Elevated levels of corticotrophin-releasing factor binding protein in the blood of patients suffering from arthritis and septicaemia and the presence of novel ligands in synovial fluid.

In view of the reported inflammatory effects of corticotrophin-releasing factor (CRF) and the associated regulatory elements in the gene of its binding protein (BP), we postulate that both BP as well as novel BP-ligands other than CRF may be involved in inflammatory disease. We have investigated BP in the blood of patients with arthritis and septicaemia and have attempted to identify CRF and other BP-ligands in synovial fluid. The BP was found to be significantly elevated in the blood of patients with rheumatoid arthritis and septicaemia. There was less BP-ligand and CRF in synovial fluid from patients with rheumatoid arthritis that from those with osteo- or psoriatic arthritis. There was at least 10-fold more BP-ligand than CRF in the fluid of all three groups of patients. A small amount of immunoreactive human (h)CRF, eluting in the expected position of CRF-41, was detected after high-pressure liquid chromatography of arthritic synovial fluid; however, the bulk of material with BP-ligand binding activity eluted earlier, suggesting that synovial fluid contained novel peptides that interacted with the BP. These results would suggest that the BP and its ligands could play an endocrine immunomodulatory role in inflammatory disease.

Including a time-of-year effect in the analysis of a matched case-control study

Motivated by a matched case-control study to investigate potential risk factors for meningococcal disease amongst adolescents, we consider the analysis of matched case-control studies where disease incidence, and possibly other risk factors, vary with time of year. For the cases, the time of infection may be recorded. For controls, however, the recorded time is simply the time of data collection, which is shortly after the time of infection for the matched case, and so depends on the latter. We show that the effect of risk factors and interactions may be adjusted for the time of year effect in a standard conditional logistic regression analysis without introducing any bias. We also show that, if the time delay between data collection for cases and controls is constant, provided this delay is not very short, estimates of the time of year effect are approximately unbiased. In the case that the length of the delay varies over time, the estimate of the time of year effect is biased. We obtain an approximate expression for the degree of bias in this case. Copyright © 2004 John Wiley & Sons, Ltd.