Exome/Genome Sequencing in Undiagnosed Syndromes

Sullivan, Jennifer; Schoch, Kelly; Spillmann, Rebecca C.; Shashi, Vandana

doi:10.1146/annurev-med-042921-110721

Cited by 21 publications

(3 citation statements)

References 95 publications

(130 reference statements)

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“…Second, our study is based on exome sequencing, which mainly captures variants in the protein-coding regions, but only has modest success in detecting structural variants, noncoding variants, intron variants, and tandem repeats. 30 Genome sequencing and long-read sequencing can better identify all the above scenarios and may provide additional genetic diagnosis. 31 Third, the depths of exome sequencing may not be enough to identify somatic variants affecting a small percentage of cells, which is of particular importance for adult patients.…”

Section: Discussionmentioning

confidence: 99%

Pathogenic Gene Spectrum and Clinical Implication in Chinese Patients with Lupus Nephritis

Zhang

Han

Jin

et al. 2023

CJASN

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Background Lupus nephritis is a rare immunological disorder. Genetic factors are considered important in its causation. We aim to systematically investigate the rare pathogenic gene variants in patients with lupus nephritis. Methods Whole-exome sequencing was used to screen pathogenic gene variants in 1886 probands with lupus nephritis. Variants were interpreted on the basis of known pathogenic variants or the American College of Medical Genetics and Genomics guidelines and studied by functional analysis, including RNA sequencing, quantitative PCR, cytometric bead array, and Western blotting. Results Mendelian form of lupus nephritis was confirmed in 71 probands, involving 63 variants in 39 pathogenic genes. The detection yield was 4%. The pathogenic genes enriched in nuclear factor kappa-B (NF-κB), type I interferon, phosphatidylinositol-3-kinase/serine/threonine kinase Akt (PI3K/AKT), Ras GTPase/mitogen-activated protein kinase (RAS/MAPK), and Janus kinase/signal transducer and activator of transcription (JAK/STAT) pathways. Clinical manifestation patterns were diverse among different signaling pathways. More than 50% of the pathogenic gene variants were reported to be associated with lupus or lupus nephritis for the first time. The identified pathogenic gene variants of lupus nephritis overlapped with those of autoinflammatory and immunodeficiency diseases. Inflammatory signatures, such as cytokine levels of IL-6, IL-8, IL-1β, IFNα, IFNγ, and IP10 in serum and transcriptional levels of interferon-stimulated genes in blood, were significantly higher in patients with pathogenic gene variants compared with controls. The overall survival rate of patients with pathogenic gene variants was lower than those without pathogenic gene variants. Conclusions A small fraction of patients with lupus nephritis had identifiable pathogenic gene variants, primarily in NF-κB, type I interferon, PI3K/AKT, JAK/STAT, RAS/MAPK, and complement pathways.

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Section: Discussionmentioning

confidence: 99%

Pathogenic Gene Spectrum and Clinical Implication in Chinese Patients with Lupus Nephritis

Zhang

Han

Jin

et al. 2023

CJASN

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“…If a key determinant of penetrance was not present among the observations, then a conditionally pathogenic variant can be labeled a Variant of Unknown Significance or even Benign . This creates many issues but it seems particularly troublesome in the clinic when sequencing patients to identify the cause of rare syndromes 38 . Imagine trying to annotate the phenylalanine hydroxylase gene variants that cause phenylketonuria 39 in a population with almost no access to foods that contain phenylalanine.…”

Section: Downplaying This Heterogeneity Impairs Clinical Communicatio...mentioning

confidence: 99%

Characterizing the pathogenicity of genetic variants: the consequences of context

Ciesielski,

Sirugo,

Iyengar

et al. 2024

npj Genom. Med.

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Beyond initial discovery of a pathogenic variant, establishing that a variant is recurrently associated with disease is important for understanding clinical impact and disease etiology. Disappointingly, our ability to characterize pathogenicity under varied circumstances is limited. Here we discuss the role of genetic and environmental background and how it affects variant penetrance and outcomes. Specifically, genetic and environmental settings determine penetrance, and we should expect lower penetrance where contexts are diverse. For example, when over 5000 ClinVar pathogenic and loss-of-function variants were assessed in two large biobanks, UK Biobank and BioMe, the mean penetrance was only 7%. This indicates that the participants in the family-based, clinical, and case-control studies that identified these variants were more homogenous and enriched for etiologic co-factors, and the winner’s curse was at play. We also emphasize that the outcome of interest can vary across conditions. The variant that causes hemoglobin S can increase the risk of death from sickling, lower the risk of death from malaria, or increase the risk of kidney disease, depending on the presence of other variants, the endemicity of malaria, and a suite of other factors. Overall, annotation on a single continuum from benign to pathogenic attempts to shoehorn a complex phenomenon into an overly simplistic framework. Variant effects often vary by context, and thus it is critical to assess potential pathogenicity in different settings. There is no panacea or easy fix, but we offer two recommendations for consideration. First, we need to routinely evaluate contexts such as sex and genetic ancestry by conducting stratified analyses and developing methods that can detect heterogenous effects (e.g. female-to-male allele proportion ratios). Second, we need to consistently document what we know about effect modifiers in our annotation databases. These are not the only possible approaches, but they begin to provide means to create robust annotations of pathogenicity.

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“…Recognizing these limitations, the American College of Medical Genetics and Genomics (ACMG) and the Association for Molecular Pathology (AMP) have established comprehensive guidelines, including the PP3 criterion, which calls for the agreement of multiple computational evidence to support the pathogenicity of a variant (11). These guidelines have substantially improved the consistency and accuracy of genetic diagnoses but still face challenges, particularly with rare genetic disorders where less information is available (5,12). Another significant challenge in genetic diagnostics is dealing with Variants of Uncertain Significance (VUS), whose health impacts are poorly understood.…”

Section: Introductionmentioning

confidence: 99%

A New Era in Missense Variant Analysis: Statistical Insights and the Introduction of VAMPP-Score for Pathogenicity Assessment

Aydin,

Ergun,

Akgun-Dogan

et al. 2024

Preprint

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The clinical interpretation of missense variants is critically important in diagnostics due to their potential to cause mild-to-severe effects on phenotype by altering protein structure. Evaluating these variants is essential because they can significantly impact disease outcomes and patient management. Many computational predictors, known as in silico pathogenicity predictors (ISPPs), have been developed to support the assessment of variant pathogenicity. Despite the abundance of these ISPPs, their predictions often lack accuracy and consistency, primarily due to limited data availability and the presence of erroneous data. This inconsistency can lead to false positive or negative results in pathogenicity evaluation, highlighting the need for standardization. The necessity for reliable evaluation methods has driven the development of numerous ISPPs, each attempting to address different aspects of variant interpretation. However, the sheer number of ISPPs and their varied performances make it challenging to achieve consensus in predictions. Therefore, a comprehensive statistical approach to evaluate and integrate these predictors is essential to improve accuracy. Here, we present a comprehensive statistical analysis comparing 52 available ISPPs, which aims to enhance the precision of variant classification. Our work introduces the Variant Analysis with Multiple Pathogenicity Predictors-score (VAMPP-score), a novel statistical framework designed for the assessment of missense variants. The VAMPP-score leverages the best gene-ISPP matches based on ISPP accuracies, providing a combinatorial weighted score that improves missense variant interpretation. We chose to develop a statistical framework rather than creating a new ISPP to capitalize on the strengths of existing predictors and to address their limitations through an integrative approach. This approach not only improves the evaluation of missense variants but also offers a flexible statistical framework designed to identify and utilize the best-performing ISPPs. By enhancing the accuracy of genetic diagnostics, particularly in the reanalysis of rare and undiagnosed cases, our framework aims to improve patient outcomes and advance the field of genetic research.Our study employed a comprehensive workflow (Figure 1) to enhance the accuracy of genomic variant interpretation with in-silico pathogenicity predictor (ISPP) evaluation. This workflow led to three pivotal results:●ISPPs were categorized on their prediction approaches. This classification not only streamlined the analytical process but also enhanced the interpretability of predictor outputs.●Leveraging this categorization, we conducted a robust statistical analysis to evaluate the prediction accuracy and performance of each ISPP. Our findings revealed a significant correlation between the prediction approaches of the ISPPs and their predictive successes, confirming the utility of our categorization approach.●These insights enabled us to develop a novel scoring system—the VAMPP-score—which integrates ISPPs according to their performances.

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Exome/Genome Sequencing in Undiagnosed Syndromes

Cited by 21 publications

References 95 publications

Pathogenic Gene Spectrum and Clinical Implication in Chinese Patients with Lupus Nephritis

Pathogenic Gene Spectrum and Clinical Implication in Chinese Patients with Lupus Nephritis

Characterizing the pathogenicity of genetic variants: the consequences of context

A New Era in Missense Variant Analysis: Statistical Insights and the Introduction of VAMPP-Score for Pathogenicity Assessment

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