The complexity of identification of pathogenic variants

Introduction: Natural occurring genomic variant, from single nucleotide to balanced, unbalanced and complex rearrangements, spanning large chromosomal regions, has been reported to cause human pathologies. As such, we present cases with neurodevelopmental disorder, infertility, and recurrent miscarriage, which reflect the complexity of the identification of pathogenic variants, considering the variation spectrum, the underlying pathogenic mechanisms, and the heterogeneous clinical presentations. Methods: Long and small insert genomic sequencing (GS) was applied to four cases. Variants were identified from GS data mapped against the reference human genome and confirmed through Sanger sequencing. Results were interpreted using SVInterpreter, Exomiser, genotype-phenotype correlation and convergent genomic data analysis. Results: Although the first case is a carrier of a t(17;19)(p13.1;p13.3)mat, disrupting GSG1L2, and of a presumably paternally inherited dup(2)(q14.3q21.1), encompassing the autosomal dominant (AD) phenotype-associated PROC and HS6ST1 genes, the identified novel frameshift c.4442del, p.(Gly1481Valfs*21) variant of CHD4, was considered the disease-causing variant, since the proband’s phenotype fits the CHD4-associated Sifrim-Hitz-Weiss syndrome (Da Silva et al., 2022). Cases 2 and 3 were both reported with infertility, and carriers of t(5;9)(q31.3;p13) and t(4;21)(p14;q21.3), respectively. Our study revealed that the phenotype most plausibly resulted from a chromosomal position effect over YIPF5 and SPATC1L. The last case, presented intellectual disability and recurrent miscarriage, associated to t(7;22)(p13;q13.1). The 7p13 breakpoint disrupts the brain specific CAMK2B, causing AD mental retardation 54 (OMIM #617799), whereas increased meiotic segregation of der(22), during gametogenesis, most likely explain the reported miscarriage (David et al., 2023). Conclusions: These cases highlight the intricacy of pathogenic mechanisms leading to human disorders, the necessity for identification and evaluation of the “full” spectrum of genomic and genetic variants, of comparative reverse phenotyping, including patients with pathogenic variants affecting the same genes. Finally, highlight the need of introducing a more precise genomic medicine in clinical practice. This research was supported by FCT—Fundação para a Ciência e a Tecnologia, Research Grant HMSP-ICT/0016/2013 of the Harvard Medical School—Portugal Program.Study supported by Fundação para a Ciência e Tecnologia (HMSP-ICT/0016/2013).info:eu-repo/semantics/publishedVersio

SVInterpreter: A Comprehensive Topologically Associated Domain-Based Clinical Outcome Prediction Tool for Balanced and Unbalanced Structural Variants

With the advent of genomic sequencing, a number of balanced and unbalanced structural variants (SVs) can be detected per individual. Mainly due to incompleteness and the scattered nature of the available annotation data of the human genome, manual interpretation of the SV’s clinical significance is laborious and cumbersome. Since bioinformatic tools developed for this task are limited, a comprehensive tool to assist clinical outcome prediction of SVs is warranted. Herein, we present SVInterpreter, a free Web application, which analyzes both balanced and unbalanced SVs using topologically associated domains (TADs) as genome units. Among others, gene-associated data (as function and dosage sensitivity), phenotype similarity scores, and copy number variants (CNVs) scoring metrics are retrieved for an informed SV interpretation. For evaluation, we retrospectively applied SVInterpreter to 97 balanced (translocations and inversions) and 125 unbalanced (deletions, duplications, and insertions) previously published SVs, and 145 SVs identified from 20 clinical samples. Our results showed the ability of SVInterpreter to support the evaluation of SVs by (1) confirming more than half of the predictions of the original studies, (2) decreasing 40% of the variants of uncertain significance, and (3) indicating several potential position effect events. To our knowledge, SVInterpreter is the most comprehensive TAD-based tool to identify the possible disease-causing candidate genes and to assist prediction of the clinical outcome of SVs. SVInterpreter is available at http://dgrctools-insa.min-saude.pt/cgi-bin/SVInterpreter.py.This research was supported by national funds through FCT—Fundação para a Ciência e a Tecnologia, Research Grant HMSP-ICT/0016/2013 of the Harvard Medical School—Portugal Program in Translational Research and Informationinfo:eu-repo/semantics/publishedVersio

SVInterpreter: a web-based tool for structural variants inspection and identification of possible disease-causing candidate genes

Introduction: With the advent of genomic sequencing, the identification of structural variants (SVs) is no longer a challenge, being possible to detect an average of 5 K SVs by individual. Contrarily, the annotation of the genome is incomplete, and the data is scattered along different databases, making SV manual evaluation complicated and time-consuming. Also, the available tools are limited on their scope. Thus, to address the need of a comprehensive application to assist evaluation of clinical outcome of SVs, we developed Structural Variant Interpreter (SVInterpreter). Methods: SVInterpreter is a free Python-CGI developed Web application able to analyze SVs using Topologically Associated Domains as genome units, within which genome browsers data, medically actionable genes, virtual gene panels and HPO similarity results, among other information, is retrieved. Results: We started by re-analysing 220 published SVs, of which about 50% were previously classified as VUS. SVInterpreter corroborated the previous classification in about 84% of the SVs. In about 5% of the SVs, SVInterpreter gave indication of possible position effect, through phenotype similarity, disrupted chromatin loops or genome wide association studies. Then, we show the applicability of SVInterpreter on the clinical setting, by inspecting 15 cases analysed by chromosomal microarray or genome sequencing. Conclusions: To our knowledge, SVInterpreter is the most comprehensive TAD based tool to assist prediction of clinical outcome of SVs. Based on gathered information, identification of possible disease-causing candidate genes and SVs is easily achievable. SVInterpreter is available at http://dgrctools-insa.min-saude.pt/cgi-bin/SVInterpreter.pyinfo:eu-repo/semantics/publishedVersio

Measuring and filtering reactive inhibition is essential for assessing serial decision making and learning

Learning complex structures from stimuli requires extended exposure and often repeated observation of the same stimuli. Learning induces stimulus-dependent changes in specific performance measures. The same performance measures, however, can also be affected by processes that arise due to extended training (e.g. fatigue) but are otherwise independent from learning. Thus, a thorough assessment of the properties of learning can only be achieved by identifying and accounting for the effects of such processes. Reactive inhibition is a process that modulates behavioral performance measures on a wide range of time scales and often has opposite effects than learning. Here we develop a tool to disentangle the effects of reactive inhibition from learning in the context of an implicit learning task, the alternating serial reaction time task. Our method highlights that the magnitude of the effect of reactive inhibition on measured performance is larger than that of the acquisition of statistical structure from stimuli. We show that the effect of reactive inhibition can be identified not only in population measures but also at the level of performance of individuals, revealing varying degrees of contribution of reactive inhibition. Finally, we demonstrate that a higher proportion of behavioral variance can be explained by learning once the effects of reactive inhibition are eliminated. These results demonstrate that reactive inhibition has a fundamental effect on the behavioral performance that can be identified in individual participants and can be separated from other cognitive processes like learning

Chromosome structural variants: Epidemiology, identification and contribution to human diseases

Editorial on the Research Topic: Chromosome structural variants: Epidemiology, identification and contribution to human diseases.Human chromosome structural variants (SVs) are balanced/unbalanced genomic abnormalities that include translocation, inversion, insertion, and deletion/duplication (also known as copy-number variants, CNVs) events with a size of >50 bp. Currently, the capability of genome sequencing in the research and clinical fields has increased our capacity to detect cryptic SVs and further delineate the complexity of karyotypically/microarray detectable SVs. This has increased our knowledge of pathogenicity mechanisms by considering dysregulation of gene expression through position effects and complex interactions between gene dosage and mutational burden. However, much of the contribution of SVs to human disease is left to explore, as the incidence of SVs is still underestimated owing to limitations of current sequencing technologies and analytical pipelines, and few studies have comprehensively integrated SV information with single nucleotide variants in congenital diseases. Rigorous investigation of SV pathogenicity is warranted for clinical applications. The Research Topic in this issue is divided into three main sections: three articles demonstrate methodologies in SV identification and pathogenicity annotation; five papers discuss the spectrum of SVs in individuals with different indications; and two reports characterize sequence complexity of SVs [...].CCM acknowledges NIH P01 GM061354 and support by the NIHR Manchester Biomedical Research Centreinfo:eu-repo/semantics/publishedVersio

A Novel Frameshift CHD4 Variant Leading to Sifrim-Hitz-Weiss Syndrome in a Proband with a Subclinical Familial t(17;19) and a Large dup(2)(q14.3q21.1)

This article belongs to the Section Molecular Genetics and Genetic Diseases.The genetic complexity of neurodevelopmental disorders (NDD), combined with a heterogeneous clinical presentation, makes accurate assessment of their molecular bases and pathogenic mechanisms challenging. Our purpose is to reveal the pathogenic variant underlying a complex NDD through identification of the "full" spectrum of structural genomic and genetic variants. Therefore, clinical phenotyping and identification of variants by genome and exome sequencing, together with comprehensive assessment of these and affected candidate genes, were carried out. A maternally-inherited familial translocation [t(17;19)(p13.1;p13.3)mat] disrupting the GSG1 like 2 gene (GSG1L2), a 3.2 Mb dup(2)(q14.3q21.1) encompassing the autosomal dominant OMIM phenotype-associated PROC and HS6ST1 gene, and a novel frameshift c.4442del, p.(Gly1481Valfs*21) variant within exon 30 of the Chromodomain helicase DNA binding protein 4 (CHD4) have been identified. Considering the pathogenic potential of each variant and the proband's phenotype, we conclude that this case basically fits the Sifrim-Hitz-Weiss syndrome or CHD4-associated neurodevelopmental phenotype. Finally, our data highlight the need for identification of the "full" spectrum of structural genomic and genetic variants and of reverse comparative phenotyping, including unrelated patients with variants in same genes, for improved genomic healthcare of patients with NDD.If this article is accepted for publication, Open Access publication will be funded by UMIB—Unidade Multidisciplinar de Investigação Biomédica, ICBAS—Instituto de Ciências Biomédicas Abel Salazar, Universidade do Porto, Porto, Portugal/ITR—Laboratory for Integrative and Trans lational Research in Population Health, Porto, Portugal (https://umib.icbas.up.pt/, accessed on 14 December 2022), both supported by FCT—Fundação para a Ciência e a Tecnologia in the frameworks of UIDP/00215/2020; LA/P/0064/2020. This research was supported by national funds through FCT—Fundação para a Ciência e a Tecnologia, Research Grant HMSP-ICT/0016/2013 of the Harvard Medical School—Portugal Program in Translational Research and Information.info:eu-repo/semantics/publishedVersio

Identification of OAF and PVRL1 as candidate genes for an ocular anomaly characterized by Peters anomaly type 2 and ectopia lentis

Keratolenticular dysgenesis (KLD) and ectopia lends are congenital eye defects. The aim of this study is the identification of molecular genetic alterations responsible for those ocular anomalies with neurologic impairment in an individual with a de novo balanced chromosome translocation t(11;18)(q23.3;q11.2)dn. Disruption of OAF, the human orthologue of the Drosophila oaf, by the 11q23.3 breakpoint results in reduced expression of this transcriptional regulator. Furthermore, four most likely nonfunctional chimeric transcripts comprising up to OAF exon 3, derived from the der(11) allele, have also been identified. This locus has been implicated by publicly available genome-wide association data in corneal disease and corneal topography. The expression of the poliovirus receptor-related 1(PVRL1) or nectin cell adhesion molecule 1 (NECTIN1), a paralogue of nectin cell adhesion molecule 3 (PVRL3) associated with congenital ocular defects, situated 500 kb upstream from 11q23.3 breakpoint, is increased. The 18q11.2 breakpoint is localized between cutaneous T-cell lymphoma-associated antigen 1(CTAGE1) and retinoblastoma binding protein 8 (RBBP8) genes. Genomic imbalance that could contribute to the observed phenotype was excluded. Analysis of gene expression datasets throughout normal murine ocular lens embryogenesis suggests that OAF expression is significantly enriched in the lens from early stages of development through adulthood, whereas PVRL1 is lens-enriched until E12.5 and then down-regulated. This contrasts with the observation that the proposita's lymphoblastoid cell lines exhibit low OAF and high PVRL1 expression as compared to control, which offers further support that the alterations described above are most likely responsible for the clinical phenotype. Finally, gene interaction topology data for PVRL1 also agree with our proposal that disruption of OAF by the translocation breakpoint and misregulation of PVRL1 due to a position effect contribute to the observed ocular and neurological phenotype.Peer reviewe

Tracking the contribution of inductive bias to individualised internal models

Internal models capture the regularities of the environment and are central to understanding how humans adapt to environmental statistics. In general, the correct internal model is unknown to observers, instead they rely on an approximate model that is continually adapted throughout learning. However, experimenters assume an ideal observer model, which captures stimulus structure but ignores the diverging hypotheses that humans form during learning. We combine non-parametric Bayesian methods and probabilistic programming to infer rich and dynamic individualised internal models from response times. We demonstrate that the approach is capable of characterizing the discrepancy between the internal model maintained by individuals and the ideal observer model and to track the evolution of the contribution of the ideal observer model to the internal model throughout training. In particular, in an implicit visuomotor sequence learning task the identified discrepancy revealed an inductive bias that was consistent across individuals but varied in strength and persistence

Deterministic Evolutionary Trajectories Influence Primary Tumor Growth: TRACERx Renal.

The evolutionary features of clear-cell renal cell carcinoma (ccRCC) have not been systematically studied to date. We analyzed 1,206 primary tumor regions from 101 patients recruited into the multi-center prospective study, TRACERx Renal. We observe up to 30 driver events per tumor and show that subclonal diversification is associated with known prognostic parameters. By resolving the patterns of driver event ordering, co-occurrence, and mutual exclusivity at clone level, we show the deterministic nature of clonal evolution. ccRCC can be grouped into seven evolutionary subtypes, ranging from tumors characterized by early fixation of multiple mutational and copy number drivers and rapid metastases to highly branched tumors with >10 subclonal drivers and extensive parallel evolution associated with attenuated progression. We identify genetic diversity and chromosomal complexity as determinants of patient outcome. Our insights reconcile the variable clinical behavior of ccRCC and suggest evolutionary potential as a biomarker for both intervention and surveillance