Histopathology and molecular pathology confirmed a diagnosis of atypical Caroli's syndrome: a case report.

Caroli's syndrome is a congenital disease characterized by dilation of intrahepatic bile ducts and congenital hepatic fibrosis. It is a rare condition in clinical work. Typically, the diagnosis of this disease is confirmed through medical imaging. Here, we report a case of atypical Caroli's syndrome in a patient who presented with recurrent upper gastrointestinal tract bleeding. The patient underwent imaging examinations, liver biopsy and whole exome sequencing. The results of the imaging examination were non-specific. However, with the aid of pathological examination, the patient was diagnosed with Caroli's syndrome. In conclusion, for cases where the imaging presentation of Caroli's syndrome is inconclusive, an accurate diagnosis should rely on pathology. By discussing this specific case, our aim is to enhance readers' understanding of this disease, provide valuable information that can aid in the early detection and appropriate management of Caroli's syndrome, ultimately improving patient outcomes.

MRSD: A quantitative approach for assessing suitability of RNA-seq in the investigation of mis-splicing in Mendelian disease.

Variable levels of gene expression between tissues complicates the use of RNA sequencing of patient biosamples to delineate the impact of genomic variants. Here, we describe a gene- and tissue-specific metric to inform the feasibility of RNA sequencing. This overcomes limitations of using expression values alone as a metric to predict RNA-sequencing utility. We have derived a metric, minimum required sequencing depth (MRSD), that estimates the depth of sequencing required from RNA sequencing to achieve user-specified sequencing coverage of a gene, transcript, or group of genes. We applied MRSD across four human biosamples: whole blood, lymphoblastoid cell lines (LCLs), skeletal muscle, and cultured fibroblasts. MRSD has high precision (90.1%-98.2%) and overcomes transcript region-specific sequencing biases. Applying MRSD scoring to established disease gene panels shows that fibroblasts, of these four biosamples, are the optimum source of RNA for 63.1% of gene panels. Using this approach, up to 67.8% of the variants of uncertain significance in ClinVar that are predicted to impact splicing could be assayed by RNA sequencing in at least one of the biosamples. We demonstrate the utility and benefits of MRSD as a metric to inform functional assessment of splicing aberrations, in particular in the context of Mendelian genetic disorders to improve diagnostic yield.

PhenoApt leverages clinical expertise to prioritize candidate genes via machine learning.

In recent years, exome sequencing (ES) has shown great utility in the diagnoses of Mendelian disorders. However, after rigorous filtering, a typical ES analysis still involves the interpretation of hundreds of variants, which greatly hinders the rapid identification of causative genes. Since the interpretations of ES data require comprehensive clinical analyses, taking clinical expertise into consideration can speed the molecular diagnoses of Mendelian disorders. To leverage clinical expertise to prioritize candidate genes, we developed PhenoApt, a phenotype-driven gene prioritization tool that allows users to assign a customized weight to each phenotype, via a machine-learning algorithm. Using the ability to rank causative genes in top-10 lists as an evaluation metric, baseline analysis demonstrated that PhenoApt outperformed previous phenotype-driven gene prioritization tools by a relative increase of 22.7%-140.0% in three independent, real-world, multi-center cohorts (cohort 1, n = 185; cohort 2, n = 784; and cohort 3, n = 208). Additional trials showed that, by adding weights to clinical indications, which should be explained by the causative gene, PhenoApt performance was improved by a relative increase of 37.3% in cohort 2 (n = 471) and 21.4% in cohort 3 (n = 208). Moreover, PhenoApt could assign an intrinsic weight to each phenotype based on the likelihood of its being a Mendelian trait using term frequency-inverse document frequency techniques. When clinical indications were assigned with intrinsic weights, PhenoApt performance was improved by a relative increase of 23.7% in cohort 2 and 15.5% in cohort 3. For the integration of PhenoApt into clinical practice, we developed a user-friendly website and a command-line tool.

Prevalence of monogenic disease in paediatric patients with a predominant respiratory phenotype.

OBJECTIVE: This study aimed to investigate the prevalence and clinical characteristics of monogenic disease in paediatric patients with a predominant respiratory phenotype. METHODS: Exome sequencing was performed in a cohort of 971 children with a predominant respiratory phenotype and suspected genetic aetiology. A total of 140 positive cases were divided into subgroups based on recruitment age and the primary biological system(s) involved. RESULTS: There were 140 (14.4%) patients with a positive molecular diagnosis, and their primary clinical manifestations were respiratory distress (12.9%, 18 of 140), respiratory failure (12.9%, 18 of 140) and recurrent/persistent lower respiratory infections (66.4%, 93 of 140). Primary immunodeficiency (49.3%), multisystem malformations/syndromes (17.9%), and genetic lung disease (16.4%) were the three most common genetic causes in the cohort, and they varied among the age subgroups. A total of 72 (51.4%) patients had changes in medical management strategies after genetic diagnosis, and the rate in those with genetic lung disease (82.6%, 19 of 23) was far higher than that in patients with genetic disease with lung involvement (45.3%, 53 of 117) (p=0.001). CONCLUSION: Our findings demonstrate that exome sequencing is a valuable diagnostic tool for monogenic diseases in children with a predominant respiratory phenotype, and the genetic spectrum varies with age. Taken together, genetic diagnoses provide invaluable clinical and prognostic information that may also facilitate the development of precision medicine for paediatric patients.

Transgenic Epidermal Cultures for Junctional Epidermolysis Bullosa - 5-Year Outcomes.

Inherited junctional epidermolysis bullosa is a severe genetic skin disease that leads to epidermal loss caused by structural and mechanical fragility of the integuments. There is no established cure for junctional epidermolysis bullosa. We previously reported that genetically corrected autologous epidermal cultures regenerated almost an entire, fully functional epidermis on a child who had a devastating form of junctional epidermolysis bullosa. We now report long-term clinical outcomes in this patient. (Funded by POR FESR 2014-2020 - Regione Emilia-Romagna and others.).

Molecular Approaches Fighting Nonsense.

Nonsense mutations are the result of single nucleotide substitutions in the DNA that change a sense codon (coding for an amino acid) to a nonsense or premature termination codon (PTC) within the coding region of the mRNA [...].

Cascading epigenomic analysis for identifying disease genes from the regulatory landscape of GWAS variants.

The majority of genetic variants detected in genome wide association studies (GWAS) exert their effects on phenotypes through gene regulation. Motivated by this observation, we propose a multi-omic integration method that models the cascading effects of genetic variants from epigenome to transcriptome and eventually to the phenome in identifying target genes influenced by risk alleles. This cascading epigenomic analysis for GWAS, which we refer to as CEWAS, comprises two types of models: one for linking cis genetic effects to epigenomic variation and another for linking cis epigenomic variation to gene expression. Applying these models in cascade to GWAS summary statistics generates gene level statistics that reflect genetically-driven epigenomic effects. We show on sixteen brain-related GWAS that CEWAS provides higher gene detection rate than related methods, and finds disease relevant genes and gene sets that point toward less explored biological processes. CEWAS thus presents a novel means for exploring the regulatory landscape of GWAS variants in uncovering disease mechanisms.

Identification of differentially expressed long noncoding RNAs and pathways in liver tissues from rats with hepatic fibrosis.

To identify long non-coding RNAs (lncRNAs) and their potential roles in hepatic fibrosis in rat liver issues induced by CCl4, lncRNAs and genes were analyzed in fibrotic rat liver tissues by RNA sequencing and verified by quantitative reverse transcription polymerase chain reaction (qRT-PCR). Differentially expressed (DE) lncRNAs (DE-lncRNAs) and genes were subjected to bioinformatics analysis and used to construct a co-expression network. We identified 10 novel DE-lncRNAs that were downregulated during the hepatic fibrosis process. The cis target gene of DE-lncRNA, XLOC118358, was Met, and the cis target gene of the other nine DE-lncRNAs, XLOC004600, XLOC004605, XLOC004610, XLOC004611, XLOC004568, XLOC004580 XLOC004598, XLOC004601, and XLOC004602 was Nox4. The results of construction of a pathway-DEG co-expression network show that lncRNA-Met and lncRNAs-Nox4 were involved in oxidation-reduction processes and PI3K/Akt signaling pathway. Our results identified 10 DE-lncRNAs related to hepatic fibrosis, and the potential roles of DE-lncRNAs and target genes in hepatic fibrosis might provide new therapeutic strategies for hepatic fibrosis.

p53 Activation in Genetic Disorders: Different Routes to the Same Destination.

The tumor suppressor p53 is critical for preventing neoplastic transformation and tumor progression. Inappropriate activation of p53, however, has been observed in a number of human inherited disorders that most often affect development of the brain, craniofacial region, limb skeleton, and hematopoietic system. Genes related to these developmental disorders are essentially involved in transcriptional regulation/chromatin remodeling, rRNA metabolism, DNA damage-repair pathways, telomere maintenance, and centrosome biogenesis. Perturbation of these activities or cellular processes may result in p53 accumulation in cell cultures, animal models, and perhaps humans as well. Mouse models of several p53 activation-associated disorders essentially recapitulate human traits, and inactivation of p53 in these models can alleviate disorder-related phenotypes. In the present review, we focus on how dysfunction of the aforementioned biological processes causes developmental defects via excessive p53 activation. Notably, several disease-related genes exert a pleiotropic effect on those cellular processes, which may modulate the magnitude of p53 activation and establish or disrupt regulatory loops. Finally, we discuss potential therapeutic strategies for genetic disorders associated with p53 misactivation.

Insights into the expanding phenotypic spectrum of inherited disorders of biogenic amines.

Inherited disorders of neurotransmitter metabolism are rare neurodevelopmental diseases presenting with movement disorders and global developmental delay. This study presents the results of the first standardized deep phenotyping approach and describes the clinical and biochemical presentation at disease onset as well as diagnostic approaches of 275 patients from the registry of the International Working Group on Neurotransmitter related Disorders. The results reveal an increased rate of prematurity, a high risk for being small for gestational age and for congenital microcephaly in some disorders. Age at diagnosis and the diagnostic delay are influenced by the diagnostic methods applied and by disease-specific symptoms. The timepoint of investigation was also a significant factor: delay to diagnosis has decreased in recent years, possibly due to novel diagnostic approaches or raised awareness. Although each disorder has a specific biochemical pattern, we observed confounding exceptions to the rule. The data provide comprehensive insights into the phenotypic spectrum of neurotransmitter disorders.

Congenital hepatic fibrosis and its mimics: a clinicopathologic study of 19 cases at a single institution.

BACKGROUND: Congenital hepatic fibrosis (CHF) is a rare inherited form of ductal plate malformation associated with polycystic kidney disease. The diagnosis requires histopathologic confirmation, but can be challenging to distinguish from other undefined fibrocystic liver diseases. We aimed to describe the clinicopathologic features of congenital hepatic fibrosis (CHF), with comparisons to other entities that may clinically and/or histologically mimic CHF. METHODS: Nineteen cases that carried a clinical and/or histologic impression of CHF were identified at our institution, of which the histology was reassessed and reappraised into two categories: CHF (n=13) and mimics (n=6). The clinicopathologic features between the two groups were analyzed and compared. RESULTS: The CHF group was further sub-classified into those with clinical suspicion (CHF-c, n=8) and those as incidental histology findings (CHF-i, n=5). Patients of CHF-i were much older than CHF-c or mimics (P<0.05). Male and female were equally affected. Six of 8 CHF-c (66.7%) had concurrent kidney diseases, including 5 polycystic kidney diseases. Five of 6 mimics (83.3%) had various kidney diseases, including nephronophthisis, Alport syndrome, renal agenesis, and nephrolithiasis. None of the CHF-i patients had kidney disease, but 3 were associated with hepatic carcinomas. Histology analysis demonstrated characteristic triads (bile duct abnormalities, portal vein hypoplasia, and fibrosis) in all CHF cases. One mimic had paucity of intrahepatic bile ducts, while the other 5 mimics showed abnormal portal veins and nodular regenerative hyperplasia consistent with hepatoportal sclerosis (HPS). CONCLUSIONS: Our study demonstrates classic histology triad of CHF despite a wide spectrum of clinical presentations. HPS is unexpectedly a clinical mimicker of CHF, which can be distinguished histologically.

Differential Domain Distribution of gnomAD- and Disease-Linked Connexin Missense Variants.

Twenty-one human genes encode connexins, a family of homologous proteins making gap junction (GJ) channels, which mediate direct intercellular communication to synchronize tissue/organ activities. Genetic variants in more than half of the connexin genes are associated with dozens of different Mendelian inherited diseases. With rapid advances in DNA sequencing technology, more variants are being identified not only in families and individuals with diseases but also in people in the general population without any apparent linkage to Mendelian inherited diseases. Nevertheless, it remains challenging to classify the pathogenicity of a newly identified connexin variant. Here, we analyzed the disease- and Genome Aggregation Database (gnomAD, as a proxy of the general population)-linked variants in the coding region of the four disease-linked α connexin genes. We found that the most abundant and position-sensitive missense variants showed distinct domain distribution preference between disease- and gnomAD-linked variants. Plotting missense variants on topological and structural models revealed that disease-linked missense variants are highly enriched on the structurally stable/resolved domains, especially the pore-lining domains, while the gnomAD-linked missense variants are highly enriched in the structurally unstable/unresolved domains, especially the carboxyl terminus. In addition, disease-linked variants tend to be on highly conserved residues and those positions show evolutionary co-variation, while the gnomAD-linked missense variants are likely on less conserved residue positions and on positions without co-variation. Collectively, the revealed distribution patterns of disease- and gnomAD-linked missense variants further our understanding of the GJ structure-biological function relationship, which is valuable for classifying the pathogenicity of newly identified connexin variants.

ecRESCUE: a novel ecDHFR-regulated RESCUE system with reduced RNA off-targeting activity.

The currently available RESCUE RNA base editing system demonstrates considerable potential for the treatment of genetic diseases at the transcriptional level. However, the relatively high incidence of off-target events hampers the precise RNA editing, thereby limiting its use in the clinical setting. This study describes a new RNA base editing method, named ecRESCUE, which utilizes inducible stabilization of the protein ecDHFR DD fused at the C-terminal of the original RESCUE system. In vitro experiments in 293T cells showed that the ecRESCUE editor markedly reduced the incidence of off-target single nucleotide polymorphisms without affecting the RNA A-to-I and C-to-U base editing efficiency. Altogether, these results demonstrate that the inducible ecRESCUE system represents an attractive approach to regulate and improve the outcome of the available RNA base editor with reduced off-targeting activity. Video Abstract.

Ten Years of EWAS.

Epigenome-wide association study (EWAS) has been applied to analyze DNA methylation variation in complex diseases for a decade, and epigenome as a research target has gradually become a hot topic of current studies. The DNA methylation microarrays, next-generation, and third-generation sequencing technologies have prepared a high-quality platform for EWAS. Here, the progress of EWAS research is reviewed, its contributions to clinical applications, and mainly describe the achievements of four typical diseases. Finally, the challenges encountered by EWAS and make bold predictions for its future development are presented.

Nonsense-mediated decay is highly stable across individuals and tissues.

Precise interpretation of the effects of rare protein-truncating variants (PTVs) is important for accurate determination of variant impact. Current methods for assessing the ability of PTVs to induce nonsense-mediated decay (NMD) focus primarily on the position of the variant in the transcript. We used RNA sequencing of the Genotype Tissue Expression v.8 cohort to compute the efficiency of NMD using allelic imbalance for 2,320 rare (genome aggregation database minor allele frequency ≤ 1%) PTVs across 809 individuals in 49 tissues. We created an interpretable predictive model using penalized logistic regression in order to evaluate the comprehensive influence of variant annotation, tissue, and inter-individual variation on NMD. We found that variant position, allele frequency, the inclusion of ultra-rare and singleton variants, and conservation were predictive of allelic imbalance. Furthermore, we found that NMD effects were highly concordant across tissues and individuals. Due to this high consistency, we demonstrate in silico that utilizing peripheral tissues or cell lines provides accurate prediction of NMD for PTVs.

Urine-Derived Epithelial Cells as Models for Genetic Kidney Diseases.

Epithelial cells exfoliated in human urine can include cells anywhere from the urinary tract and kidneys; however, podocytes and proximal tubular epithelial cells (PTECs) are by far the most relevant cell types for the study of genetic kidney diseases. When maintained in vitro, they have been proven extremely valuable for discovering disease mechanisms and for the development of new therapies. Furthermore, cultured patient cells can individually represent their human sources and their specific variants for personalized medicine studies, which are recently gaining much interest. In this review, we summarize the methodology for establishing human podocyte and PTEC cell lines from urine and highlight their importance as kidney disease cell models. We explore the well-established and recent techniques of cell isolation, quantification, immortalization and characterization, and we describe their current and future applications.

Interpretable prioritization of splice variants in diagnostic next-generation sequencing.

A critical challenge in genetic diagnostics is the computational assessment of candidate splice variants, specifically the interpretation of nucleotide changes located outside of the highly conserved dinucleotide sequences at the 5' and 3' ends of introns. To address this gap, we developed the Super Quick Information-content Random-forest Learning of Splice variants (SQUIRLS) algorithm. SQUIRLS generates a small set of interpretable features for machine learning by calculating the information-content of wild-type and variant sequences of canonical and cryptic splice sites, assessing changes in candidate splicing regulatory sequences, and incorporating characteristics of the sequence such as exon length, disruptions of the AG exclusion zone, and conservation. We curated a comprehensive collection of disease-associated splice-altering variants at positions outside of the highly conserved AG/GT dinucleotides at the termini of introns. SQUIRLS trains two random-forest classifiers for the donor and for the acceptor and combines their outputs by logistic regression to yield a final score. We show that SQUIRLS transcends previous state-of-the-art accuracy in classifying splice variants as assessed by rank analysis in simulated exomes, and is significantly faster than competing methods. SQUIRLS provides tabular output files for incorporation into diagnostic pipelines for exome and genome analysis, as well as visualizations that contextualize predicted effects of variants on splicing to make it easier to interpret splice variants in diagnostic settings.

Scaling national and international improvement in virtual gene panel curation via a collaborative approach to discordance resolution.

Clinical validity assessments of gene-disease associations underpin analysis and reporting in diagnostic genomics, and yet wide variability exists in practice, particularly in use of these assessments for virtual gene panel design and maintenance. Harmonization efforts are hampered by the lack of agreed terminology, agreed gene curation standards, and platforms that can be used to identify and resolve discrepancies at scale. We undertook a systematic comparison of the content of 80 virtual gene panels used in two healthcare systems by multiple diagnostic providers in the United Kingdom and Australia. The process was enabled by a shared curation platform, PanelApp, and resulted in the identification and review of 2,144 discordant gene ratings, demonstrating the utility of sharing structured gene-disease validity assessments and collaborative discordance resolution in establishing national and international consensus.