Prioritization of Variants Detected by Next Generation Sequencing According to the Mutation Tolerance and Mutational Architecture of the Corresponding Genes

Implementing Whole Genome Sequencing (WGS) in Clinical Practice: Advantages, Challenges, and Future Perspectives

The integration of whole genome sequencing (WGS) into all aspects of modern medicine represents the next step in the evolution of healthcare. Using this technology, scientists and physicians can observe the entire human genome comprehensively, generating a plethora of new sequencing data. Modern computational analysis entails advanced algorithms for variant detection, as well as complex models for classification. Data science and machine learning play a crucial role in the processing and interpretation of results, using enormous databases and statistics to discover new and support current genotype-phenotype correlations. In clinical practice, this technology has greatly enabled the development of personalized medicine, approaching each patient individually and in accordance with their genetic and biochemical profile. The most propulsive areas include rare disease genomics, oncogenomics, pharmacogenomics, neonatal screening, and infectious disease genomics. Another crucial application of WGS lies in the field of multi-omics, working towards the complete integration of human biomolecular data. Further technological development of sequencing technologies has led to the birth of third and fourth-generation sequencing, which include long-read sequencing, single-cell genomics, and nanopore sequencing. These technologies, alongside their continued implementation into medical research and practice, show great promise for the future of the field of medicine.

Whole-Genome Profile of Greek Patients with Teratozοοspermia: Identification of Candidate Variants and Genes

Male infertility is a global health problem that affects a large number of couples worldwide. It can be categorized into specific subtypes, including teratozoospermia. The present study aimed to identify new variants associated with teratozoospermia in the Greek population and to explore the role of genes on which these were identified. For this reason, whole-genome sequencing (WGS) was performed on normozoospermic and teratozoospermic individuals, and after selecting only variants found in teratozoospermic men, these were further prioritized using a wide range of tools, functional and predictive algorithms, etc. An average of 600,000 variants were identified, and of them, 61 were characterized as high impact and 153 as moderate impact. Many of these are mapped in genes previously associated with male infertility, yet others are related for the first time to teratozoospermia. Furthermore, pathway enrichment analysis and Gene ontology (GO) analyses revealed the important role of the extracellular matrix in teratozoospermia. Therefore, the present study confirms the contribution of genes studied in the past to male infertility and sheds light on new molecular mechanisms by providing a list of variants and candidate genes associated with teratozoospermia in the Greek population.

Validation of New Gene Variant Classification Methods: a Field-Test in Diagnostic Cardiogenetics

Background: In the molecular genetic diagnostics of Mendelian disorders, solutions are needed for the major challenge of dealing with the large number of variants of uncertain significance (VUSs) identified using next-generation sequencing (NGS). Recently, promising approaches using constraint metrics to calculate case excess scores (CE), etiological fractions (EF), and gnomAD-derived constraint scores have been reported that estimate the likelihood of rare variants in specific genes or regions that are pathogenic. Our objective is to study the usability of these constraint data into variant interpretation in a diagnostic setting, using our cardiomyopathy cohort.

Methods and Results: Patients (N = 2002) referred for clinical genetic diagnostics underwent NGS testing of 55–61 genes associated with cardiomyopathies. Previously classified likely pathogenic (LP) and pathogenic (P) variants were used to validate the use of data from CE, EF, and gnomAD constraint analyses for (re)classification of associated variant types in specific cardiomyopathy subtype-related genes. The classifications corroborated in 94% (354/378) of cases. Next, we reclassified 23 unique VUSs to LP, increasing the diagnostic yield by 1.2%. In addition, 106 unique VUSs (5.3% of patients) were prioritized for co-segregation or functional analyses.

Conclusions: Our analysis confirms that the use of constraint metrics data can improve variant interpretation, and we, therefore, recommend using constraint scores on other cohorts and disorders and its inclusion in variant interpretation protocols.

Whole exome sequencing in Alopecia Areata identifies rare variants in KRT82

Alopecia areata is a complex genetic disease that results in hair loss due to the autoimmune-mediated attack of the hair follicle. We previously defined a role for both rare and common variants in our earlier GWAS and linkage studies. Here, we identify rare variants contributing to Alopecia Areata using a whole exome sequencing and gene-level burden analyses approach on 849 Alopecia Areata patients compared to 15,640 controls. KRT82 is identified as an Alopecia Areata risk gene with rare damaging variants in 51 heterozygous Alopecia Areata individuals (6.01%), achieving genome-wide significance (p = 2.18E−07). KRT82 encodes a hair-specific type II keratin that is exclusively expressed in the hair shaft cuticle during anagen phase, and its expression is decreased in Alopecia Areata patient skin and hair follicles. Finally, we find that cases with an identified damaging KRT82 variant and reduced KRT82 expression have elevated perifollicular CD8 infiltrates. In this work, we utilize whole exome sequencing to successfully identify a significant Alopecia Areata disease-relevant gene, KRT82, and reveal a proposed mechanism for rare variant predisposition leading to disrupted hair shaft integrity.

Common variants have been discovered to be associated with Alopecia Areata; however, rare variants have been less well studied. Here, the authors use whole-exome sequencing to identify associated rare variants in the hair keratin gene KRT82. Further, they find that individuals with Alopecia Areata have reduced expression of KRT82 in the skin and hair follicle.

Intellectual disability genomics: current state, pitfalls and future challenges

Intellectual disability (ID) can be caused by non-genetic and genetic factors, the latter being responsible for more than 1700 ID-related disorders. The broad ID phenotypic and genetic heterogeneity, as well as the difficulty in the establishment of the inheritance pattern, often result in a delay in the diagnosis. It has become apparent that massive parallel sequencing can overcome these difficulties. In this review we address: (i) ID genetic aetiology, (ii) clinical/medical settings testing, (iii) massive parallel sequencing, (iv) variant filtering and prioritization, (v) variant classification guidelines and functional studies, and (vi) ID diagnostic yield. Furthermore, the need for a constant update of the methodologies and functional tests, is essential. Thus, international collaborations, to gather expertise, data and resources through multidisciplinary contributions, are fundamental to keep track of the fast progress in ID gene discovery.

Genome sequencing data analysis for rare disease gene discovery

Rare diseases occur in a smaller proportion of the general population, which is variedly defined as less than 200 000 individuals (US) or in less than 1 in 2000 individuals (Europe). Although rare, they collectively make up to approximately 7000 different disorders, with majority having a genetic origin, and affect roughly 300 million people globally. Most of the patients and their families undergo a long and frustrating diagnostic odyssey. However, advances in the field of genomics have started to facilitate the process of diagnosis, though it is hindered by the difficulty in genome data analysis and interpretation. A major impediment in diagnosis is in the understanding of the diverse approaches, tools and datasets available for variant prioritization, the most important step in the analysis of millions of variants to select a few potential variants. Here we present a review of the latest methodological developments and spectrum of tools available for rare disease genetic variant discovery and recommend appropriate data interpretation methods for variant prioritization. We have categorized the resources based on various steps of the variant interpretation workflow, starting from data processing, variant calling, annotation, filtration and finally prioritization, with a special emphasis on the last two steps. The methods discussed here pertain to elucidating the genetic basis of disease in individual patient cases via trio- or family-based analysis of the genome data. We advocate the use of a combination of tools and datasets and to follow multiple iterative approaches to elucidate the potential causative variant.

FREQMAX provides an alternative approach for determining high-resolution allele frequency thresholds in carrier screening

As whole-genome data become available for increasing numbers of individuals across diverse populations, the list of genomic variants of unknown significance (VOUS) continues to grow. One powerful tool in VOUS interpretation is determining whether an allele is too common to be considered pathogenic. As genetic and epidemiological parameters vary across disease models, so too does the pathogenic allele frequency threshold for each disease gene. One threshold-setting approach is the maximum credible allele frequency (MCAF) method. However, estimating some of the input values MCAF requires, especially those involving heterogeneity, can present nontrivial statistical challenges. Here, we introduce FREQMAX, our alternative approach for determining allele frequency thresholds in carrier screening. FREQMAX makes efficient use of the data available for well-studied traits and exhibits flexibility for traits where information may be less complete. For cystic fibrosis, more alleles are excluded as benign by FREQMAX than by MCAF. For less-comprehensively characterized traits like ciliary dyskinesia and Smith-Lemli-Opitz syndrome, FREQMAX is able to set the allele frequency threshold without requiring a priori estimates of maximum genetic and allelic contributions. Furthermore, though we describe FREQMAX in the context of carrier screening, its classical population genetics framework also provides context for adaptation to other trait models.

Bi-allelic Mutations in NADSYN1 Cause Multiple Organ Defects and Expand the Genotypic Spectrum of Congenital NAD Deficiency Disorders

Birth defects occur in up to 3% of all live births and are the leading cause of infant death. Here we present five individuals from four unrelated families, individuals who share similar phenotypes with disease-causal bi-allelic variants in NADSYN1, encoding NAD synthetase 1, the final enzyme of the nicotinamide adenine dinucleotide (NAD) de novo synthesis pathway. Defects range from the isolated absence of both kidneys to multiple malformations of the vertebrae, heart, limbs, and kidney, and no affected individual survived for more than three months postnatally. NAD is an essential coenzyme for numerous cellular processes. Bi-allelic loss-of-function mutations in genes required for the de novo synthesis of NAD were previously identified in individuals with multiple congenital abnormalities affecting the heart, kidney, vertebrae, and limbs. Functional assessments of NADSYN1 missense variants, through a combination of yeast complementation and enzymatic assays, show impaired enzymatic activity and severely reduced NAD levels. Thus, NADSYN1 represents an additional gene required for NAD synthesis during embryogenesis, and NADSYN1 has bi-allelic missense variants that cause NAD deficiency-dependent malformations. Our findings expand the genotypic spectrum of congenital NAD deficiency disorders and further implicate mutation of additional genes involved in de novo NAD synthesis as potential causes of complex birth defects.

Rare Variants in 48 Genes Account for 42% of Cases of Epilepsy With or Without Neurodevelopmental Delay in 246 Pediatric Patients

In order to characterize the genetic architecture of epilepsy in a pediatric population from the Iberian Peninsula (including the Canary Islands), we conducted targeted exome sequencing of 246 patients with infantile-onset seizures with or without neurodevelopmental delay. We detected 107 variants in 48 different genes, which were implicated in neuronal excitability, neurodevelopment, synaptic transmission, and metabolic pathways. In 104 cases (42%) we detected variant(s) that we classified as pathogenic or likely pathogenic. Of the 48 mutated genes, 32 were dominant, 8 recessive and 8 X-linked. Of the patients for whom family studies could be performed and in whom pathogenic variants were identified in dominant or X-linked genes, 82% carried de novo mutations. The involvement of small copy number variations (CNVs) is 9%. The use of progressively updated custom panels with high mean vertical coverage enabled establishment of a definitive diagnosis in a large proportion of cases (42%) and detection of CNVs (even duplications) with high fidelity. In 10.5% of patients we detected associations that are pending confirmation via functional and/or familial studies. Our findings had important consequences for the clinical management of the probands, since a large proportion of the cohort had been clinically misdiagnosed, and their families were subsequently able to avail of genetic counseling. In some cases, a more appropriate treatment was selected for the patient in question, or an inappropriate treatment discontinued. Our findings suggest the existence of modifier genes that may explain the incomplete penetrance of some epilepsy-related genes. We discuss possible reasons for non-diagnosis and future research directions. Further studies will be required to uncover the roles of structural variants, epimutations, and oligogenic inheritance in epilepsy, thereby providing a more complete molecular picture of this disease. In summary, given the broad phenotypic spectrum of most epilepsy-related genes, efficient genomic tools like the targeted exome sequencing panel described here are essential for early diagnosis and treatment, and should be implemented as first-tier diagnostic tools for children with epilepsy without a clear etiologic basis.