Methodological details of biomarker measurements.

a<p>If indicated, CSF was concentrated using Millipore Amicon Ultra 3 kDa filters.</p>b<p>Only linear part of standard curve was used for quantification of protein; when concentrated CSF was used, detection limit is recalculated to reflect utilized concentration factor.</p>c<p>Intra-assay coefficient of variance could not be calculated because all data were below the detection limit of the assay.</p

Cerebrospinal Fluid IL-12p40, CXCL13 and IL-8 as a Combinatorial Biomarker of Active Intrathecal Inflammation

<div><p>Diagnosis and management of the neuroinflammatory diseases of the central nervous system (CNS) are hindered by the lack of reliable biomarkers of active intrathecal inflammation. We hypothesized that measuring several putative inflammatory biomarkers simultaneously will augment specificity and sensitivity of the biomarker to the clinically useful range. Based on our pilot experiment in which we measured 18 inflammatory biomarkers in 10-fold concentrated cerebrospinal fluid (CSF) derived from 16 untreated patients with highly active multiple sclerosis (MS) we selected a combination of three CSF biomarkers, IL-12p40, CXCL13 and IL-8, for further validation.</p> <p>Concentrations of IL-12p40, CXCL13 and IL-8 were determined in a blinded fashion in CSF samples from an initial cohort (n = 72) and a confirmatory cohort (n = 167) of prospectively collected, untreated subjects presenting for a diagnostic work-up of possible neuroimmunological disorder. Diagnostic conclusion was based on a thorough clinical workup, which included laboratory assessment of the blood and CSF, neuroimaging and longitudinal follow-up. Receiver operating characteristic (ROC) curve analysis in conjunction with principal component analysis (PCA), which was used to combine information from all three biomarkers, assessed the diagnostic value of measured biomarkers.</p> <p>Each of the three biomarkers was significantly increased in MS and other inflammatory neurological disease (OIND) in comparison to non-inflammatory neurological disorder patients (NIND) at least in one cohort. However, considering all three biomarkers together improved accuracy of predicting the presence of intrathecal inflammation to the consistently good to excellent range (area under the ROC curve = 0.868–0.924).</p> <p>Future clinical studies will determine if a combinatorial biomarker consisting of CSF IL-12p40, CXCL13 and IL-8 provides utility in determining the presence of active intrathecal inflammation in diagnostically uncertain cases and in therapeutic development and management.</p> </div

Correlations between CSF IL-12p40, CXCL13 and IL-8 (all measured in pg/ml) and traditional clinical measures of intrathecal inflammation: CSF biomarkers measured by NIH clinical laboratory: WBC count (# of cells per mm³ measured in unspun CSF), IgG index (normal range 0.26–0.62), OCB and total protein (g/dl) and CEL measured as described in detail in method section.

<p>Correlation coefficients and p values are detailed in each panel. The data originate from the confirmatory (NIB) cohort only.</p

ROC curves for all three CSF biomarkers and their PCA1 for both WMS and NIB cohorts.

<p>ROC curves for all three CSF biomarkers and their PCA1 for both WMS and NIB cohorts.</p

Clinical utility of CSF biomarkers.

*<p>AUC is the percentage of randomly drawn pairs for which the test is correct (i.e. it correctly classifies the two patients in the pair).</p

Diagnostic and demographic data.

<p>Age and sex were considered as covariate (if p<0.1). Three subjects with progressive MS in WMS cohort were excluded from ANOVA or ANCOVA.</p>a<p>p<0.05 vs. RR-MS;</p>b<p>p<0.05 vs. Progressive MS;</p>c<p>p<0.05 vs. OIND.</p

Soft Null Hypotheses: A Case Study of Image Enhancement Detection in Brain Lesions

<div><p>This work is motivated by a study of a population of multiple sclerosis (MS) patients using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to identify active brain lesions. At each visit, a contrast agent is administered intravenously to a subject and a series of images are acquired to reveal the location and activity of MS lesions within the brain. Our goal is to identify the enhancing lesion locations at the subject level and lesion enhancement patterns at the population level. We analyze a total of 20 subjects scanned at 63 visits (∼30Gb), the largest population of such clinical brain images. After addressing the computational challenges, we propose possible solutions to the difficult problem of transforming a qualitative scientific null hypothesis, such as “this voxel does not enhance”, to a well-defined and numerically testable null hypothesis based on the existing data. We call such procedure “soft null” hypothesis testing as opposed to the standard “hard null” hypothesis testing. This problem is fundamentally different from: 1) finding testing statistics when a quantitative null hypothesis is given; 2) clustering using a mixture distribution; or 3) setting a reasonable threshold with a parametric null assumption.</p></div

HHV-6A and HHV-6B duplex ddPCR assay design and specificity validation.

<p>(A) Primers were designed to amplify an 89 base pair region of <i>U57</i>, encoding the major capsid protein of HHV-6. The shared forward and reverse primers (in bold) amplify both HHV-6A and HHV-6B, while the probes are specific for each virus with a three base pair mismatch. The HHV-6A probe sequence is in blue, while the HHV-6B probe sequence is in green. (B) The probes distinguish HHV-6A and HHV-6B viral DNA with high specificity. The HHV-6A FAM-labeled probe binds HHV-6A DNA (blue droplets in left plot) but not HHV-6B DNA. Likewise, the HHV-6B VIC-labeled probe binds HHV-6B DNA (green droplets in right plot), but not HHV-6A DNA.</p

Identification of potentially chromosomally integrated blood donors using duplex and triplex ddPCR assays.

<p>(A) In a duplex reaction, donor 27867 was calculated to have 1.02 copies HHV-6A per cell. (B) In a duplex reaction, donor 28319 was calculated to have 0.98 copies HHV-6B per cell. The corresponding plots for the housekeeping gene <i>RPP30</i> (insets) were used to quantify the number of cells. (C) Triplex ddPCR of PBMC DNA from potentially chromosomally integrated donors. All three primer/probe sets (HHV-6A, HHV-6B and RPP30) can be assayed in a single well, using fluorescence intensities to distinguish between the droplet populations (labeled). In a triplex reaction, donor 27867 was calculated to have 1.09 copies HHV-6A per cell. (D) In a triplex reaction, donor 28319 was calculated to have 1.04 copies HHV-6B per cell.</p

HHV-6 viruses detected in 57% healthy donor PBMC samples: 50% coinfection of HHV-6A and HHV-6B.

<p>Representative ddPCR plots with corresponding housekeeping gene (<i>RPP30</i>) as insets shown in A-C. (A) No positivity detected. (B) Only HHV-6B positivity (green droplets, lower right quadrant) detected. (C) Coinfection of HHV-6A and HHV-6B (blue droplets in upper left and green droplets in lower right quadrants, respectively) detected. (D) Group analysis of 46 healthy donor PBMC samples, with a mean (solid line) of 455 total HHV-6 copies/10⁶ cells. Each circle represents a donor. Closed circles represent detection of both HHV-6A and HHV-6B, while open circles represent detection of only HHV-6B. (E) The amount of HHV-6A and HHV-6B in the coinfected healthy donors (closed circles in D). The ratio of 6A/6B copies/10⁶ PBMC ranged from 0.01–0.25.</p