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BackgroundClinical exome sequencing typically achieves diagnostic yields of 30%–57.5% in individuals with monogenic rare diseases. Undiagnosed diseases programmes implement strategies to improve diagnostic outcomes for these individuals.AimWe share the lessons learnt from the first 3 years of the Undiagnosed Diseases Program-Victoria, an Australian programme embedded within a clinical genetics service in the state of Victoria with a focus on paediatric rare diseases.MethodsWe enrolled families who remained without a diagnosis after clinical genomic (panel, exome or genome) sequencing between 2016 and 2018. We used family-based exome sequencing (family ES), family-based genome sequencing (family GS), RNA sequencing (RNA-seq) and high-resolution chromosomal microarray (CMA) with research-based analysis.ResultsIn 150 families, we achieved a diagnosis or strong candidate in 64 (42.7%) (37 in known genes with a consistent phenotype, 3 in known genes with a novel phenotype and 24 in novel disease genes). Fifty-four diagnoses or strong candidates were made by family ES, six by family GS with RNA-seq, two by high-resolution CMA and two by data reanalysis.ConclusionWe share our lessons learnt from the programme. Flexible implementation of multiple strategies allowed for scalability and response to the availability of new technologies. Broad implementation of family ES with research-based analysis showed promising yields post a negative clinical singleton ES. RNA-seq offered multiple benefits in family ES-negative populations. International data sharing strategies were critical in facilitating collaborations to establish novel disease–gene associations. Finally, the integrated approach of a multiskilled, multidisciplinary team was fundamental to having diverse perspectives and strategic decision-making.

Background Our primary aim was to evaluate the systematic reanalysis of singleton exome sequencing (ES) data for unsolved cases referred for any indication. A secondary objective was to undertake a literature review of studies examining the reanalysis of genomic data from unsolved cases. Methods We examined data from 58 unsolved cases referred between June 2016 and March 2017. First reanalysis at 4–13 months after the initial report considered genes newly associated with disease since the original analysis; second reanalysis at 9–18 months considered all disease‐associated genes. At 25–34 months we reviewed all cases and the strategies which solved them. Results Reanalysis of existing ES data alone at two timepoints did not yield new diagnoses. Over the same timeframe, 10 new diagnoses were obtained (17%) from additional strategies, such as microarray detection of copy number variation, repeat sequencing to improve coverage, and trio sequencing. Twenty‐seven peer‐reviewed articles were identified on the literature review, with a median new diagnosis rate via reanalysis of 15% and median reanalysis timeframe of 22 months. Conclusion Our findings suggest that an interval of greater than 18 months from the original report may be optimal for reanalysis. We also recommend a multi‐faceted strategy for cases remaining unsolved after singleton ES. We evaluated the systematic reanalysis of singleton exome sequencing (ES) data for unsolved cases and undertook a literature review of studies examining reanalysis of genomic data from unsolved cases. Our findings suggest that an interval of greater than 18 months from the original report may be optimal for reanalysis. We also recommend a multi‐faceted strategy for cases remaining unsolved after singleton ES.

The purpose of the study was to implement and prospectively evaluate the outcomes of a rapid genomic diagnosis program at two pediatric tertiary centers. Rapid singleton whole-exome sequencing (rWES) was performed in acutely unwell pediatric patients with suspected monogenic disorders. Laboratory and clinical barriers to implementation were addressed through continuous multidisciplinary review of process parameters. Diagnostic and clinical utility and cost-effectiveness of rWES were assessed. Of 40 enrolled patients, 21 (52.5%) received a diagnosis, with median time to report of 16 days (range 9–109 days). A result was provided during the first hospital admission in 28 of 36 inpatients (78%). Clinical management changed in 12 of the 21 diagnosed patients (57%), including the provision of lifesaving treatment, avoidance of invasive biopsies, and palliative care guidance. The cost per diagnosis was AU$13,388 (US$10,453). Additional cost savings from avoidance of planned tests and procedures and reduced length of stay are estimated to be around AU$543,178 (US$424,101). The clear relative advantage of rWES, joint clinical and laboratory leadership, and the creation of a multidisciplinary “rapid team” were key to successful implementation. Rapid genomic testing in acute pediatrics is not only feasible but also cost-effective, and has high diagnostic and clinical utility. It requires a whole-of-system approach for successful implementation.

Purpose Cost-effectiveness evaluations of first-line genomic sequencing (GS) in the diagnosis of children with genetic conditions are limited by the lack of well-defined comparative cohorts. We sought to evaluate the cost-effectiveness of early GS in pediatric patients with complex monogenic conditions compared with a matched historical cohort. Methods Data, including investigation costs, were collected in a prospective cohort of 92 pediatric patients undergoing singleton GS over an 18-month period (2016–2017) with two of the following: a condition with high mortality, multisystem disease involving three or more organs, or severe limitation of daily function. Comparative data were collected in a matched historical cohort who underwent traditional investigations in the years 2012–2013. Results GS yielded a diagnosis in 42% while traditional investigations yielded a diagnosis in 23% ( p  = 0.003). A change in management was experienced by 74% of patients diagnosed following GS, compared with 32% diagnosed following traditional investigations. Singleton GS at a cost of AU$3100 resulted in a mean saving per person of AU$3602 (95% confidence interval [CI] AU$2520–4685). Cost savings occurred across all investigation subtypes and were only minimally offset by clinical management costs. Conclusion GS in complex pediatric patients saves significant costs and doubles the diagnostic yield of traditional approaches.

PurposeBinding proteins (G-proteins) mediate signalling pathways involved in diverse cellular functions and comprise Gα and Gβγ units. Human diseases have been reported for all five Gβ proteins. A de novo missense variant in GNB2 was recently reported in one individual with developmental delay/intellectual disability (DD/ID) and dysmorphism. We aim to confirm GNB2 as a neurodevelopmental disease gene, and elucidate the GNB2-associated neurodevelopmental phenotype in a patient cohort.MethodsWe discovered a GNB2 variant in the index case via exome sequencing and sought individuals with GNB2 variants via international data-sharing initiatives. In silico modelling of the variants was assessed, along with multiple lines of evidence in keeping with American College of Medical Genetics and Genomics guidelines for interpretation of sequence variants.ResultsWe identified 12 unrelated individuals with five de novo missense variants in GNB2, four of which are recurrent: p.(Ala73Thr), p.(Gly77Arg), p.(Lys89Glu) and p.(Lys89Thr). All individuals have DD/ID with variable dysmorphism and extraneurologic features. The variants are located at the universally conserved shared interface with the Gα subunit, which modelling suggests weaken this interaction.ConclusionMissense variants in GNB2 cause a congenital neurodevelopmental disorder with variable syndromic features, broadening the spectrum of multisystem phenotypes associated with variants in genes encoding G-proteins.

Background Only half of individuals with suspected rare diseases receive a genetic diagnosis following genomic testing. A genetic diagnosis allows access to appropriate care, restores reproductive confidence and reduces the number of potentially unnecessary interventions. A major barrier is the lack of disease agnostic functional tests suitable for implementation in routine diagnostics that can provide evidence supporting pathogenicity of novel variants, especially those refractory to RNA sequencing. Methods Focusing on mitochondrial disease, we describe an untargeted mass-spectrometry based proteomics pipeline that can quantify proteins encoded by > 50% of Mendelian disease genes and > 80% of known mitochondrial disease genes in clinically relevant sample types, including peripheral blood mononuclear cells (PBMCs). In total we profiled > 90 individuals including undiagnosed individuals suspected of mitochondrial disease and a supporting cohort of disease controls harbouring pathogenic variants in nuclear and mitochondrial genes. Proteomics data were benchmarked against pathology accredited respiratory chain enzymology to assess the performance of proteomics as a functional test. Proteomics testing was subsequently applied to individuals with suspected mitochondrial disease, including a critically ill infant with a view toward rapid interpretation of variants identified in ultra-rapid genome sequencing. Results Proteomics testing provided evidence to support variant pathogenicity in 83% of individuals in a cohort with confirmed mitochondrial disease, outperforming clinical respiratory chain enzymology. Freely available bioinformatic tools and criteria developed for this study ( https://rdms.app/ ) allow mitochondrial dysfunction to be identified in proteomics data with high confidence. Application of proteomics to undiagnosed individuals led to 6 additional diagnoses, including a mitochondrial phenocopy disorder, highlighting the disease agnostic nature of proteomics. Use of PBMCs as a sample type allowed rapid return of proteomics data supporting pathogenicity of novel variants identified through ultra-rapid genome sequencing in as little as 54 h. Conclusions This study provides a framework to support the integration of a single untargeted proteomics test into routine diagnostic practice for the diagnosis of mitochondrial and potentially other rare genetic disorders in clinically actionable timelines, offering a paradigm shift for the functional validation of genetic variants.

The ability of innate immune cells to sense and respond to impending danger varies by anatomical location. The liver is considered tolerogenic but is still capable of mounting a successful immune response to clear various infections. To understand whether hepatic immune cells tune their response to different infectious challenges, we probed mononuclear cells purified from human healthy and diseased livers with distinct pathogen-associated molecules. We discovered that only the TLR8 agonist ssRNA40 selectively activated liver-resident innate immune cells to produce substantial quantities of IFN-γ. We identified CD161(Bright) mucosal-associated invariant T (MAIT) and CD56(Bright) NK cells as the responding liver-resident innate immune cells. Their activation was not directly induced by the TLR8 agonist but was dependent on IL-12 and IL-18 production by ssRNA40-activated intrahepatic monocytes. Importantly, the ssRNA40-induced cytokine-dependent activation of MAIT cells mirrored responses induced by bacteria, i.e., generating a selective production of high levels of IFN-γ, without the concomitant production of TNF-α or IL-17A. The intrahepatic IFN-γ production could be detected not only in healthy livers, but also in HBV- or HCV-infected livers. In conclusion, the human liver harbors a network of immune cells able to modulate their immunological responses to different pathogen-associated molecules. Their ability to generate a strong production of IFN-γ upon stimulation with TLR8 agonist opens new therapeutic opportunities for the treatment of diverse liver pathologies.

Background Representing biological networks as graphs is a powerful approach to reveal underlying patterns, signatures, and critical components from high-throughput biomolecular data. However, graphs do not natively capture the multi-way relationships present among genes and proteins in biological systems. Hypergraphs are generalizations of graphs that naturally model multi-way relationships and have shown promise in modeling systems such as protein complexes and metabolic reactions. In this paper we seek to understand how hypergraphs can more faithfully identify, and potentially predict, important genes based on complex relationships inferred from genomic expression data sets. Results We compiled a novel data set of transcriptional host response to pathogenic viral infections and formulated relationships between genes as a hypergraph where hyperedges represent significantly perturbed genes, and vertices represent individual biological samples with specific experimental conditions. We find that hypergraph betweenness centrality is a superior method for identification of genes important to viral response when compared with graph centrality. Conclusions Our results demonstrate the utility of using hypergraphs to represent complex biological systems and highlight central important responses in common to a variety of highly pathogenic viruses.

Dietary fibre positively influences gut microbiome composition, enhancing the metabolism of dietary flavonoids to produce bioactive metabolites. These synergistic activities facilitate the beneficial effects of dietary flavonoids on cardiometabolic health parameters. The aims of this study were to investigate whether isoquercetin (a major dietary flavonoid) and inulin (soluble fibre), either alone or in combination could improve features of the metabolic syndrome. Following a 1 week acclimatization, male C57BL6 mice (6–8 weeks) were randomly assigned to; (i) normal chow diet (n = 10), (ii) high fat (HF) diet (n = 10), (iii) HF diet + 0.05% isoquercetin (n = 10), (iv) HF diet + 5% inulin, or (v) HF diet + 0.05% isoquercetin + 5% inulin (n = 10). Body weight and food intake were measured weekly. At 12 weeks, glucose and insulin tolerance tests were performed, and blood, faecal samples, liver, skeletal muscle and adipose tissue were collected. At 12 weeks, mice on the HF diet had significantly elevated body weights as well as impaired glucose tolerance and insulin sensitivity compared to the normal chow mice. Supplementation with either isoquercetin or inulin had no effect, however mice receiving the combination had attenuated weight gain, improved glucose tolerance and insulin sensitivity, reduced hepatic lipid accumulation, adipocyte hypertrophy, circulating leptin and adipose FGF21 levels, compared to mice receiving the HF diet. Additionally, mice on the combination diet had improvements in the composition and functionality of their gut microbiome as well as production of short chain fatty acids. In conclusion, long-term supplementation with the dietary flavonoid isoquercetin and the soluble fibre inulin can attenuate development of the metabolic syndrome in mice fed a high fat diet. This protective effect appears to be mediated, in part, through beneficial changes to the microbiome.