Clinical disease progression and biomarkers in Niemann-Pick disease type C: a prospective cohort study.
Biomarkers
Cholestane-triol
Heat shock protein
Lysosomal storage disease
NPC Clinical Severity Scale (NPCCSS)
Natural history of disease
Niemann–Pick type C (NPC) disease
Observational study
Reliability
Journal
Orphanet journal of rare diseases
ISSN: 1750-1172
Titre abrégé: Orphanet J Rare Dis
Pays: England
ID NLM: 101266602
Informations de publication
Date de publication:
23 11 2020
23 11 2020
Historique:
received:
11
06
2020
accepted:
10
11
2020
entrez:
24
11
2020
pubmed:
25
11
2020
medline:
22
6
2021
Statut:
epublish
Résumé
Niemann-Pick disease type C (NPC) is a rare, progressive, neurodegenerative disease associated with neurovisceral manifestations resulting from lysosomal dysfunction and aberrant lipid accumulation. A multicentre, prospective observational study (Clinical Trials.gov ID: NCT02435030) of individuals with genetically confirmed NPC1 or NPC2 receiving routine clinical care was conducted, to prospectively characterize and measure NPC disease progression and to investigate potential NPC-related biomarkers versus healthy individuals. Progression was measured using the abbreviated 5-domain NPC Clinical Severity Scale (NPCCSS), 17-domain NPCCSS and NPC clinical database (NPC-cdb) score. Cholesterol esterification and heat shock protein 70 (HSP70) levels were assessed from peripheral blood mononuclear cells (PBMCs), cholestane-3β,5α-,6β-triol (cholestane-triol) from serum, and unesterified cholesterol from both PBMCs and skin biopsy samples. The inter- and intra-rater reliability of the 5-domain NPCCSS was assessed by 13 expert clinicians' rating of four participants via video recordings, repeated after ≥ 3 weeks. Intraclass correlation coefficients (ICCs) were calculated. Of the 36 individuals with NPC (2-18 years) enrolled, 31 (86.1%) completed the 6-14-month observation period; 30/36 (83.3%) were receiving miglustat as part of routine clinical care. A mean (± SD) increase in 5-domain NPCCSS scores of 1.4 (± 2.9) was observed, corresponding to an annualized progression rate of 1.5. On the 17-domain NPCCSS, a mean (± SD) progression of 2.7 (± 4.0) was reported. Compared with healthy individuals, the NPC population had significantly lower levels of cholesterol esterification (p < 0.0001), HSP70 (p < 0.0001) and skin unesterified cholesterol (p = 0.0006). Cholestane-triol levels were significantly higher in individuals with NPC versus healthy individuals (p = 0.008) and correlated with the 5-domain NPCCSS (Spearman's correlation coefficient = 0.265, p = 0.0411). The 5-domain NPCCSS showed high ICC agreement in inter-rater reliability (ICC = 0.995) and intra-rater reliability (ICC = 0.937). Progression rates observed were consistent with other reports on disease progression in NPC. The 5-domain NPCCSS reliability study supports its use as an abbreviated alternative to the 17-domain NPCCSS that focuses on the most relevant domains of the disease. The data support the use of cholestane-triol as a disease monitoring biomarker and the novel methods of measuring unesterified cholesterol could be applicable to support NPC diagnosis. Levels of HSP70 in individuals with NPC were significantly decreased compared with healthy individuals. CT-ORZY-NPC-001: ClincalTrials.gov NCT02435030, Registered 6 May 2015, https://clinicaltrials.gov/ct2/show/NCT02435030 ; EudraCT 2014-005,194-37, Registered 28 April 2015, https://www.clinicaltrialsregister.eu/ctr-search/trial/2014-005194-37/DE . OR-REL-NPC-01: Unregistered.
Sections du résumé
BACKGROUND
Niemann-Pick disease type C (NPC) is a rare, progressive, neurodegenerative disease associated with neurovisceral manifestations resulting from lysosomal dysfunction and aberrant lipid accumulation. A multicentre, prospective observational study (Clinical Trials.gov ID: NCT02435030) of individuals with genetically confirmed NPC1 or NPC2 receiving routine clinical care was conducted, to prospectively characterize and measure NPC disease progression and to investigate potential NPC-related biomarkers versus healthy individuals. Progression was measured using the abbreviated 5-domain NPC Clinical Severity Scale (NPCCSS), 17-domain NPCCSS and NPC clinical database (NPC-cdb) score. Cholesterol esterification and heat shock protein 70 (HSP70) levels were assessed from peripheral blood mononuclear cells (PBMCs), cholestane-3β,5α-,6β-triol (cholestane-triol) from serum, and unesterified cholesterol from both PBMCs and skin biopsy samples. The inter- and intra-rater reliability of the 5-domain NPCCSS was assessed by 13 expert clinicians' rating of four participants via video recordings, repeated after ≥ 3 weeks. Intraclass correlation coefficients (ICCs) were calculated.
RESULTS
Of the 36 individuals with NPC (2-18 years) enrolled, 31 (86.1%) completed the 6-14-month observation period; 30/36 (83.3%) were receiving miglustat as part of routine clinical care. A mean (± SD) increase in 5-domain NPCCSS scores of 1.4 (± 2.9) was observed, corresponding to an annualized progression rate of 1.5. On the 17-domain NPCCSS, a mean (± SD) progression of 2.7 (± 4.0) was reported. Compared with healthy individuals, the NPC population had significantly lower levels of cholesterol esterification (p < 0.0001), HSP70 (p < 0.0001) and skin unesterified cholesterol (p = 0.0006). Cholestane-triol levels were significantly higher in individuals with NPC versus healthy individuals (p = 0.008) and correlated with the 5-domain NPCCSS (Spearman's correlation coefficient = 0.265, p = 0.0411). The 5-domain NPCCSS showed high ICC agreement in inter-rater reliability (ICC = 0.995) and intra-rater reliability (ICC = 0.937).
CONCLUSIONS
Progression rates observed were consistent with other reports on disease progression in NPC. The 5-domain NPCCSS reliability study supports its use as an abbreviated alternative to the 17-domain NPCCSS that focuses on the most relevant domains of the disease. The data support the use of cholestane-triol as a disease monitoring biomarker and the novel methods of measuring unesterified cholesterol could be applicable to support NPC diagnosis. Levels of HSP70 in individuals with NPC were significantly decreased compared with healthy individuals.
TRIAL REGISTRATION
CT-ORZY-NPC-001: ClincalTrials.gov NCT02435030, Registered 6 May 2015, https://clinicaltrials.gov/ct2/show/NCT02435030 ; EudraCT 2014-005,194-37, Registered 28 April 2015, https://www.clinicaltrialsregister.eu/ctr-search/trial/2014-005194-37/DE . OR-REL-NPC-01: Unregistered.
Identifiants
pubmed: 33228797
doi: 10.1186/s13023-020-01616-0
pii: 10.1186/s13023-020-01616-0
pmc: PMC7684888
doi:
Substances chimiques
Biomarkers
0
Banques de données
ClinicalTrials.gov
['NCT02435030']
Types de publication
Journal Article
Multicenter Study
Observational Study
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
328Commentaires et corrections
Type : ErratumIn
Références
Vanier M. Niemann-Pick disease type C. Orphanet J Rare Dis. 2010;5:16.
pubmed: 20525256
pmcid: 2902432
Hammond N, Munkacsi AB, Sturley SL. The complexity of a monogenic neurodegenerative disease: more than two decades of therapeutic driven research into Niemann-Pick type C disease. Biochim Biophys Acta Mol Cell Biol Lipids. 2019;1864(8):1109–23.
pubmed: 31002946
Naureckiene S, Sleat DE, Lackland H, Fensom A, Vanier MT, Wattiaux R, et al. Identification of HE1 as the second gene of Niemann-Pick C disease. Science. 2000;290(5500):2298–301.
pubmed: 11125141
Lloyd-Evans E, Platt FM. Lipids on trial: the search for the offending metabolite in Niemann-Pick type C disease. Traffic. 2010;11(4):419–28.
pubmed: 20059748
Rosenbaum AI, Maxfield FR. Niemann-Pick type C disease: molecular mechanisms and potential therapeutic approaches. J Neurochem. 2011;116(5):789–95.
pubmed: 20807315
pmcid: 3008286
Chung C, Elrick MJ, Dell’Orco JM, Qin ZS, Kalyana-Sundaram S, Chinnaiyan AM, et al. Heat shock protein beta-1 modifies anterior to posterior Purkinje cell vulnerability in a mouse model of Niemann-Pick type C disease. PLoS Genet. 2016;12(5):e1006042.
pubmed: 27152617
pmcid: 4859571
Patterson M, Clayton P, Gissen P, Anheim M, Bauer P, Bonnot O, et al. Recommendations for the detection and diagnosis of Niemann-Pick disease type C: An update. Neurol Clin Pract. 2017;7(6):499–511.
pubmed: 29431164
pmcid: 5800709
Wraith JE, Sedel F, Pineda M, Wijburg FA, Hendriksz CJ, Fahey M, et al. Niemann-Pick type C suspicion index tool: analyses by age and association of manifestations. J Inherit Metab Dis. 2014;37(1):93–101.
pubmed: 23793527
Kirkegaard T, Roth A, Petersen N, Mahalka A, Olsen O, Moilanen I, et al. Hsp70 stabilizes lysosomes and reverts Niemann-Pick disease-associated lysosomal pathology. Nature. 2010;463(7280):549–53.
pubmed: 20111001
Patterson MC, Mengel E, Wijburg FA, Muller A, Schwierin B, Drevon H, et al. Disease and patient characteristics in NP-C patients: findings from an international disease registry. Orphanet J Rare Dis. 2013;8:12.
pubmed: 23324478
pmcid: 3558399
Thurm A, Farmer C, Farhat NY, Wiggs E, Black D, Porter FD. Cohort study of neurocognitive functioning and adaptive behaviour in children and adolescents with Niemann-Pick Disease type C1. Dev Med Child Neurol. 2016;58(3):262–9.
pubmed: 26586413
Dardis A, Zampieri S, Gellera C, Carrozzo R, Cattarossi S, Peruzzo P, et al. Molecular genetics of Niemann-Pick type C disease in Italy: an update on 105 patients and description of 18 NPC1 novel variants. J Clin Med. 2020;9:3.
Garbade SF, Zielonka M, Komatsuzaki S, Kolker S, Hoffmann GF, Hinderhofer K, et al. Quantitative retrospective natural history modeling for orphan drug development. J Inherit Metab Dis. 2020:1–11.
Higgins JJ, Patterson MC, Dambrosia JM, Pikus AT, Pentchev PG, Sato S, et al. A clinical staging classification for type C Niemann-Pick disease. Neurology. 1992;42(12):2286–90.
pubmed: 1461380
Iturriaga C, Pineda M, Fernandez-Valero EM, Vanier MT, Coll MJ. Niemann-Pick C disease in Spain: clinical spectrum and development of a disability scale. J Neurol Sci. 2006;249(1):1–6.
pubmed: 16814322
Yanjanin NM, Velez JI, Gropman A, King K, Bianconi SE, Conley SK, et al. Linear clinical progression, independent of age of onset, in Niemann-Pick disease, type C. Am J Med Genet B Neuropsychiatr Genet. 2010;153B(1):132–40.
pubmed: 19415691
pmcid: 2798912
Ory DS, Ottinger EA, Farhat NY, King KA, Jiang X, Weissfeld L, et al. Intrathecal 2-hydroxypropyl-beta-cyclodextrin decreases neurological disease progression in Niemann-Pick disease, type C1: a non-randomised, open-label, phase 1–2 trial. Lancet. 2017;390(10104):1758–68.
pubmed: 28803710
pmcid: 6176479
Cortina-Borja M, Vruchte D, Mengel E, Amraoui Y, Imrie J, Jones S, et al. Annual severity increment score as a tool for stratifying patients with Niemann-Pick disease type C and for recruitment to clinical trials. Orphanet J Rare Dis. 2018;13:143.
pubmed: 30115089
pmcid: 6097294
Fleiss JL, Levin B, Paik MC. Statistical methods for rates and proportions. 2nd ed. New York: Wiley; 1981.
Sim J, Wright C. Research in health care: concepts, designs and methods: Nelson Thornes; 2000.
Geberhiwot T, Moro A, Dardis A, Ramaswami U, Sirrs S, Marfa MP, et al. Consensus clinical management guidelines for Niemann-Pick disease type C. Orphanet J Rare Dis. 2018;13(1):50.
pubmed: 29625568
pmcid: 5889539
Porter FD, Scherrer DE, Lanier MH, Langmade SJ, Molugu V, Gale SE, et al. Cholesterol oxidation products are sensitive and specific blood-based biomarkers for Niemann-Pick C1 disease. Sci Transl Med. 2010;2(56):56–81.
Jiang X, Sidhu R, Porter FD, Yanjanin NM, Speak AO, te Vruchte DT, et al. A sensitive and specific LC-MS/MS method for rapid diagnosis of Niemann-Pick C1 disease from human plasma. J Lipid Res. 2011;52(7):1435–45.
pubmed: 21518695
pmcid: 3122908
Vanier MT, Latour P. Laboratory diagnosis of Niemann-Pick disease type C: the filipin staining test. Methods Cell Biol. 2015;126:357–75.
pubmed: 25665455
Vanier MT, Wenger DA, Comly ME, Rousson R, Brady RO, Pentchev PG. Niemann-Pick disease group C: clinical variability and diagnosis based on defective cholesterol esterification A collaborative study on 70 patients. Clin Genet. 1988;33(5):331–48.
pubmed: 3378364
Gomez-Pastor R, Burchfiel ET, Thiele DJ. Regulation of heat shock transcription factors and their roles in physiology and disease. Nat Rev Mol Cell Biol. 2018;19(1):4–19.
pubmed: 28852220
pmcid: 28852220
Kirkegaard T, Gray J, Priestman D, Wallom K, Atkins J, Olsen O, et al. Heat shock protein-based therapy as a potential candidate for treating the sphingolipidoses. Sci Transl Med. 2016;8:355.
Nakasone N, Nakamura Y, Higaki K, Oumi N, Ohno K, Ninomiya H. Endoplasmic reticulum-associated degradation of Niemann-Pick C1. J Biol Chem. 2014;289:19714–25.
pubmed: 24891511
pmcid: 4094081
Rosenzweig R, Nillegoda NB, Mayer MP, Bukau B. The Hsp70 chaperone network. Nat Rev Mol Cell Biol. 2019;20(11):665–80.
pubmed: 31253954
Hartl FU, Bracher A, Hayer-Hartl M. Molecular chaperones in protein folding and proteostasis. Nature. 2011;475(7356):324–32.
Petersen NH, Kirkegaard T, Olsen OD, Jaattela M. Connecting Hsp70, sphingolipid metabolism and lysosomal stability. Cell Cycle. 2010;9(12):2305–9.
pubmed: 20519957
Nylandsted J, Gyrd-Hansen M, Danielewicz A, Fehrenbacher N, Lademann U, Hoyer-Hansen M, et al. Heat shock protein 70 promotes cell survival by inhibiting lysosomal membrane permeabilization. J Exp Med. 2004;200(4):425–35.
pubmed: 15314073
pmcid: 2211935
Barna J, Csermely P, Vellai T. Roles of heat shock factor 1 beyond the heat shock response. Cell Mol Life Sci. 2018;75(16):2897–916.
pubmed: 29774376
Watanabe Y, Tsujimura A, Taguchi K, Tanaka M. HSF1 stress response pathway regulates autophagy receptor SQSTM1/p62-associated proteostasis. Autophagy. 2017;13(1):133–48.
pubmed: 27846364
Kalmar B, Greensmith L. Activation of the heat shock response in a primary cellular model of motoneuron neurodegeneration-evidence for neuroprotective and neurotoxic effects. Cell Mol Biol Lett. 2009;14(2):319–35.
pubmed: 19183864
pmcid: 6275696
Kalmar B, Lu C, Greensmith L. The role of heat shock proteins in Amyotrophic Lateral Sclerosis: the therapeutic potential of Arimoclomol. Pharmacol Ther. 2014;141(1):40–54.
pubmed: 23978556
Penke B, Bogar F, Crul T, Santha M, Toth M, Vigh L. Heat shock proteins and autophagy pathways in neuroprotection: from molecular bases to pharmalogical interventions. Int J Mol Sci. 2018;19:325.
pmcid: 5796267
Sarna JR, Larouche M, Marzban H, Sillitoe RV, Rancourt DE, Hawkes R. Patterned Purkinje cell degeneration in mouse models of Niemann-Pick type C disease. J Comp Neurol. 2003;456(3):279–91.
pubmed: 12528192
NCT02435030. A prospective non-therapeutic study in patients diagnosed with Niemann-Pick disease Type C. Clinical Trials; 2015.
Runz H, Dolle D, Schlitter AM, Zschocke J. NPC-db, a Niemann-Pick type C disease gene variation database. Hum Mutat. 2008;29(3):345–50.
pubmed: 18081003
Deodato F, Boenzi S, Taurisano R, Semeraro M, Sacchetti E, Carrozzo R, et al. The impact of biomarkers analysis in the diagnosis of Niemann-Pick C disease and acid sphingomyelinase deficiency. Clin Chim Acta. 2018;486:387–94.
pubmed: 30153451
Linacre J. Many-facet Rasch Measurement. Chicago: MESA Press; 1994.
Garbade SF, Zielonka M, Komatzsuzaki S, Kolker S, Hoffmann GH, Hinderhofer K, et al. Supporting orphan drug development with retrospective quantiative natural history modeling—conceptual framework, opportunities and limitations. J Inherit Metab Dis. 2020:Submitted, under review.
Kassen S, Parseghian C, Andrews P, Jacoby J, Marella P, McGlocklin S, et al. Niemann–Pick type C patient and caregiver voices: externally-led, patient-focused drug development meeting. 2019.
Schmitz-Hubsch T, du Montcel ST, Baliko L, Berciano J, Boesch S, Depondt C, et al. Scale for the assessment and rating of ataxia: development of a new clinical scale. Neurology. 2006;66(11):1717–20.
pubmed: 16769946
Poole JL, Burtner PA, Torres TA, McMullen CK, Markham A, Marcum ML, et al. Measuring dexterity in children using the Nine-hole Peg Test. J Hand Ther. 2005;18(3):348–51.
pubmed: 16059856
Millat G, Marcais C, Tomasetto C, Chikh K, Fensom AH, Harzer K, et al. Niemann-Pick C1 disease: correlations between NPC1 mutations, levels of NPC1 protein, and phenotypes emphasize the functional significance of the putative sterol-sensing domain and of the cysteine-rich luminal loop. Am J Hum Genet. 2001;68(6):1373–85.
pubmed: 11333381
pmcid: 1226124
Platt FM, d’Azzo A, Davidson BL, Neufeld EF, Tifft CJ. Lysosomal storage diseases. Nat Rev Dis Primers. 2018;4(1):27.
pubmed: 30275469
Seker Yilmaz B, Baruteau J, Rahim AA, Gissen P. Clinical and Molecular Features of Early Infantile Niemann Pick Type C Disease. Int J Mol Sci. 2020;21(14).
Park WD, O’Brien JF, Lundquist PA, Kraft DL, Vockley CW, Karnes PS, et al. Identification of 58 novel mutations in Niemann-Pick disease type C: correlation with biochemical phenotype and importance of PTC1-like domains in NPC1. Hum Mutat. 2003;22(4):313–25.
pubmed: 12955717
Jiang X, Sidhu R, Mydock-McGrane L, Hsu FF, Covey DF, Scherrer DE, et al. Development of a bile acid-based newborn screen for Niemann-Pick disease type C. Sci Transl Med. 2016;8(337):337–63.
Mashima R, Maekawa M, Narita A, Okuyama T, Mano N. Elevation of plasma lysosphingomyelin-509 and urinary bile acid metabolite in Niemann-Pick disease type C-affected individuals. Mol Genet Metab Rep. 2018;15:90–5.
pubmed: 30023294
pmcid: 6047109
Maekawa M, Jinnoh I, Matsumoto Y, Narita A, Mashima R, Takahashi H, et al. Structural determination of lysosphingomyelin-509 and discovery of novel class lipids from patients with Niemann-Pick disease type C. Int J Mol Sci. 2019;20(20):5018.
pmcid: 6829288
Platt FM, Wassif C, Colaco A, Dardis A, Lloyd-Evans E, Bembi B, et al. Disorders of cholesterol metabolism and their unanticipated convergent mechanisms of disease. Annu Rev Genomics Hum Genet. 2014;15:173–94.
pubmed: 25184529
pmcid: 6292211
Ingemann L, Kirkegaard T. Lysosomal storage diseases and the heat shock response: convergences and therapeutic opportunities. J Lipid Res. 2014;55(11):2198–210.
pubmed: 24837749
pmcid: 4617124
Madden J, Coward JC, Shearman CP, Grimble RF, Calder PC. Hsp70 expression in monocytes from patients with peripheral arterial disease and healthy controls: monocyte Hsp70 in PAD. Cell Biol Toxicol. 2010;26(3):215–23.
pubmed: 19672680
European Medicines Agency. Summary of product characteristics for miglustat 2009. Accessed 7 February. https://www.ema.europa.eu/en/documents/product-information/zavesca-epar-product-information_en.pdf .
Imrie J, Heptinstall L, Knight S, Strong K. Observational cohort study of the natural history of Niemann-Pick disease type C in the UK: a 5-year update from the UK clinical database. BMC Neurol. 2015;15:257.
pubmed: 26666848
pmcid: 4678528
NCT02612129. Arimoclomol prospective study in patients diagnosed with Niemann–Pick disease type C. 2019.
International Conference on Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use. ICH harmonised tripartite guideline. Guideline for good clinical practice 1996. Accessed 4 October 2019. https://www.ich.org/fileadmin/Public_Web_Site/ICH_Products/Guidelines/Efficacy/E6_R1/Step4/E6_R1__Guideline.pdf
World Medical Association. Declaration of Helsinki: Ethical Principles for Medical Research Involving Human Subjects. Accessed 4 October 2019. https://www.wma.net/en/30publications/10policies/b3/index.html .
Stampfer M, Theiss S, Amraoui Y, Jiang X, Keller S, Ory DS, et al. Niemann-Pick disease type C clinical database: cognitive and coordination deficits are early disease indicators. Orphanet J Rare Dis. 2013;8:35.
pubmed: 23433426
pmcid: 3649939
Van Reenen, Janssen BM, Oppe M, Kreimeier S, Greiner W. EQ-5D-Y user guide: basic information on how to use the EQ-5D-Y instrument: EuroQol Group; 2014. https://euroqol.org/wp-content/uploads/2019/10/EQ-5D-Y-User-Guide.pdf .
Crosley LK, Duthie SJ, Polley AC, Bouwman FG, Heim C, Mulholland F, et al. Variation in protein levels obtained from human blood cells and biofluids for platelet, peripheral blood mononuclear cell, plasma, urine and saliva proteomics. Genes Nutr. 2009;4(2):95–102.
pubmed: 19408033
pmcid: 2690729
Devlin NJ, Parkin D, Browne J. Patient-reported outcome measures in the NHS: new methods for analysing and reporting EQ-5D data. Health Econ. 2010;19(8):886–905.
pubmed: 20623685
Landis JR, Koch GG. The measurement of observer agreement for categorical data. Biometrics. 1977;33(1):159–74.
pubmed: 843571
pmcid: 843571