A novel, highly sensitive and specific biomarker for Niemann-Pick type C1 disease

Anne-Katrin Giese, Hermann Mascher, Ulrike Grittner, Sabrina Eichler, Guido Kramp, Jan Lukas, Danielle te Vruchte, Nada Al Eisa, Mario Cortina-Borja, Forbes D Porter, Frances M Platt, Arndt Rolfs, Anne-Katrin Giese, Hermann Mascher, Ulrike Grittner, Sabrina Eichler, Guido Kramp, Jan Lukas, Danielle te Vruchte, Nada Al Eisa, Mario Cortina-Borja, Forbes D Porter, Frances M Platt, Arndt Rolfs

Abstract

Background: Lysosomal storage disorders (LSDs), are a heterogeneous group of rare disorders caused by defects in genes encoding for proteins involved in the lysosomal degradation of macromolecules. They occur at a frequency of about 1 in 5,000 live births, though recent neonatal screening suggests a higher incidence. New treatment options for LSDs demand a rapid, early diagnosis of LSDs if maximal clinical benefit is to be achieved.

Methods: Here, we describe a novel, highly specific and sensitive biomarker for Niemann-Pick Type C disease type 1 (NPC1), lyso-sphingomyelin-509. We cross-validate this biomarker with cholestane-3β,5α,6β-triol and relative lysosomal volume. The primary cohort for establishment of the biomarker contained 135 NPC1 patients, 66 NPC1 carriers, 241 patients with other LSDs and 46 healthy controls.

Results: With a sensitivity of 100.0% and specificity of 91.0% a cut-off of 1.4 ng/ml was established. Comparison with cholestane-3β,5α,6β-triol and relative acidic compartment volume measurements were carried out with a subset of 125 subjects. Both cholestane-3β,5α,6β-triol and lyso-Sphingomyelin-509 were sufficient in establishing the diagnosis of NPC1 and correlated with disease severity.

Conclusion: In summary, we have established a new biomarker for the diagnosis of NPC1, and further studies will be conducted to assess correlation to disease progress and monitoring treatment.

Figures

Figure 1
Figure 1
Chemical structure of Lyso-Sphingomyelin-509. This substance was analysed by HPLC-MS/MS with high sensitivity and specificity of diagnosing NPC. The precise structure of lyso-SM-509 has not yet been elucidated.
Figure 2
Figure 2
Levels of lyso-SM-509 in patients with NPC1 (n = 110), NP-A/B (n = 21), as well as healthy controls (n = 43) and NPC1 carriers (n = 63) and NP-A/B carriers (n = 5). (A) Lyso-SM-509 allows distinguishing between healthy controls and patients with NPC1. Notably, the biomarker levels are for NP-A/B patients were 3.55-times higher (29.4 ng/ml (IQR: 14.8-40.0). Notably, only in two cases lyso-SM-509 levels above 2.5 ng/ml can be detected in a carrier of a NPC1 mutation and in none of the healthy controls. (B) Levels of lyso-SM-509 in NPC1 by age. Note that Lyso-SM-509 is higher in younger NPC1 patients (ρ = -0.519, p < 0.001), reflecting the severity of early onset disease as shown by Te Vruchte and colleagues (11).
Figure 3
Figure 3
Comparison of Lyso-SM-509, cholestane-3β,5α,6β-triol and MEFL. (A) Boxplot of lyso-SM-509 by genotype, (B) boxplot of cholestane-3β,5α,6β-triol by genotype, (C) boxplot of MEFL (LysoTracker) by genotype. Both lyso-SM-509 and cholestane-3β,5α,6β-triol facilitate the distinction of NPC patients from healthy controls.
Figure 4
Figure 4
Comparison of MEFL (LysoTracker) (log scale) and lyso-SM-509 (linear scale). Levels of lyso-SM-509 significantly correlate with MEFL in NPC1 patients (ρ =0.432, p < 0.001). The Red line is a linear model.
Figure 5
Figure 5
Cholestane-3β,5α,6β-triol vs lyso-SM-509 (log-log scale) by genotype. Lyso-SM-509 and cholestane-3β,5α,6β-triol correlate very well by genotype (Healthy controls, NPC1 carriers and NPC1 patients; ρ = 0.675, p <0.001); blue line is a super smoother.
Figure 6
Figure 6
Linear Modelling for all NPC patients. Linear modelling was performed for all NPC patients were ASIS, Lyso-SM-509 (A), MEFL (B) and cholestane-3β,5α,6β-triol (C) were available. Each patient contributes only one measurement. All three biomarkers significantly correlated with ASIS (p = 0.003 (A), p = 0.039 (B), and p < 0.001 (C). The red lines correspond to the linear models fitted.

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Source: PubMed

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