A t(3;9)(q25.1;q34.3) translocation leading to OLFM1 fusion transcripts in Gilles de la Tourette syndrome, OCD and ADHD

Bertelsen, Birgitte; Melchior, Linea Cecilie; Jensen, Lars Riff; Groth, Camilla; Nazaryan, Lusine; Debes, Nanette Mol; Skov, Liselotte; Xie, Gangcai; Sun, Wei; Brøndum‐Nielsen, Karen; Kuß, Andreas W.; Chen, Wei; Tümer, Zeynep

doi:10.1016/j.psychres.2014.12.028

Cited by 18 publications

(9 citation statements)

References 43 publications

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“…Increased levels of Nogo-A have been reported in schizophrenia (Novak et al, 2002), multiple sclerosis (Satoh et al, 2005), temporal lobe epilepsy (Bandtlow et al, 2004) and Alzheimer’s disease (Gil et al, 2006). An increasing number of mutations and genetic variants in genes depicted in Figure 1 have been found coupled to neuropsychiatric and neurodegenerative disorders, including schizophrenia (NgR1/Nogo-A: Budel et al, 2008; Willi and Schwab, 2013; Andrews and Fernandez-Enright, 2015), (LGI1/NgR1: Thomas et al, 2016), ALS (NgR1: Amy et al, 2015), Pelizaeus-Merzbacher disease (MAG: Lossos et al, 2015), Parkinson’s disease (Lingo-1: Chen et al, 2015), Tourette syndrome/OCD/ADHD (Olfactomedin: Bertelsen et al, 2015) and epilepsy (LgI1: Fukata et al, 2010); (ADAM22: Muona et al, 2016), further emphasizing the importance of normal Nogo-type control of synaptic plasticity. Current knowledge has also led to the initiations of clinical trials in spinal cord injury (NCT00406016), multiple sclerosis (Ineichen et al, 2017), and ALS in which disease a large phase II trial shows no positive effects of Nogo-A antibodies (Meininger et al, 2014).…”

Section: Discussionmentioning

confidence: 99%

Spatiotemporal and Long Lasting Modulation of 11 Key Nogo Signaling Genes in Response to Strong Neuroexcitation

Karlsson

Wellfelt

Olson

2017

Front. Mol. Neurosci.

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Inhibition of nerve growth and plasticity in the CNS is to a large part mediated by Nogo-like signaling, now encompassing a plethora of ligands, receptors, co-receptors and modulators. Here we describe the distribution and levels of mRNA encoding 11 key genes involved in Nogo-like signaling (Nogo-A, Oligodendrocyte-Myelin glycoprotein (OMgp), Nogo receptor 1 (NgR1), NgR2, NgR3, Lingo-1, TNF receptor orphan Y (Troy), Olfactomedin, Lateral olfactory tract usher substance (Lotus) and membrane-type matrix metalloproteinase-3 (MT3-MPP)), as well as BDNF and GAPDH. Expression was analyzed in nine different brain areas before, and at eight time points during the first 3 days after a strong neuroexcitatory stimulation, caused by one kainic acid injection. A temporo-spatial pattern of orderly transcriptional regulations emerges that strengthens the role of Nogo-signaling mechanisms for synaptic plasticity in synchrony with transcriptional increases of BDNF mRNA. For most Nogo-type signaling genes, the largest alterations of mRNA levels occur in the dentate gyrus, with marked alterations also in the CA1 region. Changes occurred somewhat later in several areas of the cerebral cortex. The detailed spatio-temporal pattern of mRNA presence and kainic acid-induced transcriptional response is gene-specific. We reveal that several different gene alterations combine to decrease (and later increase) Nogo-like signaling, as expected to allow structural plasticity responses. Other genes are altered in the opposite direction, suggesting that the system prepares in advance in order to rapidly restore balance. However, the fact that Lingo-1 shows a seemingly opposite, plasticity inhibiting response to kainic acid (strong increase of mRNA in the dentate gyrus), may instead suggest a plasticity-enhancing intracellular function of this presumed NgR1 co-receptor.

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Section: Discussionmentioning

confidence: 99%

Spatiotemporal and Long Lasting Modulation of 11 Key Nogo Signaling Genes in Response to Strong Neuroexcitation

Karlsson

Wellfelt

Olson

2017

Front. Mol. Neurosci.

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“…Fusion genes are well documented in hematological and solid tissue cancers and are used as biomarkers for early diagnosis and therapeutic targets [ 164 ]. Independent case studies have reported fusion transcripts in many non-cancer diseases like brain malformation [ 165 , 166 ], intellectual disability [ 167 , 168 ], spastic paraplegia [ 169 ], and Gille de la Tourette Syndrome [ 170 ]. Oliver et al [ 136 ] tailored a fusion identification pipeline for rare disease patients and applied it to a cohort of 47 individuals who previously had negative or partial diagnoses through exome sequencing.…”

Section: Transcriptomicsmentioning

confidence: 99%

A guide for the diagnosis of rare and undiagnosed disease: beyond the exome

2022

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Rare diseases affect 30 million people in the USA and more than 300–400 million worldwide, often causing chronic illness, disability, and premature death. Traditional diagnostic techniques rely heavily on heuristic approaches, coupling clinical experience from prior rare disease presentations with the medical literature. A large number of rare disease patients remain undiagnosed for years and many even die without an accurate diagnosis. In recent years, gene panels, microarrays, and exome sequencing have helped to identify the molecular cause of such rare and undiagnosed diseases. These technologies have allowed diagnoses for a sizable proportion (25–35%) of undiagnosed patients, often with actionable findings. However, a large proportion of these patients remain undiagnosed. In this review, we focus on technologies that can be adopted if exome sequencing is unrevealing. We discuss the benefits of sequencing the whole genome and the additional benefit that may be offered by long-read technology, pan-genome reference, transcriptomics, metabolomics, proteomics, and methyl profiling. We highlight computational methods to help identify regionally distant patients with similar phenotypes or similar genetic mutations. Finally, we describe approaches to automate and accelerate genomic analysis. The strategies discussed here are intended to serve as a guide for clinicians and researchers in the next steps when encountering patients with non-diagnostic exomes.

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“…This is despite the fact that mechanisms commonly responsible for fusion transcript formation, including deletions, inversions and translocations, often underlie inherited conditions [10]. Indeed, case studies have reported fusion transcripts in disease including brain malformation [11] [12] [13], intellectual disability [14] [15] [16] [17] [18], schizophrenia [19] [20], spastic paraplegia [21], autism spectrum disorder [22], Gille de la Tourette Syndrome [23] and more [24] [25] [10]. These sporadic cases suggest that the systematic inclusion of fusion transcript detection in RNA-based analysis of rare undiagnosed disease may lead to improved diagnostic rates.…”

Section: Introductionmentioning

confidence: 99%

A tailored approach to fusion transcript identification increases diagnosis of rare inherited disease

et al. 2019

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BackgroundRNA sequencing has been proposed as a means of increasing diagnostic rates in studies of undiagnosed rare inherited disease. Recent studies have reported diagnostic improvements in the range of 7.5–35% by profiling splicing, gene expression quantification and allele specific expression. To-date however, no study has systematically assessed the presence of gene-fusion transcripts in cases of germline disease. Fusion transcripts are routinely identified in cancer studies and are increasingly recognized as having diagnostic, prognostic or therapeutic relevance. Isolated reports exist of fusion transcripts being detected in cases of developmental and neurological phenotypes, and thus, systematic application of fusion detection to germline conditions may further increase diagnostic rates. However, current fusion detection methods are unsuited to the investigation of germline disease due to performance biases arising from their development using tumor, cell-line or in-silico data.MethodsWe describe a tailored approach to fusion candidate identification and prioritization in a cohort of 47 undiagnosed, suspected inherited disease patients. We modify an existing fusion transcript detection algorithm by eliminating its cell line-derived filtering steps, and instead, prioritize candidates using a custom workflow that integrates genomic and transcriptomic sequence alignment, biological and technical annotations, customized categorization logic, and phenotypic prioritization.ResultsWe demonstrate that our approach to fusion transcript identification and prioritization detects genuine fusion events excluded by standard analyses and efficiently removes phenotypically unimportant candidates and false positive events, resulting in a reduced candidate list enriched for events with potential phenotypic relevance. We describe the successful genetic resolution of two previously undiagnosed disease cases through the detection of pathogenic fusion transcripts. Furthermore, we report the experimental validation of five additional cases of fusion transcripts with potential phenotypic relevance.ConclusionsThe approach we describe can be implemented to enable the detection of phenotypically relevant fusion transcripts in studies of rare inherited disease. Fusion transcript detection has the potential to increase diagnostic rates in rare inherited disease and should be included in RNA-based analytical pipelines aimed at genetic diagnosis.

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A t(3;9)(q25.1;q34.3) translocation leading to OLFM1 fusion transcripts in Gilles de la Tourette syndrome, OCD and ADHD

Cited by 18 publications

References 43 publications

Spatiotemporal and Long Lasting Modulation of 11 Key Nogo Signaling Genes in Response to Strong Neuroexcitation

Spatiotemporal and Long Lasting Modulation of 11 Key Nogo Signaling Genes in Response to Strong Neuroexcitation

A guide for the diagnosis of rare and undiagnosed disease: beyond the exome

A tailored approach to fusion transcript identification increases diagnosis of rare inherited disease

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