-nucleotide variants, copy number variants, mitochondrial variants, repeat expansions, and structural variants in a single assay. Despite the clear technical superiority, the full clinical utility of GS has yet to be determined.

METHODS

We systematically evaluated 2100 clinical GS index cases performed in our laboratory to explore the diagnostic yield of GS as first-tier and as follow-up testing.

RESULTS

The overall diagnostic yield was 28% (585/2100). The diagnostic yield for GS as the first-tier test was 26% (294/1146). Among cases with prior non-diagnostic genetic tests, GS provided a diagnosis for 27% (247/910) of cases, including 56 cases with prior exome sequencing (ES). Although re-analysis of previous ES might have resolved the diagnosis in 29 cases, diagnoses for 27 cases would have been missed because of the technical inferiority of ES. Moreover, GS further disclosed additional genetic etiology in 3 out of 44 cases with existing partial diagnosis.

CONCLUSION

We present the largest-to-date GS data set of a clinically heterogeneous cohort from a single clinical laboratory. Our data demonstrate that GS should be considered as the first-tier genetic test that has the potential to shorten the diagnostic odyssey.

Integrating RNA-Seq into genome sequencing workflow enhances the analysis of structural variants causing neurodevelopmental disorders

BACKGROUND

Molecular diagnosis of neurodevelopmental disorders (NDDs) is mainly based on exome sequencing (ES), with a diagnostic yield of 31% for isolated and 53% for syndromic NDD. As sequencing costs decrease, genome sequencing (GS) is gradually replacing ES for genome-wide molecular testing. As many variants detected by GS only are in deep intronic or non-coding regions, the interpretation of their impact may be difficult. Here, we showed that integrating RNA-Seq into the GS workflow can enhance the analysis of the molecular causes of NDD, especially structural variants (SVs), by providing valuable complementary information such as aberrant splicing, aberrant expression and monoallelic expression.

METHODS

We performed trio-GS on a cohort of 33 individuals with NDD for whom ES was inconclusive. RNA-Seq on skin fibroblasts was then performed in nine individuals for whom GS was inconclusive and optical genome mapping (OGM) was performed in two individuals with an SV of unknown significance.

RESULTS

We identified pathogenic or likely pathogenic variants in 16 individuals (48%) and six variants of uncertain significance. RNA-Seq contributed to the interpretation in three individuals, and OGM helped to characterise two SVs.

CONCLUSION

Our study confirmed that GS significantly improves the diagnostic performance of NDDs. However, most variants detectable by GS alone are structural or located in non-coding regions, which can pose challenges for interpretation. Integration of RNA-Seq data overcame this limitation by confirming the impact of variants at the transcriptional or regulatory level. This result paves the way for new routinely applicable diagnostic protocols.

International Undiagnosed Diseases Programs (UDPs): components and outcomes

Over the last 15 years, Undiagnosed Diseases Programs have emerged to address the significant number of individuals with suspected but undiagnosed rare genetic diseases, integrating research and clinical care to optimize diagnostic outcomes. This narrative review summarizes the published literature surrounding Undiagnosed Diseases Programs worldwide, including thirteen studies that evaluate outcomes and two commentary papers. Commonalities in the diagnostic and research process of Undiagnosed Diseases Programs are explored through an appraisal of available literature. This exploration allowed for an assessment of the strengths and limitations of each of the six common steps, namely enrollment, comprehensive clinical phenotyping, research diagnostics, data sharing and matchmaking, results, and follow-up. Current literature highlights the potential utility of Undiagnosed Diseases Programs in research diagnostics. Since participants have often had extensive previous genetic studies, research pipelines allow for diagnostic approaches beyond exome or whole genome sequencing, through reanalysis using research-grade bioinformatics tools and multi-omics technologies. The overall diagnostic yield is presented by study, since different selection criteria at enrollment and reporting processes make comparisons challenging and not particularly informative. Nonetheless, diagnostic yield in an undiagnosed cohort reflects the potential of an Undiagnosed Diseases Program. Further comparisons and exploration of the outcomes of Undiagnosed Diseases Programs worldwide will allow for the development and improvement of the diagnostic and research process and in turn improve the value and utility of an Undiagnosed Diseases Program.

Third-generation sequencing for genetic disease

Third-generation sequencing (TGS) has led to a brave new revolution in detecting genetic diseases over the last few years. TGS has been rapidly developed for genetic disease applications owing to its significant advantages such as long read length, rapid detection, and precise detection of complex and rare structural variants. This approach greatly improves the efficiency of disease diagnosis and complements the shortcomings of short-read sequencing. In this paper, we first briefly introduce the working mechanism of one of the most important representatives of TGS, single-molecule real-time (SMRT) sequencing by Pacific Bioscience (PacBio), followed by a review and comparison of the advantages and disadvantages of different sequencing technologies. Finally, we focused on the progress of SMRT sequencing applications in genetic disease detection. Future perspectives on the applications of TGS in other fields were also presented. With the continuous innovation of the SMRT technologies and the expansion of their fields of application, SMRT sequencing has broad clinical application prospects in genetic diseases detection, and is expected to become an important tool for the molecular diagnosis of other diseases.

The use of precision diagnostics for monogenic diabetes: a systematic review and expert opinion

BACKGROUND

Monogenic diabetes presents opportunities for precision medicine but is underdiagnosed. This review systematically assessed the evidence for (1) clinical criteria and (2) methods for genetic testing for monogenic diabetes, summarized resources for (3) considering a gene or (4) variant as causal for monogenic diabetes, provided expert recommendations for (5) reporting of results; and reviewed (6) next steps after monogenic diabetes diagnosis and (7) challenges in precision medicine field.

METHODS

Pubmed and Embase databases were searched (1990-2022) using inclusion/exclusion criteria for studies that sequenced one or more monogenic diabetes genes in at least 100 probands (Question 1), evaluated a non-obsolete genetic testing method to diagnose monogenic diabetes (Question 2). The risk of bias was assessed using the revised QUADAS-2 tool. Existing guidelines were summarized for questions 3-5, and review of studies for questions 6-7, supplemented by expert recommendations. Results were summarized in tables and informed recommendations for clinical practice.

RESULTS

There are 100, 32, 36, and 14 studies included for questions 1, 2, 6, and 7 respectively. On this basis, four recommendations for who to test and five on how to test for monogenic diabetes are provided. Existing guidelines for variant curation and gene-disease validity curation are summarized. Reporting by gene names is recommended as an alternative to the term MODY. Key steps after making a genetic diagnosis and major gaps in our current knowledge are highlighted.

CONCLUSIONS

We provide a synthesis of current evidence and expert opinion on how to use precision diagnostics to identify individuals with monogenic diabetes.

Precision medicine in rare diseases: What is next?

Molecular diagnostics is a cornerstone of modern precision medicine, broadly understood as tailoring an individual's treatment, follow-up, and care based on molecular data. In rare diseases (RDs), molecular diagnoses reveal valuable information about the cause of symptoms, disease progression, familial risk, and in certain cases, unlock access to targeted therapies. Due to decreasing DNA sequencing costs, genome sequencing (GS) is emerging as the primary method for precision diagnostics in RDs. Several ongoing European initiatives for precision medicine have chosen GS as their method of choice. Recent research supports the role for GS as first-line genetic investigation in individuals with suspected RD, due to its improved diagnostic yield compared to other methods. Moreover, GS can detect a broad range of genetic aberrations including those in noncoding regions, producing comprehensive data that can be periodically reanalyzed for years to come when further evidence emerges. Indeed, targeted drug development and repurposing of medicines can be accelerated as more individuals with RDs receive a molecular diagnosis. Multidisciplinary teams in which clinical specialists collaborate with geneticists, genomics education of professionals and the public, and dialogue with patient advocacy groups are essential elements for the integration of precision medicine into clinical practice worldwide. It is also paramount that large research projects share genetic data and leverage novel technologies to fully diagnose individuals with RDs. In conclusion, GS increases diagnostic yields and is a crucial step toward precision medicine for RDs. Its clinical implementation will enable better patient management, unlock targeted therapies, and guide the development of innovative treatments.

Comparative Benchmarking of Optical Genome Mapping and Chromosomal Microarray Reveals High Technological Concordance in CNV Identification and Additional Structural Variant Refinement

The recommended practice for individuals suspected of a genetic etiology for disorders including unexplained developmental delay/intellectual disability (DD/ID), autism spectrum disorders (ASD), and multiple congenital anomalies (MCA) involves a genetic testing workflow including chromosomal microarray (CMA), Fragile-X testing, karyotype analysis, and/or sequencing-based gene panels. Since genomic imbalances are often found to be causative, CMA is recommended as first tier testing for many indications. Optical genome mapping (OGM) is an emerging next generation cytogenomic technique that can detect not only copy number variants (CNVs), triploidy and absence of heterozygosity (AOH) like CMA, but can also define the location of duplications, and detect other structural variants (SVs), including balanced rearrangements and repeat expansions/contractions. This study compares OGM to CMA for clinically reported genomic variants, some of these samples also have structural characterization by fluorescence in situ hybridization (FISH). OGM was performed on IRB approved, de-identified specimens from 55 individuals with genomic abnormalities previously identified by CMA (61 clinically reported abnormalities). SVs identified by OGM were filtered by a control database to remove polymorphic variants and against an established gene list to prioritize clinically relevant findings before comparing with CMA and FISH results. OGM results showed 100% concordance with CMA findings for pathogenic variants and 98% concordant for all pathogenic/likely pathogenic/variants of uncertain significance (VUS), while also providing additional insight into the genomic structure of abnormalities that CMA was unable to provide. OGM demonstrates equivalent performance to CMA for CNV and AOH detection, enhanced by its ability to determine the structure of the genome. This work adds to an increasing body of evidence on the analytical validity and ability to detect clinically relevant abnormalities identified by CMA. Moreover, OGM identifies translocations, structures of duplications and complex CNVs intractable by CMA, yielding additional clinical utility.

A Systematic Review of the use of Precision Diagnostics in Monogenic Diabetes

Monogenic forms of diabetes present opportunities for precision medicine as identification of the underlying genetic cause has implications for treatment and prognosis. However, genetic testing remains inconsistent across countries and health providers, often resulting in both missed diagnosis and misclassification of diabetes type. One of the barriers to deploying genetic testing is uncertainty over whom to test as the clinical features for monogenic diabetes overlap with those for both type 1 and type 2 diabetes. In this review, we perform a systematic evaluation of the evidence for the clinical and biochemical criteria used to guide selection of individuals with diabetes for genetic testing and review the evidence for the optimal methods for variant detection in genes involved in monogenic diabetes. In parallel we revisit the current clinical guidelines for genetic testing for monogenic diabetes and provide expert opinion on the interpretation and reporting of genetic tests. We provide a series of recommendations for the field informed by our systematic review, synthesizing evidence, and expert opinion. Finally, we identify major challenges for the field and highlight areas for future research and investment to support wider implementation of precision diagnostics for monogenic diabetes.

The evolution of comprehensive genetic analysis in neurology: Implications for precision medicine

Technological advancements have facilitated the availability of reliable and thorough genetic analysis in many medical fields, including neurology. In this review, we focus on the importance of selecting the appropriate genetic test to aid in the accurate identification of disease utilizing currently employed technologies for analyzing monogenic neurological disorders. Moreover, the applicability of comprehensive analysis via NGS for various genetically heterogeneous neurological disorders is reviewed, revealing its efficiency in clarifying a frequently cloudy diagnostic picture and delivering a conclusive and solid diagnosis that is essential for the proper management of the patient. The feasibility and effectiveness of medical genetics in neurology require interdisciplinary cooperation among several medical specialties and geneticists, to select and perform the most relevant test according to each patient's medical history, using the most appropriate technological tools. The prerequisites for a comprehensive genetic analysis are discussed, highlighting the utility of appropriate gene selection, variant annotation, and classification. Moreover, genetic counseling and interdisciplinary collaboration could improve diagnostic yield further. Additionally, a sub-analysis is conducted on the 1,502,769 variation records with submitted interpretations in the Clinical Variation (ClinVar) database, with a focus on neurology-related genes, to clarify the value of suitable variant categorization. Finally, we review the current applications of genetic analysis in the diagnosis and personalized management of neurological patients and the advances in the research and scientific knowledge of hereditary neurological disorders that are evolving the utility of genetic analysis towards the individualization of the treatment strategy.

Genome-Wide Sequencing Modalities for Children with Unexplained Global Developmental Delay and Intellectual Disabilities—A Narrative Review

Unexplained global developmental delay (GDD) and intellectual disabilities (ID) together affect nearly 2% of the pediatric population. Establishing an etiologic diagnosis is crucial for disease management, prognostic evaluation, and provision of physical and psychological support for both the patient and the family. Advancements in genome sequencing have allowed rapid accumulation of gene–disorder associations and have accelerated the search for an etiologic diagnosis for unexplained GDD/ID. We reviewed recent studies that utilized genome-wide analysis technologies, and we discussed their diagnostic yield, strengths, and limitations. Overall, exome sequencing (ES) and genome sequencing (GS) outperformed chromosomal microarrays and targeted panel sequencing. GS provides coverage for both ES and chromosomal microarray regions, providing the maximal diagnostic potential, and the cost of ES and reanalysis of ES-negative results is currently still lower than that of GS alone. Therefore, singleton or trio ES is the more cost-effective option for the initial investigation of individuals with GDD/ID in clinical practice compared to a staged approach or GS alone. Based on these updated evidence, we proposed an evaluation algorithm with ES as the first-tier evaluation for unexplained GDD/ID.

Economic evaluation of next-generation sequencing techniques in diagnosis of genetic disorders: A systematic review

In recent years, massively parallel sequencing or next generation sequencing (NGS) has considerably changed both the research and diagnostic fields, and rapid developments have led to the combination of NGS techniques in clinical practice, ease of analysis, and detection of genetic mutations. This article aimed at reviewing the economic evaluation studies of the NGS techniques in the diagnosis of genetic diseases. In this systematic review, scientific databases (PubMed, EMBASE, Web of Science, Cochrane, Scopus, and CEA registry) were searched from 2005 to 2022 to identify the related literature on the economic evaluation of NGS techniques in the diagnosis of genetic diseases. Full-text reviews and data extraction were all performed by two independent researchers. The quality of all the articles included in this study was evaluated using the Checklist of Quality of Health Economic Studies (QHES). Out of 20 521 screened abstracts, 36 studies met the inclusion criteria. The mean score of the QHES checklist for the studies was 0.78 (high quality). Seventeen studies were conducted based on modeling. Cost-effectiveness analysis, cost-utility analysis, and cost-minimization analysis were done in 26 studies, 13 studies, and 1 study, respectively. Based on the available evidence and findings, exome sequencing, which is one of the NGS techniques, could have the potential to be used as a cost-effective genomic test to diagnose children with suspected genetic diseases. The results of the present study support the cost-effectiveness of exome sequencing in diagnosing suspected genetic disorders. However, the use of exome sequencing as a first- or second-line diagnostic test is still controversial. Most studies have been conducted in high-income countries, and research on the cost-effectiveness of NGS methods is recommended in low- and middle-income countries.

Genetically transitional disease: a new concept in genomic medicine

Traditional classification of genetic diseases as monogenic and polygenic has lagged far behind scientific progress. In this opinion article, we propose and define a new terminology, genetically transitional disease (GTD), referring to cases where a large-effect mutation is necessary, but not sufficient, to cause disease. This leads to a working disease nosology based on gradients of four types of genetic architecture: monogenic, polygenic, GTD, and mixed. We present four scenarios under which GTD may occur; namely, subsets of traditionally Mendelian disease, modifiable Tier 1 monogenic conditions, variable penetrance, and situations where a genetic mutational spectrum produces qualitatively divergent pathologies. The implications of the new nosology in precision medicine are discussed, in which therapeutic options may target the molecular cause or the disease phenotype.