Assessment of plasma chitotriosidase activity, CCL18/PARC concentration and NP-C suspicion index in the diagnosis of Niemann-Pick disease type C: A prospective observational study

Background: Niemann-Pick disease type C (NP-C) is a rare, autosomal recessive neurodegenerative disease caused by mutations in either the NPC1 or NPC2 genes. The diagnosis of NP-C remains challenging due to the non-specific, heterogeneous nature of signs/symptoms. This study assessed the utility of plasma chitotriosidase (ChT) and Chemokine (C-C motif) ligand 18 (CCL18)/pulmonary and activation-regulated chemokine (PARC) in conjunction with the NP-C suspicion index (NP-C SI) for guiding confirmatory laboratory testing in patients with suspected NP-C. Methods: In a prospective observational cohort study, incorporating a retrospective determination of NP-C SI scores, two different diagnostic approaches were applied in two separate groups of unrelated patients from 51 Spanish medical centers (n = 118 in both groups). From Jan 2010 to Apr 2012 (Period 1), patients with =2 clinical signs/symptoms of NP-C were considered ''suspected NP-C'' cases, and NPC1/NPC2 sequencing, plasma chitotriosidase (ChT), CCL18/PARC and sphingomyelinase levels were assessed. Based on findings in Period 1, plasma ChT and CCL18/PARC, and NP-C SI prediction scores were determined in a second group of patients between May 2012 and Apr 2014 (Period 2), and NPC1 and NPC2 were sequenced only in those with elevated ChT and/or elevated CCL18/PARC and/or NP-C SI =70. Filipin staining and 7-ketocholesterol (7-KC) measurements were performed in all patients with NP-C gene mutations, where possible. Results: In total across Periods 1 and 2, 10/236 (4%) patients had a confirmed diagnosis o NP-C based on gene sequencing (5/118 4.2%] in each Period): all of these patients had two causal NPC1 mutations. Single mutant NPC1 alleles were detected in 8/236 (3%) patients, overall. Positive filipin staining results comprised three classical and five variant biochemical phenotypes. No NPC2 mutations were detected. All patients with NPC1 mutations had high ChT activity, high CCL18/PARC concentrations and/or NP-C SI scores =70. Plasma 7-KC was higher than control cut-off values in all patients with two NPC1 mutations, and in the majority of patients with single mutations. Family studies identified three further NP-C patients. Conclusion: This approach may be very useful for laboratories that do not have mass spectrometry facilities and therefore, they cannot use other NP-C biomarkers for diagnosis

Expert systems for flow cytometry data analysis: A preliminary report

Flow Cytometry has become an accepted technique in the clinical laboratory for rapid immunophenotyping of patient blood samples. Multiple, fluorescent labeled monoclonal antibodies are used to tag the cells, which are then analyzed one at a time at rates of several thousand cells a second. Patient samples are processed through the flow cytometer at more than one a minute. Clinicians are being overwhelmed by the large amount of data that must be analyzed to provide the information needed to assist in disease diagnosis. An expert system is being developed to assist clinicians in analyzing this multivariate flow cytometry data. The data from each sample are processed by a clustering algorithm, which finds the means of the distinct cell subpopulations in a sample. These mean values of fluorescence are translated into words such as negative,'' dim'' and bright'' and the words are combined into patterns that are matched against the premises on the left hand side of the rules used to identify the disease categories. This is a report of work in progress. 13 refs., 4 figs

A clinical flow cytometry data analysis assistant

A rule-based expert system is being developed to assist clinicians in the analysis of multivariate flow cytometry data for patients with leukemias or lymphomas. The cells are stained with fluorescently labeled monoclonal antibodies and the cell fluorescence is measured with a flow cytometer. Cluster analysis is used to isolate subpopulations in the data on which the clinical decisions are made. Symbolic facts for the expert system are instantiated using these numerical data and the knowledge of the clinicians and experts in flow cytometry. The first prototype used a decision tree and rigid rules. Is successfully classified only nine of eleven leukemia cases. A second prototype incorporating certainty factors into the rules is now being developed that should remove the need for a rigid decision tree. 9 refs

A CLIPS expert system for clinical flow cytometry data analysis

An expert system is being developed using CLIPS to assist clinicians in the analysis of multivariate flow cytometry data from cancer patients. Cluster analysis is used to find subpopulations representing various cell types in multiple datasets each consisting of four to five measurements on each of 5000 cells. CLIPS facts are derived from results of the clustering. CLIPS rules are based on the expertise of Drs. Stewart, Duque, and Braylan. The rules incorporate certainty factors based on case histories