Feasibility of predicting allele specific expression from DNA sequencing using machine learning

Allele specific expression (ASE) concerns divergent expression quantity of alternative alleles and is measured by RNA sequencing. Multiple studies show that ASE plays a role in hereditary diseases by modulating penetrance or phenotype severity. However, genome diagnostics is based on DNA sequencing and therefore neglects gene expression regulation such as ASE. To take advantage of ASE in absence of RNA sequencing, it must be predicted using only DNA variation. We have constructed ASE models from BIOS (n = 3432) and GTEx (n = 369) that predict ASE using DNA features. These models are highly reproducible and comprise many different feature types, highlighting the complex regulation that underlies ASE. We applied the BIOS-trained model to population variants in three genes in which ASE plays a clinically relevant role: BRCA2, RET and NF1. This resulted in predicted ASE effects for 27 variants, of which 10 were known pathogenic variants. We demonstrated that ASE can be predicted from DNA features using machine learning. Future efforts may improve sensitivity and translate these models into a new type of genome diagnostic tool that prioritizes candidate pathogenic variants or regulators thereof for follow-up validation by RNA sequencing. All used code and machine learning models are available at GitHub and Zenodo

Dysregulation of miRNA-30e-3p targeting IL-1β in an international cohort of systemic autoinflammatory disease patients

Abstract: Autoinflammation is the standard mechanism seen in systemic autoinflammatory disease (SAID) patients. This study aimed to investigate the effect of a candidate miRNA, miR-30e-3p, which was identified in our previous study, on the autoinflammation phenotype seen in SAID patients and to analyze its expression in a larger group of European SAID patients. We examined the potential anti-inflammatory effect of miR-30e-3p, which we had defined as one of the differentially expressed miRNAs in microarray analysis involved in inflammation-related pathways. This study validated our previous microarray results of miR-30e-3p in a cohort involving European SAID patients. We performed cell culture transfection assays for miR-30e-3p. Then, in transfected cells, we analyzed expression levels of pro-inflammatory genes; IL-1β, TNF-α, TGF-β, and MEFV. We also performed functional experiments, caspase-1 activation by fluorometric assay kit, apoptosis assay by flow cytometry, and cell migration assays by wound healing and filter system to understand the possible effect of miR-30e-3p on inflammation. Following these functional assays, 3'UTR luciferase activity assay and western blotting were carried out to identify the target gene of the aforementioned miRNA. MiR-30e-3p was decreased in severe European SAID patients like the Turkish patients. The functional assays associated with inflammation suggested that miR-30e-3p has an anti-inflammatory effect. 3'UTR luciferase activity assay demonstrated that miR-30e-3p directly binds to interleukin-1-beta (IL-1β), one of the critical molecules of inflammatory pathways, and reduces both RNA and protein levels of IL-1β. miR-30e-3p, which has been associated with IL-1β, a principal component of inflammation, might be of potential diagnostic and therapeutic value for SAIDs. Key Messages: miR-30e-3p, which targets IL-1β, could have a role in the pathogenesis of SAID patients.miR-30e-3p has a role in regulating inflammatory pathways like migration, caspase-1 activation.miR-30e-3p has the potential to be used for future diagnostic and therapeutic approaches.</p

National external quality assessment for next-generation sequencing-based diagnostics of primary immunodeficiencies

Dutch genome diagnostic centers (GDC) use next-generation sequencing (NGS)-based diagnostic applications for the diagnosis of primary immunodeficiencies (PIDs). The interpretation of genetic variants in many PIDs is complicated because of the phenotypic and genetic heterogeneity. To analyze uniformity of variant filtering, interpretation, and reporting in NGS-based diagnostics for PID, an external quality assessment was performed. Four main Dutch GDCs participated in the quality assessment. Unannotated variant call format (VCF) files of two PID patient analyses per laboratory were distributed among the four GDCs, analyzed, and interpreted (eight analyses in total). Variants that would be reported to the clinician and/or advised for further investigation were compared between the centers. A survey measuring the experiences of clinical laboratory geneticists was part of the study. Analysis of samples with confirmed diagnoses showed that all centers reported at least the variants classified as likely pathogenic (LP) or pathogenic (P) variants in all samples, except for variants in two genes (PSTPIP1 and BTK). The absence of clinical information complicated correct classification of variants. In this external quality assessment, the final interpretation and conclusions of the genetic analyses were uniform among the four participating genetic centers. Clinical and immunological data provided by a medical specialist are required to be able to draw proper conclusions from genetic data

CAPICE:a computational method for Consequence-Agnostic Pathogenicity Interpretation of Clinical Exome variations

Exome sequencing is now mainstream in clinical practice. However, identification of pathogenic Mendelian variants remains time-consuming, in part, because the limited accuracy of current computational prediction methods requires manual classification by experts. Here we introduce CAPICE, a new machine-learning-based method for prioritizing pathogenic variants, including SNVs and short InDels. CAPICE outperforms the best general (CADD, GAVIN) and consequence-type-specific (REVEL, ClinPred) computational prediction methods, for both rare and ultra-rare variants. CAPICE is easily added to diagnostic pipelines as pre-computed score file or command-line software, or using online MOLGENIS web service with API. Download CAPICE for free and open-source (LGPLv3) at https://github.com/molgenis/capice.

ISSAID/EMQN Best Practice Guidelines for the Genetic Diagnosis of Monogenic Autoinflammatory Diseases in the Next-Generation Sequencing Era

Abstract Background Monogenic autoinflammatory diseases are caused by pathogenic variants in genes that regulate innate immune responses, and are characterized by sterile systemic inflammatory episodes. Since symptoms can overlap within this rapidly expanding disease category, accurate genetic diagnosis is of the utmost importance to initiate early inflammation-targeted treatment and prevent clinically significant or life-threatening complications. Initial recommendations for the genetic diagnosis of autoinflammatory diseases were limited to a gene-by-gene diagnosis strategy based on the Sanger method, and restricted to the 4 prototypic recurrent fevers (MEFV, MVK, TNFRSF1A, and NLRP3 genes). The development of best practices guidelines integrating critical recent discoveries has become essential. Methods The preparatory steps included 2 online surveys and pathogenicity annotation of newly recommended genes. The current guidelines were drafted by European Molecular Genetics Quality Network members, then discussed by a panel of experts of the International Society for Systemic Autoinflammatory Diseases during a consensus meeting. Results In these guidelines, we combine the diagnostic strength of next-generation sequencing and recommendations to 4 more recently identified genes (ADA2, NOD2, PSTPIP1, and TNFAIP3), nonclassical pathogenic genetic alterations, and atypical phenotypes. We present a referral-based decision tree for test scope and method (Sanger versus next-generation sequencing) and recommend on complementary explorations for mosaicism, copy-number variants, and gene dose. A genotype table based on the 5-category variant pathogenicity classification provides the clinical significance of prototypic genotypes per gene and disease. Conclusions These guidelines will orient and assist geneticists and health practitioners in providing up-to-date and appropriate diagnosis to their patients

A novel pathogenic MLH1 missense mutation, c.112A > C, p.Asn38His, in six families with Lynch syndrome

<p>Abstract</p> <p>Background</p> <p>An unclassified variant (UV) in exon 1 of the <it>MLH1 </it>gene, c.112A > C, p.Asn38His, was found in six families who meet diagnostic criteria for Lynch syndrome. The pathogenicity of this variant was unknown. We aim to elucidate the pathogenicity of this <it>MLH1 </it>variant in order to counsel these families adequately and to enable predictive testing in healthy at-risk relatives.</p> <p>Methods</p> <p>We studied clinical data, microsatellite instability and immunohistochemical staining of MMR proteins, and performed genealogy, haplotype analysis and DNA testing of control samples.</p> <p>Results</p> <p>The UV showed co-segregation with the disease in all families. All investigated tumors showed a microsatellite instable pattern. Immunohistochemical data were variable among tested tumors. Three families had a common ancestor and all families originated from the same geographical area in The Netherlands. Haplotype analysis showed a common haplotype in all six families.</p> <p>Conclusions</p> <p>We conclude that the <it>MLH1 </it>variant is a pathogenic mutation and genealogy and haplotype analysis results strongly suggest that it is a Dutch founder mutation. Our findings imply that predictive testing can be offered to healthy family members. The immunohistochemical data of MMR protein expression show that interpreting these results in case of a missense mutation should be done with caution.</p

The Human Phenotype Ontology in 2024: phenotypes around the world.

The Human Phenotype Ontology (HPO) is a widely used resource that comprehensively organizes and defines the phenotypic features of human disease, enabling computational inference and supporting genomic and phenotypic analyses through semantic similarity and machine learning algorithms. The HPO has widespread applications in clinical diagnostics and translational research, including genomic diagnostics, gene-disease discovery, and cohort analytics. In recent years, groups around the world have developed translations of the HPO from English to other languages, and the HPO browser has been internationalized, allowing users to view HPO term labels and in many cases synonyms and definitions in ten languages in addition to English. Since our last report, a total of 2239 new HPO terms and 49235 new HPO annotations were developed, many in collaboration with external groups in the fields of psychiatry, arthrogryposis, immunology and cardiology. The Medical Action Ontology (MAxO) is a new effort to model treatments and other measures taken for clinical management. Finally, the HPO consortium is contributing to efforts to integrate the HPO and the GA4GH Phenopacket Schema into electronic health records (EHRs) with the goal of more standardized and computable integration of rare disease data in EHRs

Delineating the molecular and phenotypic spectrum of the SETD1B-related syndrome

Purpose: Pathogenic variants in SETD1B have been associated with a syndromic neurodevelopmental disorder including intellectual disability, language delay, and seizures. To date, clinical features have been described for 11 patients with (likely) pathogenic SETD1B sequence variants. This study aims to further delineate the spectrum of the SETD1B-related syndrome based on characterizing an expanded patient cohort. Methods: We perform an in-depth clinical characterization of a cohort of 36 unpublished individuals with SETD1B sequence variants, describing their molecular and phenotypic spectrum. Selected variants were functionally tested using in vitro and genome-wide methylation assays. Results: Our data present evidence for a loss-of-function mechanism of SETD1B variants, resulting in a core clinical phenotype of global developmental delay, language delay including regression, intellectual disability, autism and other behavioral issues, and variable epilepsy phenotypes. Developmental delay appeared to precede seizure onset, suggesting SETD1B dysfunction impacts physiological neurodevelopment even in the absence of epileptic activity. Males are significantly overrepresented and more severely affected, and we speculate that sex-linked traits could affect susceptibility to penetrance and the clinical spectrum of SETD1B variants. Conclusion: Insights from this extensive cohort will facilitate the counseling regarding the molecular and phenotypic landscape of newly diagnosed patients with the SETD1B-related syndrome

Twist exome capture allows for lower average sequence coverage in clinical exome sequencing

Background Exome and genome sequencing are the predominant techniques in the diagnosis and research of genetic disorders. Sufficient, uniform and reproducible/consistent sequence coverage is a main determinant for the sensitivity to detect single-nucleotide (SNVs) and copy number variants (CNVs). Here we compared the ability to obtain comprehensive exome coverage for recent exome capture kits and genome sequencing techniques. Results We compared three different widely used enrichment kits (Agilent SureSelect Human All Exon V5, Agilent SureSelect Human All Exon V7 and Twist Bioscience) as well as short-read and long-read WGS. We show that the Twist exome capture significantly improves complete coverage and coverage uniformity across coding regions compared to other exome capture kits. Twist performance is comparable to that of both short- and long-read whole genome sequencing. Additionally, we show that even at a reduced average coverage of 70× there is only minimal loss in sensitivity for SNV and CNV detection. Conclusion We conclude that exome sequencing with Twist represents a significant improvement and could be performed at lower sequence coverage compared to other exome capture techniques