From the Journal of Clinical Microbiology, 17 July 2013 [Epub ahead of print].
High Coxiella burnetii DNA load in serum during acute Q fever is associated with progression to a serologic profile indicative of chronic Q fever.
Wielders CC, Wijnbergen PC, Renders NH, Schellekens JJ, Schneeberger PM,
Wever PC, Hermans MH.
Department of Medical Microbiology and Infection Control, Jeroen Bosch Hospital, ‘s-Hertogenbosch, the Netherlands.
PCR is very effective in diagnosing acute Q fever at the early stages of infection, when bacterial DNA is present in the bloodstream but antibodies have not yet developed. The objective of this study was to further analyze the diagnostic value of real-time PCR (qPCR) in diagnosing acute Q fever in an outbreak situation.
At the Jeroen Bosch Hospital, in 2009, qPCR for Coxiella burnetii DNA was performed for 2,715 patients suspected of having acute Q fever (positive: n=385; negative: n=2,330). Sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of the qPCR were calculated for patients with a negative qPCR with a follow-up sample within 14 days (n=305), and qPCR positive patients with at least one follow-up sample (n=369).
The correctness of the qPCR was based on immunofluorescence assay results of samples submitted for qPCR and follow-up. Sensitivity of the Q fever qPCR was 92.2%, specificity 98.9%, PPV 99.2%, and NPV 89.8%.
Patients who later developed a serologic profile indicative of chronic Q fever infection had during the acute phase a significantly higher C. burnetii DNA load than patients who did not (p<0.001). qPCR is a valuable tool in the diagnosis of acute Q fever and should be used in outbreak situations when onset of symptoms is <15 days. Special attention is needed in the follow-up of patients with high C. burnetii DNA loads during the acute phase, as this might be an indicator for the development of a serologic profile indicative of a chronic infection.
From ‘Analyst’,21 August 2013. First published online, 4 April 2013.
A bloodspot-based diagnostic test for fibromyalgia syndrome and related disorders
Kevin V. Hackshaw(a), Luis Rodriguez-Saona(b), Marcal Plans(b), Lauren N. Bell(d) and C.A. Tony Buffington(c,*)
(a) Departments of Internal Medicine, Division of Rheumatology, The Ohio State University, Columbus, USA
(b) Food Science and Technology, The Ohio State University, Columbus, USA
© Veterinary Clinical Sciences, The Ohio State University, 601 Vernon L. Tharp Street, Columbus, USA E-mail: Buffington.firstname.lastname@example.org
(d) Metabolon Inc., 617 Davis Drive, Suite 400, Durham, USA
(*) Corresponding author
The aim of this study was to investigate the ability of a rapid biomarker-based method for diagnosis of fibromyalgia syndrome (FM) using mid-infrared microspectroscopy (IRMS) to differentiate patients with FM from those with osteoarthritis (OA) and rheumatoid arthritis (RA), and to identify molecular species associated with the spectral patterns.
Under IRB approval, blood samples were collected from patients diagnosed with FM (n=14), RA (n=15), or OA (n=12). Samples were prepared, placed onto a highly reflective slide, and spectra were collected using IRMS. Spectra were analyzed using multivariate statistical modeling to differentiate groups.
Aliquots of samples also were subjected to metabolomic analysis. IRMS separated subjects into classes based on spectral information with no misclassifications among FM and RA or OA patients. Interclass distances of 15.4 (FM vs. RA), 14.7 (FM vs. OA) and 2.5 (RA vs. OA) among subjects, demonstrating the ability of IRMS to achieve reliable resolution of unique spectral patterns specific to FM.
Metabolomic analysis revealed that RA and OA groups were metabolically similar, whereas biochemical differences were identified in the FM that were quite distinctive from those found in the other two groups. Both IRMS and metabolomic analysis identified changes in tryptophan catabolism pathway that differentiated patients with FM from those with RA or OA.