Genome analysis and knowledge-driven variant interpretation with TGex

Novel Loss-of-Function SYCP2 Variants in Infertile Males Upgrade the Gene-Disease Clinical Validity Classification for SYCP2 and Male Infertility to Strong

Male infertility affects approximately 7% of the male population, and about 15% of these cases are predicted to have a genetic etiology. One gene implicated in autosomal dominant male infertility, SYCP2, encodes a protein critical for the synapsis of homologous chromosomes during meiosis I, resulting in impaired spermatogenesis. However, the clinical validity of the gene-disease pair was previously categorized as on the border of limited and moderate due to few reported cases. This study investigates the genetic cause of infertility for three unrelated Chinese patients with oligoasthenozoospermia. Whole exome sequencing (WES) and subsequent Sanger sequencing revealed novel heterozygous loss-of-function (LOF) variants in SYCP2 (c.89dup, c.946_947del, and c.4378_4379del). These cases, combined with the previously reported cases, provide strong genetic evidence supporting an autosomal dominant inheritance pattern. The experimental evidence also demonstrates a critical role for SYCP2 in spermatogenesis. Collectively, this updated assessment of the genetic and experimental evidence upgrades the gene-disease association strength of SYCP2 and autosomal dominant male infertility from on the border of limited and moderate to strong. The reclassification improves SYCP2 variant interpretation and qualifies it for the inclusion on diagnostic male infertility gene panels and prioritization in whole exome or genome studies for related phenotypes. These findings therefore improve the clinical interpretation of SYCP2 LOF variants.

Prevalence of common autosomal recessive mutation carriers in women in the Southern Vietnam following the application of expanded carrier screening

The common autosomal recessive (AR) mutation carrier is still unknown in Vietnam. This study aims to identify the most common AR gene mutation carriers in women of reproductive age to build a Vietnamese-specific carrier screening panel for AR and X-linked disorders in the preconception and prenatal healthcare program. A cross-sectional study was conducted at University Medical Center-Branch 2 in Ho Chi Minh City from December 1st, 2020, to June 30th, 2023. 338 women have consented to take a 5 mL blood test to identify 540 recessive genes. The carrier screening panel was designed based on the American College of Medical Genetics and Genomics (ACMG)-recommended genes and suggestions from 104 clinical experts in Vietnam. Obstetricians and genetic experts counseled all positive testing results to discuss the possibility of recessive diseases in their offspring. The most common recessive disorders were defined at a prevalence of 1 in 60 or greater, and those were added to a Vietnamese-specific carrier screening panel. 338 non-pregnant and pregnant women underwent the expanded carrier screening (ECS). The carrier frequency was 63.6%, in which 215 women carried at least one AR gene mutation. GJB2 hearing impairment was identified as the most common chronic condition (1 in 5). The second most common AR disorder was beta-thalassemia (1 in 16), followed by cystic fibrosis (1 in 23), G6PD deficiency (1 in 28), Wilson's disease (1 in 31), Usher's syndrome (1 in 31), and glycogen storage disease (1 in 56). Seven common recessive genes were added in ethnic-based carrier screening. Women in the South of Vietnam have been carried for many recessive conditions at high frequency, such as hearing impairment, genetic anemia, and cystic fibrosis. It is necessary to implement a preconception and prenatal screening program by using seven widely popular AR genes in a Vietnamese-specific carrier screening panel to reduce the burden related to AR and X-linked disorders.

Intellectual disability syndrome associated with a homozygous founder variant in SGSM3 in Ashkenazi Jews

BACKGROUND

Neurodevelopmental disorders (NDDs) impact both the development and functioning of the brain and exhibit clinical and genetic variability. RAP and RAB proteins, belonging to the RAS superfamily, are identified as established contributors to NDDs. However, the involvement of SGSM (small G protein signalling modulator), another member of the RAS family, in NDDs has not been previously documented.

METHODS

Proband-only or trio exome sequencing was performed on DNA samples obtained from affected individuals and available family members. The variant prioritisation process focused on identifying rare deleterious variants. International collaboration aided in the identification of additional affected individuals.

RESULTS

We identified 13 patients from 8 families of Ashkenazi Jewish origin who all carried the same homozygous frameshift variant in SGSM3 gene. The variant was predicted to cause a loss of function, potentially leading to impaired protein structure or function. The variant co-segregated with the disease in all available family members. The affected individuals displayed mild global developmental delay and mild to moderate intellectual disability. Additional prevalent phenotypes observed included hypotonia, behavioural challenges and short stature.

CONCLUSIONS

An Ashkenazi Jewish homozygous founder variant in SGSM3 was discovered in individuals with NDDs and short stature. This finding establishes a connection between another member of the RAS family and NDDs. Additional research is needed to uncover the specific molecular mechanisms by which SGSM3 influences neurodevelopmental processes and the regulation of growth.

Complex rearrangement in TBC1D4 in an individual with diabetes due to severe insulin resistance syndrome

Severe insulin resistance syndromes result from primary insulin signaling defects, adipose tissue abnormalities or other complex syndromes. Mutations in TBC1D4 lead to partial insulin signaling defects, characterized mainly by postprandial insulin resistance. We describe an individual with severe insulin-resistant diabetes unresponsive to multiple therapies, in whom exome and genome analyses identified a complex rearrangement in TBC1D4. The rearrangement was of the pattern DUP-TRP/INV-DUP, with mutational signatures suggestive of replicative repair and Alu-Alu recombination as the underlying mechanisms. TBC1D4 encodes the TBC1D4/AS160 RabGTPase activating protein (RabGAP) involved in the translocation of glucose transporter 4 (GLUT4) from the cytosol to the cell membrane. Although the precise functional mechanism underlying insulin resistance in the proband is yet to be determined, this case provides further support for the link between TBC1D4 and hereditary insulin-resistant diabetes.

Complex Genomic Rearrangement Patterns in Malignant Pleural Mesothelioma due to Environmental Asbestos Exposure

Malignant pleural mesothelioma (MPM) is a rare type of cancer, and its main risk factor is exposure to asbestos. Accordingly, our knowledge of the genomic structure of an MPM tumor is limited when compared to other cancers. In this study, we aimed to characterize complex genomic rearrangement patterns and variations to better understand the genomics of MPM tumors. We comparatively scanned 3 MPM tumor genomes by Whole-Genome Sequencing and High-Resolution SNP array. We also used various computational algorithms to detect both CNAs and complex chromosomal rearrangements. Genomic data obtained from each bioinformatics tool are interpreted comparatively to better understand CNAs and cancer-related Nucleotide variations in MPM tumors. In patients 1 and 2, we found pathogenic nucleotide variants of BAP1, RB1, and TP53. These two MPM genomes exhibited a highly rearranged chromosomal rearrangement pattern resembling Chromomanagesis particularly in the form of Chromoanasynthesis. In patient 3, we found nucleotide variants of important cancer-related genes, including TGFBR1, KMT2C, and PALLD, to have lower chromosomal rearrangement complexity compared with patients 1 and 2. We also detected several actionable nucleotide variants including XRCC1, ERCC2. We also discovered the SKA3-DDX10 fusion in two MPM genomes, which is a novel finding for MPM. We found that MPM genomes are very complex, suggesting that this highly rearranged pattern is strongly related to driver mutational status like BAP1, TP53 and RB1.

Qingfei Formula Protects against Human Respiratory Syn cytial Virus-induced Lung Inflammatory Injury by Regulating the M APK Signaling Pathway

OBJECTIVE

Qingfei formula (QF) is an empirical formula that shows good clinical efficacy in treating human respiratory syncytial virus pneumonia (RSVP). However, the underlying mechanism remains unclear. This study explores the possible pharmacological actions of QF in RSVP treatment.

METHODS

We used a network pharmacology approach to identify the active ingredients of QF, forecast possible therapeutic targets, and analyze biological processes and pathways. Molecular docking simulation was used to evaluate the binding capability of active ingredients and therapeutic targets. Finally, in vivo experiments confirmed the reliability of network pharmacology-based prediction of underlying mechanisms.

RESULTS

The study identified 92 potential therapeutic targets and corresponding 131 active ingredients. Enrichment analysis showed that QF downregulated the MAPK signaling pathway and suppressed the inflammatory injury to the lungs induced by the RSV virus. Molecular docking simulations demonstrated that the core active ingredients of QF could stably bind to genes associated with the MAPK signaling pathway. QF had a protective effect against pneumonia in RSV-infected mice. The QF group exhibited a significant reduction in the levels of inflammatory mediators, interleukin- 6 (IL-6), interleukin-8 (CXCL8, IL-8), and P-STAT3, compared to the RSV-induced group. The QF group showed remarkably inhibited MAPK1+3(P-ERK1+2) and MAPK8(P-JNK) protein expression.

CONCLUSION

The current study showed that QF downregulated the MAPK signaling pathway, which inhibited pulmonary inflammation triggered by RSV infection. This study recommends the appropriate use of QF in the clinical management of RSVP.

Two novel mutations within FREM1 gene in patients with bifid nose

BACKGROUND

Bifid nose is a rare congenital deformity and the etiology is unknown. The purpose of this study was to report genetic variation in family of patients with bifid nose.

METHODS

Twenty-three consecutive patients who were diagnosed with mild bifid nose were operated with z-plasty from 2009 to 2021. Three underage patients (a pair of twins and a girl) from two family lines, who came to our hospital for surgical treatment, were enrolled. Whole exome sequencing and Sanger sequencing were conducted. Z-shaped flaps were created and the cartilago alaris major were re-stitched. Photographs and CT scan before and after surgery were obtained. Clinical outcomes, complications and patients' satisfaction were evaluated and analyzed. The follow-up time ranges from 2 to 3 years (2.4 ± 1.2 years).

RESULTS

Most patients were satisfied with the outcome (96.2%). The nasal deformities were corrected successfully with z-plasty technique in one-stage. FREM1 c.870_876del and c.2 T > C were detected with Whole exome sequencing, which have not been reported before. The results of Sanger sequencing were consistent with those of Whole exome sequencing.

CONCLUSIONS

The newly detected mutations of FREM1 have a certain heritability, and are helpful to make an accurate diagnosis and provide a better understanding of bifid nose mechanism. Z-plasty technique can be an effective technical approach for correcting mild bifid nose deformity.

SINE-VNTR-Alu retrotransposon insertion as a novel mutational event underlying Glanzmann thrombasthenia

BACKGROUND

Glanzmann thrombasthenia (GT) is an autosomal recessive platelet aggregation disorder caused by mutations in ITGA2B or ITGB3.

OBJECTIVES

We aimed to assess the phenotype and investigate the genetic etiology of a GT pedigree.

METHODS

A patient with bleeding manifestations and mild mental retardation was enrolled. Complete blood count, coagulation, and platelet aggregation tests were performed. Causal mutations were identified via whole exome and genome sequencing and subsequently confirmed through polymerase chain reaction and Sanger sequencing. The transcription of ITGB3 was characterized using RNA sequencing and reverse transcription polymerase chain reaction. The αⅡb and β3 biosynthesis was investigated via whole blood flow cytometry and in vitro studies.

RESULTS

GT was diagnosed in a patient with defective platelet aggregation. Novel compound heterozygous ITGB3 variants were identified, with a maternal nonsense mutation (c.2222G>A, p.Trp741∗) and a paternal SINE-VNTR-Alu (SVA) retrotransposon insertion. The 5' truncated SVA element was inserted in a sense orientation in intron 11 of ITGB3, resulting in aberrant splicing of ITGB3 and significantly reducing β3 protein content. Meanwhile, both the expression and transportation of β3 were damaged by the ITGB3 c.2222G>A. Almost no αⅡb and β3 expressions were detected on the patient's platelets surface.

CONCLUSION

Novel compound heterozygous ITGB3 mutations were identified in the GT pedigree, resulting in defects of αⅡbβ3 biosynthesis. This is the first report of SVA retrotransposon insertion in the genetic pathogenesis of GT. Our study highlights the importance of combining multiple high-throughput sequencing technologies for the molecular diagnosis of genetic disorders.

Toward advanced diagnosis and management of inherited arrhythmia syndromes: Harnessing the capabilities of artificial intelligence and machine learning

The use of advanced computational technologies, such as artificial intelligence (AI), is now exerting a significant influence on various aspects of life, including health care and science. AI has garnered remarkable public notice with the release of deep learning models that can model anything from artwork to academic papers with minimal human intervention. Machine learning, a method that uses algorithms to extract information from raw data and represent it in a model, and deep learning, a method that uses multiple layers to progressively extract higher-level features from the raw input with minimal human intervention, are increasingly leveraged to tackle problems in the health sector, including utilization for clinical decision support in cardiovascular medicine. Inherited arrhythmia syndromes are a clinical domain where multiple unanswered questions remain despite unprecedented progress over the past 2 decades with the introduction of large panel genetic testing and the first steps in precision medicine. In particular, AI tools can help address gaps in clinical diagnosis by identifying individuals with concealed or transient phenotypes; enhance risk stratification by elevating recognition of underlying risk burden beyond widely recognized risk factors; improve prediction of response to therapy, and further prognostication. In this contemporary review, we provide a summary of the AI models developed to solve challenges in inherited arrhythmia syndromes and also outline gaps that can be filled with the development of intelligent AI models.

Biallelic loss of function variants in WBP4, encoding a spliceosome protein, result in a variable neurodevelopmental delay syndrome

Over two dozen spliceosome proteins are involved in human diseases, also referred to as spliceosomopathies. WBP4 (WW Domain Binding Protein 4) is part of the early spliceosomal complex, and was not described before in the context of human pathologies. Ascertained through GeneMatcher we identified eleven patients from eight families, with a severe neurodevelopmental syndrome with variable manifestations. Clinical manifestations included hypotonia, global developmental delay, severe intellectual disability, brain abnormalities, musculoskeletal and gastrointestinal abnormalities. Genetic analysis revealed overall five different homozygous loss-of-function variants in WBP4. Immunoblotting on fibroblasts from two affected individuals with different genetic variants demonstrated complete loss of protein, and RNA sequencing analysis uncovered shared abnormal splicing patterns, including enrichment for abnormalities of the nervous system and musculoskeletal system genes, suggesting that the overlapping differentially spliced genes are related to the common phenotypes of the probands. We conclude that biallelic variants in WBP4 cause a spliceosomopathy. Further functional studies are called for better understanding of the mechanism of pathogenicity.

Var∣Decrypt: a novel and user-friendly tool to explore and prioritize variants in whole-exome sequencing data

BACKGROUND

High-throughput sequencing (HTS) offers unprecedented opportunities for the discovery of causative gene variants in multiple human disorders including cancers, and has revolutionized clinical diagnostics. However, despite more than a decade of use of HTS-based assays, extracting relevant functional information from whole-exome sequencing (WES) data remains challenging, especially for non-specialists lacking in-depth bioinformatic skills.

RESULTS

To address this limitation, we developed Var∣Decrypt, a web-based tool designed to greatly facilitate WES data browsing and analysis. Var∣Decrypt offers a wide range of gene and variant filtering possibilities, clustering and enrichment tools, providing an efficient way to derive patient-specific functional information and to prioritize gene variants for functional analyses. We applied Var∣Decrypt on WES datasets of 10 acute erythroid leukemia patients, a rare and aggressive form of leukemia, and recovered known disease oncogenes in addition to novel putative drivers. We additionally validated the performance of Var∣Decrypt using an independent dataset of ~ 90 multiple myeloma WES, recapitulating the identified deregulated genes and pathways, showing the general applicability and versatility of Var∣Decrypt for WES analysis.

CONCLUSION

Despite years of use of WES in human health for diagnosis and discovery of disease drivers, WES data analysis still remains a complex task requiring advanced bioinformatic skills. In that context, there is a need for user-friendly all-in-one dedicated tools for data analysis, to allow biologists and clinicians to extract relevant biological information from patient datasets. Here, we provide Var∣Decrypt (trial version accessible here: https://vardecrypt.com/app/vardecrypt ), a simple and intuitive Rshiny application created to fill this gap. Source code and detailed user tutorial are available at https://gitlab.com/mohammadsalma/vardecrypt .

Integrating metabolomics and network pharmacology to assess the effects of quercetin on lung inflammatory injury induced by human respiratory syncytial virus

Quercetin (QR) has significant anti-respiratory syncytial virus (RSV) effects. However, its therapeutic mechanism has not been thoroughly explored. In this study, a lung inflammatory injury model caused by RSV was established in mice. Untargeted lung tissue metabolomics was used to identify differential metabolites and metabolic pathways. Network pharmacology was used to predict potential therapeutic targets of QR and analyze biological functions and pathways modulated by QR. By overlapping the results of the metabolomics and the network pharmacology analyses, the common targets of QR that were likely to be involved in the amelioration of RSV-induced lung inflammatory injury by QR were identified. Metabolomics analysis identified 52 differential metabolites and 244 corresponding targets, while network pharmacology analysis identified 126 potential targets of QR. By intersecting these 244 targets with the 126 targets, hypoxanthine-guanine phosphoribosyltransferase (HPRT1), thymidine phosphorylase (TYMP), lactoperoxidase (LPO), myeloperoxidase (MPO), and cytochrome P450 19A1 (CYP19A1) were identified as the common targets. The key targets, HPRT1, TYMP, LPO, and MPO, were components of purine metabolic pathways. The present study demonstrated that QR effectively ameliorated RSV-induced lung inflammatory injury in the established mouse model. Combining metabolomics and network pharmacology showed that the anti-RSV effect of QR was closely associated with purine metabolism pathways.

Application of Prenatal Whole Exome Sequencing for Structural Congenital Anomalies-Experience from a Local Prenatal Diagnostic Laboratory

Fetal structural congenital abnormalities (SCAs) complicate 2-3% of all pregnancies. Whole-exome sequencing (WES) has been increasingly adopted prenatally when karyotyping and chromosomal microarray do not yield a diagnosis. This is a retrospective cohort study of 104 fetuses with SCAs identified on antenatal ultrasound in Hong Kong, where whole exome sequencing is performed. Molecular diagnosis was obtained in 25 of the 104 fetuses (24%). The highest diagnostic rate was found in fetuses with multiple SCAs (29.2%), particularly those with involvement of the cardiac and musculoskeletal systems. Variants of uncertain significance were detected in 8 out of the 104 fetuses (7.7%). Our study shows the utility of WES in the prenatal setting, and the extended use of the technology would be recommended in addition to conventional genetic workup.

Central resources of variant discovery and annotation and its role in precision medicine

Rapid technological advancement in high-throughput genomics, microarray, and deep sequencing technologies has accelerated the possibility of more complex precision medicine research using large amounts of heterogeneous health-related data from patients, including genomic variants. Genomic variants can be identified and annotated based on the reference human genome either within the sequence as a whole or in a putative functional genomic element. The American College of Medical Genetics and Genomics (ACMG) and the Association for Molecular Pathology (AMP) mutually created standards and guidelines for the appraisal of proof to expand consistency and straightforwardness in clinical variation interpretations. Various efforts toward precision medicine have been facilitated by many national and international public databases that classify and annotate genomic variation. In the present study, several resources are highlighted with recognition and data spreading of clinically important genetic variations.

Selective degradation of tRNASer(AGY) is the primary driver for mitochondrial seryl-tRNA synthetase-related disease

Mitochondrial translation is of high significance for cellular energy homeostasis. Aminoacyl-tRNA synthetases (aaRSs) are crucial translational components. Mitochondrial aaRS variants cause various human diseases. However, the pathogenesis of the vast majority of these diseases remains unknown. Here, we identified two novel SARS2 (encoding mitochondrial seryl-tRNA synthetase) variants that cause a multisystem disorder. c.654-14T > A mutation induced mRNA mis-splicing, generating a peptide insertion in the active site; c.1519dupC swapped a critical tRNA-binding motif in the C-terminus due to stop codon readthrough. Both mutants exhibited severely diminished tRNA binding and aminoacylation capacities. A marked reduction in mitochondrial tRNASer(AGY) was observed due to RNA degradation in patient-derived induced pluripotent stem cells (iPSCs), causing impaired translation and comprehensive mitochondrial function deficiencies. These impairments were efficiently rescued by wild-type SARS2 overexpression. Either mutation caused early embryonic fatality in mice. Heterozygous mice displayed reduced muscle tissue-specific levels of tRNASers. Our findings elucidated the biochemical and cellular consequences of impaired translation mediated by SARS2, suggesting that reduced abundance of tRNASer(AGY) is a key determinant for development of SARS2-related diseases.

Exploration of Tools for the Interpretation of Human Non-Coding Variants

The advent of Whole Genome Sequencing (WGS) broadened the genetic variation detection range, revealing the presence of variants even in non-coding regions of the genome, which would have been missed using targeted approaches. One of the most challenging issues in WGS analysis regards the interpretation of annotated variants. This review focuses on tools suitable for the functional annotation of variants falling into non-coding regions. It couples the description of non-coding genomic areas with the results and performance of existing tools for a functional interpretation of the effect of variants in these regions. Tools were tested in a controlled genomic scenario, representing the ground-truth and allowing us to determine software performance.

Whole Genome Sequencing Applied in Familial Hamartomatous Polyposis Identifies Novel Structural Variations

Hamartomatous polyposis syndromes (HPS) are rare cancer-predisposing disorders including Juvenile polyposis (JPS), Peutz–Jeghers (PJS) and PTEN hamartomatous syndromes (PHS). Penetrant mutations in corresponding genes (SMAD4, BMPR1A, STK11, PTEN and AKT1), are usually diagnosed via a next-generation-sequencing gene panel (NGS-GP) for tailored surveillance and preimplantation testing for monogenic disorders (PGT-M). Five probands with HPS phenotype, with no genetic diagnosis per genetic workup, underwent whole-genome sequencing (WGS) that identified structural genetic alterations: two novel inversions in BMPRA1 and STK11, two BMPR1A-deletions, known as founders among Bukharan Jews, and BMPR1A microdeletion. BMPR1A inversion was validated by “junction fragment” amplification and direct testing. PGT-M was performed via multiplex-PCR and enabled successful birth of a non-carrier baby. WGS may be considered for HPS patients with no NGS-GP findings to exclude structural alterations.

Mechanism of Action of Zhi Gan Cao Decoction for Atrial Fibrillation and Myocardial Fibrosis in a Mouse Model of Atrial Fibrillation: A Network Pharmacology-Based Study

Atrial fibrillation (AF), a commonly seen cardiac disease without optimal curative treatment option, is usually treated by traditional Chinese medicine in China. The Zhi-Gan-Cao decoction (ZGCD) is an alternative medicine for clinical use and has definitive effects. It remains to be defined regarding the specific components and related mechanisms of ZGCD for the treatment of AF. We determined the primary constituents and major targets of the herbs in ZGCD using the TCMSP, HERB, and BATMAN-TCM databases. The UniProt databank database amended and combined the prospective names to supply objective data and records. Every target connected to AF was generated using the GeneCards databank, Drugbank database, TTD, Disgenet database, and OMIM. After identifying possible common targets between ZGCD and AF, the interface network illustration “ZGCD component-AF-target” was created using Cytoscape. We obtained 175 constituents and 839 targets for seven herbal drug categories in the ZGCD and identified 1008 targets of AF. After merging and removing repetitions, 136 collective targets between the ZGCD and AF were removed using the Cytoscape system. These renowned targets were generated from 38 suitable components from among the 157 components. GO enhancement examination and KEGG enrichment analysis by Metascape identified the close connection between the critical target genes and 20 signaling pathways. Then, we injected isoproterenol subcutaneously into the mouse and gave gavage with roasted licorice soup. Two weeks later, mouse were processed and sampled for testing. The results of HE and Masson staining showed that ZGCD effectively alleviated the degree of myocardial fibrosis. As indicated by qRT-PCR and Western blotting, ZGCD significantly reduced COL1A1, COL1A2, COL3A1, and TGF-β1 in myocardial fibrotic tissue to reduce myocardial fibrosis and treat AF by interfering with the expression of COL1A1, COL1A2, COL3A1, and TGF-β1 in myocardial tissue. ZGCD may treat AF by lowering the degree of myocardial fibrosis.

Static and Motion Facial Analysis for Craniofacial Assessment and Diagnosing Diseases

Deviation from a normal facial shape and symmetry can arise from numerous sources, including physical injury and congenital birth defects. Such abnormalities can have important aesthetic and functional consequences. Furthermore, in clinical genetics distinctive facial appearances are often associated with clinical or genetic diagnoses; the recognition of a characteristic facial appearance can substantially narrow the search space of potential diagnoses for the clinician. Unusual patterns of facial movement and expression can indicate disturbances to normal mechanical functioning or emotional affect. Computational analyses of static and moving 2D and 3D images can serve clinicians and researchers by detecting and describing facial structural, mechanical, and affective abnormalities objectively. In this review we survey traditional and emerging methods of facial analysis, including statistical shape modeling, syndrome classification, modeling clinical face phenotype spaces, and analysis of facial motion and affect. Expected final online publication date for the Annual Review of Biomedical Data Science, Volume 5 is August 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

A machine learning approach based on ACMG/AMP guidelines for genomic variant classification and prioritization

Genomic variant interpretation is a critical step of the diagnostic procedure, often supported by the application of tools that may predict the damaging impact of each variant or provide a guidelines-based classification. We propose the application of Machine Learning methodologies, in particular Penalized Logistic Regression, to support variant classification and prioritization. Our approach combines ACMG/AMP guidelines for germline variant interpretation as well as variant annotation features and provides a probabilistic score of pathogenicity, thus supporting the prioritization and classification of variants that would be interpreted as uncertain by the ACMG/AMP guidelines. We compared different approaches in terms of variant prioritization and classification on different datasets, showing that our data-driven approach is able to solve more variant of uncertain significance (VUS) cases in comparison with guidelines-based approaches and in silico prediction tools.

Molecular diagnosis for growth hormone deficiency in Chinese children and adolescents and evaluation of impact of rare genetic variants on treatment efficacy of growth hormone

BACKGROUND

Growth hormone is an effective therapy for growth hormone deficiency (GHD) but with a rather variable individual sensitivity. It is unclear whether rare genetic variants may contribute to the differential GH responsiveness.

METHODS

The present study aims to investigate the molecular etiology of GHD in Chinese children and adolescents and evaluate the impact of rare variants on therapeutic efficacies of GH.

RESULTS

Twenty-one rare heterozygous variant were classified as promising uncertain significance (n = 14), pathogenic (n = 5) or likely pathogenic (n = 2) for 21 of the 93 GHD patients. After GHD patients harboring these rare variants were excluded, inter-individual variability in the response to GH therapy obviously reduced and the negative correlation between initiation age of treatment and height SDS change became stronger in the group without rare variants. Among rare variants, 7 (likely) pathogenic variants (7.5%, 7/93) involved a total of 6 genes not only associated with GH secretion (PROKR2, LZTR1), but also growth plate chondrocyte signaling (ACAN, FBN1, COL9A1) or genetic syndromes (PTPN11).

CONCLUSIONS

Rare genetic variants are an important factor contributing to differential GH responsiveness and genetic testing should be factored into accurate diagnosis and treatment decision making in the future.

CLINICAL TRIAL REGISTRATION NUMBER

ChiCTR1900026510.

Remediation of ABCG5-Linked Macrothrombocytopenia With Ezetimibe Therapy

To investigate refractory hypercholesterolemia, a female patient and relatives were subjected to whole-genome sequencing. The proband was found to have compound heterozygous substitutions p. Arg446Gln and c.1118+3G>T in ABCG5, one of two genes causing sitosterolemia. When tracing these variants in the full pedigree, all maternally related heterozygotes for the intronic ABCG5 variant exhibited large platelets (over 30 fl), which segregated in an autosomal dominant manner, consistent with macrothrombocytopenia, or large platelet syndrome which may be associated with a bleeding tendency. In vitro cell-line and in vivo rat model experiments supported a pathogenic role for the variant and the macrothrombocytopenia was recapitulated in heterozygous rats and human cell lines exhibiting that single variant. Ezetimibe treatment successfully ameliorated all the symptoms of the proband with sitosterolemia and resolved the macrothrombocytopenia of the treated heterozygote relatives. Subsequently, in follow up these observations, platelet size, and size distribution were measured in 1,180 individuals; 30 were found to be clinically abnormal, three of which carried a single known pathogenic ABCG5 variant (p.Arg446Ter) and two individuals carried novel ABCG5 variants of uncertain significance. In this study, we discovered that identification of large platelets and therefore a possible macrothrombocytopenia diagnosis could easily be inadvertently missed in clinical practice due to variable instrument settings. These findings suggest that ABCG5 heterozygosity may cause macrothrombocytopenia, that Ezetimibe treatment may resolve macrothrombocytopenia in such individuals, and that increased attention to platelet size on complete blood counts can aid in the identification of candidates for ABCG5 genetic testing who might benefit from Ezetimibe treatment.

Knowledge bases and software support for variant interpretation in precision oncology

Precision oncology is a rapidly evolving interdisciplinary medical specialty. Comprehensive cancer panels are becoming increasingly available at pathology departments worldwide, creating the urgent need for scalable cancer variant annotation and molecularly informed treatment recommendations. A wealth of mainly academia-driven knowledge bases calls for software tools supporting the multi-step diagnostic process. We derive a comprehensive list of knowledge bases relevant for variant interpretation by a review of existing literature followed by a survey among medical experts from university hospitals in Germany. In addition, we review cancer variant interpretation tools, which integrate multiple knowledge bases. We categorize the knowledge bases along the diagnostic process in precision oncology and analyze programmatic access options as well as the integration of knowledge bases into software tools. The most commonly used knowledge bases provide good programmatic access options and have been integrated into a range of software tools. For the wider set of knowledge bases, access options vary across different parts of the diagnostic process. Programmatic access is limited for information regarding clinical classifications of variants and for therapy recommendations. The main issue for databases used for biological classification of pathogenic variants and pathway context information is the lack of standardized interfaces. There is no single cancer variant interpretation tool that integrates all identified knowledge bases. Specialized tools are available and need to be further developed for different steps in the diagnostic process.

Powerful use of automated prioritization of candidate variants in genetic hearing loss with extreme etiologic heterogeneity

Variant prioritization of exome sequencing (ES) data for molecular diagnosis of sensorineural hearing loss (SNHL) with extreme etiologic heterogeneity poses a significant challenge. This study used an automated variant prioritization system (“EVIDENCE”) to analyze SNHL patient data and assess its diagnostic accuracy. We performed ES of 263 probands manifesting mild to moderate or higher degrees of SNHL. Candidate variants were classified according to the 2015 American College of Medical Genetics guidelines, and we compared the accuracy, call rates, and efficiency of variant prioritizations performed manually by humans or using EVIDENCE. In our in silico panel, 21 synthetic cases were successfully analyzed by EVIDENCE. In our cohort, the ES diagnostic yield for SNHL by manual analysis was 50.19% (132/263) and 50.95% (134/263) by EVIDENCE. EVIDENCE processed ES data 24-fold faster than humans, and the concordant call rate between humans and EVIDENCE was 97.72% (257/263). Additionally, EVIDENCE outperformed human accuracy, especially at discovering causative variants of rare syndromic deafness, whereas flexible interpretations that required predefined specific genotype–phenotype correlations were possible only by manual prioritization. The automated variant prioritization system remarkably facilitated the molecular diagnosis of hearing loss with high accuracy and efficiency, fostering the popularization of molecular genetic diagnosis of SNHL.

Bi-allelic PAGR1 variants are associated with microcephaly and a severe neurodevelopmental disorder: Genetic evidence from two families

Exome and genome sequencing were used to identify the genetic etiology of a severe neurodevelopmental disorder in two unrelated Ashkenazi Jewish families with three affected individuals. The clinical findings included a prenatal presentation of microcephaly, polyhydramnios and clenched hands while postnatal findings included microcephaly, severe developmental delay, dysmorphism, neurologic deficits, and death in infancy. A shared rare homozygous, missense variant (c.274A > G; p.Ser92Gly, NM_024516.4) was identified in PAGR1, a gene currently not associated with a Mendelian disease. PAGR1 encodes a component of the histone methyltransferase MLL2/MLL3 complex and may function in the DNA damage response pathway. Complete knockout of the murine Pagr1a is embryonic-lethal. Given the available evidence, PAGR1 is a strong candidate gene for a novel autosomal recessive severe syndromic neurodevelopmental disorder.

Levodopa-responsive dystonia caused by biallelic PRKN exon inversion invisible to exome sequencing

Biallelic pathogenic variants in PRKN (PARK2), encoding the E3 ubiquitin ligase parkin, lead to early-onset Parkinson's disease. Structural variants, including duplications or deletions, are common in PRKN due to their location within the fragile site FRA6E. These variants are readily detectable by copy number variation analysis. We studied four siblings with levodopa-responsive dystonia by exome sequencing followed by genome sequencing. Affected individuals developed juvenile levodopa-responsive dystonia with subsequent appearance of parkinsonism and motor fluctuations that improved by subthalamic stimulation. Exome sequencing and copy number variation analysis were not diagnostic, yet revealed a shared homozygous block including PRKN. Genome sequencing revealed an inversion within PRKN, with intronic breakpoints flanking exon 5. Breakpoint junction analysis implicated non-homologous end joining and possibly replicative mechanisms as the repair pathways involved. Analysis of cDNA indicated skipping of exon 5 (84 bp) that was replaced by 93 bp of retained intronic sequence, preserving the reading frame yet altering a significant number of residues. Balanced copy number inversions in PRKN are associated with a severe phenotype. Such structural variants, undetected by exome analysis and by copy number variation analysis, should be considered in the relevant clinical setting. These findings raise the possibility that PRKN structural variants are more common than currently estimated.

Predicting pathogenic non-coding SVs disrupting the 3D genome in 1646 whole cancer genomes using multiple instance learning

Over the past years, large consortia have been established to fuel the sequencing of whole genomes of many cancer patients. Despite the increased abundance in tools to study the impact of SNVs, non-coding SVs have been largely ignored in these data. Here, we introduce svMIL2, an improved version of our Multiple Instance Learning-based method to study the effect of somatic non-coding SVs disrupting boundaries of TADs and CTCF loops in 1646 cancer genomes. We demonstrate that svMIL2 predicts pathogenic non-coding SVs with an average AUC of 0.86 across 12 cancer types, and identifies non-coding SVs affecting well-known driver genes. The disruption of active (super) enhancers in open chromatin regions appears to be a common mechanism by which non-coding SVs exert their pathogenicity. Finally, our results reveal that the contribution of pathogenic non-coding SVs as opposed to driver SNVs may highly vary between cancers, with notably high numbers of genes being disrupted by pathogenic non-coding SVs in ovarian and pancreatic cancer. Taken together, our machine learning method offers a potent way to prioritize putatively pathogenic non-coding SVs and leverage non-coding SVs to identify driver genes. Moreover, our analysis of 1646 cancer genomes demonstrates the importance of including non-coding SVs in cancer diagnostics.

Cruxome: a powerful tool for annotating, interpreting and reporting genetic variants

Background

Next-generation sequencing (NGS) is an efficient tool used for identifying pathogenic variants that cause Mendelian disorders. However, the lack of bioinformatics training of researchers makes the interpretation of identified variants a challenge in terms of precision and efficiency. In addition, the non-standardized phenotypic description of human diseases also makes it difficult to establish an integrated analysis pathway for variant annotation and interpretation. Solutions to these bottlenecks are urgently needed.

Results

We develop a tool named “Cruxome” to automatically annotate and interpret single nucleotide variants (SNVs) and small insertions and deletions (InDels). Our approach greatly simplifies the current burdensome task of clinical geneticists and scientists to identify the causative pathogenic variants and build personal knowledge reference bases. The integrated architecture of Cruxome offers key advantages such as an interactive and user-friendly interface and the assimilation of electronic health records of the patient. By combining a natural language processing algorithm, Cruxome can efficiently process the clinical description of diseases to HPO standardized vocabularies. By using machine learning, in silico predictive algorithms, integrated multiple databases and supplementary tools, Cruxome can automatically process SNVs and InDels variants (trio-family or proband-only cases) and clinical diagnosis records, then annotate, score, identify and interpret pathogenic variants to finally generate a standardized clinical report following American College of Medical Genetics and Genomics/ Association for Molecular Pathology (ACMG/AMP) guidelines. Cruxome also provides supplementary tools to examine and visualize the genes or variations in historical cases, which can help to better understand the genetic basis of the disease.

Conclusions

Cruxome is an efficient tool for annotation and interpretation of variations and dramatically reduces the workload for clinical geneticists and researchers to interpret NGS results, simplifying their decision-making processes. We present an online version of Cruxome, which is freely available to academics and clinical researchers. The site is accessible at http://114.251.61.49:10024/cruxome/.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07728-6.

Exploration of the mechanism of Zisheng Shenqi decoction against gout arthritis using network pharmacology

BACKGROUND

In this study, the network pharmacological methods were used to predict the target of effective components of compounds in Zisheng Shenqi Decoction (ZSD, or Nourishing Kidney Qi Decoction) in the treatment of gouty arthritis (GA).

METHOD

The main effective components and corresponding key targets of herbs in the ZSD were discerned through the Traditional Chinese Medicine Systems Pharmacology Database and Analysis (TCMSP), Bioinformatics Analysis Tool for Molecular mechanism of Traditional Chinese Medicine (BATMAN-TCM) database. UniProt database and Swiss Target Prediction (STP) database was used to rectify and unify the target names and supply the target information. The targets related to GA were obtained by using GeneCards database. After we discovered the potential common targets between ZSD and GA, the interaction network diagram of "ZSD-component-GA-target" was constructed by Cytoscape software (Version 3.7.1). Subsequently, the Protein-protein interaction (PPI) network of ZSD effective components-targets and GA-related targets was constructed by Search Tool for the Retrieval of Interacting Genes Database (STRING). Bioconductor package "org.Hs.eg.db" and "cluster profiler" package were installed in R software (Version 3.6.0) which used for Gene Ontology analysis and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway enrichment analysis.

RESULTS

146 components and 613 targets of 11 herbal medicines in the ZSD were got from TCMSP database and BATMAN-TCM database. 987 targets of GA were obtained from GeneCards database. After intersected and removed duplications, 132 common targets between ZSD and GA were screened out by Cytoscape software (Version 3.7.1). These common targets derived from 81 effective components of 146 components, such as quercetin, stigmasterol and kaempferol. They were closely related to anti-inflammatory, analgesic and anti oxidative stress and the principal targets comprised of Purinergic receptor P2X, ligand-gated ion channel 7 (P2x7R), Nod-like receptor protein 3 (NLRP3) and IL-1β. GO enrichment analysis and KEGG pathway enrichment analysis by R software (Version 3.6.0) showed that the key target genes had close relationship with oxidative stress, reactive oxygen species (ROS) metabolic process and leukocyte migration in aspects of biological process, cell components and molecular function. It also indicated that ZSD could decrease inflammatory reaction, alleviate ROS accumulation and attenuate pain by regulating P2 × 7R and NOD like receptor signaling pathway of inflammatory reaction.

CONCLUSION

A total of 81 effective components and 132 common target genes between ZSD and GA were screened by network pharmacology. The PPI network, GO enrichment analysis and KEGG pathway enrichment analysis suggested that ZSD can exerte anti-inflammatory and analgesic effects on the treatment of GA by reducing decreasing inflammatory reaction, alleviating ROS accumulation, and attenuating pain. The possible molecular mechanism of it mainly involved multiple components, multiple targets and multiple signaling pathways, which provided a comprehensive understanding for further study. In general, the network pharmacological method applied in this study provides an alternative strategy for the mechanism of ZSD in the treatment of GA.