Variants In Mendelian Diseases Research Articles

Regional-specific calibration enables application of computational evidence for clinical classification of 5′ cis-regulatory variants in Mendelian disease

To date, clinical genetic testing for Mendelian disease variants has focused heavily on exonic coding and intronic gene regions. This multi-step study was undertaken to provide an evidence base for selecting and applying computational approaches for use in clinical classification of 5' cis-regulatory region variants. Curated datasets of clinically reported disease-causing 5' cis-regulatory region variants and variants from matched genomic regions in population controls were used to calibrate six bioinformatic tools as predictors of variant pathogenicity. Likelihood ratio estimates were aligned to code weights following ClinGen recommendations for application of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology (ACMG/AMP) classification scheme. Considering code assignment across all reference dataset variants, performance was best for CADD (81.2%) and REMM (81.5%). Optimized thresholds provided moderate evidence toward pathogenicity (CADD, REMM) and moderate (CADD) or supporting (REMM) evidence against pathogenicity. Both sensitivity and specificity of prediction were improved when further categorizing variants based on location in an EPDnew-defined promoter region. Combining predictions (CADD, REMM, and location in a promoter region) increased specificity at the expense of sensitivity. Importantly, the optimal CADD thresholds for assigning ACMG/AMP codes PP3 (≥10) and BP4 (≤8) were vastly different from recommendations for protein-coding variants (PP3≥25.3; BP4≤22.7); CADD <22.7 would incorrectly assign BP4 for >90% of reported disease-causing cis-regulatory region variants. Our results demonstrate the need to consider a tiered approach and tailored score thresholds to optimize bioinformatic impact prediction for clinical classification of 5' cis-regulatory region variants.

Genetic prevalence and clinical relevance of canine Mendelian disease variants in over one million dogs.

Hundreds of genetic variants implicated in Mendelian disease have been characterized in dogs and commercial screening is being offered for most of them worldwide. There is typically limited information available regarding the broader population frequency of variants and uncertainty regarding their functional and clinical impact in ancestry backgrounds beyond the discovery breed. Genetic panel screening of disease-associated variants, commercially offered directly to the consumer or via a veterinary clinician, provides an opportunity to establish large-scale cohorts with phenotype data available to address open questions related to variant prevalence and relevance. We screened the largest canine cohort examined in a single study to date (1,054,293 representative dogs from our existing cohort of 3.5 million; a total of 811,628 mixed breed dogs and 242,665 purebreds from more than 150 countries) to examine the prevalence and distribution of a total of 250 genetic disease-associated variants in the general population. Electronic medical records from veterinary clinics were available for 43.5% of the genotyped dogs, enabling the clinical impact of variants to be investigated. We provide detailed frequencies for all tested variants across breeds and find that 57% of dogs carry at least one copy of a studied Mendelian disease-associated variant. Focusing on a subset of variants, we provide evidence of full penetrance for 10 variants, and plausible evidence for clinical significance of 22 variants, on diverse breed backgrounds. Specifically, we report that inherited hypocatalasia is a notable oral health condition, confirm that factor VII deficiency presents as subclinical bleeding propensity and verify two genetic causes of reduced leg length. We further assess genome-wide heterozygosity levels in over 100 breeds, and show that a reduction in genome-wide heterozygosity is associated with an increased Mendelian disease variant load. The accumulated knowledge represents a resource to guide discussions on genetic test relevance by breed.

A spectrum of recessiveness among Mendelian disease variants in UK Biobank

Recent work has found increasing evidence of mitigated, incompletely penetrant phenotypes in heterozygous carriers of recessive Mendelian disease variants. We leveraged whole-exome imputation within the full UK Biobank cohort (n ∼ 500K) to extend such analyses to 3,475 rare variants curated from ClinVar and OMIM. Testing these variants for association with 58 quantitative traits yielded 102 significant associations involving variants previously implicated in 34 different diseases. Notable examples included a POR missense variant implicated in Antley-Bixler syndrome that associated with a 1.76 (SE 0.27) cm increase in height and an ABCA3 missense variant implicated in interstitial lung disease that associated with reduced FEV1/FVC ratio. Association analyses with 1,134 disease traits yielded five additional variant-disease associations. We also observed contrasting levels of recessiveness between two more-common, classical Mendelian diseases. Carriers of cystic fibrosis variants exhibited increased risk of several mitigated disease phenotypes, whereas carriers of spinal muscular atrophy alleles showed no evidence of altered phenotypes. Incomplete penetrance of cystic fibrosis carrier phenotypes did not appear to be mediated by common allelic variation on the functional haplotype. Our results show that many disease-associated recessive variants can produce mitigated phenotypes in heterozygous carriers and motivate further work exploring penetrance mechanisms.

P135: THE CLINGEN HEMOGLOBINOPATHY VARIANT CURATION EXPERT PANEL

Background: Accurate and consistent interpretation of sequence variants is integral to the delivery of safe and reliable diagnostic genetic services. To standardize the interpretation process, in 2015, the American College of Medical Genetics and Genomics (ACMG) and the Association for Molecular Pathology (AMP) published a joint guideline based on different lines of evidence for the classification of sequence variants in Mendelian diseases. The generality of this guideline necessitates the application of expert judgment when evaluating and weighing evidence for variant interpretation. The Clinical Genome Resource (ClinGen) assembles Variant Curation Expert Panels (VCEPs) to perform gene- and disease-specific modifications of the ACMG/AMP framework. The ClinGen Hemoglobinopathy VCEP was created collaboratively between the ITHANET portal and the Global Globin Network of the Human Variome Project towards comprehensive annotation of all variants related to hemoglobinopathies. Aim: The adaptation of the ACMG/AMP variant interpretation guidelines of use in hemoglobinopathies. Methods: The Hemoglobinopathy VCEP focuses on the review and annotation of variants located in the globin gene clusters, namely α-globin locus (NG_000006), which includes genes HBA1, HBA2 and HBZ, and β-globin locus (NG_000007) which includes genes HBB, HBD, HBG1, HBG2 and HBE and the regulatory element LCRB. Using a consensus approach and guidance by the ClinGen Sequence Variant Interpretation Working Group, the Hemoglobinopathy VCEP has prepared a pre-final version of the specified ACMG/AMP criteria for hemoglobinopathies. Results: The Hemoglobinopathy VCEP developed disease-specific rules for sequence variant classification based on evidence criteria that assess variant frequency, variant types and disease causality, protein domains and mutational hotspots implicated in disease, clinical manifestations, segregation, in silico predictions and functional evidence. Conclusions: For the first time, the Hemoglobinopathy VCEP will provide a standardised classification of the pathogenicity of variants related to hemoglobinopathies. The Hemoglobinopathy VCEP specifications were approved by ClinGen in April 2021 (Step 2 approval), which initiated the process of further validation and adaptation with known globin gene variants in a pilot study (toward Step 3 approval).

Adapting the ACMG/AMP variant classification framework: A perspective from the ClinGen Hemoglobinopathy Variant Curation Expert Panel.

Accurate and consistent interpretation of sequence variants is integral to the delivery of safe and reliable diagnostic genetic services. To standardize the interpretation process, in 2015, the American College of Medical Genetics and Genomics (ACMG) and the Association for Molecular Pathology (AMP) published a joint guideline based on a set of shared standards for the classification of variants in Mendelian diseases. The generality of these standards and their subjective interpretation between laboratories has prompted efforts to reduce discordance of variant classifications, with a focus on the expert specification of the ACMG/AMP guidelines for individual genes or diseases. Herein, we describe our experience as a ClinGen Variant Curation Expert Panel to adapt the ACMG/AMP criteria for the classification of variants in three globin genes (HBB, HBA2, and HBA1) related to recessively inherited hemoglobinopathies, including five evidence categories, as use cases demonstrating the process of specification and the underlying rationale.

Improving genetic diagnosis of Mendelian disease with RNA sequencing: a narrative review

Abstract Targeted sequencing and whole exome sequencing are the most common approaches used to detect causative variants in Mendelian diseases; however, using DNA-based sequencing techniques, the current molecular diagnostic yield is at best 50%. In recent years, RNA sequencing has been shown to be able to provide a genetic diagnosis in patients whose conditions were previously unable to be identified by DNA analysis. RNA sequencing can reveal expression outliers, aberrant splicing events, allele-specific expression, and new pathogenic variants, and as such can complement and expand on the traditional genomic methods used to diagnose Mendelian diseases. Therefore, RNA sequencing is expected to become a routine method for genetic diagnosis in the future. This article reviews the applications and challenges of RNA sequencing in the genetic diagnosis of Mendelian diseases.

ORVAL: a novel platform for the prediction and exploration of disease-causing oligogenic variant combinations.

A tremendous amount of DNA sequencing data is being produced around the world with the ambition to capture in more detail the mechanisms underlying human diseases. While numerous bioinformatics tools exist that allow the discovery of causal variants in Mendelian diseases, little to no support is provided to do the same for variant combinations, an essential task for the discovery of the causes of oligogenic diseases. ORVAL (the Oligogenic Resource for Variant AnaLysis), which is presented here, provides an answer to this problem by focusing on generating networks of candidate pathogenic variant combinations in gene pairs, as opposed to isolated variants in unique genes. This online platform integrates innovative machine learning methods for combinatorial variant pathogenicity prediction with visualization techniques, offering several interactive and exploratory tools, such as pathogenic gene and protein interaction networks, a ranking of pathogenic gene pairs, as well as visual mappings of the cellular location and pathway information. ORVAL is the first web-based exploration platform dedicated to identifying networks of candidate pathogenic variant combinations with the sole ambition to help in uncovering oligogenic causes for patients that cannot rely on the classical disease analysis tools. ORVAL is available at https://orval.ibsquare.be.

NCBoost classifies pathogenic non-coding variants in Mendelian diseases through supervised learning on purifying selection signals in humans

State-of-the-art methods assessing pathogenic non-coding variants have mostly been characterized on common disease-associated polymorphisms, yet with modest accuracy and strong positional biases. In this study, we curated 737 high-confidence pathogenic non-coding variants associated with monogenic Mendelian diseases. In addition to interspecies conservation, a comprehensive set of recent and ongoing purifying selection signals in humans is explored, accounting for lineage-specific regulatory elements. Supervised learning using gradient tree boosting on such features achieves a high predictive performance and overcomes positional bias. NCBoost performs consistently across diverse learning and independent testing data sets and outperforms other existing reference methods.

ClinVar database of global familial hypercholesterolemia-associated DNA variants.

Accurate and consistent variant classification is imperative for incorporation of rapidly developing sequencing technologies into genomic medicine for improved patient care. An essential requirement for achieving standardized and reliable variant interpretation is data sharing, facilitated by a centralized open-source database. Familial hypercholesterolemia (FH) is an exemplar of the utility of such a resource: it has a high incidence, a favorable prognosis with early intervention and treatment, and cascade screening can be offered to families if a causative variant is identified. ClinVar, an NCBI-funded resource, has become the primary repository for clinically relevant variants in Mendelian disease, including FH. Here, we present the concerted efforts made by the Clinical Genome Resource, through the FH Variant Curation Expert Panel and global FH community, to increase submission of FH-associated variants into ClinVar. Variant-level data was categorized by submitter, variant characteristics, classification method, and available supporting data. To further reform interpretation of FH-associated variants, areas for improvement in variant submissions were identified; these include a need for more detailed submissions and submission of supporting variant-level data, both retrospectively and prospectively. Collaborating to provide thorough, reliable evidence-based variant interpretation will ultimately improve the care of FH patients.

Gene-based segregation method for identifying rare variants in family-based sequencing studies.

Whole-exome sequencing using family data has identified rare coding variants in Mendelian diseases or complex diseases with Mendelian subtypes, using filters based on variant novelty, functionality, and segregation with the phenotype within families. However, formal statistical approaches are limited. We propose a gene-based segregation test (GESE) that quantifies the uncertainty of the filtering approach. It is constructed using the probability of segregation events under the null hypothesis of Mendelian transmission. This test takes into account different degrees of relatedness in families, the number of functional rare variants in the gene, and their minor allele frequencies in the corresponding population. In addition, a weighted version of this test allows incorporating additional subject phenotypes to improve statistical power. We show via simulations that the GESE and weighted GESE tests maintain appropriate type I error rate, and have greater power than several commonly used region-based methods. We apply our method to whole-exome sequencing data from 49 extended pedigrees with severe, early-onset chronic obstructive pulmonary disease (COPD) in the Boston Early-Onset COPD study (BEOCOPD) and identify several promising candidate genes. Our proposed methods show great potential for identifying rare coding variants of large effect and high penetrance for family-based sequencing data. The proposed tests are implemented in an R package that is available on CRAN (https://cran.r-project.org/web/packages/GESE/).

Whole Genome Sequencing of 10,000 Rare Disease Patients Reveals Digenic Inheritance of Blood Disorders

Inherited bleeding, thrombotic and platelet disorders (BPDs) affect approximately 3M people worldwide and an appreciable portion have a disorder of megakaryopoiesis and the production and function of platelets, including the formation of granules. While genetic variants in 76 genes have been implicated in BPDs, many patients remain without a molecular diagnosis (Lentaigne et al, Simeoni et al). We hypothesised that some of these disorders may be caused by compound inheritance of variants in two different genes, a mode of inheritance thus far never implicated in BPDs.For the pilot phase of the 100 000 Genomes Project we have sequenced the whole genomes of 10,000 individuals consisting of probands with molecularly unexplained rare disorders and their close relatives, with 3,000 having inherited disorders of the blood and immune system. We searched for causal variants in known BPD-related genes and employed a new statistical method for Bayesian evaluation of rare variants in Mendelian disease (BeviMed) (Greene et al) to identify novel marginal associations between rare variants and disease status. Where the identified variants could not individually explain the phenotype in full within the pedigrees, we searched for additional variants affecting other BPD-related genes or novel genes identified using BeviMed.First, we have identified a large pedigree in which certain members with mild thrombocytopenia (lower 10th percentile of the population distribution) are affected by a single variant encoding a premature stop at residue 69 in the major isoform of the tropomyosin gene TPM4 expressed in megakaryocytes (Pleines et al). Other members of the family have distinctly more severe macrothrombocytopenia (with platelet counts as low as 24x109/l) and this is due to inheritance of a second variant in the actinin gene ACTN1 leading to a Thr340Met substitution, demonstrating a compound additive effect of variants in two genes encoding cytoskeletal proteins important for actin polymerization and thereby causing inadequate platelet formation. It is noteworthy that both of these genes have been identified in a genome wide association study of the count and mean volume of platelets (Gieger et al). Second, we used BeviMed to identify genes containing variants that are marginally associated with a syndrome defined by a platelet granule defect combined with familial autism (Bijl et al). The strongest association is due to splice variants in a granule-related gene on Chr17p13 but in all four unrelated cases at least one additional variant is required to explain the observed segregation patterns. Two of these unrelated cases harbor variants in two other marginally associated genes at Chr9q32 and Chr4q31 and a third harbors a de novo copy number variant. These additional variants likely explain why the children in three of the families are affected by this syndrome while their parents are not.In conclusion, we have used whole genome sequencing, pedigree building, detailed platelet phenotyping and new association approaches to identify the first cases of digenic inheritance of BPDs. Our results illustrate the cooperative role of different cytoskeletal proteins in platelet formation and cement the role of granule biology in the function of both platelets and neurons.

A Whole-Genome Analysis Framework for Effective Identification of Pathogenic Regulatory Variants in Mendelian Disease

The interpretation of non-coding variants still constitutes a major challenge in the application of whole-genome sequencing in Mendelian disease, especially for single-nucleotide and other small non-coding variants. Here we present Genomiser, an analysis framework that is able not only to score the relevance of variation in the non-coding genome, but also to associate regulatory variants to specific Mendelian diseases. Genomiser scores variants through either existing methods such as CADD or a bespoke machine learning method and combines these with allele frequency, regulatory sequences, chromosomal topological domains, and phenotypic relevance todiscover variants associated to specific Mendelian disorders. Overall, Genomiser is able to identify causal regulatory variants as thetop candidate in 77% of simulated whole genomes, allowing effective detection and discovery of regulatory variants in Mendelian disease.

Disease-associated variants in different categories of disease located in distinct regulatory elements.

BackgroundThe invention of high throughput sequencing technologies has led to the discoveries of hundreds of thousands of genetic variants associated with thousands of human diseases. Many of these genetic variants are located outside the protein coding regions, and as such, it is challenging to interpret the function of these genetic variants by traditional genetic approaches. Recent genome-wide functional genomics studies, such as FANTOM5 and ENCODE have uncovered a large number of regulatory elements across hundreds of different tissues or cell lines in the human genome. These findings provide an opportunity to study the interaction between regulatory elements and disease-associated genetic variants. Identifying these diseased-related regulatory elements will shed light on understanding the mechanisms of how these variants regulate gene expression and ultimately result in disease formation and progression.ResultsIn this study, we curated and categorized 27,558 Mendelian disease variants, 20,964 complex disease variants, 5,809 cancer predisposing germline variants, and 43,364 recurrent cancer somatic mutations. Compared against nine different types of regulatory regions from FANTOM5 and ENCODE projects, we found that different types of disease variants show distinctive propensity for particular regulatory elements. Mendelian disease variants and recurrent cancer somatic mutations are 22-fold and 10- fold significantly enriched in promoter regions respectively (q<0.001), compared with allele-frequency-matched genomic background. Separate from these two categories, cancer predisposing germline variants are 27-fold enriched in histone modification regions (q<0.001), 10-fold enriched in chromatin physical interaction regions (q<0.001), and 6-fold enriched in transcription promoters (q<0.001). Furthermore, Mendelian disease variants and recurrent cancer somatic mutations share very similar distribution across types of functional effects.We further found that regulatory regions are located within over 50% coding exon regions. Transcription promoters, methylation regions, and transcription insulators have the highest density of disease variants, with 472, 239, and 72 disease variants per one million base pairs, respectively.ConclusionsDisease-associated variants in different disease categories are preferentially located in particular regulatory elements. These results will be useful for an overall understanding about the differences among the pathogenic mechanisms of various disease-associated variants.

Exome Sequencing Identifies Potential Risk Variants for Mendelian Disorders at High Prevalence in Qatar

Exome sequencing of families of related individuals has been highly successful in identifying genetic polymorphisms responsible for Mendelian disorders. Here, we demonstrate the value of the reverse approach, where we use exome sequencing of a sample of unrelated individuals to analyze allele frequencies of known causal mutations for Mendelian diseases. We sequenced the exomes of 100 individuals representing the three major genetic subgroups of the Qatari population (Q1 Bedouin, Q2 Persian-South Asian, Q3 African) and identified 37 variants in 33 genes with effects on 36 clinically significant Mendelian diseases. These include variants not present in 1000 Genomes and variants at high frequency when compared with 1000 Genomes populations. Several of these Mendelian variants were only segregating in one Qatari subpopulation, where the observed subpopulation specificity trends were confirmed in an independent population of 386 Qataris. Premarital genetic screening in Qatar tests for only four out of the 37, such that this study provides a set of Mendelian disease variants with potential impact on the epidemiological profile of the population that could be incorporated into the testing program if further experimental and clinical characterization confirms high penetrance.