Deep Intronic FGF14 GAA Repeat Expansion in Late-Onset Cerebellar Ataxia.

BACKGROUND: The late-onset cerebellar ataxias (LOCAs) have largely resisted molecular diagnosis. METHODS: We sequenced the genomes of six persons with autosomal dominant LOCA who were members of three French Canadian families and identified a candidate pathogenic repeat expansion. We then tested for association between the repeat expansion and disease in two independent case-control series - one French Canadian (66 patients and 209 controls) and the other German (228 patients and 199 controls). We also genotyped the repeat in 20 Australian and 31 Indian index patients. We assayed gene and protein expression in two postmortem cerebellum specimens and two induced pluripotent stem-cell (iPSC)-derived motor-neuron cell lines. RESULTS: In the six French Canadian patients, we identified a GAA repeat expansion deep in the first intron of FGF14, which encodes fibroblast growth factor 14. Cosegregation of the repeat expansion with disease in the families supported a pathogenic threshold of at least 250 GAA repeats ([GAA]≥250). There was significant association between FGF14 (GAA)≥250 expansions and LOCA in the French Canadian series (odds ratio, 105.60; 95% confidence interval [CI], 31.09 to 334.20; P<0.001) and in the German series (odds ratio, 8.76; 95% CI, 3.45 to 20.84; P<0.001). The repeat expansion was present in 61%, 18%, 15%, and 10% of French Canadian, German, Australian, and Indian index patients, respectively. In total, we identified 128 patients with LOCA who carried an FGF14 (GAA)≥250 expansion. Postmortem cerebellum specimens and iPSC-derived motor neurons from patients showed reduced expression of FGF14 RNA and protein. CONCLUSIONS: A dominantly inherited deep intronic GAA repeat expansion in FGF14 was found to be associated with LOCA. (Funded by Fondation Groupe Monaco and others.).

Repeat expansions nested within tandem CNVs: a unique structural change in GLS exemplifies the diagnostic challenges of non-coding pathogenic variation.

Glutaminase deficiency has recently been associated with ataxia and developmental delay due to repeat expansions in the 5'UTR of the glutaminase (GLS) gene. Patients with the described GLS repeat expansion may indeed remain undiagnosed due to the rarity of this variant, the challenge of its detection and the recency of its discovery. In this study, we combined advanced bioinformatics screening of ~3000 genomes and ~1500 exomes with optical genome mapping and long-read sequencing for confirmation studies. We identified two GLS families, previously intensely and unsuccessfully analyzed. One family carries an unusual and complex structural change involving a homozygous repeat expansion nested within a quadruplication event in the 5'UTR of GLS. Glutaminase deficiency and its metabolic consequences were validated by in-depth biochemical analysis. The identified GLS patients showed progressive early-onset ataxia, cognitive deficits, pyramidal tract damage and optic atrophy, thus demonstrating susceptibility of several specific neuron populations to glutaminase deficiency. This large-scale screening study demonstrates the ability of bioinformatics analysis-validated by latest state-of-the-art technologies (optical genome mapping and long-read sequencing)-to effectively flag complex repeat expansions using short-read datasets and thus facilitate diagnosis of ultra-rare disorders.

RFC1 repeat expansions: A recurrent cause of sensory and autonomic neuropathy with cough and ataxia.

BACKGROUND AND PURPOSE: Ataxia and cough are rare features in hereditary sensory and autonomic neuropathies (HSAN), a group of diseases of mostly unknown genetic cause. Biallelic repeat expansions in RFC1 are associated with cerebellar ataxia, neuropathy, and vestibular areflexia syndrome (CANVAS). This study aimed to investigate the prevalence of RFC1 repeat expansions in a cohort of HSAN patients. METHODS: After unremarkable whole-exome sequencing (WES) analysis, we performed repeat-primed PCR to detect intronic RFC1 expansions in 12 HSAN families, who all presented with chronic cough. RESULTS: In these patients, 75% carried biallelic expansions of the pathogenic AAGGG motif. Compared with RFC1-/- cases, RFC1+/+ cases presented more consistently with positive sensory and autonomic symptoms. Afferent ataxia was more severe in the RFC1+/+ cohort and cerebellar ataxia was a common feature (21%). CONCLUSIONS: We demonstrate that RFC1 is a frequent cause of (WES-negative) HSAN with chronic cough and ataxia. The diagnostic yield of RFC1 repeat-primed PCR was surprisingly high, given that HSAN is genetically poorly understood. This combination of HSAN, ataxia, and chronic cough symptoms represents a new nosological entity within the neuropathy-ataxia spectrum.

Assessing non-Mendelian inheritance in inherited axonopathies.

PURPOSE: Inherited axonopathies (IA) are rare, clinically and genetically heterogeneous diseases that lead to length-dependent degeneration of the long axons in central (hereditary spastic paraplegia [HSP]) and peripheral (Charcot-Marie-Tooth type 2 [CMT2]) nervous systems. Mendelian high-penetrance alleles in over 100 different genes have been shown to cause IA; however, about 50% of IA cases do not receive a genetic diagnosis. A more comprehensive spectrum of causative genes and alleles is warranted, including causative and risk alleles, as well as oligogenic multilocus inheritance. METHODS: Through international collaboration, IA exome studies are beginning to be sufficiently powered to perform a pilot rare variant burden analysis. After extensive quality control, our cohort contained 343 CMT cases, 515 HSP cases, and 935 non-neurological controls. We assessed the cumulative mutational burden across disease genes, explored the evidence for multilocus inheritance, and performed an exome-wide rare variant burden analysis. RESULTS: We replicated the previously described mutational burden in a much larger cohort of CMT cases, and observed the same effect in HSP cases. We identified a preliminary risk allele for CMT in the EXOC4 gene (p value= 6.9 × 10-6, odds ratio [OR] = 2.1) and explored the possibility of multilocus inheritance in IA. CONCLUSION: Our results support the continuing emergence of complex inheritance mechanisms in historically Mendelian disorders.

Inhibition of fascin in cancer and stromal cells blocks ovarian cancer metastasis.

OBJECTIVE: Ovarian cancer (OvCa) metastasis requires the coordinated motility of both cancer and stromal cells. Cellular movement is a dynamic process that involves the synchronized assembly of f-actin bundles into cytoskeletal protrusions by fascin. Fascin directly binds f-actin and is an integral component of filopodia, lamellapodia and stress fibers. Here, we examine the expression pattern and function of fascin in the cancer and stromal cells of OvCa tumors. METHODS: Fascin expression was evaluated in human cells and tissues using immunohistochemistry and immunofluorescence. The functional role of fascin in cancer and stromal cells was assessed with in vitro functional assays, an ex vivo colonization assay and in vivo metastasis assays using siRNA/shRNA and an inhibitor. The effect of fascin inhibition on Cdc42 and Rac1 activity was evaluated using GTPase activity assays and immunofluorescence. RESULTS: Fascin expression was found to be higher in the stromal cell, when compared to the cancer cell, compartment of ovarian tumors. The low expression of fascin in the cancer cells of the primary tumor indicated a favorable prognosis for non-serous OvCa patients. In vitro, both knockdown and pharmacologic inhibition of fascin decreased the migration of cancer and stromal cells. The inhibition of fascin impaired Cdc42 and Rac1 activity in cancer cells, and cytoskeletal reorganization in the cancer and stromal cells. Inhibition of fascin ex vivo blocked OvCa cell colonization of human omental tissue and in vivo prevented and reduced OvCa metastases in mice. Likewise, knockdown of fascin specifically in the OvCa cells using a fascin-specific lentiviral-shRNA also blocked metastasis in vivo. CONCLUSION: This study reveals the therapeutic potential of pharmacologically inhibiting fascin in both cancer and stromal cells of the OvCa tumor microenvironment.

Targeting the CACNA1A IRES as a Treatment for Spinocerebellar Ataxia Type 6.

We have discovered that the P/Q-type voltage-gated Ca2+ channel (VGCC) gene, CACNA1A, encodes both the α1A (Cav2.1) subunit and a newly recognized transcription factor, α1ACT, by means of a novel internal ribosomal entry site (IRES) within the α1A C-terminal coding region. α1ACT, when mutated with an expansion of the polyglutamine tract in the C-terminus, gives rise to spinocerebellar ataxia type 6 (SCA6). Because silencing of the entire CACNA1A gene would result in the loss of the essential Cav2.1 channel, the IRES controlling α1ACT expression is an excellent target for selective silencing of α1ACT as a therapeutic intervention for SCA6. We performed a high-throughput screen of FDA-approved small molecules using a dual luciferase reporter system and identified ten hits able to selectively inhibit the IRES. We identified four main candidates that showed selective suppression of α1ACT relative to α1A in HEK cells expressing a native CACNA1A vector. We previously pursued another avenue of molecular intervention through miRNA silencing. We studied three human miRNAs (miRNA-711, -3191-5p, -4786) that would potentially bind to sequences within the CACNA1A IRES region, based on an miRNA prediction program. Only miRNA-3191-5p was found to selectively inhibit the translation of α1ACT in cells. We developed a hyperacute model of SCA6 in mice by injecting a pathogenic form of the IRES-mediated α1ACT (AAV9-α1ACTQ33). Finally, we tested the effectiveness of the miRNA therapy by co-expressing either control miRNA or miRNA-3191-5p and found that miRNA-3191-5p decreased the levels of α1ACTQ33 and prevented the hyperacute disease in mice. These studies provide the proof of principle that a therapy directed at selectively preventing α1ACT expression could be used to treat SCA6.

RExPRT: a machine learning tool to predict pathogenicity of tandem repeat loci.

Expansions of tandem repeats (TRs) cause approximately 60 monogenic diseases. We expect that the discovery of additional pathogenic repeat expansions will narrow the diagnostic gap in many diseases. A growing number of TR expansions are being identified, and interpreting them is a challenge. We present RExPRT (Repeat EXpansion Pathogenicity pRediction Tool), a machine learning tool for distinguishing pathogenic from benign TR expansions. Our results demonstrate that an ensemble approach classifies TRs with an average precision of 93% and recall of 83%. RExPRT's high precision will be valuable in large-scale discovery studies, which require prioritization of candidate loci for follow-up studies.

Integration of transcriptomics and long-read genomics prioritizes structural variants in rare disease.

Rare structural variants (SVs) - insertions, deletions, and complex rearrangements - can cause Mendelian disease, yet they remain difficult to accurately detect and interpret. We sequenced and analyzed Oxford Nanopore long-read genomes of 68 individuals from the Undiagnosed Disease Network (UDN) with no previously identified diagnostic mutations from short-read sequencing. Using our optimized SV detection pipelines and 571 control long-read genomes, we detected 716 long-read rare (MAF < 0.01) SV alleles per genome on average, achieving a 2.4x increase from short-reads. To characterize the functional effects of rare SVs, we assessed their relationship with gene expression from blood or fibroblasts from the same individuals, and found that rare SVs overlapping enhancers were enriched (LOR = 0.46) near expression outliers. We also evaluated tandem repeat expansions (TREs) and found 14 rare TREs per genome; notably these TREs were also enriched near overexpression outliers. To prioritize candidate functional SVs, we developed Watershed-SV, a probabilistic model that integrates expression data with SV-specific genomic annotations, which significantly outperforms baseline models that don't incorporate expression data. Watershed-SV identified a median of eight high-confidence functional SVs per UDN genome. Notably, this included compound heterozygous deletions in FAM177A1 shared by two siblings, which were likely causal for a rare neurodevelopmental disorder. Our observations demonstrate the promise of integrating long-read sequencing with gene expression towards improving the prioritization of functional SVs and TREs in rare disease patients.

The GENESIS database and tools: A decade of discovery in Mendelian genomics.

In the past decade, human genetics research saw an acceleration of disease gene discovery and further dissection of the genetic architectures of many disorders. Much of this progress was enabled via data aggregation projects, collaborative data sharing among researchers, and the adoption of sophisticated and standardized bioinformatics analyses pipelines. In 2012, we launched the GENESIS platform, formerly known as GEM.app, with the aims to 1) empower clinical and basic researchers without bioinformatics expertise to analyze and explore genome level data and 2) facilitate the detection of novel pathogenic variation and novel disease genes by leveraging data aggregation and genetic matchmaking. The GENESIS database has grown to over 20,000 datasets from rare disease patients, which were provided by multiple academic research consortia and many individual investigators. Some of the largest global collections of genome-level data are available for Charcot-Marie-Tooth disease, hereditary spastic paraplegia, and cerebellar ataxia. A number of rare disease consortia and networks are archiving their data in this database. Over the past decade, more than 1500 scientists have registered and used this resource and published over 200 papers on gene and variant identifications, which garnered >6000 citations. GENESIS has supported >100 gene discoveries and contributed to approximately half of all gene identifications in the fields of inherited peripheral neuropathies and spastic paraplegia in this time frame. Many diagnostic odysseys of rare disease patients have been resolved. The concept of genomes-to-therapy has borne out for a number of such discoveries that let to rapid clinical trials and expedited natural history studies. This marks GENESIS as one of the most impactful data aggregation initiatives in rare monogenic diseases.

Deep structured learning for variant prioritization in Mendelian diseases.

Effective computer-aided or automated variant evaluations for monogenic diseases will expedite clinical diagnostic and research efforts of known and novel disease-causing genes. Here we introduce MAVERICK: a Mendelian Approach to Variant Effect pRedICtion built in Keras. MAVERICK is an ensemble of transformer-based neural networks that can classify a wide range of protein-altering single nucleotide variants (SNVs) and indels and assesses whether a variant would be pathogenic in the context of dominant or recessive inheritance. We demonstrate that MAVERICK outperforms all other major programs that assess pathogenicity in a Mendelian context. In a cohort of 644 previously solved patients with Mendelian diseases, MAVERICK ranks the causative pathogenic variant within the top five variants in over 95% of cases. Seventy-six percent of cases were solved by the top-ranked variant. MAVERICK ranks the causative pathogenic variant in hitherto novel disease genes within the first five candidate variants in 70% of cases. MAVERICK has already facilitated the identification of a novel disease gene causing a degenerative motor neuron disease. These results represent a significant step towards automated identification of causal variants in patients with Mendelian diseases.

REViewer: haplotype-resolved visualization of read alignments in and around tandem repeats.

BACKGROUND: Expansions of short tandem repeats are the cause of many neurogenetic disorders including familial amyotrophic lateral sclerosis, Huntington disease, and many others. Multiple methods have been recently developed that can identify repeat expansions in whole genome or exome sequencing data. Despite the widely recognized need for visual assessment of variant calls in clinical settings, current computational tools lack the ability to produce such visualizations for repeat expansions. Expanded repeats are difficult to visualize because they correspond to large insertions relative to the reference genome and involve many misaligning and ambiguously aligning reads. RESULTS: We implemented REViewer, a computational method for visualization of sequencing data in genomic regions containing long repeat expansions and FlipBook, a companion image viewer designed for manual curation of large collections of REViewer images. To generate a read pileup, REViewer reconstructs local haplotype sequences and distributes reads to these haplotypes in a way that is most consistent with the fragment lengths and evenness of read coverage. To create appropriate training materials for onboarding new users, we performed a concordance study involving 12 scientists involved in short tandem repeat research. We used the results of this study to create a user guide that describes the basic principles of using REViewer as well as a guide to the typical features of read pileups that correspond to low confidence repeat genotype calls. Additionally, we demonstrated that REViewer can be used to annotate clinically relevant repeat interruptions by comparing visual assessment results of 44 FMR1 repeat alleles with the results of triplet repeat primed PCR. For 38 of these alleles, the results of visual assessment were consistent with triplet repeat primed PCR. CONCLUSIONS: Read pileup plots generated by REViewer offer an intuitive way to visualize sequencing data in regions containing long repeat expansions. Laboratories can use REViewer and FlipBook to assess the quality of repeat genotype calls as well as to visually detect interruptions or other imperfections in the repeat sequence and the surrounding flanking regions. REViewer and FlipBook are available under open-source licenses at https://github.com/illumina/REViewer and https://github.com/broadinstitute/flipbook respectively.

Genetic modifiers and non-Mendelian aspects of CMT.

Charcot-Marie-Tooth (CMT) neuropathies are amongst the most common inherited diseases in neurology. While great strides have been made to identify the genesis of these diseases, a diagnostic gap of 30-60% remains. Classic models of genetic causation may be limited to fully close this gap and, thus, we review the current state and future role of alternative, non-Mendelian forms of genetics in CMT. Promising synergies exist to further define the full genetic architecture of inherited neuropathies, including affordable whole-genome sequencing, increased data aggregation and clinical collaboration, improved bioinformatics and statistical methodology, and vastly improved computational resources. Given the recent advances in genetic therapies for rare diseases, it becomes a matter of urgency to diagnose CMT patients with great fidelity. Otherwise, they will not be able to benefit from such therapeutic options, or worse, suffer harm when pathogenicity of genetic variation is falsely evaluated. In addition, the newly identified modifier and risk genes may offer alternative targets for pharmacotherapy of inherited and, potentially, even acquired forms of neuropathies.

Large scale in silico characterization of repeat expansion variation in human genomes.

Significant progress has been made in elucidating single nucleotide polymorphism diversity in the human population. However, the majority of the variation space in the genome is structural and remains partially elusive. One form of structural variation is tandem repeats (TRs). Expansion of TRs are responsible for over 40 diseases, but we hypothesize these represent only a fraction of the pathogenic repeat expansions that exist. Here we characterize long or expanded TR variation in 1,115 human genomes as well as a replication cohort of 2,504 genomes, identified using ExpansionHunter Denovo. We found that individual genomes typically harbor several rare, large TRs, generally in non-coding regions of the genome. We noticed that these large TRs are enriched in their proximity to Alu elements. The vast majority of these large TRs seem to be expansions of smaller TRs that are already present in the reference genome. We are providing this TR profile as a resource for comparison to undiagnosed rare disease genomes in order to detect novel disease-causing repeat expansions.

Quantitative High-Throughput Screening Using an Organotypic Model Identifies Compounds that Inhibit Ovarian Cancer Metastasis.

The tumor microenvironment (TME) is a key determinant of metastatic efficiency. We performed a quantitative high-throughput screen (qHTS) of diverse medicinal chemistry tractable scaffolds (44,420 compounds) and pharmacologically active small molecules (386 compounds) using a layered organotypic, robust assay representing the ovarian cancer metastatic TME. This 3D model contains primary human mesothelial cells, fibroblasts, and extracellular matrix, to which fluorescently labeled ovarian cancer cells are added. Initially, 100 compounds inhibiting ovarian cancer adhesion/invasion to the 3D model in a dose-dependent manner were identified. Of those, eight compounds were confirmed active in five high-grade serous ovarian cancer cell lines and were further validated in secondary in vitro and in vivo biological assays. Two tyrosine kinase inhibitors, PP-121 and milciclib, and a previously unreported compound, NCGC00117362, were selected because they had potency at 1 µmol/L in vitro Specifically, NCGC00117362 and PP-121 inhibited ovarian cancer adhesion, invasion, and proliferation, whereas milciclib inhibited ovarian cancer invasion and proliferation. Using in situ kinase profiling and immunoblotting, we found that milciclib targeted Cdk2 and Cdk6, and PP-121 targeted mTOR. In vivo, all three compounds prevented ovarian cancer adhesion/invasion and metastasis, prolonged survival, and reduced omental tumor growth in an intervention study. To evaluate the clinical potential of NCGC00117362, structure-activity relationship studies were performed. Four close analogues of NCGC00117362 efficiently inhibited cancer aggressiveness in vitro and metastasis in vivo Collectively, these data show that a complex 3D culture of the TME is effective in qHTS. The three compounds identified have promise as therapeutics for prevention and treatment of ovarian cancer metastasis.

Integration of genomics and transcriptomics predicts diabetic retinopathy susceptibility genes.

We determined differential gene expression in response to high glucose in lymphoblastoid cell lines derived from matched individuals with type 1 diabetes with and without retinopathy. Those genes exhibiting the largest difference in glucose response were assessed for association with diabetic retinopathy in a genome-wide association study meta-analysis. Expression quantitative trait loci (eQTLs) of the glucose response genes were tested for association with diabetic retinopathy. We detected an enrichment of the eQTLs from the glucose response genes among small association p-values and identified folliculin (FLCN) as a susceptibility gene for diabetic retinopathy. Expression of FLCN in response to glucose was greater in individuals with diabetic retinopathy. Independent cohorts of individuals with diabetes revealed an association of FLCN eQTLs with diabetic retinopathy. Mendelian randomization confirmed a direct positive effect of increased FLCN expression on retinopathy. Integrating genetic association with gene expression implicated FLCN as a disease gene for diabetic retinopathy.

One of the side effects of diabetes is loss of vision from diabetic retinopathy, which is caused by injury to the light sensing tissue in the eye, the retina. Almost all individuals with diabetes develop diabetic retinopathy to some extent, and it is the leading cause of irreversible vision loss in working-age adults in the United States. How long a person has been living with diabetes, the extent of increased blood sugars and genetics all contribute to the risk and severity of diabetic retinopathy. Unfortunately, virtually no genes associated with diabetic retinopathy have yet been identified. When a gene is activated, it produces messenger molecules known as mRNA that are used by cells as instructions to produce proteins. The analysis of mRNA molecules, as well as genes themselves, can reveal the role of certain genes in disease. The studies of all genes and their associated mRNAs are respectively called genomics and transcriptomics. Genomics reveals what genes are present, while transcriptomics shows how active genes are in different cells. Skol et al. developed methods to study genomics and transcriptomics together to help discover genes that cause diabetic retinopathy. Genes involved in how cells respond to high blood sugar were first identified using cells grown in the lab. By comparing the activity of these genes in people with and without retinopathy the study identified genes associated with an increased risk of retinopathy in diabetes. In people with retinopathy, the activity of the folliculin gene (FLCN) increased more in response to high blood sugar. This was further verified with independent groups of people and using computer models to estimate the effect of different versions of the folliculin gene. The methods used here could be applied to understand complex genetics in other diseases. The results provide new understanding of the effects of diabetes. They may also help in the development of new treatments for diabetic retinopathy, which are likely to improve on the current approach of using laser surgery or injections into the eye.