Transcriptome-directed analysis for Mendelian disease diagnosis overcomes limitations of conventional genomic testing

Diagnostic work-up in malformations of cortical development

Malformations of cortical development (MCDs) represent a heterogeneous spectrum of disorders characterized by atypical development of the cerebral cortex. MCDs are most often diagnosed on the basis of imaging, although subtle lesions, such as focal cortical dysplasia, may only be revealed on neuropathology. Different subtypes have been defined, including lissencephaly, heterotopia, cobblestone malformation, polymicrogyria, and dysgyria. Many MCDs are of genetic origin, although acquired factors, such as congenital cytomegalovirus infections and twinning sequence, can lead to similar phenotypes. In this narrative review, we provide an overview of the diagnostic approach to MCDs, which is illustrated with clinical vignettes, on diagnostic pitfalls such as somatic mosaicism and consanguinity, and recognizable phenotypes on imaging, such as tubulinopathies, the lissencephaly spectrum, tuberous sclerosis complex, and FLNA-related periventricular nodular heterotopia.

Impact of genome build on RNA-seq interpretation and diagnostics

Transcriptomics is a powerful tool for unraveling the molecular effects of genetic variants and disease diagnosis. Prior studies have demonstrated that choice of genome build impacts variant interpretation and diagnostic yield for genomic analyses. To identify the extent genome build also impacts transcriptomics analyses, we studied the effect of the hg19, hg38, and CHM13 genome builds on expression quantification and outlier detection in 386 rare disease and familial control samples from both the Undiagnosed Diseases Network and Genomics Research to Elucidate the Genetics of Rare Disease Consortium. Across six routinely collected biospecimens, 61% of quantified genes were not influenced by genome build. However, we identified 1,492 genes with build-dependent quantification, 3,377 genes with build-exclusive expression, and 9,077 genes with annotation-specific expression across six routinely collected biospecimens, including 566 clinically relevant and 512 known OMIM genes. Further, we demonstrate that between builds for a given gene, a larger difference in quantification is well correlated with a larger change in expression outlier calling. Combined, we provide a database of genes impacted by build choice and recommend that transcriptomics-guided analyses and diagnoses are cross referenced with these data for robustness.

Exploring the complexity of systemic sclerosis etiology by trio whole genome sequencing

Systemic sclerosis (SSc) is a heterogeneous rare autoimmune fibrosing disorder affecting connective tissue. The etiology of systemic sclerosis is largely unknown and many genes have been suggested as susceptibility loci of modest impact by genome-wide association study (GWAS). Multiple factors can contribute to the pathological process of the disease, which makes it more difficult to identify possible disease-causing genetic alterations. In this study, we have applied whole genome sequencing (WGS) in 101 indexed family trios, supplemented with transcriptome sequencing on cultured fibroblast cells of four patients and five family controls where available. Single nucleotide variants (SNVs) and copy number variants (CNVs) were examined, with emphasis on de novo variants. We also performed enrichment test for rare variants in candidate genes previously proposed in association with systemic sclerosis. We identified 42 exonic and 34 ncRNA de novo SNV changes in 101 trios, from a total of over 6000 de novo variants genome wide. We observed higher than expected de novo variants in PRKXP1 gene. We also observed such phenomenon along with increased expression in patient group in NEK7 gene. Additionally, we also observed significant enrichment of rare variants in candidate genes in the patient cohort, further supporting the complexity/multi-factorial etiology of systemic sclerosis. Our findings identify new candidate genes including PRKXP1 and NEK7 for future studies in SSc. We observed rare variant enrichment in candidate genes previously proposed in association with SSc, which suggest more efforts should be pursued to further investigate possible pathogenetic mechanisms associated with those candidate genes.

Genome and RNA sequencing were essential to reveal cryptic intronic variants associated to defective ATP6AP1 mRNA processing

The diagnosis of Mendelian disorders has notably advanced with integration of whole exome and genome sequencing (WES and WGS) in clinical practice. However, challenges in variant interpretation and uncovered variants by WES still leave a substantial percentage of patients undiagnosed. In this context, integrating RNA sequencing (RNA-seq) improves diagnostic workflows, particularly for WES inconclusive cases. Additionally, functional studies are often necessary to elucidate the impact of prioritized variants on gene expression and protein function. Our study focused on three unrelated male patients (P1-P3) with ATP6AP1-CDG (congenital disorder of glycosylation), presenting with intellectual disability and varying degrees of hepatopathy, glycosylation defects, and an initially inconclusive diagnosis through WES. Subsequent RNA-seq was pivotal in identifying the underlying genetic causes in P1 and P2, detecting ATP6AP1 underexpression and aberrant splicing. Molecular studies in fibroblasts confirmed these findings and identified the rare intronic variants c.289-233C > T and c.289-289G > A in P1 and P2, respectively. Trio-WGS also revealed the variant c.289-289G > A in P3, which was a de novo change in both patients. Functional assays expressing the mutant alleles in HAP1 cells demonstrated the pathogenic impact of these variants by reproducing the splicing alterations observed in patients. Our study underscores the role of RNA-seq and WGS in enhancing diagnostic rates for genetic diseases such as CDG, providing new insights into ATP6AP1-CDG molecular bases by identifying the first two deep intronic variants in this X-linked gene. Additionally, our study highlights the need to integrate RNA-seq and WGS, followed by functional validation, in routine diagnostics for a comprehensive evaluation of patients with an unidentified molecular etiology.

Reanalysis of RNA sequencing data ends diagnostic odyssey and expands the phenotypic spectrum of congenital titinopathy

Although next-generation sequencing has enabled diagnoses for many patients with Mendelian disorders, the majority remain undiagnosed. Here, we present a sibling pair who were clinically diagnosed with Escobar syndrome, however targeted gene testing was negative. Exome sequencing (ES), and later genome sequencing (GS), revealed compound heterozygous TTN variants in both siblings, a maternally inherited frameshift variant [(NM_133378.4):c.36812del; p.(Asp12271Valfs*10)], and a paternally inherited missense variant [(NM_133378.4):c.12322G > A; p.(Asp4108Asn)]. This result was considered nondiagnostic due to poor clinical fit and limited pathogenicity evidence for the missense variant of uncertain significance (VUS). Following initial nondiagnostic RNA sequencing (RNAseq) on muscle and further pursuit of other variants detected on the ES/GS, a reanalysis of noncanonical splice sites in the muscle transcriptome identified an out-of-frame exon retraction in TTN, near the known VUS. Interim literature included reports of patients with similar TTN variants who had phenotypic concordance with the siblings, and a diagnosis of a congenital titinopathy was given 4 years after the TTN variants had been initially reported. This report highlights the value of reanalysis of RNAseq with a different approach, expands the phenotypic spectrum of congenital titinopathy and also illustrates how a perceived phenotypic mismatch, and failure to consider known variants, can result in a prolongation of the diagnostic journey.

The expanding diagnostic toolbox for rare genetic diseases

Genomic technologies, such as targeted, exome and short-read genome sequencing approaches, have revolutionized the care of patients with rare genetic diseases. However, more than half of patients remain without a diagnosis. Emerging approaches from research-based settings such as long-read genome sequencing and optical genome mapping hold promise for improving the identification of disease-causal genetic variants. In addition, new omic technologies that measure the transcriptome, epigenome, proteome or metabolome are showing great potential for variant interpretation. As genetic testing options rapidly expand, the clinical community needs to be mindful of their individual strengths and limitations, as well as remaining challenges, to select the appropriate diagnostic test, correctly interpret results and drive innovation to address insufficiencies. If used effectively - through truly integrative multi-omics approaches and data sharing - the resulting large quantities of data from these established and emerging technologies will greatly improve the interpretative power of genetic and genomic diagnostics for rare diseases.

Combined exome and whole transcriptome sequencing identifies a de novo intronic SRCAP variant causing DEHMBA syndrome with severe sleep disorder

Rare heterozygous variants in exons 33-34 of the SRCAP gene are associated with Floating-Harbor syndrome and have a dominant-negative mechanism of action. At variance, heterozygous null alleles falling in other parts of the same gene cause developmental delay, hypotonia, musculoskeletal defects, and behavioral abnormalities (DEHMBA) syndrome. We report an 18-year-old man with DEHMBA syndrome and obstructive sleep apnea, who underwent exome sequencing (ES) and whole transcriptome sequencing (WTS) on peripheral blood. Trio analysis prioritized the de novo heterozygous c.5658+5 G > A variant. WTS promptly demostrated four different abnormal transcripts affecting >40% of the reads, three of which leading to a frameshift. This study demonstrated the efficacy of a combined ES-WTS approach in solving undiagnosed cases. We also speculated that sleep respiratory disorder may be an underdiagnosed complication of DEHMBA syndrome.

Genetic Evaluation for Monogenic Disorders of Low Bone Mass and Increased Bone Fragility: What Clinicians Need to Know

PURPOSE OF REVIEW

The purpose of this review is to outline the principles of clinical genetic testing and to provide practical guidance to clinicians in navigating genetic testing for patients with suspected monogenic forms of osteoporosis.

RECENT FINDINGS

Heritability assessments and genome-wide association studies have clearly shown the significant contributions of genetic variations to the pathogenesis of osteoporosis. Currently, over 50 monogenic disorders that present primarily with low bone mass and increased risk of fractures have been described. The widespread availability of clinical genetic testing offers a valuable opportunity to correctly diagnose individuals with monogenic forms of osteoporosis, thus instituting appropriate surveillance and treatment. Clinical genetic testing may identify the appropriate diagnosis in a subset of patients with low bone mass, multiple or unusual fractures, and severe or early-onset osteoporosis, and thus clinicians should be aware of how to incorporate such testing into their clinical practices.

The clinical utility and diagnostic implementation of human subject cell transdifferentiation followed by RNA sequencing

RNA sequencing (RNA-seq) has recently been used in translational research settings to facilitate diagnoses of Mendelian disorders. A significant obstacle for clinical laboratories in adopting RNA-seq is the low or absent expression of a significant number of disease-associated genes/transcripts in clinically accessible samples. As this is especially problematic in neurological diseases, we developed a clinical diagnostic approach that enhanced the detection and evaluation of tissue-specific genes/transcripts through fibroblast-to-neuron cell transdifferentiation. The approach is designed specifically to suit clinical implementation, emphasizing simplicity, cost effectiveness, turnaround time, and reproducibility. For clinical validation, we generated induced neurons (iNeurons) from 71 individuals with primary neurological phenotypes recruited to the Undiagnosed Diseases Network. The overall diagnostic yield was 25.4%. Over a quarter of the diagnostic findings benefited from transdifferentiation and could not be achieved by fibroblast RNA-seq alone. This iNeuron transcriptomic approach can be effectively integrated into diagnostic whole-transcriptome evaluation of individuals with genetic disorders.

Novel molecular mechanism in Malan syndrome uncovered through genome sequencing reanalysis, exon-level Array, and RNA sequencing

The NFIX gene encodes a DNA-binding protein belonging to the nuclear factor one (NFI) family of transcription factors. Pathogenic variants of NFIX are associated with two autosomal dominant Mendelian disorders, Malan syndrome (MIM 614753) and Marshall-Smith syndrome (MIM 602535), which are clinically distinct due to different disease-causing mechanisms. NFIX variants associated with Malan syndrome are missense variants mostly located in exon 2 encoding the N-terminal DNA binding and dimerization domain or are protein-truncating variants that trigger nonsense-mediated mRNA decay (NMD) resulting in NFIX haploinsufficiency. NFIX variants associated with Marshall-Smith syndrome are protein-truncating and are clustered between exons 6 and 10, including a recurrent Alu-mediated deletion of exons 6 and 7, which can escape NMD. The more severe phenotype of Marshall-Smith syndrome is likely due to a dominant-negative effect of these protein-truncating variants that escape NMD. Here, we report a child with clinical features of Malan syndrome who has a de novo NFIX intragenic duplication. Using genome sequencing, exon-level microarray analysis, and RNA sequencing, we show that this duplication encompasses exons 6 and 7 and leads to NFIX haploinsufficiency. To our knowledge, this is the first reported case of Malan Syndrome caused by an intragenic NFIX duplication.

Current genetic diagnostics in inborn errors of immunity

New technologies in genetic diagnostics have revolutionized the understanding and management of rare diseases. This review highlights the significant advances and latest developments in genetic diagnostics in inborn errors of immunity (IEI), which encompass a diverse group of disorders characterized by defects in the immune system, leading to increased susceptibility to infections, autoimmunity, autoinflammatory diseases, allergies, and malignancies. Various diagnostic approaches, including targeted gene sequencing panels, whole exome sequencing, whole genome sequencing, RNA sequencing, or proteomics, have enabled the identification of causative genetic variants of rare diseases. These technologies not only facilitated the accurate diagnosis of IEI but also provided valuable insights into the underlying molecular mechanisms. Emerging technologies, currently mainly used in research, such as optical genome mapping, single cell sequencing or the application of artificial intelligence will allow even more insights in the aetiology of hereditary immune defects in the near future. The integration of genetic diagnostics into clinical practice significantly impacts patient care. Genetic testing enables early diagnosis, facilitating timely interventions and personalized treatment strategies. Additionally, establishing a genetic diagnosis is necessary for genetic counselling and prognostic assessments. Identifying specific genetic variants associated with inborn errors of immunity also paved the way for the development of targeted therapies and novel therapeutic approaches. This review emphasizes the challenges related with genetic diagnosis of rare diseases and provides future directions, specifically focusing on IEI. Despite the tremendous progress achieved over the last years, several obstacles remain or have become even more important due to the increasing amount of genetic data produced for each patient. This includes, first and foremost, the interpretation of variants of unknown significance (VUS) in known IEI genes and of variants in genes of unknown significance (GUS). Although genetic diagnostics have significantly contributed to the understanding and management of IEI and other rare diseases, further research, exchange between experts from different clinical disciplines, data integration and the establishment of comprehensive guidelines are crucial to tackle the remaining challenges and maximize the potential of genetic diagnostics in the field of rare diseases, such as IEI.

Identification of Synonymous Pathogenic Variants in Monogenic Disorders by Integrating Exome with Transcriptome Sequencing

Exome sequencing is becoming a first-tier clinical diagnostic test for Mendelian diseases, drastically reducing the time and cost of diagnostic odyssey and improving the diagnosis rate. Despite its success, exome sequencing faces practical challenges in assessing the pathogenicity of numerous intronic and synonymous variants, leaving a significant proportion of patients undiagnosed. In this study, a whole-blood transcriptome database was constructed that showed the expression profile of 2981 Online Mendelian Inheritance in Man disease genes in blood samples. Meanwhile, a workflow integrating exome sequencing, blood transcriptome sequencing, and in silico prediction tools to identify and validate splicing-altering intronic or synonymous variants was proposed. Following this pipeline, seven synonymous variants in eight patients were discovered. Of these, the functional evidence of c.981G>A (PIGN), c.1161A>G (ALPL), c.858G>A (ATP6AP2), and c.1011G>T (MTHFR) have not been reported previously. RNA sequencing validation confirmed that these variants induced aberrant splicing, expanding the disease-causing variant spectrum of these genes. Overall, this study shows the feasibility of combining multi-omics data to identify splicing-altering variants, especially the power of RNA sequencing. It also reveals that synonymous variants, which often are overlooked in standard diagnostic approaches, comprise an important portion of unresolved genetic diseases.

RNA sequencing and target long-read sequencing reveal an intronic transposon insertion causing aberrant splicing

More than half of cases with suspected genetic disorders remain unsolved by genetic analysis using short-read sequencing such as exome sequencing (ES) and genome sequencing (GS). RNA sequencing (RNA-seq) and long-read sequencing (LRS) are useful for interpretation of candidate variants and detection of structural variants containing repeat sequences, respectively. Recently, adaptive sampling on nanopore sequencers enables target LRS more easily. Here, we present a Japanese girl with premature chromatid separation (PCS)/mosaic variegated aneuploidy (MVA) syndrome. ES detected a known pathogenic maternal heterozygous variant (c.1402-5A>G) in intron 10 of BUB1B (NM_001211.6), a known responsive gene for PCS/MVA syndrome with autosomal recessive inheritance. Minigene splicing assay revealed that almost all transcripts from the c.1402-5G allele have mis-splicing with 4-bp insertion. GS could not detect another pathogenic variant, while RNA-seq revealed abnormal reads in intron 2. To extensively explore variants in intron 2, we performed adaptive sampling and identified a paternal 3.0 kb insertion. Consensus sequence of 16 reads spanning the insertion showed that the insertion consists of Alu and SVA elements. Realignment of RNA-seq reads to the new reference sequence containing the insertion revealed that 16 reads have 5' splice site within the insertion and 3' splice site at exon 3, demonstrating causal relationship between the insertion and aberrant splicing. In addition, immunoblotting showed severely diminished BUB1B protein level in patient derived cells. These data suggest that detection of transcriptomic abnormalities by RNA-seq can be a clue for identifying pathogenic variants, and determination of insert sequences is one of merits of LRS.

Functional genomics and small molecules in mitochondrial neurodevelopmental disorders

Mitochondria are critical for brain development and homeostasis. Therefore, pathogenic variation in the mitochondrial or nuclear genome which disrupts mitochondrial function frequently results in developmental disorders and neurodegeneration at the organismal level. Large-scale application of genome-wide technologies to individuals with mitochondrial diseases has dramatically accelerated identification of mitochondrial disease-gene associations in humans. Multi-omic and high-throughput studies involving transcriptomics, proteomics, metabolomics, and saturation genome editing are providing deeper insights into the functional consequence of mitochondrial genomic variation. Integration of deep phenotypic and genomic data through allelic series continues to uncover novel mitochondrial functions and permit mitochondrial gene function dissection on an unprecedented scale. Finally, mitochondrial disease-gene associations illuminate disease mechanisms and thereby direct therapeutic strategies involving small molecules and RNA-DNA therapeutics. This review summarizes progress in functional genomics and small molecule therapeutics in mitochondrial neurodevelopmental disorders.

Integrating RNA-Seq into genome sequencing workflow enhances the analysis of structural variants causing neurodevelopmental disorders

BACKGROUND

Molecular diagnosis of neurodevelopmental disorders (NDDs) is mainly based on exome sequencing (ES), with a diagnostic yield of 31% for isolated and 53% for syndromic NDD. As sequencing costs decrease, genome sequencing (GS) is gradually replacing ES for genome-wide molecular testing. As many variants detected by GS only are in deep intronic or non-coding regions, the interpretation of their impact may be difficult. Here, we showed that integrating RNA-Seq into the GS workflow can enhance the analysis of the molecular causes of NDD, especially structural variants (SVs), by providing valuable complementary information such as aberrant splicing, aberrant expression and monoallelic expression.

METHODS

We performed trio-GS on a cohort of 33 individuals with NDD for whom ES was inconclusive. RNA-Seq on skin fibroblasts was then performed in nine individuals for whom GS was inconclusive and optical genome mapping (OGM) was performed in two individuals with an SV of unknown significance.

RESULTS

We identified pathogenic or likely pathogenic variants in 16 individuals (48%) and six variants of uncertain significance. RNA-Seq contributed to the interpretation in three individuals, and OGM helped to characterise two SVs.

CONCLUSION

Our study confirmed that GS significantly improves the diagnostic performance of NDDs. However, most variants detectable by GS alone are structural or located in non-coding regions, which can pose challenges for interpretation. Integration of RNA-Seq data overcame this limitation by confirming the impact of variants at the transcriptional or regulatory level. This result paves the way for new routinely applicable diagnostic protocols.

Solving the unsolved genetic epilepsies: Current and future perspectives

Many patients with epilepsy undergo exome or genome sequencing as part of a diagnostic workup; however, many remain genetically unsolved. There are various factors that account for negative results in exome/genome sequencing for patients with epilepsy: (1) the underlying cause is not genetic; (2) there is a complex polygenic explanation; (3) the illness is monogenic but the causative gene remains to be linked to a human disorder; (4) family segregation with reduced penetrance; (5) somatic mosaicism or the complexity of, for example, a structural rearrangement; or (6) limited knowledge or diagnostic tools that hinder the proper classification of a variant, resulting in its designation as a variant of unknown significance. The objective of this review is to outline some of the diagnostic options that lie beyond the exome/genome, and that might become clinically relevant within the foreseeable future. These options include: (1) re-analysis of older exome/genome data as knowledge increases or symptoms change; (2) looking for somatic mosaicism or long-read sequencing to detect low-complexity repeat variants or specific structural variants missed by traditional exome/genome sequencing; (3) exploration of the non-coding genome including disruption of topologically associated domains, long range non-coding RNA, or other regulatory elements; and finally (4) transcriptomics, DNA methylation signatures, and metabolomics as complementary diagnostic methods that may be used in the assessment of variants of unknown significance. Some of these tools are currently not integrated into standard diagnostic workup. However, it is reasonable to expect that they will become increasingly available and improve current diagnostic capabilities, thereby enabling precision diagnosis in patients who are currently undiagnosed.

Combined Bioinformatic and Splicing Analysis of Likely Benign Intronic and Synonymous Variants Reveals Evidence for Pathogenicity

Background

Current clinical variant analysis pipelines focus on coding variants and intronic variants within 10-20 bases of an exon-intron boundary that may affect splicing. The impact of newer splicing prediction algorithms combined with in vitro splicing assays on rare variants currently considered Benign/Likely Benign (B/LB) is unknown.

Methods

Exome sequencing data from 576 pediatric cancer patients enrolled in the Texas KidsCanSeq study were filtered for intronic or synonymous variants absent from population databases, predicted to alter splicing via SpliceAI (>0.20), and scored as potentially deleterious by CADD (>10.0). Total cellular RNA was extracted from monocytes and RT-PCR products analyzed. Subsequently, rare synonymous or intronic B/LB variants in a subset of genes submitted to ClinVar were similarly evaluated. Variants predicted to lead to a frameshifted splicing product were functionally assessed using an in vitro splicing reporter assay in HEK-293T cells.

Results

KidsCanSeq exome data analysis revealed a rare, heterozygous, intronic variant (NM_177438.3(DICER1):c.574-26A>G) predicted by SpliceAI to result in gain of a secondary splice acceptor site. The proband had a personal and family history of pleuropulmonary blastoma consistent with DICER1 syndrome but negative clinical sequencing reports. Proband RNA analysis revealed alternative DICER1 transcripts including the SpliceAI-predicted transcript.Similar bioinformatic analysis of synonymous or intronic B/LB variants (n=31,715) in ClinVar from 61 Mendelian disease genes yielded 18 variants, none of which could be scored by MaxEntScan. Eight of these variants were assessed (DICER1 n=4, CDH1 n=2, PALB2 n=2) using in vitro splice reporter assay and demonstrated abnormal splice products (mean 66%; range 6% to 100%). Available phenotypic information from submitting laboratories demonstrated DICER1 phenotypes in 2 families (1 variant) and breast cancer phenotypes for PALB2 in 3 families (2 variants).

Conclusions

Our results demonstrate the power of newer predictive splicing algorithms to highlight rare variants previously considered B/LB in patients with features of hereditary conditions. Incorporation of SpliceAI annotation of existing variant data combined with either direct RNA analysis or in vitro assays has the potential to identify disease-associated variants in patients without a molecular diagnosis.

Dominant negative variants in KIF5B cause osteogenesis imperfecta via down regulation of mTOR signaling

BACKGROUND

Kinesin motor proteins transport intracellular cargo, including mRNA, proteins, and organelles. Pathogenic variants in kinesin-related genes have been implicated in neurodevelopmental disorders and skeletal dysplasias. We identified de novo, heterozygous variants in KIF5B, encoding a kinesin-1 subunit, in four individuals with osteogenesis imperfecta. The variants cluster within the highly conserved kinesin motor domain and are predicted to interfere with nucleotide binding, although the mechanistic consequences on cell signaling and function are unknown.

METHODS

To understand the in vivo genetic mechanism of KIF5B variants, we modeled the p.Thr87Ile variant that was found in two patients in the C. elegans ortholog, unc-116, at the corresponding position (Thr90Ile) by CRISPR/Cas9 editing and performed functional analysis. Next, we studied the cellular and molecular consequences of the recurrent p.Thr87Ile variant by microscopy, RNA and protein analysis in NIH3T3 cells, primary human fibroblasts and bone biopsy.

RESULTS

C. elegans heterozygous for the unc-116 Thr90Ile variant displayed abnormal body length and motility phenotypes that were suppressed by additional copies of the wild type allele, consistent with a dominant negative mechanism. Time-lapse imaging of GFP-tagged mitochondria showed defective mitochondria transport in unc-116 Thr90Ile neurons providing strong evidence for disrupted kinesin motor function. Microscopy studies in human cells showed dilated endoplasmic reticulum, multiple intracellular vacuoles, and abnormal distribution of the Golgi complex, supporting an intracellular trafficking defect. RNA sequencing, proteomic analysis, and bone immunohistochemistry demonstrated down regulation of the mTOR signaling pathway that was partially rescued with leucine supplementation in patient cells.

CONCLUSION

We report dominant negative variants in the KIF5B kinesin motor domain in individuals with osteogenesis imperfecta. This study expands the spectrum of kinesin-related disorders and identifies dysregulated signaling targets for KIF5B in skeletal development.

PDIVAS: Pathogenicity predictor for Deep-Intronic Variants causing Aberrant Splicing

BACKGROUND

Deep-intronic variants that alter RNA splicing were ineffectively evaluated in the search for the cause of genetic diseases. Determination of such pathogenic variants from a vast number of deep-intronic variants (approximately 1,500,000 variants per individual) represents a technical challenge to researchers. Thus, we developed a Pathogenicity predictor for Deep-Intronic Variants causing Aberrant Splicing (PDIVAS) to easily detect pathogenic deep-intronic variants.

RESULTS

PDIVAS was trained on an ensemble machine-learning algorithm to classify pathogenic and benign variants in a curated dataset. The dataset consists of manually curated pathogenic splice-altering variants (SAVs) and commonly observed benign variants within deep introns. Splicing features and a splicing constraint metric were used to maximize the predictive sensitivity and specificity, respectively. PDIVAS showed an average precision of 0.92 and a maximum MCC of 0.88 in classifying these variants, which were the best of the previous predictors. When PDIVAS was applied to genome sequencing analysis on a threshold with 95% sensitivity for reported pathogenic SAVs, an average of 27 pathogenic candidates were extracted per individual. Furthermore, the causative variants in simulated patient genomes were more efficiently prioritized than the previous predictors.

CONCLUSION

Incorporating PDIVAS into variant interpretation pipelines will enable efficient detection of disease-causing deep-intronic SAVs and contribute to improving the diagnostic yield. PDIVAS is publicly available at https://github.com/shiro-kur/PDIVAS .

Precision medicine in rare diseases: What is next?

Molecular diagnostics is a cornerstone of modern precision medicine, broadly understood as tailoring an individual's treatment, follow-up, and care based on molecular data. In rare diseases (RDs), molecular diagnoses reveal valuable information about the cause of symptoms, disease progression, familial risk, and in certain cases, unlock access to targeted therapies. Due to decreasing DNA sequencing costs, genome sequencing (GS) is emerging as the primary method for precision diagnostics in RDs. Several ongoing European initiatives for precision medicine have chosen GS as their method of choice. Recent research supports the role for GS as first-line genetic investigation in individuals with suspected RD, due to its improved diagnostic yield compared to other methods. Moreover, GS can detect a broad range of genetic aberrations including those in noncoding regions, producing comprehensive data that can be periodically reanalyzed for years to come when further evidence emerges. Indeed, targeted drug development and repurposing of medicines can be accelerated as more individuals with RDs receive a molecular diagnosis. Multidisciplinary teams in which clinical specialists collaborate with geneticists, genomics education of professionals and the public, and dialogue with patient advocacy groups are essential elements for the integration of precision medicine into clinical practice worldwide. It is also paramount that large research projects share genetic data and leverage novel technologies to fully diagnose individuals with RDs. In conclusion, GS increases diagnostic yields and is a crucial step toward precision medicine for RDs. Its clinical implementation will enable better patient management, unlock targeted therapies, and guide the development of innovative treatments.

Downstream Assays for Variant Resolution: Epigenetics, RNA Sequnncing, and Metabolomics

As the availability of advanced molecular testing like whole exome and genome sequencing expands, it comes with the added complication of interpreting inconclusive results, including determining the relevance of variants of uncertain significance or failing to find a variant in an otherwise suspected specific genetic disorder. This complication necessitates the use of alternative testing methods to gather more information in support of, or against, a particular genetic diagnosis. Therefore, new genome-wide approaches, including DNA epigenetic testing, RNA sequencing, and metabolomics, are increasingly being used to increase the diagnostic yield when used in conjunction with more conventional genetic tests.

TBCK syndrome: a rare multi-organ neurodegenerative disease

TBCK syndrome is an autosomal recessive disorder primarily characterized by global developmental delay, hypotonia, abnormal magnetic resonance imaging (MRI), and distinctive craniofacial phenotypes. High variability is observed among affected individuals and their corresponding variants, making clinical diagnosis challenging. Here, we discuss recent breakthroughs in clinical considerations, TBCK function, and therapeutic development.

Splicing defects in rare diseases: transcriptomics and machine learning strategies towards genetic diagnosis

Genomic variants affecting pre-messenger RNA splicing and its regulation are known to underlie many rare genetic diseases. However, common workflows for genetic diagnosis and clinical variant interpretation frequently overlook splice-altering variants. To better serve patient populations and advance biomedical knowledge, it has become increasingly important to develop and refine approaches for detecting and interpreting pathogenic splicing variants. In this review, we will summarize a few recent developments and challenges in using RNA sequencing technologies for rare disease investigation. Moreover, we will discuss how recent computational splicing prediction tools have emerged as complementary approaches for revealing disease-causing variants underlying splicing defects. We speculate that continuous improvements to sequencing technologies and predictive modeling will not only expand our understanding of splicing regulation but also bring us closer to filling the diagnostic gap for rare disease patients.

Identification of molecular signatures and pathways involved in Rett syndrome using a multi-omics approach

BACKGROUND

Rett syndrome (RTT) is a neurodevelopmental disorder mainly caused by mutations in the methyl-CpG-binding protein 2 gene (MECP2). MeCP2 is a multi-functional protein involved in many cellular processes, but the mechanisms by which its dysfunction causes disease are not fully understood. The duplication of the MECP2 gene causes a distinct disorder called MECP2 duplication syndrome (MDS), highlighting the importance of tightly regulating its dosage for proper cellular function. Additionally, some patients with mutations in genes other than MECP2 exhibit phenotypic similarities with RTT, indicating that these genes may also play a role in similar cellular functions. The purpose of this study was to characterise the molecular alterations in patients with RTT in order to identify potential biomarkers or therapeutic targets for this disorder.

METHODS

We used a combination of transcriptomics (RNAseq) and proteomics (TMT mass spectrometry) to characterise the expression patterns in fibroblast cell lines from 22 patients with RTT and detected mutation in MECP2, 15 patients with MDS, 12 patients with RTT-like phenotypes and 13 healthy controls. Transcriptomics and proteomics data were used to identify differentially expressed genes at both RNA and protein levels, which were further inspected via enrichment and upstream regulator analyses and compared to find shared features in patients with RTT.

RESULTS

We identified molecular alterations in cellular functions and pathways that may contribute to the disease phenotype in patients with RTT, such as deregulated cytoskeletal components, vesicular transport elements, ribosomal subunits and mRNA processing machinery. We also compared RTT expression profiles with those of MDS seeking changes in opposite directions that could lead to the identification of MeCP2 direct targets. Some of the deregulated transcripts and proteins were consistently affected in patients with RTT-like phenotypes, revealing potentially relevant molecular processes in patients with overlapping traits and different genetic aetiology.

CONCLUSIONS

The integration of data in a multi-omics analysis has helped to interpret the molecular consequences of MECP2 dysfunction, contributing to the characterisation of the molecular landscape in patients with RTT. The comparison with MDS provides knowledge of MeCP2 direct targets, whilst the correlation with RTT-like phenotypes highlights processes potentially contributing to the pathomechanism leading these disorders.

Alu Retrotransposition Event in SPAST Gene as a Novel Cause of Hereditary Spastic Paraplegia

OBJECTIVES

To diagnose the molecular cause of hereditary spastic paraplegia (HSP) observed in a four-generation family with autosomal dominant inheritance.

METHODS

Multiplex ligation-dependent probe amplification (MLPA), whole-exome sequencing (WES), and RNA sequencing (RNA-seq) of peripheral blood leukocytes were performed. Reverse transcription polymerase chain reaction (RT-PCR) and Sanger sequencing were used to characterize target regions of SPAST.

RESULTS

A 121-bp AluYb9 insertion with a 30-bp poly-A tail flanked by 15-bp direct repeats on both sides was identified in the edge of intron 16 in SPAST that segregated with the disease phenotype.

CONCLUSIONS

We identified an intronic AluYb9 insertion inducing splicing alteration in SPAST causing pure HSP phenotype that was not detected by routine WES analysis. Our findings suggest RNA-seq is a recommended implementation for undiagnosed cases by first-line diagnostic approaches. © 2023 International Parkinson and Movement Disorder Society.

Integrative omics approaches to advance rare disease diagnostics

Over the past decade high-throughput DNA sequencing approaches, namely whole exome and whole genome sequencing became a standard procedure in Mendelian disease diagnostics. Implementation of these technologies greatly facilitated diagnostics and shifted the analysis paradigm from variant identification to prioritisation and evaluation. The diagnostic rates vary widely depending on the cohort size, heterogeneity and disease and range from around 30% to 50% leaving the majority of patients undiagnosed. Advances in omics technologies and computational analysis provide an opportunity to increase these unfavourable rates by providing evidence for disease-causing variant validation and prioritisation. This review aims to provide an overview of the current application of several omics technologies including RNA-sequencing, proteomics, metabolomics and DNA-methylation profiling for diagnostics of rare genetic diseases in general and inborn errors of metabolism in particular.

Beyond the exome: What's next in diagnostic testing for Mendelian conditions

Despite advances in clinical genetic testing, including the introduction of exome sequencing (ES), more than 50% of individuals with a suspected Mendelian condition lack a precise molecular diagnosis. Clinical evaluation is increasingly undertaken by specialists outside of clinical genetics, often occurring in a tiered fashion and typically ending after ES. The current diagnostic rate reflects multiple factors, including technical limitations, incomplete understanding of variant pathogenicity, missing genotype-phenotype associations, complex gene-environment interactions, and reporting differences between clinical labs. Maintaining a clear understanding of the rapidly evolving landscape of diagnostic tests beyond ES, and their limitations, presents a challenge for non-genetics professionals. Newer tests, such as short-read genome or RNA sequencing, can be challenging to order, and emerging technologies, such as optical genome mapping and long-read DNA sequencing, are not available clinically. Furthermore, there is no clear guidance on the next best steps after inconclusive evaluation. Here, we review why a clinical genetic evaluation may be negative, discuss questions to be asked in this setting, and provide a framework for further investigation, including the advantages and disadvantages of new approaches that are nascent in the clinical sphere. We present a guide for the next best steps after inconclusive molecular testing based upon phenotype and prior evaluation, including when to consider referral to research consortia focused on elucidating the underlying cause of rare unsolved genetic disorders.

RNA Sequencing of Urine-Derived Cells for the Characterization and Diagnosis of Osteogenesis Imperfecta

DNA sequencing is a reliable tool for identifying genetic variants in osteogenesis imperfecta (OI) but cannot always establish pathogenicity, particularly in variants altering splicing. RNA sequencing can provide functional evidence of the effect of a variant on the transcript but requires cells expressing the relevant genes. Here, we used urine-derived cells (UDC) to characterize genetic variants in patients with suspected or confirmed OI and provide evidence on the pathogenicity of variants of uncertain significance (VUS). Urine samples were obtained from 45 children and adolescents; UDC culture was successful in 40 of these participants (age range 4-20 years, 21 females), including 18 participants with OI or suspected OI who had a candidate variant or VUS on DNA sequencing. RNA was extracted from UDC and sequenced on an Illumina NextSeq550 device. Principal component analysis showed that the gene expression profiles of UDC and fibroblasts (based on Genotype Tissue Expression [GTEx] Consortium data) clustered close together and had less variability than those of whole blood cells. Transcript abundance was sufficient for analysis by RNA sequencing (defined as a median gene expression level of ≥10 transcripts per million) for 25 of the 32 bone fragility genes (78%) that were included in our diagnostic DNA sequencing panel. These results were similar to GTEx data for fibroblasts. Abnormal splicing was identified in 7 of the 8 participants with pathogenic or likely pathogenic variants in the splice region or deeper within the intron. Abnormal splicing was also observed in 2 VUS (COL1A1 c.2829+5G>A and COL1A2 c.693+6T>G), but no splice abnormality was observed in 3 other VUS. Abnormal deletions and duplications could also be observed in UDC transcripts. In conclusion, UDC are suitable for RNA transcript analysis in patients with suspected OI and can provide functional evidence for pathogenicity, in particular of variants affecting splicing. © 2023 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR).

RNA sequencing reveals a complete picture of a homozygous missense variant in a patient with VPS13D movement disorder: a case report and review of the literature

RNA sequencing (RNA-seq) is a complementary diagnostic tool to exome sequencing (ES), only recently clinically available to undiagnosed patients post-ES, that provides functional information on variants of unknown significance (VUS) by evaluating its effect on RNA transcription. ES became clinically available in the early 2010s and promised an agnostic platform for patients with a neurological disease, especially for those who believed to have a genetic etiology. However, the massive data generated by ES pose challenges in variant interpretation, especially for rare missense, synonymous, and deep intronic variants that may have a splicing effect. Without functional study and/or family segregation analysis, these rare variants would be likely interpreted as VUS which is difficult for clinicians to use in clinical care. Clinicians are able to assess the VUS for phenotypic overlap, but this additional information alone is usually not enough to re-classify a variant. Here, we report a case of a 14-month-old male who presented to clinic with a history of seizures, nystagmus, cerebral palsy, oral aversion, global developmental delay, and poor weight gain requiring gastric tube placement. ES revealed a previously unreported homozygous missense VUS, c.7406A > G p.(Asn2469Ser), in VPS13D. This variant has not been previously reported in genome aggregation database (gnomAD), ClinVar, or in any peer-reviewed published literature. By RNA-seq, we demonstrated that this variant mainly impacts splicing and results in a frameshift and early termination. It is expected to generate either a truncated protein, p.(Val2468fs*19), or no protein from this transcript due to nonsense-mediated mRNA decay leading to VPS13D deficiency. To our knowledge, this is the first case utilizing RNA-seq to further functionally characterize a homozygous novel missense VUS in VPS13D and confirm its impact on splicing. This confirmed pathogenicity gave the diagnosis of VPS13D movement disorder to this patient. Therefore, clinicians should consider utilizing RNA-seq to clarify VUS by evaluating its effect on RNA transcription.

Integrated multi-omics for rapid rare disease diagnosis on a national scale

Critically ill infants and children with rare diseases need equitable access to rapid and accurate diagnosis to direct clinical management. Over 2 years, the Acute Care Genomics program provided whole-genome sequencing to 290 families whose critically ill infants and children were admitted to hospitals throughout Australia with suspected genetic conditions. The average time to result was 2.9 d and diagnostic yield was 47%. We performed additional bioinformatic analyses and transcriptome sequencing in all patients who remained undiagnosed. Long-read sequencing and functional assays, ranging from clinically accredited enzyme analysis to bespoke quantitative proteomics, were deployed in selected cases. This resulted in an additional 19 diagnoses and an overall diagnostic yield of 54%. Diagnostic variants ranged from structural chromosomal abnormalities through to an intronic retrotransposon, disrupting splicing. Critical care management changed in 120 diagnosed patients (77%). This included major impacts, such as informing precision treatments, surgical and transplant decisions and palliation, in 94 patients (60%). Our results provide preliminary evidence of the clinical utility of integrating multi-omic approaches into mainstream diagnostic practice to fully realize the potential of rare disease genomic testing in a timely manner.

An FBN1 deep intronic variant is associated with pseudoexon formation and a variable Marfan phenotype in a five generation family

Exome sequencing of genes associated with heritable thoracic aortic disease (HTAD) failed to identify a pathogenic variant in a large family with Marfan syndrome (MFS). A genome-wide linkage analysis for thoracic aortic disease identified a peak at 15q21.1, and genome sequencing identified a novel deep intronic FBN1 variant that segregated with thoracic aortic disease in the family (LOD score 2.7) and was predicted to alter splicing. RT-PCR and bulk RNA sequencing of RNA harvested from fibroblasts explanted from the affected proband revealed an insertion of a pseudoexon between exons 13 and 14 of the FBN1 transcript, predicted to lead to nonsense mediated decay (NMD). Treating the fibroblasts with an NMD inhibitor, cycloheximide, greatly improved the detection of the pseudoexon-containing transcript. Family members with the FBN1 variant had later onset aortic events and fewer MFS systemic features than typical for individuals with haploinsufficiency of FBN1. Variable penetrance of the phenotype and negative genetic testing in MFS families should raise the possibility of deep intronic FBN1 variants and the need for additional molecular studies.

Generation of tandem alternative splice acceptor sites and CLTC haploinsufficiency: A cause of CLTC-related disorder

Tandem splice acceptors (NAGN_n AG) are a common mechanism of alternative splicing, but variants that are likely to generate or to disrupt tandem splice sites have rarely been reported as disease causing. We identify a pathogenic intron 23 CLTC variant (NM_004859.4:c.[3766-13_3766-5del];[=]) in a propositus with intellectual disability and behavioral problems. By RNAseq analysis of peripheral blood mRNA, this variant generates transcripts using cryptic proximal splice acceptors (NM_004859.4: r.3765_3766insTTCACAGAAAGGAACTAG, and NM_004859.4:r.3765_3766insAAAGGAACTAG). Given that the propositus expresses 38% the level of CLTC transcripts as unaffected controls, these variant transcripts, which encode premature termination codons, likely undergo nonsense mediated mRNA decay (NMD). This is the first functional evidence for CLTC haploinsufficiency as a cause of CLTC-related disorder and the first evidence that the generation of tandem alternative splice sites causes CLTC-related disorder. We suggest that variants creating tandem alternative splice sites are an underreported disease mechanism and that transcriptome-level analysis should be routinely pursued to define the pathogenicity of such variants.

Evolution of clinical and radiological presentations of spondyloepimetaphyseal dysplasia, RPL13-related: Description of 11 further cases

Spondyloepimetaphyseal dysplasia (SEMD), RPL13-related is caused by heterozygous variants in RPL13, which encodes the ribosomal protein eL13, a component of the 60S human ribosomal subunit. Here, we describe the clinical and radiological evolution of 11 individuals, 7 children and 4 adults, from 6 families. Some of the skeletal features improved during the course of this condition, whilst others worsened. We describe for the first time "corner fractures" as a feature of this dysplasia which as with other dysplasias disappear with age. In addition, we review the heights and skeletal anomalies of these reported here and previously in a total of 25 individuals from 15 families. In this study, six different RPL13 variants were identified, five of which were novel. All were located in the apparently hotspot region, located in intron 5 and exon 6. Splicing assays were performed for two of the three previously undescribed splicing variants. Until now, all splice variants have occurred in the intron 5 splice donor site, incorporating an additional 18 amino acids to the mutant protein. Here, we report the first variant in intron 5 splice acceptor site which generates two aberrant transcripts, deleting the first three and four amino acids encoded by exon 6. Thus, this study doubles the number of SEMD-RPL13-related cases and variants reported to date and describes unreported age-related clinical and radiological features.

Loss-of-function variants in MYCBP2 cause neurobehavioural phenotypes and corpus callosum defects

The corpus callosum is a bundle of axon fibres that connects the two hemispheres of the brain. Neurodevelopmental disorders that feature dysgenesis of the corpus callosum as a core phenotype offer a valuable window into pathology derived from abnormal axon development. Here, we describe a cohort of eight patients with a neurodevelopmental disorder characterized by a range of deficits including corpus callosum abnormalities, developmental delay, intellectual disability, epilepsy and autistic features. Each patient harboured a distinct de novo variant in MYCBP2, a gene encoding an atypical really interesting new gene (RING) ubiquitin ligase and signalling hub with evolutionarily conserved functions in axon development. We used CRISPR/Cas9 gene editing to introduce disease-associated variants into conserved residues in the Caenorhabditis elegans MYCBP2 orthologue, RPM-1, and evaluated functional outcomes in vivo. Consistent with variable phenotypes in patients with MYCBP2 variants, C. elegans carrying the corresponding human mutations in rpm-1 displayed axonal and behavioural abnormalities including altered habituation. Furthermore, abnormal axonal accumulation of the autophagy marker LGG-1/LC3 occurred in variants that affect RPM-1 ubiquitin ligase activity. Functional genetic outcomes from anatomical, cell biological and behavioural readouts indicate that MYCBP2 variants are likely to result in loss of function. Collectively, our results from multiple human patients and CRISPR gene editing with an in vivo animal model support a direct link between MYCBP2 and a human neurodevelopmental spectrum disorder that we term, MYCBP2-related developmental delay with corpus callosum defects (MDCD).

Implementation of Exome Sequencing in Clinical Practice for Neurological Disorders

Neurological disorders (ND) are diseases that affect the brain and the central and autonomic nervous systems, such as neurodevelopmental disorders, cerebellar ataxias, Parkinson’s disease, or epilepsies. Nowadays, recommendations of the American College of Medical Genetics and Genomics strongly recommend applying next generation sequencing (NGS) as a first-line test in patients with these disorders. Whole exome sequencing (WES) is widely regarded as the current technology of choice for diagnosing monogenic ND. The introduction of NGS allows for rapid and inexpensive large-scale genomic analysis and has led to enormous progress in deciphering monogenic forms of various genetic diseases. The simultaneous analysis of several potentially mutated genes improves the diagnostic process, making it faster and more efficient. The main aim of this report is to discuss the impact and advantages of the implementation of WES into the clinical diagnosis and management of ND. Therefore, we have performed a retrospective evaluation of WES application in 209 cases referred to the Department of Biochemistry and Molecular Genetics of the Hospital Clinic of Barcelona for WES sequencing derived from neurologists or clinical geneticists. In addition, we have further discussed some important facts regarding classification criteria for pathogenicity of rare variants, variants of unknown significance, deleterious variants, different clinical phenotypes, or frequency of actionable secondary findings. Different studies have shown that WES implementation establish diagnostic rate around 32% in ND and the continuous molecular diagnosis is essential to solve the remaining cases.

Trio RNA sequencing in a cohort of medically complex children

Genome sequencing (GS) is a powerful test for the diagnosis of rare genetic disorders. Although GS can enumerate most non-coding variation, determining which non-coding variants are disease-causing is challenging. RNA sequencing (RNA-seq) has emerged as an important tool to help address this issue, but its diagnostic utility remains understudied, and the added value of a trio design is unknown. We performed GS plus RNA-seq from blood using an automated clinical-grade high-throughput platform on 97 individuals from 39 families where the proband was a child with unexplained medical complexity. RNA-seq was an effective adjunct test when paired with GS. It enabled clarification of putative splice variants in three families, but it did not reveal variants not already identified by GS analysis. Trio RNA-seq decreased the number of candidates requiring manual review when filtering for de novo dominant disease-causing variants, allowing for the exclusion of 16% of gene-expression outliers and 27% of allele-specific-expression outliers. However, clear diagnostic benefit from the trio design was not observed. Blood-based RNA-seq can facilitate genome analysis in children with suspected undiagnosed genetic disease. In contrast to DNA sequencing, the clinical advantages of a trio RNA-seq design may be more limited.

Genetics of mitochondrial diseases: Current approaches for the molecular diagnosis

Mitochondrial diseases are a genetically and phenotypically variable set of monogenic disorders. The main characteristic of mitochondrial diseases is a defective oxidative phosphorylation. Both nuclear and mitochondrial DNA encode the approximately 1500 mitochondrial proteins. Since identification of the first mitochondrial disease gene in 1988 a total of 425 genes have been associated with mitochondrial diseases. Mitochondrial dysfunctions can be caused both by pathogenic variants in the mitochondrial DNA or the nuclear DNA. Hence, besides maternal inheritance, mitochondrial diseases can follow all modes of Mendelian inheritance. The maternal inheritance and tissue specificity distinguish molecular diagnostics of mitochondrial disorders from other rare disorders. With the advances made in the next-generation sequencing technology, whole exome sequencing and even whole-genome sequencing are now the established methods of choice for molecular diagnostics of mitochondrial diseases. They reach a diagnostic rate of more than 50% in clinically suspected mitochondrial disease patients. Moreover, next-generation sequencing is delivering a constantly growing number of novel mitochondrial disease genes. This chapter reviews mitochondrial and nuclear causes of mitochondrial diseases, molecular diagnostic methodologies, and their current challenges and perspectives.

Web-accessible application for identifying pathogenic transcripts with RNA-seq: Increased sensitivity in diagnosis of neurodevelopmental disorders

For neurodevelopmental disorders (NDDs), a molecular diagnosis is key for management, predicting outcome, and counseling. Often, routine DNA-based tests fail to establish a genetic diagnosis in NDDs. Transcriptome analysis (RNA sequencing [RNA-seq]) promises to improve the diagnostic yield but has not been applied to NDDs in routine diagnostics. Here, we explored the diagnostic potential of RNA-seq in 96 individuals including 67 undiagnosed subjects with NDDs. We performed RNA-seq on single individuals' cultured skin fibroblasts, with and without cycloheximide treatment, and used modified OUTRIDER Z scores to detect gene expression outliers and mis-splicing by exonic and intronic outliers. Analysis was performed by a user-friendly web application, and candidate pathogenic transcriptional events were confirmed by secondary assays. We identified intragenic deletions, monoallelic expression, and pseudoexonic insertions but also synonymous and non-synonymous variants with deleterious effects on transcription, increasing the diagnostic yield for NDDs by 13%. We found that cycloheximide treatment and exonic/intronic Z score analysis increased detection and resolution of aberrant splicing. Importantly, in one individual mis-splicing was found in a candidate gene nearly matching the individual's specific phenotype. However, pathogenic splicing occurred in another neuronal-expressed gene and provided a molecular diagnosis, stressing the need to customize RNA-seq. Lastly, our web browser application allowed custom analysis settings that facilitate diagnostic application and ranked pathogenic transcripts as top candidates. Our results demonstrate that RNA-seq is a complementary method in the genomic diagnosis of NDDs and, by providing accessible analysis with improved sensitivity, our transcriptome analysis approach facilitates wider implementation of RNA-seq in routine genome diagnostics.

RNA Sequencing as a Diagnostic Tool

This JAMA Insights discusses RNA sequencing, which allows detection of qualitative and quantitative changes in RNA expression across the genome in clinical samples, and how it may improve molecular diagnostic rates achieved by diagnostic exome sequencing and whole-genome sequencing alone.

Stepwise use of genomics and transcriptomics technologies increases diagnostic yield in Mendelian disorders

Purpose: Multi-omics offer worthwhile and increasingly accessible technologies to diagnostic laboratories seeking potential second-tier strategies to help patients with unresolved rare diseases, especially patients clinically diagnosed with a rare OMIM (Online Mendelian Inheritance in Man) disease. However, no consensus exists regarding the optimal diagnostic care pathway to adopt after negative results with standard approaches. Methods: In 15 unsolved individuals clinically diagnosed with recognizable OMIM diseases but with negative or inconclusive first-line genetic results, we explored the utility of a multi-step approach using several novel omics technologies to establish a molecular diagnosis. Inclusion criteria included a clinical autosomal recessive disease diagnosis and single heterozygous pathogenic variant in the gene of interest identified by first-line analysis (60%-9/15) or a clinical diagnosis of an X-linked recessive or autosomal dominant disease with no causative variant identified (40%-6/15). We performed a multi-step analysis involving short-read genome sequencing (srGS) and complementary approaches such as mRNA sequencing (mRNA-seq), long-read genome sequencing (lrG), or optical genome mapping (oGM) selected according to the outcome of the GS analysis. Results: SrGS alone or in combination with additional genomic and/or transcriptomic technologies allowed us to resolve 87% of individuals by identifying single nucleotide variants/indels missed by first-line targeted tests, identifying variants affecting transcription, or structural variants sometimes requiring lrGS or oGM for their characterization. Conclusion: Hypothesis-driven implementation of combined omics technologies is particularly effective in identifying molecular etiologies. In this study, we detail our experience of the implementation of genomics and transcriptomics technologies in a pilot cohort of previously investigated patients with a typical clinical diagnosis without molecular etiology.

A recurrent single-exon deletion in TBCK might be under-recognized in patients with infantile hypotonia and psychomotor delay

Advanced bioinformatics algorithms allow detection of multiple-exon copy-number variations (CNVs) from exome sequencing (ES) data, while detection of single-exon CNVs remains challenging. A retrospective review of Baylor Genetics' clinical ES patient cohort identified four individuals with homozygous single-exon deletions of TBCK (exon 23, NM_001163435.2), a gene associated with an autosomal recessive neurodevelopmental phenotype. To evaluate the prevalence of this deletion and its contribution to disease, we retrospectively analyzed single nucleotide polymorphism (SNP) array data for 8194 individuals undergoing ES, followed by PCR confirmation and RT-PCR on individuals carrying homozygous or heterozygous exon 23 TBCK deletions. A fifth individual was diagnosed with the TBCK-related disorder due to a heterozygous exon 23 deletion in trans with a c.1860+1G>A (NM_001163435.2) pathogenic variant, and three additional heterozygous carriers were identified. Affected individuals and carriers were from diverse ethnicities including European Caucasian, South Asian, Middle Eastern, Hispanic American and African American, with only one family reporting consanguinity. RT-PCR revealed two out-of-frame transcripts related to the exon 23 deletion. Our results highlight the importance of identifying single-exon deletions in clinical ES, especially for genes carrying recurrent deletions. For patients with early-onset hypotonia and psychomotor delay, this single-exon TBCK deletion might be under-recognized due to technical limitations of ES.

Deep intronic NIPBL de novo mutations and differential diagnoses revealed by whole genome and RNA sequencing in Cornelia de Lange syndrome patients

Cornelia de Lange syndrome (CdLS; MIM# 122470) is a rare developmental disorder. Pathogenic variants in 5 genes explain approximately 50% cases, leaving the other 50% unsolved. We performed whole genome sequencing (WGS) ± RNA sequencing (RNA-seq) in 5 unsolved trios fulfilling the following criteria: (i) clinical diagnosis of classic CdLS, (ii) negative gene panel sequencing from blood and saliva-isolated DNA, (iii) unaffected parents' DNA samples available and (iv) proband's blood-isolated RNA available. A pathogenic de novo mutation (DNM) was observed in a CdLS differential diagnosis gene in 3/5 patients, namely POU3F3, SPEN, and TAF1. In the other two, we identified two distinct deep intronic DNM in NIPBL predicted to create a novel splice site. RT-PCRs and RNA-Seq showed aberrant transcripts leading to the creation of a novel frameshift exon. Our findings suggest the relevance of WGS in unsolved suspected CdLS cases and that deep intronic variants may account for a proportion of them.

Characterization of a novel deep-intronic variant in DYNC2H1 identified by whole-exome sequencing in a patient with a lethal form of a short-rib thoracic dysplasia type III

Biallelic pathogenic variants in DYNC2H1 are the cause of short-rib thoracic dysplasia type III with or without polydactyly (OMIM #613091), a skeletal ciliopathy characterized by thoracic hypoplasia due to short ribs. In this report, we review the case of a patient who was admitted to the Neonatal Intensive Care Unit (NICU) of Indiana University Health (IUH) for respiratory support after experiencing respiratory distress secondary to a small, narrow chest causing restrictive lung disease. Additional phenotypic features include postaxial polydactyly, short proximal long bones, and ambiguous genitalia were noted. Exome sequencing (ES) revealed a maternally inherited likely pathogenic variant c.10322C > T p.(Leu3448Pro) in the DYNC2H1 gene. However, there was no variant found on the paternal allele. Microarray analysis to detect deletion or duplication in DYNC2H1 was normal. Therefore, there was insufficient evidence to establish a molecular diagnosis. To further explore the data and perform additional investigations, the patient was subsequently enrolled in the Undiagnosed Rare Disease Clinic (URDC) at Indiana University School of Medicine (IUSM). The investigators at the URDC performed a reanalysis of the ES raw data, which revealed a paternally inherited DYNC2H1 deep-intronic variant c.10606-14A > G predicted to create a strong cryptic acceptor splice site. Additionally, the RNA sequencing of fibroblasts demonstrated partial intron retention predicted to cause a premature stop codon and nonsense-mediated mRNA decay (NMD). Droplet digital RT-PCR (RT-ddPCR) showed a drastic reduction by 74% of DYNCH2H1 mRNA levels. As a result, the intronic variant was subsequently reclassified as likely pathogenic resulting in a definitive clinical and genetic diagnosis for this patient. Reanalysis of ES and fibroblast mRNA experiments confirmed the pathogenicity of the splicing variants to supplement critical information not revealed in original ES or CMA reports. The NICU and URDC collaboration ended the diagnostic odyssey for this family; furthermore, its importance is emphasized by the possibility of prenatally diagnosing the mother's current pregnancy.

Combining genetic constraint with predictions of alternative splicing to prioritize deleterious splicing in rare disease studies

Background

Despite numerous molecular and computational advances, roughly half of patients with a rare disease remain undiagnosed after exome or genome sequencing. A particularly challenging barrier to diagnosis is identifying variants that cause deleterious alternative splicing at intronic or exonic loci outside of canonical donor or acceptor splice sites.

Results

Several existing tools predict the likelihood that a genetic variant causes alternative splicing. We sought to extend such methods by developing a new metric that aids in discerning whether a genetic variant leads to deleterious alternative splicing. Our metric combines genetic variation in the Genome Aggregate Database with alternative splicing predictions from SpliceAI to compare observed and expected levels of splice-altering genetic variation. We infer genic regions with significantly less splice-altering variation than expected to be constrained. The resulting model of regional splicing constraint captures differential splicing constraint across gene and exon categories, and the most constrained genic regions are enriched for pathogenic splice-altering variants. Building from this model, we developed ConSpliceML. This ensemble machine learning approach combines regional splicing constraint with multiple per-nucleotide alternative splicing scores to guide the prediction of deleterious splicing variants in protein-coding genes. ConSpliceML more accurately distinguishes deleterious and benign splicing variants than state-of-the-art splicing prediction methods, especially in “cryptic” splicing regions beyond canonical donor or acceptor splice sites.

Conclusion

Integrating a model of genetic constraint with annotations from existing alternative splicing tools allows ConSpliceML to prioritize potentially deleterious splice-altering variants in studies of rare human diseases.

Transcriptome analysis provides critical answers to the "variants of uncertain significance" conundrum

While whole-genome and exome sequencing have transformed our collective understanding of genetics' role in disease pathogenesis, there are certain conditions and populations for whom DNA-level data fails to identify the underlying genetic etiology. Specifically, patients of non-White race and non-European ancestry are disproportionately affected by "variants of unknown/uncertain significance" (VUS), limiting the scope of precision medicine for minority patients and perpetuating health disparities. VUS often include deep intronic and splicing variants which are difficult to interpret from DNA data alone. RNA analysis can illuminate the consequences of VUS, thereby allowing for their reclassification as pathogenic versus benign. Here we review the critical role transcriptome analysis plays in clarifying VUS in both neoplastic and non-neoplastic diseases.

Rapid genome sequencing for pediatrics

The advancements made in next-generation sequencing (NGS) technology over the past two decades have transformed our understanding of genetic variation in humans and had a profound impact on our ability to diagnose patients with rare genetic diseases. In this review, we discuss the recently developed application of rapid NGS techniques, used to diagnose pediatric patients with suspected rare diseases who are critically ill. We highlight the challenges associated with performing such clinical diagnostics tests in terms of the laboratory infrastructure, bioinformatic analysis pipelines, and the ethical considerations that need to be addressed. We end by looking at what future developments in this field may look like and how they can be used to augment the genetic data to further improve the diagnostic rates for these high-priority patients.

OMIXCARE: OMICS technologies solved about 33% of the patients with heterogeneous rare neuro-developmental disorders and negative exome sequencing results and identified 13% additional candidate variants

Purpose: Patients with rare or ultra-rare genetic diseases, which affect 350 million people worldwide, may experience a diagnostic odyssey. High-throughput sequencing leads to an etiological diagnosis in up to 50% of individuals with heterogeneous neurodevelopmental or malformation disorders. There is a growing interest in additional omics technologies in translational research settings to examine the remaining unsolved cases. Methods: We gathered 30 individuals with malformation syndromes and/or severe neurodevelopmental disorders with negative trio exome sequencing and array comparative genomic hybridization results through a multicenter project. We applied short-read genome sequencing, total RNA sequencing, and DNA methylation analysis, in that order, as complementary translational research tools for a molecular diagnosis. Results: The cohort was mainly composed of pediatric individuals with a median age of 13.7 years (4 years and 6 months to 35 years and 1 month). Genome sequencing alone identified at least one variant with a high level of evidence of pathogenicity in 8/30 individuals (26.7%) and at least a candidate disease-causing variant in 7/30 other individuals (23.3%). RNA-seq data in 23 individuals allowed two additional individuals (8.7%) to be diagnosed, confirming the implication of two pathogenic variants (8.7%), and excluding one candidate variant (4.3%). Finally, DNA methylation analysis confirmed one diagnosis identified by genome sequencing (Kabuki syndrome) and identified an episignature compatible with a BAFopathy in a patient with a clinical diagnosis of Coffin-Siris with negative genome and RNA-seq results in blood. Conclusion: Overall, our integrated genome, transcriptome, and DNA methylation analysis solved 10/30 (33.3%) cases and identified a strong candidate gene in 4/30 (13.3%) of the patients with rare neurodevelopmental disorders and negative exome sequencing results.

Can tandem alternative splicing and evasion of premature termination codon surveillance contribute to attenuated Peutz-Jeghers syndrome?

Alternative use of short distance tandem sites such as NAGN_n AG are a common mechanism of alternative splicing; however, single nucleotide variants are rarely reported as likely to generate or to disrupt tandem splice sites. We identify a pathogenic intron 5 STK11 variant (NM_000455.4:c.[735-6A>G];[=]) segregating with the mucocutaneous features but not the hamartomatous polyps of Peutz-Jeghers syndrome in two individuals. By RNAseq analysis of peripheral blood mRNA, this variant was shown to generate a novel and preferentially used tandem proximal splice acceptor (AAGTGAAG). The variant transcript (NM_000455.4:c.734_734 + 1insTGAAG), which encodes a frameshift (p.[Tyr246Glufs*43]) constituted 36%-43% of STK11 transcripts suggesting partial escape from nonsense mediated mRNA decay and translation of a truncated protein. A review of the ClinVar database identified other similar variants. We suggest that nucleotide changes creating or disrupting tandem alternative splice sites are a pertinent disease mechanism and require contextualization for clinical reporting. Additionally, we hypothesize that some pathogenic STK11 variants cause an attenuated phenotype.

Epigenomic Approaches for the Diagnosis of Rare Diseases

Rare diseases affect more than 300 million people worldwide. Diagnosing rare diseases is a major challenge as they have different causes and etiologies. Careful assessment of clinical symptoms often leads to the testing of the most common genetic alterations that could explain the disease. Patients with negative results for these tests frequently undergo whole exome or genome sequencing, leading to the identification of the molecular cause of the disease in 50% of patients at best. Therefore, a significant proportion of patients remain undiagnosed after sequencing their genome. Recently, approaches based on functional aspects of the genome, including transcriptomics and epigenomics, are beginning to emerge. Here, we will review these approaches, including studies that have successfully provided diagnoses for complex undiagnosed cases.