Niemann-Pick type C disease (NP-C) is a progressive lysosomal lipid storage disease caused by mutations in the NPC1 and NPC2 genes. NPC1 is essential for transporting cholesterol and other lipids out of lysosomes, but little is known about the mechanisms that control its cellular abundance and localization. Here we show that a reduction of TMEM97, a cholesterol-responsive NPC1-binding protein, increases NPC1 levels in cells through a post-transcriptional mechanism. Reducing TMEM97 through RNA-interference reduces lysosomal lipid storage and restores cholesterol trafficking to the endoplasmic reticulum in cell models of NP-C. In TMEM97 knockdown cells, NPC1 levels can be reinstated with wild type TMEM97, but not TMEM97 missing an ER-retention signal suggesting that TMEM97 contributes to controlling the availability of NPC1 to the cell. Importantly, knockdown of TMEM97 also increases levels of residual NPC1 in NPC1-mutant patient fibroblasts and reduces cholesterol storage in an NPC1-dependent manner. Our findings propose TMEM97 inhibition as a novel strategy to increase residual NPC1 levels in cells and a potential therapeutic target for NP-C.

BackgroundThe neurodegenerative lysosomal storage disorder Niemann-Pick disease type C (NP-C) is characterized by a broad clinical variability involving neurological, psychiatric and systemic signs. Diverse patterns of disease manifestation and progression considerably delay its diagnosis. Here we introduce the NP-C clinical database (NPC-cdb) to systematically obtain, store and analyze diagnostic and clinical findings in patients with NP-C. We apply NPC-cdb to study NP-C temporal expression in a large German-Swiss patient cohort.MethodsCurrent and past medical history was systematically acquired from 42 patients using tailored questionnaires. Manifestation of 72 distinct neuropsychiatric signs was modeled over the course of disease. The sequence of disease progression was re-constructed by a novel clinical outcome scale (NPC-cdb score).ResultsThe efficiency of current clinical diagnostic standards negatively correlates with duration of disease (p<3.9x10-4), suggesting insufficient sensitivity in patients early in the disease process. Neurological signs considered as typical for NP-C were frequent (e.g., cognitive impairment 86%, ataxia 79%, vertical supranuclear gaze palsy 76%) and their presence co-occurred with accelerated diagnosis. However, less specific neuropsychiatric signs were reported to arise considerably more early in the disease process (e.g., clumsiness -4.9±1.1 y before diagnosis). Most patients showed a steady disease progression that correlated with age at neurological onset. However, a distinct subcohort (n=6) with initially steadily progressing disease later showed a 2.9-fold accelerated progression that was associated with the onset of seizures (p<7x10-4), suggesting seizures as predictive for a poor prognosis.ConclusionsConsidering early, but less specific neuropsychiatric signs may accelerate the path to diagnosing NP-C in a patient.

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A fundamental challenge to contemporary genetics is to distinguish rare missense alleles that disrupt protein functions from the majority of alleles neutral on protein activities. High-throughput experimental tools to securely discriminate between disruptive and non-disruptive missense alleles are currently missing. Here we establish a scalable cell-based strategy to profile the biological effects and likely disease relevance of rare missense variants in vitro. We apply this strategy to systematically characterize missense alleles in the low-density lipoprotein receptor (LDLR) gene identified through exome sequencing of 3,235 individuals and exome-chip profiling of 39,186 individuals. Our strategy reliably identifies disruptive missense alleles, and disruptive-allele carriers have higher plasma LDL-cholesterol (LDL-C). Importantly, considering experimental data refined the risk of rare LDLR allele carriers from 4.5- to 25.3-fold for high LDL-C, and from 2.1- to 20-fold for early-onset myocardial infarction. Our study generates proof-of-concept that systematic functional variant profiling may empower rare variant-association studies by orders of magnitude.