Emerging therapeutic targets for narcolepsy

Vringer, Marieke; Kornum, Birgitte Rahbek

doi:10.1080/14728222.2021.1969361

Cited by 6 publications

(6 citation statements)

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“…To investigate TCR activation specificity by antigens, we randomly selected 48 clones cocultured with previously reported 28 binders originating from different Pandemrix and virus segments (HA, 8; NP, 7; NA, 3) and HCRT ( 10 , 42 ), including pHA 273–287 , NP 17–31 , HCRT 54–66-NH2 , and HCRT 86–97-NH2 ( Dataset S1 ). These latter HCRT peptides contain C-terminal binding core GNHAAGILTL/M but differ in length and amidation (preproHCRT14/15 are C-terminal nonamidated; Dataset S1 ).…”

Section: Resultsmentioning

confidence: 99%

“…Narcolepsy type 1 (NT1) is caused by a loss of hypocretin/orexin (HCRT) neurons in the mediolateral hypothalamus ( 1 – 3 ), with recent data suggesting reversion of the human and animal phenotype with orexin agonists. The disease is strongly associated with human leukocyte antigen (HLA) DQB1*06:02/DQA1*01:02 (98% vs. 25%) (DQ0602) and displays weaker genetic associations with other immune loci, thus suggesting autoimmunity ( 4 – 9 ), although not meeting all criteria for being classified as an autoimmune disease ( 10 ). Like other autoimmune diseases, NT1 presents with increased comorbidity with other autoimmune conditions and asthma ( 11 – 13 ).…”

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confidence: 99%

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Characterization of T cell receptors reactive to HCRT _NH2 , pHA _273-287 , and NP _17-31 in control and narcolepsy patients

Luo

Zhang

Lin

et al. 2022

Proc. Natl. Acad. Sci. U.S.A.

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Narcolepsy type 1 (NT1), a disorder caused by hypocretin/orexin (HCRT) cell loss, is associated with human leukocyte antigen (HLA)-DQ0602 (98%) and T cell receptor (TCR) polymorphisms. Increased CD4 + T cell reactivity to HCRT, especially DQ0602-presented amidated C-terminal HCRT (HCRT NH2 ), has been reported, and homology with pHA 273–287 flu antigens from pandemic 2009 H1N1, an established trigger of the disease, suggests molecular mimicry. In this work, we extended DQ0602 tetramer and dextramer data to 77 cases and 44 controls, replicating our prior finding and testing 709 TCRs in Jurkat 76 T cells for functional activation. We found that fewer TCRs isolated with HCRT NH2 (∼11%) versus pHA 273–287 or NP 17–31 antigens (∼50%) were activated by their ligand. Single-cell characterization did not reveal phenotype differences in influenza versus HCRT NH2 -reactive T cells, and analysis of TCR CDR3αβ sequences showed TCR clustering by responses to antigens but no cross-peptide class reactivity. Our results do not support the existence of molecular mimicry between HCRT and pHA 273–287 or NP 17–31 .

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Section: Resultsmentioning

confidence: 99%

mentioning

confidence: 99%

Characterization of T cell receptors reactive to HCRT _NH2 , pHA _273-287 , and NP _17-31 in control and narcolepsy patients

Luo

Zhang

Lin

et al. 2022

Proc. Natl. Acad. Sci. U.S.A.

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“…Narcolepsy type 1 (NT1) is a rare neurological disorder, with a prevalence of only 0.02% to 0.05% [ 1 , 2 ]. Due to uncontrollable lethargy and unpredictable cataplexy, patients with narcolepsy are seriously affected in their ability to study, live, and work, while even causing accidents that endanger lives and property [ 3 ].…”

Section: Introductionmentioning

confidence: 99%

Abnormal Regional Spontaneous Neural Activity and Functional Connectivity in Unmedicated Patients with Narcolepsy Type 1: A Resting-State fMRI Study

Zhan²,

Liu³

et al. 2022

IJERPH

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Background: Previous Resting-state functional magnetic resonance imaging (fMRI) studies have mainly focused on cerebral functional alteration in processing different emotional stimuli in patients with narcolepsy type 1 (NT1), but were short of exploration of characteristic brain activity and its remote interaction patterns. This study aimed to investigate the spontaneous blood oxygen fluctuations at rest and to elucidate the neural mechanisms underlying neuropsychiatric behavior. Method: A total of 18 unmedicated patients with NT1 and matched healthy individuals were recruited in a resting-state fMRI study. Magnetic resonance imaging (MRI) data were first analyzed using fractional low-frequency amplitude of low-frequency fluctuation (fALFF) to detect changes in local neural activity, and regions with group differences were taken as regions of interest (ROIs). Secondly, functional connectivity (FC) analysis was used to explore altered connectivity between ROIs and other areas. Lastly, the relationship between functional brain activity and neuropsychiatric behaviors was analyzed with correlation analysis. Results: fALFF analysis revealed enhanced neural activity in bilateral fusiform gyrus (FFG), right precentral gyrus, and left postcentral gyrus (PoCG) in the NT1 group. The patients indicated reduced activity in the bilateral temporal pole middle temporal gyrus (TPOmid), left caudate nucleus (CAU), left parahippocampus, left precuneus (PCUN), right amygdala, and right anterior cingulate and paracingulate gyri. ESS score was negatively correlated with fALFF in the right FFG. The NT1 group revealed decreased connectivity between left TPOmid and right PoCG, the bilateral middle frontal gyrus, left superior frontal gyrus, medial, and right supramarginal gyrus. Epworth Sleepiness Scale (ESS) was negatively correlated with FC of the left TPOmid with left putamen (PUT) in NT1. Compared with healthy controls (HCs), enhanced FC of the left CAU with right FFG was positively associated with MSLT-SOREMPs in patients. Furthermore, increased FC of the left PCUN with right PoCG was positively correlated with SDS score. Conclusions: We found that multiple functional activities related to the processing of emotional regulation and sensory information processing were abnormal, and some were related to clinical characteristics. fALFF in the left postcentral or right precentral gyrus may be used as a biomarker of narcolepsy, whereas fALFF in the right fusiform and the FC strength of the left temporal pole middle temporal gyrus with the putamen may be clinical indicators to assess the drowsiness severity of narcolepsy.

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“…4 Orexin-targeted precision therapies for narcolepsy type 1 are being developed actively. 5,6 These agents hope to build on the already established concept that treatment of hypersomnia and cataplexy can be separate, with some medications treating only hypersomnia, only cataplexy, or both. 5,6 As is commonly seen in data-driven phenotyping approaches, the authors did not look at the direct clinical implications of each phenotype.…”

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confidence: 99%

“…5,6 These agents hope to build on the already established concept that treatment of hypersomnia and cataplexy can be separate, with some medications treating only hypersomnia, only cataplexy, or both. 5,6 As is commonly seen in data-driven phenotyping approaches, the authors did not look at the direct clinical implications of each phenotype. For example, patients who were phenotype 1 may be failed by modafinil but respond well to oxybates, or patients who were phenotype 6 may transition to narcolepsy type 1 after 6 to 12 months.…”

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confidence: 99%

Working Toward Clinically Meaningful Subtypes of Hypersomnolence Using Data-Driven Phenotyping, but Not There Yet

Kerr

2022

Neurology

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Neurologists establish individualized treatment plans that are based on specific diagnoses. This includes both the main diagnosis (e.g., hypersomnolence) and any subcategories that will influence the neurologist's recommendations (e.g., narcolepsy type 1).1 Traditionally, these diagnoses are based on criteria determined by expert consensus such as the International Classification of Sleep Disorders (ICSD-3).2 While the experts who develop these criteria leverage their extensive experience to justify their clinical value, these criteria are ultimately qualitative and subject to the strengths and limitations of human cognition to identify patterns in complex data. As we enter the era of precision medicine, data-driven methods seek to supplement this human judgment to ensure that these diagnostic criteria truly inform and improve clinical care.

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Emerging therapeutic targets for narcolepsy

Cited by 6 publications

References 142 publications

Characterization of T cell receptors reactive to HCRT _NH2 , pHA _273-287 , and NP _17-31 in control and narcolepsy patients

Characterization of T cell receptors reactive to HCRT _NH2 , pHA _273-287 , and NP _17-31 in control and narcolepsy patients

Abnormal Regional Spontaneous Neural Activity and Functional Connectivity in Unmedicated Patients with Narcolepsy Type 1: A Resting-State fMRI Study

Working Toward Clinically Meaningful Subtypes of Hypersomnolence Using Data-Driven Phenotyping, but Not There Yet

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Emerging therapeutic targets for narcolepsy

Cited by 6 publications

References 142 publications

Characterization of T cell receptors reactive to HCRT NH2 , pHA 273-287 , and NP 17-31 in control and narcolepsy patients

Characterization of T cell receptors reactive to HCRT NH2 , pHA 273-287 , and NP 17-31 in control and narcolepsy patients

Abnormal Regional Spontaneous Neural Activity and Functional Connectivity in Unmedicated Patients with Narcolepsy Type 1: A Resting-State fMRI Study

Working Toward Clinically Meaningful Subtypes of Hypersomnolence Using Data-Driven Phenotyping, but Not There Yet

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Characterization of T cell receptors reactive to HCRT _NH2 , pHA _273-287 , and NP _17-31 in control and narcolepsy patients

Characterization of T cell receptors reactive to HCRT _NH2 , pHA _273-287 , and NP _17-31 in control and narcolepsy patients