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In oncology, there is a critical need for robust biomarkers that can be easily translated into the clinic. We introduce a novel approach using paired differential gene expression analysis for biological feature selection in machine learning models, enhancing robustness and interpretability while accounting for patient variability. This method compares primary tumor tissue with the same patient's healthy tissue, improving gene selection by eliminating individual-specific artifacts. A focus on carcinoma was selected due to its prevalence and the availability of the data; we aim to identify biomarkers involved in general carcinoma progression, including less-researched types. Our findings identified 27 pivotal genes that can distinguish between healthy and carcinoma tissue, even in unseen carcinoma types. Additionally, the panel could precisely identify the tissue-of-origin in the eight carcinoma types used in the discovery phase. Notably, in a proof of concept, the model accurately identified the primary tissue origin in metastatic samples despite limited sample availability. Functional annotation reveals these genes' involvement in cancer hallmarks, detecting subtle variations across carcinoma types. We propose paired differential gene expression analysis as a reference method for the discovering of robust biomarkers. [ABSTRACT FROM AUTHOR]

Abstract Background Though next-generation sequencing (NGS) tests like exome sequencing (ES), genome sequencing (GS), and panels derived from exome and genome data (EGBP) are effective for rare diseases, the ideal diagnostic approach is debated. Limited research has explored reanalyzing raw ES and GS data post-negative EGBP results for diagnostics. Results: We analyzed complete ES/GS raw sequencing data from Mayo Clinic's Program for Rare and Undiagnosed Diseases (PRaUD) patients to assess whether supplementary findings could augment diagnostic yield. ES data from 80 patients (59 adults) and GS data from 20 patients (10 adults), averaging 43 years in age, were analyzed. Most patients had renal (n=44) and auto-inflammatory (n=29) phenotypes. Ninety-six cases had negative findings and in four cases additional genetic variants were found, including a variant related to a recently described disease (RRAGD-related hypomagnesemia), a variant missed due to discordant inheritance pattern (COL4A3), a variant with high allelic frequency (NPHS2) in the general population, and a variant associated with an initially untargeted phenotype (HNF1A). Conclusion: ES and GS show diagnostic yields comparable to EGBP for single-system diseases. However, EGBP's limitations in detecting new disease-associated genes underscore the necessity for periodic updates.

Background: Though next-generation sequencing (NGS) tests like exome sequencing (ES), genome sequencing (GS), and panels derived from exome and genome data (EGBP) are effective for rare diseases, the ideal diagnostic approach is debated. Limited research has explored reanalyzing raw ES and GS data post-negative EGBP results for diagnostics. Results: We analyzed complete ES/GS raw sequencing data from Mayo Clinic's Program for Rare and Undiagnosed Diseases (PRaUD) patients to assess whether supplementary findings could augment diagnostic yield. ES data from 80 patients (59 adults) and GS data from 20 patients (10 adults), averaging 43 years in age, were analyzed. Most patients had renal (n=44) and auto-inflammatory (n=29) phenotypes. Ninety-six cases had negative findings and in four cases additional genetic variants were found, including a variant related to a recently described disease (RRAGD-related hypomagnesemia), a variant missed due to discordant inheritance pattern (COL4A3), a variant with high allelic frequency (NPHS2) in the general population, and a variant associated with an initially untargeted phenotype (HNF1A). Conclusion: ES and GS show diagnostic yields comparable to EGBP for single-system diseases. However, EGBP's limitations in detecting new disease-associated genes underscore the necessity for periodic updates. [ABSTRACT FROM AUTHOR]

Objective: In 2021, the Clinical Genome Resource (ClinGen) amyotrophic lateral sclerosis (ALS) spectrum disorders Gene Curation Expert Panel (GCEP) was established to evaluate the strength of evidence for genes previously reported to be associated with ALS. Through this endeavor, we will provide standardized guidance to laboratories on which genes should be included in clinical genetic testing panels for ALS. In this manuscript, we aimed to assess the heterogeneity in the current global landscape of clinical genetic testing for ALS. Methods: We reviewed the National Institutes of Health (NIH) Genetic Testing Registry (GTR) and members of the ALS GCEP to source frequently used testing panels and compare the genes included on the tests. Results: 14 clinical panels specific to ALS from 14 laboratories covered 4 to 54 genes. All panels report on ANG, SOD1, TARDBP, and VAPB; 50% included or offered the option of including C9orf72 hexanucleotide repeat expansion (HRE) analysis. Of the 91 genes included in at least one of the panels, 40 (44.0%) were included on only a single panel. We could not find a direct link to ALS in the literature for 14 (15.4%) included genes. Conclusions: The variability across the surveyed clinical genetic panels is concerning due to the possibility of reduced diagnostic yields in clinical practice and risk of a missed diagnoses for patients. Our results highlight the necessity for consensus regarding the appropriateness of gene inclusions in clinical genetic ALS tests to improve its application for patients living with ALS and their families. [ABSTRACT FROM AUTHOR]

Abstract Background At present, the hereditary hearing loss homepage, ( https://hereditaryhearingloss.org/ ), includes 258 deafness genes and more than 500 genes that have been reported to cause deafness. With few exceptions, the region-specific distributions are unclear for many of the identified variants and genes. Methods Here, we used a custom capture panel to perform targeted sequencing of 518 genes in a cohort of 879 deaf Chinese probands who lived in Yunnan. Mutation sites of the parents were performed by high-throughput sequencing and validated by Sanger sequencing. Results The ratio of male to female patients was close to 1:1 (441:438) and the age of onset was mainly under six. Most patients (93.5%) were diagnosed with moderate to severe deafness. Four hundred and twenty-eight patients had variants in a deafness gene, with a detection rate of 48.7%. Pathogenic variants were detected in 98 genes and a number of these were recurrent within the cohort. However, many of the variants were rarely observed in the cohort. In accordance with the American College of Medical Genetics and Genomics, pathogenic, likely pathogenic and variants of uncertain significance accounted for 34.3%, 19.3% and 46.4% of all detected variants, respectively. The most common genes included GJB2, SLC26A4, MYO15A, MYO7A, TMC1, CDH23, USH2A and WFS1, which contained variants in more than ten cases. The two genes with the highest mutation frequency were GJB2 and SLC26A4, which accounted for 28.5% (122/428) of positive patients. We showed that more than 60.3% of coding variants were rare and novel. Of the variants that we detected, 80.0% were in coding regions, 17.9% were in introns and 2.1% were copy number variants. Conclusion The common mutation genes and loci detected in this study were different from those detected in other regions or ethnic groups, which suggested that genetic screening or testing programs for deafness should be formulated in accordance with the genetic characteristics of the region.

Colorectal cancer is one of the most common tumors, and genetic predisposition is one of the key risk factors in the development of this malignancy. Lynch syndrome and familial adenomatous polyposis are the best-known genetic diseases associated with hereditary colorectal cancer. However, some other genetic disorders confer an increased risk of colorectal cancer, such as Li–Fraumeni syndrome (TP53 gene), MUTYH-associated polyposis (MUTYH gene), Peutz–Jeghers syndrome (STK11 gene), Cowden syndrome (PTEN gene), and juvenile polyposis syndrome (BMPR1A and SMAD4 genes). Moreover, the recent advances in molecular techniques, in particular Next-Generation Sequencing, have led to the identification of many new genes involved in the predisposition to colorectal cancers, such as RPS20, POLE, POLD1, AXIN2, NTHL1, MSH3, RNF43 and GREM1. In this review, we summarized the past and more recent findings in the field of cancer predisposition genes, with insights into the role of the encoded proteins and into the associated genetic disorders. Furthermore, we discussed the possible clinical utility of genetic testing in terms of prevention protocols and therapeutic approaches. [ABSTRACT FROM AUTHOR]

Background: At present, the hereditary hearing loss homepage, (https://hereditaryhearingloss.org/), includes 258 deafness genes and more than 500 genes that have been reported to cause deafness. With few exceptions, the region-specific distributions are unclear for many of the identified variants and genes. Methods: Here, we used a custom capture panel to perform targeted sequencing of 518 genes in a cohort of 879 deaf Chinese probands who lived in Yunnan. Mutation sites of the parents were performed by high-throughput sequencing and validated by Sanger sequencing. Results: The ratio of male to female patients was close to 1:1 (441:438) and the age of onset was mainly under six. Most patients (93.5%) were diagnosed with moderate to severe deafness. Four hundred and twenty-eight patients had variants in a deafness gene, with a detection rate of 48.7%. Pathogenic variants were detected in 98 genes and a number of these were recurrent within the cohort. However, many of the variants were rarely observed in the cohort. In accordance with the American College of Medical Genetics and Genomics, pathogenic, likely pathogenic and variants of uncertain significance accounted for 34.3%, 19.3% and 46.4% of all detected variants, respectively. The most common genes included GJB2, SLC26A4, MYO15A, MYO7A, TMC1, CDH23, USH2A and WFS1, which contained variants in more than ten cases. The two genes with the highest mutation frequency were GJB2 and SLC26A4, which accounted for 28.5% (122/428) of positive patients. We showed that more than 60.3% of coding variants were rare and novel. Of the variants that we detected, 80.0% were in coding regions, 17.9% were in introns and 2.1% were copy number variants. Conclusion: The common mutation genes and loci detected in this study were different from those detected in other regions or ethnic groups, which suggested that genetic screening or testing programs for deafness should be formulated in accordance with the genetic characteristics of the region. [ABSTRACT FROM AUTHOR]

Abstract Background Targeted Next Generation Sequencing is a common and powerful approach used in both clinical and research settings. However, at present, a large fraction of the acquired genetic information is not used since pathogenicity cannot be assessed for most variants. Further complicating this scenario is the increasingly frequent description of a poli/oligogenic pattern of inheritance showing the contribution of multiple variants in increasing disease risk. We present an approach in which the entire genetic information provided by target sequencing is transformed into binary data on which we performed statistical, machine learning, and network analyses to extract all valuable information from the entire genetic profile. To test this approach and unbiasedly explore the presence of recurrent genetic patterns, we studied a cohort of 112 patients affected either by genetic Creutzfeldt–Jakob (CJD) disease caused by two mutations in the PRNP gene (p.E200K and p.V210I) with different penetrance or by sporadic Alzheimer disease (sAD). Results Unsupervised methods can identify functionally relevant sources of variation in the data, like haplogroups and polymorphisms that do not follow Hardy–Weinberg equilibrium, such as the NOTCH3 rs11670823 (c.3837 + 21 T > A). Supervised classifiers can recognize clinical phenotypes with high accuracy based on the mutational profile of patients. In addition, we found a similar alteration of allele frequencies compared the European population in sporadic patients and in V210I-CJD, a poorly penetrant PRNP mutation, and sAD, suggesting shared oligogenic patterns in different types of dementia. Pathway enrichment and protein–protein interaction network revealed different altered pathways between the two PRNP mutations. Conclusions We propose this workflow as a possible approach to gain deeper insights into the genetic information derived from target sequencing, to identify recurrent genetic patterns and improve the understanding of complex diseases. This work could also represent a possible starting point of a predictive tool for personalized medicine and advanced diagnostic applications.

New methods and demonstrations of feasibility guide future implementation of genomic population health screening programs. This is the first report of genomic population screening in a primary care, non-research setting using existing large carrier and health risk gene sequencing panels combined into one 432-gene test that is offered to adults of any health status. This report summarizes basic demographic data and analyses patterns of pathogenic and likely pathogenic genetic findings for the first 300 individuals tested in this real-world scenario. We devised a classification system for gene results to facilitate clear message development for our Genomic Medicine Action Plan messaging tool used to summarize and activate results for patients and primary care providers. Potential genetic health risks of various magnitudes for a broad range of disorders were identified in 16% to 34% of tested individuals. The frequency depends on criteria used for the type and penetrance of risk. 86% of individuals are carriers for one or more recessive diseases. Detecting, reporting, and guiding response to diverse genetic health risks and recessive carrier states in a single primary care genomic screening test appears feasible and effective. This is an important step toward exploring an exome or genome sequence as a multi-purpose clinical screening tool. [ABSTRACT FROM AUTHOR]

The diagnosis of inherited neuromuscular disorders is challenging due to their genetic and phenotypic variability. Traditionally, neurophysiology and histopathology were primarily used in the initial diagnostic approach to these conditions. Sanger sequencing for molecular diagnosis was less frequently utilized as its application was a time-consuming and cost-intensive process. The advent and accessibility of next-generation sequencing (NGS) has revolutionized the evaluation process of genetically heterogenous neuromuscular disorders. Current NGS diagnostic testing approaches include gene panels, whole exome sequencing (WES), and whole genome sequencing (WGS). Gene panels are often the most widely used, being more accessible due to availability and affordability. In this mini-review, we describe the benefits and risks of clinical genetic testing. We also discuss the utility, benefits, challenges, and limitations of using gene panels in the evaluation of neuromuscular disorders. [ABSTRACT FROM AUTHOR]

The diagnosis of inherited neuromuscular disorders is challenging due to their genetic and phenotypic variability. Traditionally, neurophysiology and histopathology were primarily used in the initial diagnostic approach to these conditions. Sanger sequencing for molecular diagnosis was less frequently utilized as its application was a time-consuming and cost-intensive process. The advent and accessibility of next-generation sequencing (NGS) has revolutionized the evaluation process of genetically heterogenous neuromuscular disorders. Current NGS diagnostic testing approaches include gene panels, whole exome sequencing (WES), and whole genome sequencing (WGS). Gene panels are often the most widely used, being more accessible due to availability and affordability. In this mini-review, we describe the benefits and risks of clinical genetic testing. We also discuss the utility, benefits, challenges, and limitations of using gene panels in the evaluation of neuromuscular disorders.

As life span rises, dementia has become a growing public health issue. According to current estimates, almost 50 million people worldwide have dementia, and the number is expected to grow. Next generation sequencing (NGS) methods have helped significantly with identifying causative gene variants related to various cognitive disorders. Our study aimed to analyze the genetic basis of cognitive disorders using NGS clinical exome panel. The study included a total number of 15 unrelated cases diagnosed with cognitive disorders, all negative after standard targeted genetic testing was performed (available at Neurology Clinic, UCCS, Belgrade, Serbia). Preference was given to familial cases with early presentation or complex phenotype. Sequencing of a clinical exome (CE) panel for 4813 genes with known associated clinical phenotypes was performed using TruSight One sequencing panel on an Illumina MiSeq NGS platform according to the manufacturer's instructions (Illumina, San Diego, CA, USA). Variants were analyzed with Illumina Variant Studio v3 software provided by Illumina as well as a previously developed pipeline. Variants analysis and interpretation were based on phenotype gene target approach, literature and databases search, allele frequency, and pathogenicity prediction by in silico software. All causative variants were confirmed by Sanger sequencing. Whenever possible, additional family members were studied for segregation analysis. CE panel analysis revealed a likely genetic cause in four patients. We have detected two missense heterozygous pathogenic variants in the PSEN1 gene in one patient each and homozygous nonsense pathogenic variant in the OPTN gene in two more patients. Detected pathogenic variants are in line with the clinical phenotype of our patients. In the rest of the 11 cases, genetic diagnosis remains unclear. The results of our study emphasize the significance of CE panel analysis in establishing a diagnosis for patients with dementia. Furthermore, give us insight into the complexity of the genetic background of this group of disorders. [ABSTRACT FROM AUTHOR]

Understanding whether there is enough evidence to implicate a gene's role in a given disease, as well as the mechanisms by which variants in this gene might cause this disease, is essential to determine clinical relevance. The National Institutes of Health‐funded Clinical Genome Resource (ClinGen) has developed evaluation frameworks to assess both the strength of evidence supporting a relationship between a gene and disease (gene‐disease validity), and whether loss (haploinsufficiency) or gain (triplosensitivity) of individual genes or genomic regions is a mechanism for disease (dosage sensitivity). ClinGen actively applies these frameworks across multiple disease domains, and makes this information publicly available via its website (https://www.clinicalgenome.org/) for use in multiple applications, including clinical variant classification. Here, we describe how the results of these curation processes can be utilized to inform the appropriate application of pathogenicity criteria for both sequence and copy number variants, as well as to guide test development and inform genomic filtering pipelines. [ABSTRACT FROM AUTHOR]

We present cases of 3 children diagnosed with the same genetic condition, Gitelman syndrome, at different stages using various genetic methods: panel testing, targeted single gene sequencing, and exome sequencing. We discuss the advantages and disadvantages of each method and review the potential of genomic sequencing for early disease detection.

The inherited retinal dystrophies (IRDs) are a clinically and genetically complex group of disorders primarily affecting the rod and cone photoreceptors or other retinal neuronal layers, with emerging therapies heralding the need for accurate molecular diagnosis. Targeted capture and panel-based strategies examining the partial or full exome deliver molecular diagnoses in many IRD families tested. However, approximately one in three families remain unsolved and unable to obtain personalised recurrence risk or access to new clinical trials or therapy. In this study, we investigated whole genome sequencing (WGS), focused assays and functional studies to assist with unsolved IRD cases and facilitate integration of these approaches to a broad molecular diagnostic clinical service. The WGS approach identified variants not covered or underinvestigated by targeted capture panel-based clinical testing strategies in six families. This included structural variants, with notable benefit of the WGS approach in repetitive regions demonstrated by a family with a hybrid gene and hemizygous missense variant involving the opsin genes, OPN1LW and OPN1MW. There was also benefit in investigation of the repetitive GC-rich ORF15 region of RPGR. Further molecular investigations were facilitated by focused assays in these regions. Deep intronic variants were identified in IQCB1 and ABCA4, with functional RNA based studies of the IQCB1 variant revealing activation of a cryptic splice acceptor site. While targeted capture panel-based methods are successful in achieving an efficient molecular diagnosis in a proportion of cases, this study highlights the additional benefit and clinical value that may be derived from WGS, focused assays and functional genomics in the highly heterogeneous IRDs. [ABSTRACT FROM AUTHOR]

Background: Targeted Next Generation Sequencing is a common and powerful approach used in both clinical and research settings. However, at present, a large fraction of the acquired genetic information is not used since pathogenicity cannot be assessed for most variants. Further complicating this scenario is the increasingly frequent description of a poli/oligogenic pattern of inheritance showing the contribution of multiple variants in increasing disease risk. We present an approach in which the entire genetic information provided by target sequencing is transformed into binary data on which we performed statistical, machine learning, and network analyses to extract all valuable information from the entire genetic profile. To test this approach and unbiasedly explore the presence of recurrent genetic patterns, we studied a cohort of 112 patients affected either by genetic Creutzfeldt–Jakob (CJD) disease caused by two mutations in the PRNP gene (p.E200K and p.V210I) with different penetrance or by sporadic Alzheimer disease (sAD). Results: Unsupervised methods can identify functionally relevant sources of variation in the data, like haplogroups and polymorphisms that do not follow Hardy–Weinberg equilibrium, such as the NOTCH3 rs11670823 (c.3837 + 21 T > A). Supervised classifiers can recognize clinical phenotypes with high accuracy based on the mutational profile of patients. In addition, we found a similar alteration of allele frequencies compared the European population in sporadic patients and in V210I-CJD, a poorly penetrant PRNP mutation, and sAD, suggesting shared oligogenic patterns in different types of dementia. Pathway enrichment and protein–protein interaction network revealed different altered pathways between the two PRNP mutations. Conclusions: We propose this workflow as a possible approach to gain deeper insights into the genetic information derived from target sequencing, to identify recurrent genetic patterns and improve the understanding of complex diseases. This work could also represent a possible starting point of a predictive tool for personalized medicine and advanced diagnostic applications. [ABSTRACT FROM AUTHOR]

Carrier screening has historically assessed a relatively small number of autosomal recessive and X-linked conditions selected based on frequency in a specific subpopulation and association with severe morbidity or mortality. Advances in genomic technologies enable simultaneous screening of individuals for several conditions. The American College of Medical Genetics and Genomics recently published a clinical practice resource that presents a framework when offering screening for autosomal recessive and X-linked conditions during pregnancy and preconception and recommends a tier-based approach when considering the number of conditions to screen for and their frequency within the US population in general. This laboratory technical standard aims to complement the practice resource and to put forth considerations for clinical laboratories and clinicians who offer preconception/prenatal carrier screening., Competing Interests: Conflict of Interest Saurav Guha, Mahmoud Aarabi, Marina DiStefano, and Erin Wakeling are directors of molecular testing laboratories that offer carrier screening. Honey V. Reddi is a Consultant Director for Biofidelity Inc. Jeffrey S. Dungan is a member of the Advisory Board for Informed DNA and Medical Codirector at Insight Medical Genetics, which provides genetic laboratory services. All other authors declare no conflicts of interest., (Copyright © 2024 American College of Medical Genetics and Genomics. Published by Elsevier Inc. All rights reserved.)

Developmental and epileptic encephalopathies (DEEs) are a group of severe, early onset epilepsies characterized by refractory seizures, developmental delay or regression associated with ongoing epileptic activity, and generally poor prognosis. DEE is genetically and phenotypically heterogeneous, and there is a plethora of genetic testing options to investigate the rapidly growing list of epilepsy genes. However, more than 50% of patients with DEE remain without a genetic diagnosis despite state-of-the-art genetic testing. In this review, we discuss the major advances in epilepsy genomics that have surfaced in recent years. The goal of this review is to reach a larger audience and build a better understanding of pathogenesis and genetic testing options in DEE.

While mutational signatures provide a plethora of prognostic and therapeutic insights, their application in clinical-setting, targeted gene panels is extremely limited. We develop a mutational representation model (which learns and embeds specific mutation signature connections) that enables prediction of dominant signatures with only a few mutations. We predict the dominant signatures across more than 60,000 tumors with gene panels, delineating their landscape across different cancers. Dominant signature predictions in gene panels are of clinical importance. These included UV, tobacco, and apolipoprotein B mRNA editing enzyme, catalytic polypeptide (APOBEC) signatures that are associated with better survival, independently from mutational burden. Further analyses reveal gene and mutation associations with signatures, such as SBS5 with TP53 and APOBEC with FGFR3 S249C . In a clinical use case, APOBEC signature is a robust and specific predictor for resistance to epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs). Our model provides an easy-to-use way to detect signatures in clinical setting assays with many possible clinical implications for an unprecedented number of cancer patients., Competing Interests: Declaration of interests A.Y. and S.R. are inventors on a patent application encompassing the intellectual principle of MESiCA. United States Patent and Trademark Office: application serial no. 63/406,909., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

Prostate cancer (PCa) is one of the most common cancers worldwide and a leading cause of cancer-related mortality. Although the diagnosis and treatment of prostate cancer has improved substantially in recent years, new molecular biomarkers are needed to further prolong survival and improve the quality of life in these patients. This review analyzes the current evidence for prognostic and predictive molecular biomarkers that can be applied across different clinical scenarios, ranging from localized disease to metastatic castration-resistant PCa, with a particular emphasis on the biomarkers likely to become available in routine clinical practice in the near future. There is a growing need for molecular testing to identify the most indolent types of prostate cancer to help optimize treatment strategies and spare treatment in these patients when possible. Current trends in the treatment of prostate cancer underscore the unmet clinical need for biomarkers to improve decision-making in a challenging clinical setting. [ABSTRACT FROM AUTHOR]

The synchronized advent of high-throughput next-generation sequencing technology and knowledge of the human genome has rendered exponential contributions to our understanding of the pathophysiology of glomerular kidney diseases. A genetic diagnosis can now be made or confirmed in about two-thirds of the suspected inherited glomerular diseases. Next-generation sequencing is adept at identifying single nucleotide variations and small insertions or deletions that constitute majority of the disease-causing mutations. Description of the complete mutation spectrum in syndromic glomerulopathies may require the use of both sequencing and cytogenetic methods to detect large structural DNA variation in addition to single nucleotide changes. The enthusiastic application of genetic and genomic knowledge to inherited glomerular diseases has uncovered anticipated and unforeseen challenges mainly related to the biological interpretation of variants of uncertain significance and the limited benefit on clinical management for the individual patient when a diagnosis is obtained. To attain the ultimate goal of transforming clinical decision-making based on accurate genetic diagnosis using genomic information, these challenges need to be addressed. Till then, the glory of genomic medicine stands the test of time in this gilded age of genomic advancements. [ABSTRACT FROM AUTHOR]

Genetic laboratories use custom-commercial targeted next-generation sequencing (tg-NGS) assays to identify disease-causing variants. Although the high coverage achieved with these tests allows for the detection of copy number variants (CNVs), which account for an important proportion of the genetic burden in human diseases, an easy-to-use tool for automatic CNV detection is still lacking. This article presents a new CNV detection tool optimized for tg-NGS data: PattRec. PattRec was evaluated using a wide range of data, and its performance compared with those of other CNV detection tools. The software includes features for selecting optimal controls, discarding polymorphic CNVs prior to analysis, and filtering out deletions based on SNV zygosity, and automatically creates an in-house CNV database. There is no need for high level bioinformatic expertise and users can choose color-coded xlsx output that helps to prioritize potentially pathogenic CNVs. PattRec is presented as a Java based GUI, freely available online: https://github.com/irotero/PattRec. [ABSTRACT FROM AUTHOR]

Background and purpose: Next‐generation sequencing has greatly improved the diagnostic success rates for genetic neuromuscular disorders (NMDs). Nevertheless, most patients still remain undiagnosed, and there is a need to maximize the diagnostic yield. Methods: A retrospective study was conducted on 72 patients with NMDs who underwent exome sequencing (ES), partly followed by genotype‐guided diagnostic reassessment and secondary investigations. The diagnostic yields that would have been achieved by appropriately chosen narrow and comprehensive gene panels were also analysed. Results: The initial diagnostic yield of ES was 30.6% (n = 22/72 patients). In an additional 15.3% of patients (n = 11/72) ES results were of unknown clinical significance. After genotype‐guided diagnostic reassessment and complementary investigations, the yield was increased to 37.5% (n = 27/72). Compared to ES, targeted gene panels (<25 kilobases) reached a diagnostic yield of 22.2% (n = 16/72), whereas comprehensive gene panels achieved 34.7% (n = 25/72). Conclusion: Exome sequencing allows the detection of pathogenic variants missed by (narrowly) targeted gene panel approaches. Diagnostic reassessment after genetic testing further enhances the diagnostic outcomes for NMDs. [ABSTRACT FROM AUTHOR]

Background: Primary Immunodeficiencies (PIDs) are a heterogeneous group of genetic immune disorders. While some PIDs can manifest with more than one phenotype, signs, and symptoms of various PIDs overlap considerably. Recently, novel defects in immune-related genes and additional variants in previously reported genes responsible for PIDs have been successfully identified by Next Generation Sequencing (NGS), allowing the recognition of a broad spectrum of disorders.Objective: To evaluate the strength and weakness of targeted NGS sequencing using custom-made Ion Torrent and Haloplex (Agilent) panels for diagnostics and research purposes.Methods: Five different panels including known and candidate genes were used to screen 105 patients with distinct PID features divided in three main PID categories: T cell defects, Humoral defects and Other PIDs. The Ion Torrent sequencing platform was used in 73 patients. Among these, 18 selected patients without a molecular diagnosis and 32 additional patients were analyzed by Haloplex enrichment technology.Results: The complementary use of the two custom-made targeted sequencing approaches allowed the identification of causative variants in 28.6% (n = 30) of patients. Twenty-two out of 73 (34.6%) patients were diagnosed by Ion Torrent. In this group 20 were included in the SCID/CID category. Eight out of 50 (16%) patients were diagnosed by Haloplex workflow. Ion Torrent method was highly successful for those cases with well-defined phenotypes for immunological and clinical presentation. The Haloplex approach was able to diagnose 4 SCID/CID patients and 4 additional patients with complex and extended phenotypes, embracing all three PID categories in which this approach was more efficient. Both technologies showed good gene coverage.Conclusions: NGS technology represents a powerful approach in the complex field of rare disorders but its different application should be weighted. A relatively small NGS target panel can be successfully applied for a robust diagnostic suspicion, while when the spectrum of clinical phenotypes overlaps more than one PID an in-depth NGS analysis is required, including also whole exome/genome sequencing to identify the causative gene.

Tumor mutational burden (TMB), the total number of somatic coding mutations in a tumor, is emerging as a promising biomarker for immunotherapy response in cancer patients. TMB can be quantitated by a number of NGS-based sequencing technologies. Whole Exome Sequencing (WES) allows comprehensive measurement of TMB and is considered the gold standard. However, to date WES remains confined to research settings, due to high cost of the large genomic space sequenced. In the clinical setting, instead, targeted enrichment panels (gene panels) of various genomic sizes are emerging as the routine technology for TMB assessment. This stimulated the development of various methods for panel-based TMB quantification, and prompted the multiplication of studies assessing whether TMB can be confidently estimated from the smaller genomic space sampled by gene panels. In this review, we inventory the collection of available gene panels tested for this purpose, illustrating their technical specifications and describing their accuracy and clinical value in TMB assessment. Moreover, we highlight how various experimental, platform-related or methodological variables, as well as bioinformatic pipelines, influence panel-based TMB quantification. The lack of harmonization in panel-based TMB quantification, of adequate methods to convert TMB estimates across different panels and of robust predictive cutoffs, currently represents one of the main limitations to adopt TMB as a biomarker in clinical practice. This overview on the heterogeneous landscape of panel-based TMB quantification aims at providing a context to discuss common standards and illustrates the strong need of further validation and consolidation studies for the clinical interpretation of panel-based TMB values. [ABSTRACT FROM AUTHOR]

Background: Primary Immunodeficiencies (PIDs) are a heterogeneous group of genetic immune disorders. While some PIDs can manifest with more than one phenotype, signs, and symptoms of various PIDs overlap considerably. Recently, novel defects in immune-related genes and additional variants in previously reported genes responsible for PIDs have been successfully identified by Next Generation Sequencing (NGS), allowing the recognition of a broad spectrum of disorders. Objective: To evaluate the strength and weakness of targeted NGS sequencing using custom-made Ion Torrent and Haloplex (Agilent) panels for diagnostics and research purposes. Methods: Five different panels including known and candidate genes were used to screen 105 patients with distinct PID features divided in three main PID categories: T cell defects, Humoral defects and Other PIDs. The Ion Torrent sequencing platform was used in 73 patients. Among these, 18 selected patients without a molecular diagnosis and 32 additional patients were analyzed by Haloplex enrichment technology. Results: The complementary use of the two custom-made targeted sequencing approaches allowed the identification of causative variants in 28.6% (n = 30) of patients. Twenty-two out of 73 (34.6%) patients were diagnosed by Ion Torrent. In this group 20 were included in the SCID/CID category. Eight out of 50 (16%) patients were diagnosed by Haloplex workflow. Ion Torrent method was highly successful for those cases with well-defined phenotypes for immunological and clinical presentation. The Haloplex approach was able to diagnose 4 SCID/CID patients and 4 additional patients with complex and extended phenotypes, embracing all three PID categories in which this approach was more efficient. Both technologies showed good gene coverage. Conclusions: NGS technology represents a powerful approach in the complex field of rare disorders but its different application should be weighted. A relatively small NGS target panel can be successfully applied for a robust diagnostic suspicion, while when the spectrum of clinical phenotypes overlaps more than one PID an in-depth NGS analysis is required, including also whole exome/genome sequencing to identify the causative gene. [ABSTRACT FROM AUTHOR]

Background: Recent technological advances have improved the understanding and identification of the genetic basis of intellectual disability (ID) and global developmental delay (GDD). Next-generation sequencing panels of ID genes are now available for clinical testing; however, their overall yield in clinical practice has not yet been investigated.Aim: We determined the diagnostic yield of ID gene panels in a clinical setting and explored whether any clinical features are associated with an increased diagnostic yield.Methods: We performed a systematic retrospective chart review of all patients with ID/GDD who underwent an ID gene panel between April 2014 and July 2017 at our institution. Chi-square analysis assessed whether any specific clinical features were significantly associated with a positive diagnostic yield.Results: Forty-eight subjects (18 females, 30 males; median age: 7.5 years) were included. Consanguinity was present in 17%, autism in 38%, seizures in 42%, nonspecific dysmorphic features in 67%, and abnormalities on neurological examination in 56%; furthermore, 29% of the cohort was nonverbal and 4% was nonambulatory. Four different gene panels were used. The diagnostic yield was 21% (10/48) overall, and 38% with the more recent trio-based panel. Eight of 10 patients had de novo pathogenic dominant mutations, one had an inherited pathogenic autosomal dominant mutation, and one had compound heterozygous pathogenic recessive mutations. No clinical feature was significantly associated with an increased diagnostic yield.Conclusions: Our study suggests that ID gene panels have a high yield and are a valuable diagnostic tool in the evaluation of children with ID/GDD. [ABSTRACT FROM AUTHOR]

Copy number variants (CNVs) are intermediate-scale structural variants containing copy number changes involving DNA fragments of between 1 kb and 5 Mb. Although known to account for a significant proportion of the genetic burden in human disease, the role of CNVs (especially small CNVs) is often underestimated, as they are undetectable by traditional Sanger sequencing. Since the development of next-generation sequencing (NGS) technologies, several research groups have compared depth of coverage (DoC) patterns between samples, an approach that may facilitate effective CNV detection. Most CNV detection tools based on DoC comparisons are designed to work with whole-genome sequencing (WGS) or whole-exome sequencing (WES) data. However, few methods developed to date are designed for custom/commercial targeted NGS (tg-NGS) panels, the assays most commonly used for diagnostic purposes. Moreover, the development and evaluation of these tools is hindered by (i) the scarcity of thoroughly annotated data containing CNVs and (ii) a dearth of simulation tools for WES and tg-NGS that mimic the errors and biases encountered in these data. Here, we review DoC-based CNV detection methods described in the current literature, assess their performance with simulated tg-NGS data, and discuss their strengths and weaknesses when integrated into the daily laboratory workflow. Our findings suggest that the best methods for CNV detection in tg-NGS panels are DECoN, ExomeDepth, and ExomeCNV. Regardless of the method used, there is a need to make these programs more user-friendly to enable their use by diagnostic laboratory staff who lack bioinformatics training. [ABSTRACT FROM AUTHOR]

Epilepsy is a neurological disorder characterized by an increased predisposition for seizures. Although this definition suggests that it is a single disorder, epilepsy encompasses a group of disorders with diverse aetiologies and outcomes. A genetic basis for epilepsy syndromes has been postulated for several decades, with several mutations in specific genes identified that have increased our understanding of the genetic influence on epilepsies. With 70-80% of epilepsy cases identified to have a genetic cause, there are now hundreds of genes identified to be associated with epilepsy syndromes which can be analyzed using next generation sequencing (NGS) techniques such as targeted gene panels, whole exome sequencing (WES) and whole genome sequencing (WGS). For effective use of these methodologies, diagnostic laboratories and clinicians require information on the relevant workflows including analysis and sequencing depth to understand the specific clinical application and diagnostic capabilities of these gene sequencing techniques. As epilepsy is a complex disorder, the differences associated with each technique influence the ability to form a diagnosis along with an accurate detection of the genetic etiology of the disorder. In addition, for diagnostic testing, an important parameter is the cost-effectiveness and the specific diagnostic outcome of each technique. Here, we review these commonly used NGS techniques to determine their suitability for application to epilepsy genetic diagnostic testing.

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Highlights • The diagnosis of late onset Pompe disease (LOPD) is challenging. • LOPD was identified in 10 high-risk patients. • Several factors can hamper an early diagnosis of LOPD. • Comprehensive gene panels are needed for the screening of myopathy patients. Abstract Mutations in the GAA gene may cause a late onset Pompe disease presenting with proximal weakness without the characteristic muscle pathology, and therefore a test for GAA activity is the first tier analysis in all undiagnosed patients with hyperCKemia and/or limb-girdle muscular weakness. By using MotorPlex, a targeted gene panel for next generation sequencing, we analyzed GAA and other muscle disease-genes in a large cohort of undiagnosed patients with suspected inherited skeletal muscle disorders (n = 504). In this cohort, 275 patients presented with limb-girdle phenotype and/or an isolated hyperCKemia. Mutational analysis identified GAA mutations in ten patients. Further seven affected relatives were identified by segregation studies. All the patients carried the common GAA mutation c.-32-13T >G and a second, previously reported mutation. In the subcohort of 275 patients with proximal muscle weakness and/or hyperCKemia, we identified late-onset Pompe disease in 10 patients. The clinical overlap between Pompe disease and LGMDs or other skeletal muscle disorders suggests that GAA and the genes causing a metabolic myopathy should be analyzed in all the gene panels used for testing neuromuscular patients. However, enzymatic tests are essential for the interpretation and validation of genetic results. [ABSTRACT FROM AUTHOR]

Epilepsy is a neurological disorder characterized by an increased predisposition for seizures. Although this definition suggests that it is a single disorder, epilepsy encompasses a group of disorders with diverse aetiologies and outcomes. A genetic basis for epilepsy syndromes has been postulated for several decades, with several mutations in specific genes identified that have increased our understanding of the genetic influence on epilepsies. With 70-80% of epilepsy cases identified to have a genetic cause, there are now hundreds of genes identified to be associated with epilepsy syndromes which can be analyzed using next generation sequencing (NGS) techniques such as targeted gene panels, whole exome sequencing (WES) and whole genome sequencing (WGS). For effective use of thesemethodologies, diagnostic laboratories and clinicians require information on the relevant workflows including analysis and sequencing depth to understand the specific clinical application and diagnostic capabilities of these gene sequencing techniques. As epilepsy is a complex disorder, the differences associated with each technique influence the ability to form a diagnosis along with an accurate detection of the genetic etiology of the disorder. In addition, for diagnostic testing, an important parameter is the cost-effectiveness and the specific diagnostic outcome of each technique. Here, we review these commonly used NGS techniques to determine their suitability for application to epilepsy genetic diagnostic testing. [ABSTRACT FROM AUTHOR]

Primary immunodeficiencies (PIDs) are genetic disorders impairing host immunity, leading to life-threatening infections, autoimmunity, and/or malignancies. Genomic technologies have been critical for expediting the discovery of novel genetic defects underlying PIDs, expanding our knowledge of the complex clinical phenotypes associated with PIDs, and in shifting paradigms of PID pathogenesis. Once considered Mendelian, monogenic, and completely penetrant disorders, genomic studies have redefined PIDs as a heterogeneous group of diseases found in the global population that may arise through multigenic defects, non-germline transmission, and with variable penetrance. This review examines the uses of next-generation DNA sequencing (NGS) in the diagnosis of PIDs. While whole genome sequencing identifies variants throughout the genome, whole exome sequencing sequences only the protein-coding regions within a genome, and targeted gene panels sequence only a specific cohort of genes. The advantages and limitations of each sequencing approach are compared. The complexities of variant interpretation and variant validation remain the major challenge in wide-spread implementation of these technologies. Lastly, the roles of NGS in newborn screening and precision therapeutics for individuals with PID are also addressed.

Purpose of Review: This review highlights how skeletal dysplasias are diagnosed and how our understanding of some of these conditions has now translated to treatment options. Recent Findings: The use of multigene panels, using next-generation sequence technology, has improved our ability to quickly identify the genetic etiology, which can impact management. There are successes with the use of growth hormone in individuals with SHOX deficiencies, asfotase alfa in hypophosphatasia, and some promising data for c-type natriuretic peptide for those with achondroplasia. Summary: One needs to consider that a patient with short stature has a skeletal dysplasia as options for management may be available. [ABSTRACT FROM AUTHOR]

Introduction: Hearing loss (HL) is the most common birth defect in industrialized countries with far-reaching social, psychological and cognitive implications. It is an extremely heterogeneous disease, complicating molecular testing. The introduction of next-generation sequencing (NGS) has resulted in great progress in diagnostics allowing to study all known HL genes in a single assay. The diagnostic yield is currently still limited, but has the potential to increase substantially. Areas covered: In this review the utility of NGS and the problems for comprehensive molecular testing for HL are evaluated and discussed. Expert commentary: Different publications have proven the appropriateness of NGS for molecular testing of heterogeneous diseases such as HL. However, several problems still exist, such as pseudogenic background of some genes and problematic copy number variant analysis on targeted NGS data. Another main challenge for the future will be the establishment of population specific mutation-spectra to achieve accurate personalized comprehensive molecular testing for HL. [ABSTRACT FROM PUBLISHER]

Competing Interests: Conflict of Interest The authors declare no conflicts of interest.

Next-generation sequencing (NGS) is becoming increasingly used for diagnostic mutation analysis in myeloid neoplasms and may also represent a feasible technique in mastocytosis. However, detection of the KIT D816V mutation requires a highly sensitive method in most patients due to the typically low mutation levels. In this study, we established an NGS-based KIT mutation analysis and analyzed the sensitivity of D816V detection using the Ion Torrent platform. Eighty-two individual NGS analyses were included in the study. All samples were also analyzed using highly sensitive KIT D816V mutation-specific qPCR. Measurements of the background level in D816V-negative samples supported a cutoff for positivity of 0.2% in three different NGS panels. Clinical samples from patients with SM that tested positive using qPCR with a D816V allele burden >0.2% also tested positive using NGS. Samples that tested positive using qPCR with an allele burden <0.2% tested negative using NGS. We thereby demonstrate that caution should be taken when using the potentially very sensitive NGS technique for KIT D816V mutation analysis in mastocytosis, as many patients with SM have D816V mutation levels below the detection limit of NGS. A dedicated and highly sensitive KIT D816V mutation analysis therefore remains important in mastocytosis diagnostics. [ABSTRACT FROM AUTHOR]

Prostate cancer is the most common urologic neoplasm and the second leading cause of cancer-related death among men in many developed countries. Given the highly heterogeneous behaviour of the disease, there is a great need for prognostic factors, in order to stratify the clinical risk and give the best treatment options to the patient. Clinical factors, such as prostate-specific antigen value and derivatives, and pathological factors, such as stage and Gleason grading, are well kown prognostic factors. Nomograms can provide useful prediction in each clinical sceario. The field of molecular biomarkers is briskly evolving towards personalized medicine. TMPRSS2- ERG fusion, deletion of PTEN ed and gene panels are some of the more extensively explored molecular features in prostate cancer outcome prediction. In the near future, circulating tumour cells, exosomes and microRNAs could give us further, not invasive important tools. [ABSTRACT FROM AUTHOR]